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AMD Radeon RX 9070 and 9070 XT review: RDNA 4 fixes a lot of AMD’s problems

AMD, Features, gaming, GeForce, GPUs, NVIDIA, Radeon, radeon rx 9070, radeon rx 9070 XT, rdna 4, Reviews, Tech / Kelly Newman / March 6, 2025

For $549 and $599, AMD comes close to knocking out Nvidia’s GeForce RTX 5070.

AMD’s Radeon RX 9070 and 9070 XT are its first cards based on the RDNA 4 GPU architecture. Credit: Andrew Cunningham

AMD is a company that knows a thing or two about capitalizing on a competitor’s weaknesses. The company got through its early-2010s nadir partially because its Ryzen CPUs struck just as Intel’s current manufacturing woes began to set in, first with somewhat-worse CPUs that were great value for the money and later with CPUs that were better than anything Intel could offer.

Nvidia’s untrammeled dominance of the consumer graphics card market should also be an opportunity for AMD. Nvidia’s GeForce RTX 50-series graphics cards have given buyers very little to get excited about, with an unreachably expensive high-end 5090 refresh and modest-at-best gains from 5080 and 5070-series cards that are also pretty expensive by historical standards, when you can buy them at all. Tech YouTubers—both the people making the videos and the people leaving comments underneath them—have been almost uniformly unkind to the 50 series, hinting at consumer frustrations and pent-up demand for competitive products from other companies.

Enter AMD’s Radeon RX 9070 XT and RX 9070 graphics cards. These are aimed right at the middle of the current GPU market at the intersection of high sales volume and decent profit margins. They promise good 1440p and entry-level 4K gaming performance and improved power efficiency compared to previous-generation cards, with fixes for long-time shortcomings (ray-tracing performance, video encoding, and upscaling quality) that should, in theory, make them more tempting for people looking to ditch Nvidia.

Table of Contents

RX 9070 and 9070 XT specs and speeds

	RX 9070 XT	RX 9070	RX 7900 XTX	RX 7900 XT	RX 7900 GRE	RX 7800 XT
Compute units (Stream processors)	64 RDNA4 (4,096)	56 RDNA4 (3,584)	96 RDNA3 (6,144)	84 RDNA3 (5,376)	80 RDNA3 (5,120)	60 RDNA3 (3,840)
Boost Clock	2,970 MHz	2,520 MHz	2,498 MHz	2,400 MHz	2,245 MHz	2,430 MHz
Memory Bus Width	256-bit	256-bit	384-bit	320-bit	256-bit	256-bit
Memory Bandwidth	650GB/s	650GB/s	960GB/s	800GB/s	576GB/s	624GB/s
Memory size	16GB GDDR6	16GB GDDR6	24GB GDDR6	20GB GDDR6	16GB GDDR6	16GB GDDR6
Total board power (TBP)	304 W	220 W	355 W	315 W	260 W	263 W

AMD’s high-level performance promise for the RDNA 4 architecture revolves around big increases in performance per compute unit (CU). An RDNA 4 CU, AMD says, is nearly twice as fast in rasterized performance as RDNA 2 (that is, rendering without ray-tracing effects enabled) and nearly 2.5 times as fast as RDNA 2 in games with ray-tracing effects enabled. Performance for at least some machine learning workloads also goes way up—twice as fast as RDNA 3 and four times as fast as RDNA 2.

We’ll see this in more detail when we start comparing performance, but AMD seems to have accomplished this goal. Despite having 64 or 56 compute units (for the 9070 XT and 9070, respectively), the cards’ performance often competes with AMD’s last-generation flagships, the RX 7900 XTX and 7900 XT. Those cards came with 96 and 84 compute units, respectively. The 9070 cards are specced a lot more like last generation’s RX 7800 XT—including the 16GB of GDDR6 on a 256-bit memory bus, as AMD still isn’t using GDDR6X or GDDR7—but they’re much faster than the 7800 XT was.

AMD has dramatically increased the performance-per-compute unit for RDNA 4. AMD

The 9070 series also uses a new 4 nm manufacturing process from TSMC, an upgrade from the 7000 series’ 5 nm process (and the 6 nm process used for the separate memory controller dies in higher-end RX 7000-series models that used chiplets). AMD’s GPUs are normally a bit less efficient than Nvidia’s, but the architectural improvements and the new manufacturing process allow AMD to do some important catch-up.

Both of the 9070 models we tested were ASRock Steel Legend models, and the 9070 and 9070 XT had identical designs—we’ll probably see a lot of this from AMD’s partners since the GPU dies and the 16GB RAM allotments are the same for both models. Both use two 8-pin power connectors; AMD says partners are free to use the 12-pin power connector if they want, but given Nvidia’s ongoing issues with it, most cards will likely stick with the reliable 8-pin connectors.

AMD doesn’t appear to be making and selling reference designs for the 9070 series the way it did for some RX 7000 and 6000-series GPUs or the way Nvidia does with its Founders Edition cards. From what we’ve seen, 2 or 2.5-slot, triple-fan designs will be the norm, the way they are for most midrange GPUs these days.

Testbed notes

We used the same GPU testbed for the Radeon RX 9070 series as we have for our GeForce RTX 50-series reviews.

An AMD Ryzen 7 9800X3D ensures that our graphics cards will be CPU-limited as little as possible. An ample 1050 W power supply, 32GB of DDR5-6000, and an AMD X670E motherboard with the latest BIOS installed round out the hardware. On the software side, we use an up-to-date installation of Windows 11 24H2 and recent GPU drivers for older cards, ensuring that our tests reflect whatever optimizations Microsoft, AMD, Nvidia, and game developers have made since the last generation of GPUs launched.

We have numbers for all of Nvidia’s RTX 50-series GPUs so far, plus most of the 40-series cards, most of AMD’s RX 7000-series cards, and a handful of older GPUs from the RTX 30-series and RX 6000 series. We’ll focus on comparing the 9070 XT and 9070 to other 1440p-to-4K graphics cards since those are the resolutions AMD is aiming at.

Performance

At $549 and $599, the 9070 series is priced to match Nvidia’s $549 RTX 5070 and undercut the $749 RTX 5070 Ti. So we’ll focus on comparing the 9070 series to those cards, plus the top tier of GPUs from the outgoing RX 7000-series.

Some 4K rasterized benchmarks.

Starting at the top with rasterized benchmarks with no ray-tracing effects, the 9070 XT does a good job of standing up to Nvidia’s RTX 5070 Ti, coming within a few frames per second of its performance in all the games we tested (and scoring very similarly in the 3DMark Time Spy Extreme benchmark).

Both cards are considerably faster than the RTX 5070—between 15 and 28 percent for the 9070 XT and between 5 and 13 percent for the regular 9070 (our 5070 scored weirdly low in Horizon Zero Dawn Remastered, so we’d treat those numbers as outliers for now). Both 9070 cards also stack up well next to the RX 7000 series here—the 9070 can usually just about match the performance of the 7900 XT, and the 9070 XT usually beats it by a little. Both cards thoroughly outrun the old RX 7900 GRE, which was AMD’s $549 GPU offering just a year ago.

The 7900 XT does have 20GB of RAM instead of 16GB, which might help its performance in some edge cases. But 16GB is still perfectly generous for a 1440p-to-4K graphics card—the 5070 only offers 12GB, which could end up limiting its performance in some games as RAM requirements continue to rise.

On ray-tracing improvements

Nvidia got a jump on AMD when it introduced hardware-accelerated ray-tracing in the RTX 20-series in 2018. And while these effects were only supported in a few games at the time, many modern games offer at least some kind of ray-traced lighting effects.

AMD caught up a little when it began shipping its own ray-tracing support in the RDNA2 architecture in late 2020, but the issue since then has always been that AMD cards have taken a larger performance hit than GeForce GPUs when these effects are turned on. RDNA3 promised improvements, but our tests still generally showed the same deficit as before.

So we’re looking for two things with RDNA4’s ray-tracing performance. First, we want the numbers to be higher than they were for comparably priced RX 7000-series GPUs, the same thing we look for in non-ray-traced (or rasterized) rendering performance. Second, we want the size of the performance hit to go down. To pick an example: the RX 7900 GRE could compete with Nvidia’s RTX 4070 Ti Super in games without ray tracing, but it was closer to a non-Super RTX 4070 in ray-traced games. It has helped keep AMD’s cards from being across-the-board competitive with Nvidia’s—is that any different now?

Benchmarks for games with ray-tracing effects enabled. Both AMD cards generally keep pace with the 5070 in these tests thanks to RDNA 4’s improvements.

The picture our tests paint is mixed but tentatively positive. The 9070 series and RDNA4 post solid improvements in the Cyberpunk 2077 benchmarks, substantially closing the performance gap with Nvidia. In games where AMD’s cards performed well enough before—here represented by Returnal—performance goes up, but roughly proportionately with rasterized performance. And both 9070 cards still punch below their weight in Black Myth: Wukong, falling substantially behind the 5070 under the punishing Cinematic graphics preset.

So the benefits you see, as with any GPU update, will depend a bit on the game you’re playing. There’s also a possibility that game optimizations and driver updates made with RDNA4 in mind could boost performance further. We can’t say that AMD has caught all the way up to Nvidia here—the 9070 and 9070 XT are both closer to the GeForce RTX 5070 than the 5070 Ti, despite keeping it closer to the 5070 Ti in rasterized tests—but there is real, measurable improvement here, which is what we were looking for.

Power usage

The 9070 series’ performance increases are particularly impressive when you look at the power-consumption numbers. The 9070 comes close to the 7900 XT’s performance but uses 90 W less power under load. It beats the RTX 5070 most of the time but uses around 30 W less power.

The 9070 XT is a little less impressive on this front—AMD has set clock speeds pretty high, and this can increase power use disproportionately. The 9070 XT is usually 10 or 15 percent faster than the 9070 but uses 38 percent more power. The XT’s power consumption is similar to the RTX 5070 Ti’s (a GPU it often matches) and the 7900 XT’s (a GPU it always beats), so it’s not too egregious, but it’s not as standout as the 9070’s.

AMD gives 9070 owners a couple of new toggles for power limits, though, which we’ll talk about in the next section.

Experimenting with “Total Board Power”

We don’t normally dabble much with overclocking when we review CPUs or GPUs—we’re happy to leave that to folks at other outlets. But when we review CPUs, we do usually test them with multiple power limits in place. Playing with power limits is easier (and occasionally safer) than actually overclocking, and it often comes with large gains to either performance (a chip that performs much better when given more power to work with) or efficiency (a chip that can run at nearly full speed without using as much power).

Initially, I experimented with the RX 9070’s power limits by accident. AMD sent me one version of the 9070 but exchanged it because of a minor problem the OEM identified with some units early in the production run. I had, of course, already run most of our tests on it, but that’s the way these things go sometimes.

By bumping the regular RX 9070’s TBP up just a bit, you can nudge it closer to 9070 XT-level performance.

The replacement RX 9070 card, an ASRock Steel Legend model, was performing significantly better in our tests, sometimes nearly closing the gap between the 9070 and the XT. It wasn’t until I tested power consumption that I discovered the explanation—by default, it was using a 245 W power limit rather than the AMD-defined 220 W limit. Usually, these kinds of factory tweaks don’t make much of a difference, but for the 9070, this power bump gave it a nice performance boost while still keeping it close to the 250 W power limit of the GeForce RTX 5070.

The 90-series cards we tested both add some power presets to AMD’s Adrenalin app in the Performance tab under Tuning. These replace and/or complement some of the automated overclocking and undervolting buttons that exist here for older Radeon cards. Clicking Favor Efficiency or Favor Performance can ratchet the card’s Total Board Power (TBP) up or down, limiting performance so that the card runs cooler and quieter or allowing the card to consume more power so it can run a bit faster.

The 9070 cards get slightly different performance tuning options in the Adrenalin software. These buttons mostly change the card’s Total Board Power (TBP), making it simple to either improve efficiency or boost performance a bit. Credit: Andrew Cunningham

For this particular ASRock 9070 card, the default TBP is set to 245 W. Selecting “Favor Efficiency” sets it to the default 220 W. You can double-check these values using an app like HWInfo, which displays both the current TBP and the maximum TBP in its Sensors Status window. Clicking the Custom button in the Adrenalin software gives you access to a Power Tuning slider, which for our card allowed us to ratchet the TBP up by up to 10 percent or down by as much as 30 percent.

This is all the firsthand testing we did with the power limits of the 9070 series, though I would assume that adding a bit more power also adds more overclocking headroom (bumping up the power limits is common for GPU overclockers no matter who makes your card). AMD says that some of its partners will ship 9070 XT models set to a roughly 340 W power limit out of the box but acknowledges that “you start seeing diminishing returns as you approach the top of that [power efficiency] curve.”

But it’s worth noting that the driver has another automated set-it-and-forget-it power setting you can easily use to find your preferred balance of performance and power efficiency.

A quick look at FSR4 performance

There’s a toggle in the driver for enabling FSR 4 in FSR 3.1-supporting games. Credit: Andrew Cunningham

One of AMD’s headlining improvements to the RX 90-series is the introduction of FSR 4, a new version of its FidelityFX Super Resolution upscaling algorithm. Like Nvidia’s DLSS and Intel’s XeSS, FSR 4 can take advantage of RDNA 4’s machine learning processing power to do hardware-backed upscaling instead of taking a hardware-agnostic approach as the older FSR versions did. AMD says this will improve upscaling quality, but it also means FSR4 will only work on RDNA 4 GPUs.

The good news is that FSR 3.1 and FSR 4 are forward- and backward-compatible. Games that have already added FSR 3.1 support can automatically take advantage of FSR 4, and games that support FSR 4 on the 90-series can just run FSR 3.1 on older and non-AMD GPUs.

FSR 4 comes with a small performance hit compared to FSR 3.1 at the same settings, but better overall quality can let you drop to a faster preset like Balanced or Performance and end up with more frames-per-second overall. Credit: Andrew Cunningham

The only game in our current test suite to be compatible with FSR 4 is Horizon Zero Dawn Remastered, and we tested its performance using both FSR 3.1 and FSR 4. In general, we found that FSR 4 improved visual quality at the cost of just a few frames per second when run at the same settings—not unlike using Nvidia’s recently released “transformer model” for DLSS upscaling.

Many games will let you choose which version of FSR you want to use. But for FSR 3.1 games that don’t have a built-in FSR 4 option, there’s a toggle in AMD’s Adrenalin driver you can hit to switch to the better upscaling algorithm.

Even if they come with a performance hit, new upscaling algorithms can still improve performance by making the lower-resolution presets look better. We run all of our testing in “Quality” mode, which generally renders at two-thirds of native resolution and scales up. But if FSR 4 running in Balanced or Performance mode looks the same to your eyes as FSR 3.1 running in Quality mode, you can still end up with a net performance improvement in the end.

RX 9070 or 9070 XT?

Just $50 separates the advertised price of the 9070 from that of the 9070 XT, something both Nvidia and AMD have done in the past that I find a bit annoying. If you have $549 to spend on a graphics card, you can almost certainly scrape together $599 for a graphics card. All else being equal, I’d tell most people trying to choose one of these to just spring for the 9070 XT.

That said, availability and retail pricing for these might be all over the place. If your choices are a regular RX 9070 or nothing, or an RX 9070 at $549 and an RX 9070 XT at any price higher than $599, I would just grab a 9070 and not sweat it too much. The two cards aren’t that far apart in performance, especially if you bump the 9070’s TBP up a little bit, and games that are playable on one will be playable at similar settings on the other.

Pretty close to great

If you’re building a 1440p or 4K gaming box, the 9070 series might be the ones to beat right now. Credit: Andrew Cunningham

We’ve got plenty of objective data in here, so I don’t mind saying that I came into this review kind of wanting to like the 9070 and 9070 XT. Nvidia’s 50-series cards have mostly upheld the status quo, and for the last couple of years, the status quo has been sustained high prices and very modest generational upgrades. And who doesn’t like an underdog story?

I think our test results mostly justify my priors. The RX 9070 and 9070 XT are very competitive graphics cards, helped along by a particularly mediocre RTX 5070 refresh from Nvidia. In non-ray-traced games, both cards wipe the floor with the 5070 and come close to competing with the $749 RTX 5070 Ti. In games and synthetic benchmarks with ray-tracing effects on, both cards can usually match or slightly beat the similarly priced 5070, partially (if not entirely) addressing AMD’s longstanding performance deficit here. Neither card comes close to the 5070 Ti in these games, but they’re also not priced like a 5070 Ti.

Just as impressively, the Radeon cards compete with the GeForce cards while consuming similar amounts of power. At stock settings, the RX 9070 uses roughly the same amount of power under load as a 4070 Super but with better performance. The 9070 XT uses about as much power as a 5070 Ti, with similar performance before you turn ray-tracing on. Power efficiency was a small but consistent drawback for the RX 7000 series compared to GeForce cards, and the 9070 cards mostly erase that disadvantage. AMD is also less stingy with the RAM, giving you 16GB for the price Nvidia charges for 12GB.

Some of the old caveats still apply. Radeons take a bigger performance hit, proportionally, than GeForce cards. DLSS already looks pretty good and is widely supported, while FSR 3.1/FSR 4 adoption is still relatively low. Nvidia has a nearly monopolistic grip on the dedicated GPU market, which means many apps, AI workloads, and games support its GPUs best/first/exclusively. AMD is always playing catch-up to Nvidia in some respect, and Nvidia keeps progressing quickly enough that it feels like AMD never quite has the opportunity to close the gap.

AMD also doesn’t have an answer for DLSS Multi-Frame Generation. The benefits of that technology are fairly narrow, and you already get most of those benefits with single-frame generation. But it’s still a thing that Nvidia does that AMDon’t.

Overall, the RX 9070 cards are both awfully tempting competitors to the GeForce RTX 5070—and occasionally even the 5070 Ti. They’re great at 1440p and decent at 4K. Sure, I’d like to see them priced another $50 or $100 cheaper to well and truly undercut the 5070 and bring 1440p-to-4K performance t0 a sub-$500 graphics card. It would be nice to see AMD undercut Nvidia’s GPUs as ruthlessly as it undercut Intel’s CPUs nearly a decade ago. But these RDNA4 GPUs have way fewer downsides than previous-generation cards, and they come at a moment of relative weakness for Nvidia. We’ll see if the sales follow.

The good

Great 1440p performance and solid 4K performance
16GB of RAM
Decisively beats Nvidia’s RTX 5070, including in most ray-traced games
RX 9070 XT is competitive with RTX 5070 Ti in non-ray-traced games for less money
Both cards match or beat the RX 7900 XT, AMD’s second-fastest card from the last generation
Decent power efficiency for the 9070 XT and great power efficiency for the 9070
Automated options for tuning overall power use to prioritize either efficiency or performance
Reliable 8-pin power connectors available in many cards

The bad

Nvidia’s ray-tracing performance is still usually better
At $549 and $599, pricing matches but doesn’t undercut the RTX 5070
FSR 4 isn’t as widely supported as DLSS and may not be for a while

The ugly

Playing the “can you actually buy these for AMD’s advertised prices” game

Andrew is a Senior Technology Reporter at Ars Technica, with a focus on consumer tech including computer hardware and in-depth reviews of operating systems like Windows and macOS. Andrew lives in Philadelphia and co-hosts a weekly book podcast called Overdue.

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AI versus the brain and the race for general intelligence

AI, Biology, Features, large language models, learning, memory, Neuroscience, Science / DJ Henderson / March 3, 2025

Intelligence, ±artificial

We already have an example of general intelligence, and it doesn’t look like AI.

There’s no question that AI systems have accomplished some impressive feats, mastering games, writing text, and generating convincing images and video. That’s gotten some people talking about the possibility that we’re on the cusp of AGI, or artificial general intelligence. While some of this is marketing fanfare, enough people in the field are taking the idea seriously that it warrants a closer look.

Many arguments come down to the question of how AGI is defined, which people in the field can’t seem to agree upon. This contributes to estimates of its advent that range from “it’s practically here” to “we’ll never achieve it.” Given that range, it’s impossible to provide any sort of informed perspective on how close we are.

But we do have an existing example of AGI without the “A”—the intelligence provided by the animal brain, particularly the human one. And one thing is clear: The systems being touted as evidence that AGI is just around the corner do not work at all like the brain does. That may not be a fatal flaw, or even a flaw at all. It’s entirely possible that there’s more than one way to reach intelligence, depending on how it’s defined. But at least some of the differences are likely to be functionally significant, and the fact that AI is taking a very different route from the one working example we have is likely to be meaningful.

With all that in mind, let’s look at some of the things the brain does that current AI systems can’t.

Defining AGI might help

Artificial general intelligence hasn’t really been defined. Those who argue that it’s imminent are either vague about what they expect the first AGI systems to be capable of or simply define it as the ability to dramatically exceed human performance at a limited number of tasks. Predictions of AGI’s arrival in the intermediate term tend to focus on AI systems demonstrating specific behaviors that seem human-like. The further one goes out on the timeline, the greater the emphasis on the “G” of AGI and its implication of systems that are far less specialized.

But most of these predictions are coming from people working in companies with a commercial interest in AI. It was notable that none of the researchers we talked to for this article were willing to offer a definition of AGI. They were, however, willing to point out how current systems fall short.

“I think that AGI would be something that is going to be more robust, more stable—not necessarily smarter in general but more coherent in its abilities,” said Ariel Goldstein, a researcher at Hebrew University of Jerusalem. “You’d expect a system that can do X and Y to also be able to do Z and T. Somehow, these systems seem to be more fragmented in a way. To be surprisingly good at one thing and then surprisingly bad at another thing that seems related.”

“I think that’s a big distinction, this idea of generalizability,” echoed neuroscientist Christa Baker of NC State University. “You can learn how to analyze logic in one sphere, but if you come to a new circumstance, it’s not like now you’re an idiot.”

Mariano Schain, a Google engineer who has collaborated with Goldstein, focused on the abilities that underlie this generalizability. He mentioned both long-term and task-specific memory and the ability to deploy skills developed in one task in different contexts. These are limited-to-nonexistent in existing AI systems.

Beyond those specific limits, Baker noted that “there’s long been this very human-centric idea of intelligence that only humans are intelligent.” That’s fallen away within the scientific community as we’ve studied more about animal behavior. But there’s still a bias to privilege human-like behaviors, such as the human-sounding responses generated by large language models

The fruit flies that Baker studies can integrate multiple types of sensory information, control four sets of limbs, navigate complex environments, satisfy their own energy needs, produce new generations of brains, and more. And they do that all with brains that contain under 150,000 neurons, far fewer than current large language models.

These capabilities are complicated enough that it’s not entirely clear how the brain enables them. (If we knew how, it might be possible to engineer artificial systems with similar capacities.) But we do know a fair bit about how brains operate, and there are some very obvious ways that they differ from the artificial systems we’ve created so far.

Neurons vs. artificial neurons

Most current AI systems, including all large language models, are based on what are called neural networks. These were intentionally designed to mimic how some areas of the brain operate, with large numbers of artificial neurons taking an input, modifying it, and then passing the modified information on to another layer of artificial neurons. Each of these artificial neurons can pass the information on to multiple instances in the next layer, with different weights applied to each connection. In turn, each of the artificial neurons in the next layer can receive input from multiple sources in the previous one.

After passing through enough layers, the final layer is read and transformed into an output, such as the pixels in an image that correspond to a cat.

While that system is modeled on the behavior of some structures within the brain, it’s a very limited approximation. For one, all artificial neurons are functionally equivalent—there’s no specialization. In contrast, real neurons are highly specialized; they use a variety of neurotransmitters and take input from a range of extra-neural inputs like hormones. Some specialize in sending inhibitory signals while others activate the neurons they interact with. Different physical structures allow them to make different numbers and connections.

In addition, rather than simply forwarding a single value to the next layer, real neurons communicate through an analog series of activity spikes, sending trains of pulses that vary in timing and intensity. This allows for a degree of non-deterministic noise in communications.

Finally, while organized layers are a feature of a few structures in brains, they’re far from the rule. “What we found is it’s—at least in the fly—much more interconnected,” Baker told Ars. “You can’t really identify this strictly hierarchical network.”

With near-complete connection maps of the fly brain becoming available, she told Ars that researchers are “finding lateral connections or feedback projections, or what we call recurrent loops, where we’ve got neurons that are making a little circle and connectivity patterns. I think those things are probably going to be a lot more widespread than we currently appreciate.”

While we’re only beginning to understand the functional consequences of all this complexity, it’s safe to say that it allows networks composed of actual neurons far more flexibility in how they process information—a flexibility that may underly how these neurons get re-deployed in a way that these researchers identified as crucial for some form of generalized intelligence.

But the differences between neural networks and the real-world brains they were modeled on go well beyond the functional differences we’ve talked about so far. They extend to significant differences in how these functional units are organized.

The brain isn’t monolithic

The neural networks we’ve generated so far are largely specialized systems meant to handle a single task. Even the most complicated tasks, like the prediction of protein structures, have typically relied on the interaction of only two or three specialized systems. In contrast, the typical brain has a lot of functional units. Some of these operate by sequentially processing a single set of inputs in something resembling a pipeline. But many others can operate in parallel, in some cases without any input activity going on elsewhere in the brain.

To give a sense of what this looks like, let’s think about what’s going on as you read this article. Doing so requires systems that handle motor control, which keep your head and eyes focused on the screen. Part of this system operates via feedback from the neurons that are processing the read material, causing small eye movements that help your eyes move across individual sentences and between lines.

Separately, there’s part of your brain devoted to telling the visual system what not to pay attention to, like the icon showing an ever-growing number of unread emails. Those of us who can read a webpage without even noticing the ads on it presumably have a very well-developed system in place for ignoring things. Reading this article may also mean you’re engaging the systems that handle other senses, getting you to ignore things like the noise of your heating system coming on while remaining alert for things that might signify threats, like an unexplained sound in the next room.

The input generated by the visual system then needs to be processed, from individual character recognition up to the identification of words and sentences, processes that involve systems in areas of the brain involved in both visual processing and language. Again, this is an iterative process, where building meaning from a sentence may require many eye movements to scan back and forth across a sentence, improving reading comprehension—and requiring many of these systems to communicate among themselves.

As meaning gets extracted from a sentence, other parts of the brain integrate it with information obtained in earlier sentences, which tends to engage yet another area of the brain, one that handles a short-term memory system called working memory. Meanwhile, other systems will be searching long-term memory, finding related material that can help the brain place the new information within the context of what it already knows. Still other specialized brain areas are checking for things like whether there’s any emotional content to the material you’re reading.

All of these different areas are engaged without you being consciously aware of the need for them.

In contrast, something like ChatGPT, despite having a lot of artificial neurons, is monolithic: No specialized structures are allocated before training starts. That’s in sharp contrast to a brain. “The brain does not start out as a bag of neurons and then as a baby it needs to make sense of the world and then determine what connections to make,” Baker noted. “There already a lot of constraints and specifics that are already set up.”

Even in cases where it’s not possible to see any physical distinction between cells specialized for different functions, Baker noted that we can often find differences in what genes are active.

In contrast, pre-planned modularity is relatively new to the AI world. In software development, “This concept of modularity is well established, so we have the whole methodology around it, how to manage it,” Schain said, “it’s really an aspect that is important for maybe achieving AI systems that can then operate similarly to the human brain.” There are a few cases where developers have enforced modularity on systems, but Goldstein said these systems need to be trained with all the modules in place to see any gain in performance.

None of this is saying that a modular system can’t arise within a neural network as a result of its training. But so far, we have very limited evidence that they do. And since we mostly deploy each system for a very limited number of tasks, there’s no reason to think modularity will be valuable.

There is some reason to believe that this modularity is key to the brain’s incredible flexibility. The region that recognizes emotion-evoking content in written text can also recognize it in music and images, for example. But the evidence here is mixed. There are some clear instances where a single brain region handles related tasks, but that’s not consistently the case; Baker noted that, “When you’re talking humans, there are parts of the brain that are dedicated to understanding speech, and there are different areas that are involved in producing speech.”

This sort of re-use of would also provide an advantage in terms of learning since behaviors developed in one context could potentially be deployed in others. But as we’ll see, the differences between brains and AI when it comes to learning are far more comprehensive than that.

The brain is constantly training

Current AIs generally have two states: training and deployment. Training is where the AI learns its behavior; deployment is where that behavior is put to use. This isn’t absolute, as the behavior can be tweaked in response to things learned during deployment, like finding out it recommends eating a rock daily. But for the most part, once the weights among the connections of a neural network are determined through training, they’re retained.

That may be starting to change a bit, Schain said. “There is now maybe a shift in similarity where AI systems are using more and more what they call the test time compute, where at inference time you do much more than before, kind of a parallel to how the human brain operates,” he told Ars. But it’s still the case that neural networks are essentially useless without an extended training period.

In contrast, a brain doesn’t have distinct learning and active states; it’s constantly in both modes. In many cases, the brain learns while doing. Baker described that in terms of learning to take jumpshots: “Once you have made your movement, the ball has left your hand, it’s going to land somewhere. So that visual signal—that comparison of where it landed versus where you wanted it to go—is what we call an error signal. That’s detected by the cerebellum, and its goal is to minimize that error signal. So the next time you do it, the brain is trying to compensate for what you did last time.”

It makes for very different learning curves. An AI is typically not very useful until it has had a substantial amount of training. In contrast, a human can often pick up basic competence in a very short amount of time (and without massive energy use). “Even if you’re put into a situation where you’ve never been before, you can still figure it out,” Baker said. “If you see a new object, you don’t have to be trained on that a thousand times to know how to use it. A lot of the time, [if] you see it one time, you can make predictions.”

As a result, while an AI system with sufficient training may ultimately outperform the human, the human will typically reach a high level of performance faster. And unlike an AI, a human’s performance doesn’t remain static. Incremental improvements and innovative approaches are both still possible. This also allows humans to adjust to changed circumstances more readily. An AI trained on the body of written material up until 2020 might struggle to comprehend teen-speak in 2030; humans could at least potentially adjust to the shifts in language. (Though maybe an AI trained to respond to confusing phrasing with “get off my lawn” would be indistinguishable.)

Finally, since the brain is a flexible learning device, the lessons learned from one skill can be applied to related skills. So the ability to recognize tones and read sheet music can help with the mastery of multiple musical instruments. Chemistry and cooking share overlapping skillsets. And when it comes to schooling, learning how to learn can be used to master a wide range of topics.

In contrast, it’s essentially impossible to use an AI model trained on one topic for much else. The biggest exceptions are large language models, which seem to be able to solve problems on a wide variety of topics if they’re presented as text. But here, there’s still a dependence on sufficient examples of similar problems appearing in the body of text the system was trained on. To give an example, something like ChatGPT can seem to be able to solve math problems, but it’s best at solving things that were discussed in its training materials; giving it something new will generally cause it to stumble.

Déjà vu

For Schain, however, the biggest difference between AI and biology is in terms of memory. For many AIs, “memory” is indistinguishable from the computational resources that allow it to perform a task and was formed during training. For the large language models, it includes both the weights of connections learned then and a narrow “context window” that encompasses any recent exchanges with a single user. In contrast, biological systems have a lifetime of memories to rely on.

“For AI, it’s very basic: It’s like the memory is in the weights [of connections] or in the context. But with a human brain, it’s a much more sophisticated mechanism, still to be uncovered. It’s more distributed. There is the short term and long term, and it has to do a lot with different timescales. Memory for the last second, a minute and a day or a year or years, and they all may be relevant.”

This lifetime of memories can be key to making intelligence general. It helps us recognize the possibilities and limits of drawing analogies between different circumstances or applying things learned in one context versus another. It provides us with insights that let us solve problems that we’ve never confronted before. And, of course, it also ensures that the horrible bit of pop music you were exposed to in your teens remains an earworm well into your 80s.

The differences between how brains and AIs handle memory, however, are very hard to describe. AIs don’t really have distinct memory, while the use of memory as the brain handles a task more sophisticated than navigating a maze is generally so poorly understood that it’s difficult to discuss at all. All we can really say is that there are clear differences there.

Facing limits

It’s difficult to think about AI without recognizing the enormous energy and computational resources involved in training one. And in this case, it’s potentially relevant. Brains have evolved under enormous energy constraints and continue to operate using well under the energy that a daily diet can provide. That has forced biology to figure out ways to optimize its resources and get the most out of the resources it does commit to.

In contrast, the story of recent developments in AI is largely one of throwing more resources at them. And plans for the future seem to (so far at least) involve more of this, including larger training data sets and ever more artificial neurons and connections among them. All of this comes at a time when the best current AIs are already using three orders of magnitude more neurons than we’d find in a fly’s brain and have nowhere near the fly’s general capabilities.

It remains possible that there is more than one route to those general capabilities and that some offshoot of today’s AI systems will eventually find a different route. But if it turns out that we have to bring our computerized systems closer to biology to get there, we’ll run into a serious roadblock: We don’t fully understand the biology yet.

“I guess I am not optimistic that any kind of artificial neural network will ever be able to achieve the same plasticity, the same generalizability, the same flexibility that a human brain has,” Baker said. “That’s just because we don’t even know how it gets it; we don’t know how that arises. So how do you build that into a system?”

John is Ars Technica’s science editor. He has a Bachelor of Arts in Biochemistry from Columbia University, and a Ph.D. in Molecular and Cell Biology from the University of California, Berkeley. When physically separated from his keyboard, he tends to seek out a bicycle, or a scenic location for communing with his hiking boots.

AI versus the brain and the race for general intelligence Read More »

11 standouts from Steam Next Fest’s thousands of free game demos

Demo impressions, Features, Game demos, gaming, steam, steam games / 9u50fv / February 26, 2025

Let Ars help you find some needles in Steam’s massive haystack of game trials.

If you head over to the Steam Next Fest charts right now, Valve will offer you a glimpse of the 2,228 games offering free downloadable demos as part of the event through Sunday, March 3. That is way too many games to effectively evaluate in such a short time, even with the massive resources of the Ars Orbiting HQ.

But we haven’t let that stop us from trying. With the assistance of some early access provided by Valve and game publishers, we’ve spent the last few days playing dozens and dozens of the most promising Next Fest demos in an attempt to pull out some interesting-looking needles from Valve’s massive haystack. Below are the results of that search—a varied list of 11 titles we think are worth investing some time (and zero dollars of money) into a demo download.

But this is just a starting point. Please use the comments below to share any other diamonds in the rough you think your fellow Ars readers need to know about.

Afterblast

Developer: Lumino Games

Planned release date: April 2025

Popular steam tags: FPS, Online Co-Op, Action Roguelike, Roguelite

Steam page

Start with the roguelike, room-based shooting action of Returnal. Move it to a first-person perspective and add in the double-jump-and-dash movement system of the new Doom games. Throw in a Halo Infinite-style grappling hook that can be used for traversal or combat. The result would come pretty close to Afterblast, a twitch-action shooter that shines from the jump in this fast-paced demo.

This is the kind of game where halting your movement for even a split second often means being instantly overwhelmed by enemies that swarm from all angles. Rather than being hard to handle, though, the game’s zippy movement makes it feel relatively simple to jump and dash from ledge to ledge, avoiding bullet-hell style projectile patterns as you do.

The grappling hook is by far the most satisfying part of the demo, though. Beyond jumping out of the way of opposing fire, you can also use it to drag yourself over to stunned enemies, exploding them into piles of goo and collectible items. Bouncing from enemy to enemy in this way, with a few well-placed jumps and dashes in between, felt like being a kid bouncing on a trampoline.

The Afterblast demo provides a feel for the game’s randomized item system, which gives access to automated drones, powerful grenades, and other superpowers that should make each run feel unique. We can’t wait to see more.

-Kyle Orland

Castle V Castle

Developer: Nopopo

Planned release date: “Coming soon”

Popular steam tags: Card Battler, Roguelite, Card Game, PvE

Steam page

If you remember cult-classic Flash game Castle Wars, you already know the basics of Castle V Castle. You and your opponent take turns using a handful of cards to either build up your own castle or break down the castle on the other side until one castle has been reduced to rubble. You then improve your deck and do it all again.

Playing effectively means figuring out when to attack, when to defend, and when to use cards to bulk up the various resources needed to play future cards. Strong play requires thinking a few moves ahead, both to avoid being left with a hand of unplayable cards and to counter or reflect potential incoming attacks from your opponent (or deny them the resources they might need).

An extremely clean black and white interface and quick, amusing animations make this a very easy game to pick up and play. But it’s the strategy of taking on short-term risks to get long-term rewards that will keep you coming back for round after round. And while the demo’s extremely punishing daily challenges are good for some continued longevity, we’re hoping the final game will add online multiplayer battles rather than just letting us beat down the AI over and over again.

-Kyle Orland

Dragonkin: The Banished

Developer: Eko Software

Planned release date: March 6, 2025 (Early Access)

Popular steam tags: Action, Hack and Slash, Adventure, RPG, Loot

Steam page

If you’ve grown tired of Diablo IV but are looking for another dark, mouse-based action RPG to scratch the same itch, Dragonkin: The Banished should be right up your alley. Just like in Diablo, the name of the game here is clicking to move and attack swarms of enemies in dark isometric dungeons, throwing in some magical attacks with the number keys on your keyboard as needed.

The Dragonkin demo leads you through a lot of extremely expository and overwrought cutscenes, broken up by short playable vignettes that introduce you to the main character classes: the heavy, the archer, the fire mage, etc. These introductory characters seem extremely overpowered for the early game, cutting through enemy grunts like butter while barely taking a scratch from underpowered opposition attacks. But it gives a good feel for the wide variety of available attacks available, from radiating lightning to a satisfying bull charge.

It’s only after this introduction that you’re thrown into a more standard challenge, clearing out a dungeon with a low-level character that needs all the help they can get. While the moment to moment gameplay will be familiar to Diablo heads, a few small touches like a handy dash-dodge maneuver make it all lean a bit more towards the “action” side of “action RPG.”

If you’re looking for pyrotechnic explosions, cinematic cut scenes, and plenty of things to click on, you could definitely do a lot worse.

-Kyle Orland

Glum

Developer: CinderCat Games

Planned release date: 2025

Popular steam tags: Adventure, Funny, Singleplayer

Steam page

First-person shooters are obviously all about the shooting—it’s right there in the name, after all. But the most satisfying part of these games is often running right up to an enemy and pounding them with a suspiciously powerful close-range melee attack.

Glum takes this satisfying melee bit and makes it the focus of the whole game. Instead of fists or a bludgeoning weapon, though, your main melee weapon in Glum is a steel-toed boot. You’ll see that boot hovering menacingly and incongruously in front of you as you zip around vaguely medieval-themed rooms, charging back with a bent knee for perfectly timed strikes as soon as an enemy gets in your face.

The Glum demo already takes this “first-person booter” concept in some interesting directions, providing plenty of barrels and other heavy objects you can convert into single-use projectile weapons with a kick from the right angle. You can also kick off of walls and other angled surfaces to fly through the air in some surprisingly satisfying and floaty platforming, which is key to finding the many secrets hidden in the demo’s tutorial-esque rooms.

But the most satisfying part is still kicking an enemy directly and watching the ragdoll corpse fly off a wall and back toward your boot, where you can send it flying into other encroaching foes. The light-hearted comedy action is especially welcome in an industry that sometimes seems full of first-person games that are too full of themselves.

-Kyle Orland

Guntouchables

Developer: Game Swing

Planned release date: “To be announced”

Popular steam tags: Action Roguelike, Multiplayer, Post-apocalyptic

Steam page

Seeing and hearing the pre-game logo screen for Ghost Ship Games immediately puts my brain into Deep Rock Galactic mode: headset on, workday stress abandoned, beverage ready. Guntouchables, published by Ghost Ship and developed by Game Swing, could readily fit into that slot. It’s a multiplayer-first overhead shooter in which you and up to three other sausage-y folks with tiny stick legs grab loot, kill baddies, and get the heck out of there. If it’s been a moment since you and your squad have shot some things together, send them a message and link the demo.

A horde of mutants have overrun the world, and you and your fellow redneck preppers are having their moment. You pick a weapon, like the precise but slow hunting rifle or pray-and-spray SMG, and a character, each with their own secondary weapons and skill trees. The game shows you a map with stuff to grab or destroy and the car you need to reach to escape. Then you’re off, moving with WASD keys and aiming in a circle with a mouse. The demo wasn’t ready for controller play yet, but I could see it coming in the future (along with another justification for the trackpads on the Steam Deck).

I cajoled a friend into playing, and we had a great time, both blasting and winning, but also explaining to each other just how dumb that last move was. The game could do more to help you quickly identify and distinguish among your teammates, as they’re currently all green names and health bars. And an optional tutorial mission would go a long way to help explain weapon and item mechanics that we had to test out live. But it’s a demo, and the core experience—shoot, run, grab, swarm coming, panic—already feels plenty strong. There’s a goofy, lightly icky charm to the voice-overs and visuals, and the upgrade paths are pleasantly addictive. It’s a ridiculous game with a ridiculous name, and I recommend it.

-Kevin Purdy

Hyper Empire

Developer: Fair Weather Studios

Planned release date: Q1 2025

Popular steam tags: 4X, Turn-Based Strategy, Auto Battler, Strategy

Steam page

When you play an RPG or strategy game, do you spend hours just staring at the tech tree, trying to figure out the upgrade path that will maximize your power going forward? If so, you’ll probably love Hyper Empire, a super-condensed 4X space simulation where a good 80 percent of the game is spent staring at a menu screen and deciding how best to spend your limited resources.

That’s actually more interesting than it might initially sound. You need to spend money on a fleet of ships to defend your carrier from potential attack, of course. But spending too much on powerful ships means you can’t invest in the outpost stations and tools that will bring in even more resources (and more powerful ships) later in the run. The balance between short-term risk and long-term reward seems well-tuned for those who like to agonize over every potential decision.

When battles inevitably happen, they play out as automated orgies of interstellar explosions that can be a joy to watch, especially once you hit a critical mass of defensive ships. And while random happenings can influence your resources between those battles, none of them have seemed too impactful in the demo so far.

The biggest problem with Hyper Empires right now is that the demo caps out at 30 turns, right when the “just one more turn” resource-building loop is starting to get good. We can’t wait to continue to juggle a bunch of numbers like an intergalactic accountant in the full game.

-Kyle Orland

Monaco 2

Developer: Pocketwatch Games

Planned release date: 2025

Popular steam tags: Co-op, Heist, Indie, Arcade, Top-Down, Loot

Steam page

It’s been well over a decade since the first Monaco wowed us with its ultra-stylish overhead “heist simulator” gameplay. This long-delayed sequel keeps the same basic find-the-Macguffin-and-escape gameplay, but now with vibrant 3D graphics and more complex, multi-floor building layouts.

As with the first Monaco, this is a stealth game that doesn’t absolutely require stealth. Sure, it’s easier if you sneak by the guards and cameras without raising the alarm, using handy sightlines and quiet movements to avoid detection. But if you’re found, the game quickly transitions into something of a 3D game of Pac-Man, where you have to outrun the guards and use hidden corridors or hidey-holes to outsmart them.

The Monaco 2 demo includes four classes of thieves, each with their own unique way of distracting or avoiding the guards. I especially liked the socialite, who uses a toy poodle to charm nearby guards into ignoring her, and the tech specialist, who can use a drone to interact with doors and items while he hides in relative safety.

The updated 3D viewpoint loses some of the simplistic charm of the original’s overhead perspective. Still, this modernized version of the classic stealth game is incredibly easy to pick up and play, especially with a few friends in co-op mode.

-Kyle Orland

Monster Train 2

Developer: Shiny Shoe

Planned release date: “Coming Soon”

Popular steam tags: Strategy, Card Game, Roguelike, Demons, PvP

Steam page

Monster Train 2 is a lot more Monster Train. Given that the original is in my top five of all-time Steam game hours, I’m happy about that. Just 30 minutes into testing it, I had to tell myself, “No, this really is the last round,” and physically walk away to enforce it. Well, the last round, and then some upgrade shopping. OK, one more and then no more.

Monster Train 2 is, like the original, an amalgam of turn-based tactics and roguelike deckbuilding, with a heaven-versus-hell backstory that is arch, goofy, and entirely skippable. Enemies enter your train on the bottom of three decks and fight their way upward, turn by turn. Your card deck has hellish monsters that you place across three levels of your train and spells that can damage, buff your monsters, and debuff their misguided angels. The music is high-energy melodic metal, the art pops off the screen, and the challenge is largely the same: balancing momentary threats against the need to prepare for future baddies.

Besides new monsters, cards, and clans, the sequel adds some new things, all of which might add up to be a bit too much to manage for some folks. Hero-type creatures can have abilities with cooldowns. New card types include equipment you can put on creatures and abilities you can apply to train floors. You can customize your train and upgrade its core pyre with abilities. This demo had me forgetting monster abilities and feeling overwhelmed with where to focus my upgrades. And yet I had a good time, and I’ll probably learn a new approach to turn actions over time. Hell, after all, devours the indolent.

-Kevin Purdy

Reignbreaker

Developer: Studio Fizbin

Planned release date: March 18, 2025

Popular steam tags: Indie, Hack and Slash, Action Roguelike, Combat

Steam page

The surface similarities between Reignbreaker and Hades are hard to ignore. But Reignbreaker‘s flavor of isometric run-and-gun-and-bash gameplay sets itself apart instantly with an extremely compelling steampunk aesthetic, full of clanging metal sound effects and relentless robotic enemies. That extends to the art direction, with thick outlines making it easy to pick out the color-coded hazards from the dull blues and grays of the metal-and-stone backgrounds.

Reignbreaker also stands out for some extremely chunky-feeling melee attacks and a javelin that can be used for powerful ranged projectiles or slammed down as a temporary turret. Tight controls make it a joy to dash between enemy projectiles as you wait for the opportune moment to go in for the kill. The Reignbreaker demo also shows off a few of the powerful bosses that will require most players to acquire a few permanent power-ups before making it too deep into the game’s randomized corridors.

This is one to keep an eye on as Hades 2 continues to barrel through Early Access toward its eventual final release

-Kyle Orland

Shuffle Tactics

Developer: Club Sandwich

Planned release date: “Coming soon”

Popular steam tags: Singleplayer, Roguelike, Tactical RPG, Isometric

Steam page

Like any good game with the word “Tactics” in its title, Shuffle Tactics is all about positioning. Move your units on a grid to maximize the damage they can inflict on enemies while minimizing the counterattacks that will inevitably come on their next turn. You know the drill.

But Shuffle Tactics adds just a hint of Slay the Spire into the mix, limiting your actions to those drawn from a deck of cards that you can build and modify between battles. As the game goes on, that means you might not be sure what options will be available on your next turn, forcing some quick improvisation if you want to maximize your chances.

I’m already a big fan of the demo’s satisfying sword-throwing mechanic, which lets you toss your melee weapon for a ranged attack and then call it back for more damage when it returns to your hand. I’m also enamored with the game’s evocative pixel-art animations, which make every movement and attack a joy to watch.

My biggest problem is that the demo gets very difficult very quickly; I had quite a few runs fall apart incredibly early when faced with an unavoidable “Elite” matchup that I wasn’t yet powerful enough to conquer. Hopefully. the developer can work out the balancing issues before launch because this mix of tactical strategy and card-based luck is a match made in heaven.

-Kyle Orland

Squirreled Away

Developer: Far Seas

Planned release date: “Coming soon”

Popular steam tags: Exploration, Third Person, Cute, Relaxing

Steam page

“Be the squirrel” is Far Seas’ description of its upcoming game, and while that’s a big promise, Squirreled Away seems on track to deliver. You’re not just a squirrel, mind you, but a tool-crafting, home-building, achievement-unlocking squirrel, owing to the demands of the gaming format. But when moving around, you get to experience the manic, sticky-pawed, and often weightless nature of squirreldom. Why do squirrels run corkscrews around the perimeter of a tree instead of climbing straight up? Maybe because, like me, they’re trying to keep up with their camera view on their right controller stick while moving with the left.

Squirreled Away‘s demo gives you a taste of its core mechanics, like stashing away items in a cache for winter or building an axe out of a pebble and twig so you can break larger branches into sticks for a fellow squirrel. The look, feel, and sound of the experience are decidedly calm, with single-instrument melodies lilting in and out as you scamper about, gather resources, and unlock quests and areas. You have health and stamina bars, but the game is gentle if you run them out, sending you back to safety or reminding you to eat some food.

It feels like a more kinetic Animal Crossing, with friendly animals and low-stakes challenges. Except that at any time, you could bail on your tasks, scamper upward, and leap from one far-out branch to another, living out the daydreams of anybody who works next to a window overlooking a tree.

– Kevin Purdy

Kyle Orland has been the Senior Gaming Editor at Ars Technica since 2012, writing primarily about the business, tech, and culture behind video games. He has journalism and computer science degrees from University of Maryland. He once wrote a whole book about Minesweeper.

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Reddit mods are fighting to keep AI slop off subreddits. They could use help.

AI, Features, generative ai, reddit, Social Media, Tech / Mike M. / February 18, 2025

Mods ask Reddit for tools as generative AI gets more popular and inconspicuous.

Credit: Aurich Lawson (based on a still from Getty Images)

Like it or not, generative AI is carving out its place in the world. And some Reddit users are definitely in the “don’t like it” category. While some subreddits openly welcome AI-generated images, videos, and text, others have responded to the growing trend by banning most or all posts made with the technology.

To better understand the reasoning and obstacles associated with these bans, Ars Technica spoke with moderators of subreddits that totally or partially ban generative AI. Almost all these volunteers described moderating against generative AI as a time-consuming challenge they expect to get more difficult as time goes on. And most are hoping that Reddit will release a tool to help their efforts.

It’s hard to know how much AI-generated content is actually on Reddit, and getting an estimate would be a large undertaking. Image library Freepik has analyzed the use of AI-generated content on social media but leaves Reddit out of its research because “it would take loads of time to manually comb through thousands of threads within the platform,” spokesperson Bella Valentini told me. For its part, Reddit doesn’t publicly disclose how many Reddit posts involve generative AI use.

To be clear, we’re not suggesting that Reddit has a large problem with generative AI use. By now, many subreddits seem to have agreed on their approach to AI-generated posts, and generative AI has not superseded the real, human voices that have made Reddit popular.

Still, mods largely agree that generative AI will likely get more popular on Reddit over the next few years, making generative AI modding increasingly important to both moderators and general users. Generative AI’s rising popularity has also had implications for Reddit the company, which in 2024 started licensing Reddit posts to train the large language models (LLMs) powering generative AI.

(Note: All the moderators I spoke with for this story requested that I use their Reddit usernames instead of their real names due to privacy concerns.)

No generative AI allowed

When it comes to anti-generative AI rules, numerous subreddits have zero-tolerance policies, while others permit posts that use generative AI if it’s combined with human elements or is executed very well. These rules task mods with identifying posts using generative AI and determining if they fit the criteria to be permitted on the subreddit.

Many subreddits have rules against posts made with generative AI because their mod teams or members consider such posts “low effort” or believe AI is counterintuitive to the subreddit’s mission of providing real human expertise and creations.

“At a basic level, generative AI removes the human element from the Internet; if we allowed it, then it would undermine the very point of r/AskHistorians, which is engagement with experts,” the mods of r/AskHistorians told me in a collective statement.

The subreddit’s goal is to provide historical information, and its mods think generative AI could make information shared on the subreddit less accurate. “[Generative AI] is likely to hallucinate facts, generate non-existent references, or otherwise provide misleading content,” the mods said. “Someone getting answers from an LLM can’t respond to follow-ups because they aren’t an expert. We have built a reputation as a reliable source of historical information, and the use of [generative AI], especially without oversight, puts that at risk.”

Similarly, Halaku, a mod of r/wheeloftime, told me that the subreddit’s mods banned generative AI because “we focus on genuine discussion.” Halaku believes AI content can’t facilitate “organic, genuine discussion” and “can drown out actual artwork being done by actual artists.”

The r/lego subreddit banned AI-generated art because it caused confusion in online fan communities and retail stores selling Lego products, r/lego mod Mescad said. “People would see AI-generated art that looked like Lego on [I]nstagram or [F]acebook and then go into the store to ask to buy it,” they explained. “We decided that our community’s dedication to authentic Lego products doesn’t include AI-generated art.”

Not all of Reddit is against generative AI, of course. Subreddits dedicated to the technology exist, and some general subreddits permit the use of generative AI in some or all forms.

“When it comes to bans, I would rather focus on hate speech, Nazi salutes, and things that actually harm the subreddits,” said 3rdusernameiveused, who moderates r/consoom and r/TeamBuilder25, which don’t ban generative AI. “AI art does not do that… If I was going to ban [something] for ‘moral’ reasons, it probably won’t be AI art.”

“Overwhelmingly low-effort slop”

Some generative AI bans are reflective of concerns that people are not being properly compensated for the content they create, which is then fed into LLM training.

Mod Mathgeek007 told me that r/DeadlockTheGame bans generative AI because its members consider it “a form of uncredited theft,” adding:

You aren’t allowed to sell/advertise the workers of others, and AI in a sense is using patterns derived from the work of others to create mockeries. I’d personally have less of an issue with it if the artists involved were credited and compensated—and there are some niche AI tools that do this.

Other moderators simply think generative AI reduces the quality of a subreddit’s content.

“It often just doesn’t look good… the art can often look subpar,” Mathgeek007 said.

Similarly, r/videos bans most AI-generated content because, according to its announcement, the videos are “annoying” and “just bad video” 99 percent of the time. In an online interview, r/videos mod Abrownn told me:

It’s overwhelmingly low-effort slop thrown together simply for views/ad revenue. The creators rarely care enough to put real effort into post-generation [or] editing of the content [and] rarely have coherent narratives [in] the videos, etc. It seems like they just throw the generated content into a video, export it, and call it a day.

An r/fakemon mod told me, “I can’t think of anything more low-effort in terms of art creation than just typing words and having it generated for you.”

Some moderators say generative AI helps people spam unwanted content on a subreddit, including posts that are irrelevant to the subreddit and posts that attack users.

“[Generative AI] content is almost entirely posted for purely self promotional/monetary reasons, and we as mods on Reddit are constantly dealing with abusive users just spamming their content without regard for the rules,” Abrownn said.

A moderator of the r/wallpaper subreddit, which permits generative AI, disagrees. The mod told me that generative AI “provides new routes for novel content” in the subreddit and questioned concerns about generative AI stealing from human artists or offering lower-quality work, saying those problems aren’t unique to generative AI:

Even in our community, we observe human-generated content that is subjectively low quality (poor camera/[P]hotoshopping skills, low-resolution source material, intentional “shitposting”). It can be argued that AI-generated content amplifies this behavior, but our experience (which we haven’t quantified) is that the rate of such behavior (whether human-generated or AI-generated content) has not changed much within our own community.

But we’re not a very active community—[about] 13 posts per day … so it very well could be a “frog in boiling water” situation.

Generative AI “wastes our time”

Many mods are confident in their ability to effectively identify posts that use generative AI. A bigger problem is how much time it takes to identify these posts and remove them.

The r/AskHistorians mods, for example, noted that all bans on the subreddit (including bans unrelated to AI) have “an appeals process,” and “making these assessments and reviewing AI appeals means we’re spending a considerable amount of time on something we didn’t have to worry about a few years ago.”

They added:

Frankly, the biggest challenge with [generative AI] usage is that it wastes our time. The time spent evaluating responses for AI use, responding to AI evangelists who try to flood our subreddit with inaccurate slop and then argue with us in modmail, [direct messages that message a subreddits’ mod team], and discussing edge cases could better be spent on other subreddit projects, like our podcast, newsletter, and AMAs, … providing feedback to users, or moderating input from users who intend to positively contribute to the community.

Several other mods I spoke with agree. Mathgeek007, for example, named “fighting AI bros” as a common obstacle. And for r/wheeloftime moderator Halaku, the biggest challenge in moderating against generative AI is “a generational one.”

“Some of the current generation don’t have a problem with it being AI because content is content, and [they think] we’re being elitist by arguing otherwise, and they want to argue about it,” they said.

A couple of mods noted that it’s less time-consuming to moderate subreddits that ban generative AI than it is to moderate those that allow posts using generative AI, depending on the context.

“On subreddits where we allowed AI, I often take a bit longer time to actually go into each post where I feel like… it’s been AI-generated to actually look at it and make a decision,” explained N3DSdude, a mod of several subreddits with rules against generative AI, including r/DeadlockTheGame.

MyarinTime, a moderator for r/lewdgames, which allows generative AI images, highlighted the challenges of identifying human-prompted generative AI content versus AI-generated content prompted by a bot:

When the AI bomb started, most of those bots started using AI content to work around our filters. Most of those bots started showing some random AI render, so it looks like you’re actually talking about a game when you’re not. There’s no way to know when those posts are legit games unless [you check] them one by one. I honestly believe it would be easier if we kick any post with [AI-]generated image… instead of checking if a button was pressed by a human or not.

Mods expect things to get worse

Most mods told me it’s pretty easy for them to detect posts made with generative AI, pointing to the distinct tone and favored phrases of AI-generated text. A few said that AI-generated video is harder to spot but still detectable. But as generative AI gets more advanced, moderators are expecting their work to get harder.

In a joint statement, r/dune mods Blue_Three and Herbalhippie said, “AI used to have a problem making hands—i.e., too many fingers, etc.—but as time goes on, this is less and less of an issue.”

R/videos’ Abrownn also wonders how easy it will be to detect AI-generated Reddit content “as AI tools advance and content becomes more lifelike.”

Mathgeek007 added:

AI is becoming tougher to spot and is being propagated at a larger rate. When AI style becomes normalized, it becomes tougher to fight. I expect generative AI to get significantly worse—until it becomes indistinguishable from ordinary art.

Moderators currently use various methods to fight generative AI, but they’re not perfect. r/AskHistorians mods, for example, use “AI detectors, which are unreliable, problematic, and sometimes require paid subscriptions, as well as our own ability to detect AI through experience and expertise,” while N3DSdude pointed to tools like Quid and GPTZero.

To manage current and future work around blocking generative AI, most of the mods I spoke with said they’d like Reddit to release a proprietary tool to help them.

“I’ve yet to see a reliable tool that can detect AI-generated video content,” Aabrown said. “Even if we did have such a tool, we’d be putting hundreds of hours of content through the tool daily, which would get rather expensive rather quickly. And we’re unpaid volunteer moderators, so we will be outgunned shortly when it comes to detecting this type of content at scale. We can only hope that Reddit will offer us a tool at some point in the near future that can help deal with this issue.”

A Reddit spokesperson told me that the company is evaluating what such a tool could look like. But Reddit doesn’t have a rule banning generative AI overall, and the spokesperson said the company doesn’t want to release a tool that would hinder expression or creativity.

For now, Reddit seems content to rely on moderators to remove AI-generated content when appropriate. Reddit’s spokesperson added:

Our moderation approach helps ensure that content on Reddit is curated by real humans. Moderators are quick to remove content that doesn’t follow community rules, including harmful or irrelevant AI-generated content—we don’t see this changing in the near future.

Making a generative AI Reddit tool wouldn’t be easy

Reddit is handling the evolving concerns around generative AI as it has handled other content issues, including by leveraging AI and machine learning tools. Reddit’s spokesperson said that this includes testing tools that can identify AI-generated media, such as images of politicians.

But making a proprietary tool that allows moderators to detect AI-generated posts won’t be easy, if it happens at all. The current tools for detecting generative AI are limited in their capabilities, and as generative AI advances, Reddit would need to provide tools that are more advanced than the AI-detecting tools that are currently available.

That would require a good deal of technical resources and would also likely present notable economic challenges for the social media platform, which only became profitable last year. And as noted by r/videos moderator Abrownn, tools for detecting AI-generated video still have a long way to go, making a Reddit-specific system especially challenging to create.

But even with a hypothetical Reddit tool, moderators would still have their work cut out for them. And because Reddit’s popularity is largely due to its content from real humans, that work is important.

Since Reddit’s inception, that has meant relying on moderators, which Reddit has said it intends to keep doing. As r/dune mods Blue_Three and herbalhippie put it, it’s in Reddit’s “best interest that much/most content remains organic in nature.” After all, Reddit’s profitability has a lot to do with how much AI companies are willing to pay to access Reddit data. That value would likely decline if Reddit posts became largely AI-generated themselves.

But providing the technology to ensure that generative AI isn’t abused on Reddit would be a large challege. For now, volunteer laborers will continue to bear the brunt of generative AI moderation.

Advance Publications, which owns Ars Technica parent Condé Nast, is the largest shareholder of Reddit.

Scharon is a Senior Technology Reporter at Ars Technica writing news, reviews, and analysis on consumer gadgets and services. She’s been reporting on technology for over 10 years, with bylines at Tom’s Hardware, Channelnomics, and CRN UK.

Reddit mods are fighting to keep AI slop off subreddits. They could use help. Read More »

After 50 years, Ars staffers pick their favorite Saturday Night Live sketches

culture, Features, Saturday Night Live / DJ Henderson / February 15, 2025

“Do not taunt Happy Fun Ball.”

American musician Stevie Wonder (left) appears on an episode of ‘Saturday Night Live’ with comedian and actor Eddie Murphy, New York, New York, May 6, 1983. Credit: Anthony Barboza/Getty Images

The venerable late-night sketch comedy show Saturday Night Live is celebrating its 50th anniversary season this year. NBC will air a special on Sunday evening featuring current and former cast members.

I’ve long been a big fan of the show, since I was a kid in the late 1980s watching cast members such as Phil Hartman, Dana Carvey, and Jan Hooks. By then, the show was more than a decade old. It had already spawned huge Hollywood stars like Chevy Chase and Eddie Murphy and had gone through some near-death experiences as it struggled to find its footing.

The show most definitely does not appeal to some people. When I asked the Ars editorial team to share their favorite sketches, a few writers told me they had never found Saturday Night Live funny, hadn’t watched it in decades, or just did not get the premise of the show. Others, of course, love the show’s ability to poke fun at the cultural and political zeitgeist of the moment.

With the rise of the Internet, Saturday Night Live has become much more accessible. If you don’t care to watch live on Saturday night or record the show, its sketches are available on YouTube within a day or two. Not all of the show’s 10,000-odd sketches from the last five decades are available online, but many of them are.

With that said, here are some of our favorites!

Celebrity Hot Tub Party (Season 9)

Saturday Night Live has a thing for hot tubs, and it starts here, with the greatest of all hot tub parties.

Should you get in the water? Will it make you sweat?

Good god!

Celebrity Hot Tub.

—Ken Fisher

Papyrus (Season 43)

Some of SNL’s best skits satirize cultural touchstones that seem like they’d be way too niche but actually resonate broadly with its audience—like Font Snobs, i.e., those people who sneer at fonts like Comic-Sans (you know who you are) in favor of more serious options like the all-time favorite Helvetica. (Seriously, Helvetica has its own documentary.)

In “Papyrus,” host Ryan Gosling played Steven, a man who becomes obsessed with the fact that the person who designed the Avatar logo chose to use Papyrus. “Was it laziness? Was it cruelty?” Why would any self-respecting graphic designer select the same font one sees all over in “hookah bars, Shakira merch, [and] off-brand teas”? The skit is played straight as a tense psychological thriller and ends with a frustrated Steven screaming, “I know what you did!” in front of the graphic designer’s house while the designer smirks in triumph.

There was even a sequel last year in which Gosling’s Steven is in a support group and seems to have recovered from the trauma of seeing the hated font everywhere—as long as he avoids triggers. Then he learns that the font for Avatar: The Way of Water is just Papyrus in bold.

So begins an elaborate plot to infiltrate a graphic designer awards event to confront his tormentor head-on. The twist: Steven achieves a personal epiphany instead and confronts the root of his trauma: the fact that he was never able to understand his father, Jonathan WingDings. “My dad was so hard to read,” a weeping Steven laments as he finally gets some much-needed closure. Like most sequels, it doesn’t quite capture the magic of the original, but it’s still a charming addition to the archive.

Papyrus.

—Jennifer Ouellette

Washington’s Dream (Season 49)

The only SNL skit known and loved by all my kids. Nate Bargatze is George Washington, who explains his dream of “liberty” to soldiers in his revolutionary army. Washington’s future America is heavy on bizarre weights, measures, and rules, though not quite so concerned about things like slavery.

Washington’s Dream.

—Nate Anderson

Commercial parodies

I’ve always been partial to SNL‘s commercial parodies, probably because I saw way too many similar (but earnest) commercials while watching terrestrial TV growing up.

The other good thing about the commercial format is that it’s hard to make them longer than about two minutes, so they don’t outstay their welcome like some other SNL sketches

It’s hard to pick just one, so I’ll give a trio, along with the bits I think about and/or quote regularly.

Old Glory Insurance: “I don’t even know why the scientists make them!” (Season 21)

Old Glory Insurance.

First Citywide Change Bank: “All the time, our customers ask us, ‘How do you make money doing this?’ The answer is simple: volume.” (Season 14)

First CityWide Change Bank.

Happy Fun Ball: “Do not taunt Happy Fun Ball” (Season 16)

Happy Fun Ball.

—Kyle Orland

Anything with Phil Hartman (Seasons 12 to 20)

Phil Hartman was a regular on Saturday Night Live throughout my high school and college years, and it was nice to know that on the rare Saturday night when I did not have a date or plans, he and the cast would be on television to provide entertainment. He was the “glue” guy during his time on the show, playing a variety of roles and holding the show together.

Here are some of his most memorable sketches, at least to me.

Anal Retentive Chef. Hartman acts as Gene, who is… well, anal retentive. He appeared in five different skits over the years. This is the first one. (Season 14)

The Anal Retentive Chef.

Hartman had incredible range. During his first year on the show, he played President Reagan, who at the time had acquired the reputation of becoming doddering and forgetful. However, as Hartman clearly shows us in this sketch, that is far from reality. (Season 12)

President Reagan, Mastermind.

And here he is a few years later, during the first year of President Clinton’s term in office. This skit also features Chris Farley, who was memorable in almost everything he appeared in. “Do you mind if I wash it down?” (Season 18)

President Bill Clinton at McDonald’s.

Kyle has noted commercial parodies above, and there are many good ones. Hartman often appeared in these because he did such a good job of playing the “straight man” character in comedy, the generally normal person in contrast to all of the wackiness happening in a scene. One of Hartman’s most famous commercials is for Colon Blow cereal. However, my favorite is this zany commercial for Jiffy Pop… Airbags. (Season 17)

Jiffy Pop Airbag.

—Eric Berger

Motherlover (Season 34)

The Lonely Island (an American comedy trio, formed by Andy Samberg, Jorma Taccone, and Akiva Schaffer, which wrote comedy music videos) had bigger, more viral hits, but nothing surpasses the subversiveness of “to me, you’re like a brother, so be my motherlover.”

Motherlover.

—Jacob May

More Cowbell (Season 25)

This classic sketch gets featured on almost all SNL “best of” lists; “more cowbell” even made it into the dictionary. It’s a sendup of VH1’s “Behind the Music,” focused on the recording of Blue Oyster Cult’s 1975 hit “Don’t Fear the Reaper,” which features a distinctive percussive cowbell in the background. Will Ferrell is perfection as fictional cowbell player Gene Frenkel, whose overly enthusiastic playing is a distraction to his bandmates. But Christopher Walken’s “legendary” (and fictional) producer Bruce Dickinson loves the cowbell, encouraging Gene to “really explore the studio space” with each successive take. “I gotta have more cowbell, baby!”

Things escalate as Gene’s playing first becomes too flamboyant, and then passive-aggressive, until the band works through its tensions and decides to embrace the cowbell after all. The comic timing is spot on, and the cast doesn’t let the joke run too long (a common flaw in lesser SNL skits). Ferrell’s physical antics and Walken’s brilliantly deadpan delivery—”I got a fever and the only prescription is more cowbell!”—has the cast on the verge of breaking character throughout. It deserves its place in the pantheon of SNL‘s best.

More Cowbell.

—Jennifer Ouellette

The Californians (Season 37-present day)

I was going to go with Old Glory Insurance as my favorite SNL skit, but since Kyle already grabbed that one, I have to fall back on some of my runners-up. And although the Microsoft Robots and Career Day and even good ol’ Jingleheimer Junction almost topped my list, ultimately, I have to give it up to the recurring SNL skit that has probably given me more joy than anything the show has done since John Belushi’s samurai librarian. I am speaking of The Californians.

This fake soap opera, featuring a cast of perpetually blonde, perpetually unfaithful, perpetually directions-obsessed California stereotypes hits me just right. The elements that get repeated in every skit (including and especially Fred Armisen’s inevitable “WHATAREYUUUUDUUUUUUUINGHERE” or the locally produced furniture that everyone makes a point of using in the second act) are the kind of absurdities that get funnier over time, and it’s awesome to see guest stars try on the hyper-SoCal accent that is mandatory for all characters in the Californians’ universe.

Special props to Kristen Wiig, too—she’s inevitably hilarious, but her incredulous line reading when Mick Jagger shows up as Stuart’s long-absent father (“STUART! You never told me you had a dad!”) can and will fully send me into doubled-over hysterics every single time.

The Californians.

—Lee Hutchinson

What’s the fuss about?

In more than 20 years of living in the United States, few things still remain as far outside my cultural frame of reference as SNL. Whenever someone makes an unintelligible joke in Slack (or IRC before it) and everyone laughs, it invariably turns out to be some SNL thing that anyone who grew up here instinctively understands.

To me, it was always just *crickets*.

—Jonathan Gitlin

Black Jeopardy (Season 42)

Kenan Thompson was the show’s first cast member born after SNL‘s premiere in 1975, and after joining the show in 2003, he has become its longest-running cast member. Whenever he is on screen, you know you’re about to see something hilarious. One of his best roles on SNL has become the “game show host,” with long-running bits on Family Feud and the absurdly hilarious Black Jeopardy. The most famous of these latter skits occurred in 2016, when Tom Hanks appeared. If you haven’t watched it, you really must.

Black Jeopardy.

—Eric Berger

Josh Acid (Season 15)

One of my favorite SNL sketches (and perhaps one of the most underrated) is an Old West send-up featuring a sheriff named “Josh Acid” (played by Mel Gibson during his hosting appearance in 1989), who keeps two bottles of acid in holsters instead of the standard six-shooter revolvers.

The character is a hero in his town, but when he throws acid on people, their skin melts, and they die a horrible, gruesome death. The townspeople witness one such death and say it’s “gross.” In response, the main character cites Jim Bowie using a Bowie knife and says, “I use acid because that’s my name.” At one point, Kevin Nealon, as the bartender, says the town is grateful he’s cleaned up the place, but “it’s just that we’re not sure which is worse: lawlessness, or having to watch people die horribly from acid.”

Later, when a woman asks Josh to choose between her or acid, he says, “Frida, I took a job, and that job’s not done until every criminal in this territory is either behind bars or melted down.”

The sketch is just absurdly ridiculous in a delightful way, and it gleefully subverts the stoic nobility of the stereotypical Western hero, which is a trope baby boomers grew up with on TV. If I were to stretch, I’d also say it works because it lampoons the idea that some methods of legally or rightfully killing someone are more honorable and socially acceptable than others.

It’s not on YouTube that I can find, but I found a copy on TikTok.

—Benj Edwards

Hidden Camera Commercials (Season 17)

For me—and, I suspect, most people—there are several “golden ages” of SNL. But if I had to pick just one, it would be the Chris Farley era. The crown jewel of Farley’s SNL tenure was certainly the Bob Odenkirk- penned “Van Down by the River.” Today, though, I’d like to highlight a deeper cut: a coffee commercial in which Farley’s character is told he is drinking decaf coffee instead of regular. Instead of being delighted that he can’t tell the difference in taste, he gets… ANGRY.

Farley’s incredulous “what?” and dawning rage at being deceived never fail to make me laugh.

Hidden Camera Commercials.

—Aaron Zimmerman

Wake Up and Smile (Season 21)

SNL loves to take a simple idea and repeat it—sometimes without enough progression. But “Wake Up and Smile” stands out by following its simple idea (perky morning show hosts are lost without their teleprompters) into an incredibly dark place. In six minutes, you can watch the polished veneer of civilization collapse into tribal violence, all within the absurdist confines of a vapid TV show. In the end, everyone wakes from their temporary dystopian dreamland. Well, except for the weatherman.

Wake Up and Smile

—Nate Anderson

Thanks, Nate, and everyone who contributed. Indeed, one of the joys of watching the show live is you never know when a sketch is going to dark or very, very dark.

Eric Berger is the senior space editor at Ars Technica, covering everything from astronomy to private space to NASA policy, and author of two books: Liftoff, about the rise of SpaceX; and Reentry, on the development of the Falcon 9 rocket and Dragon. A certified meteorologist, Eric lives in Houston.

After 50 years, Ars staffers pick their favorite Saturday Night Live sketches Read More »

CenturyLink nightmares: Users keep asking Ars for help with multi-month outages

centurylink, Features, Policy / DJ Henderson / February 11, 2025

What were you waiting for?

After getting confirmation that the outages were fixed, we asked the CenturyLink spokesperson whether the company has “a plan to make sure that customer outages are always fixed when a customer contacts the company instead of waiting for a reporter to contact the company on the customer’s behalf weeks later.”

Here is the answer we got from CenturyLink: “Restoring customer service is a priority, and we apologized for the delay. We’re looking at why there was a repair delay.”

It appears that nothing has changed. Even as John’s problem was fixed, CenturyLink users in other states suffered even longer outages, and no one showed up for scheduled repair appointments. These outages weren’t fixed until late January—and only after the customers contacted us to ask for help.

Karen Kurt, a resident of Sheridan, Oregon, emailed us on January 23 to report that she had no CenturyLink DSL Internet service since November 4, 2024. One of her neighbors was also suffering through the months-long outage.

“We have set up repair tickets only to have them voided and/or canceled,” Kurt told us. “We have sat at home on the designated repair day from 8–5 pm, and no one shows up.” Kurt’s CenturyLink phone and Internet service costs $172.04 a month, according to a recent bill she provided us. Kurt said she also has frequent CenturyLink phone outages, including some stretches that occurred during the three-month Internet outage.

Separately, a CenturyLink customer named David Stromberg in Bellevue, Washington, told us that his phone service had been out since September 16. He repeatedly scheduled repair appointments, but the scheduled days went by with no repairs. “Every couple weeks, they do this and the tech doesn’t show up,” he said.

“Quick” fixes

As far as we can tell, there weren’t any complex technical problems preventing CenturyLink from ending these outages. Once the public relations department heard from Ars, CenturyLink sent technicians to each area, and the customers had their services restored.

On the afternoon of January 24, we contacted CenturyLink about the outage affecting Kurt and her neighbor. CenturyLink restored service for both houses less than three hours later, finally ending outages that lasted over 11 weeks.

On Sunday, January 26, we informed CenturyLink’s public relations team about the outage affecting Stromberg in Washington. Service was restored about 48 hours later, ending the phone outage that lasted well over four months.

As we’ve done in previous cases, we asked CenturyLink why the outages lasted so long and why the company repeatedly failed to show up for repair appointments. We did not receive any substantive answer. “Services have been restored, and appropriate credits will be provided,” the CenturyLink spokesperson replied.

Stromberg said getting the credit wasn’t so simple. “We contacted them after service was restored. They credited the full amount, but it took a few phone calls. They also gave us a verbal apology,” he told us. He said they pay $80.67 a month for CenturyLink phone service and that they get Internet access from Comcast.

Kurt said she had to call CenturyLink each month the outage dragged on to obtain a bill credit. Though the outage is over, she said her Internet access has been unreliable since the fix, with webpages often taking painfully long times to load.

Kurt has only a 1.5Mbps DSL connection, so it’s not a modern Internet connection even on a good day. CenturyLink told us it found no further problems on its end, so it appears that Kurt is stuck with what she has for now.

Desperation

“We are just desperate,” Kurt told us when she first reached out. Kurt, a retired teacher, said she and her husband were driving to a library to access the Internet and help grandchildren with schoolwork. She said there’s no reliable cell service in the area and that they are on a waiting list for Starlink satellite service.

Kurt said her husband once suggested they switch to a different Internet provider, and she pointed out that there aren’t any better options. On the Starlink website, entering their address shows they are in an area labeled as sold out.

Although repair appointments came and went without a fix, Kurt said she received emails from CenturyLink falsely claiming that service had been restored. Kurt said she spoke with technicians doing work nearby and asked if CenturyLink is trying to force people to drop the service because it doesn’t want to serve the area anymore.

Kurt said a technician replied that there are some areas CenturyLink doesn’t want to serve anymore but that her address isn’t on that list. A technician explained that they have too much work, she said.

CenturyLink has touted its investments in modern fiber networks but hasn’t upgraded the old copper lines in Kurt’s area and many others.

“This is DSL. No fiber here!” Kurt told us. “Sometimes when things are congested, you can make a sandwich while things download. I have been told that is because this area is like a glass of water. At first, there were only a few of us drinking out of the glass. Now, CenturyLink has many more customers drinking out of that same glass, and so things are slower/congested at various times of the day.”

Kurt said the service tends to work better in mid-morning, early afternoon, after 9 pm on weeknights, and on weekends. “Sometimes pages take a bit of time to load. That is especially frustrating while doing school work with my grandson and granddaughter,” she said.

CenturyLink Internet even slower than expected

After the nearly three-month outage ended, Kurt told us on January 27 that “many times, we will get Internet back for two or three days, only to lose it again.” This seemed to be what happened on Sunday, February 2, when Kurt told us her Internet stopped working again and that she couldn’t reach a human at CenturyLink. She restarted the router but could not open webpages.

We followed up with CenturyLink’s public relations department again, but this time, the company said its network was performing as expected. “We ran a check and called Karen regarding her service,” CenturyLink told us on February 3. “Everything looks good on our end, with no problems reported since the 24th. She mentioned that she could access some sites, but the speed seemed really slow. We reminded her that she has a 1.5Mbps service. Karen acknowledged this but felt it was slower than expected.”

Kurt told us that her Internet is currently slower than it was before the outage. “Before October, at least the webpages loaded,” she said. Now, “the pages either do not load, continue to attempt to load, or finally time out.”

While Kurt is suffering from a lack of broadband competition, municipalities sometimes build public broadband networks when private companies fail to adequately serve their residents. ISPs such as CenturyLink have lobbied against these efforts to expand broadband access.

In May 2024, we wrote about how public broadband advocates say they’ve seen a big increase in opposition from “dark money” groups that don’t have to reveal their donors. At the time, CenturyLink did not answer questions about specific donations but defended its opposition to government-operated networks.

“We know it will take everyone working together to close the digital divide,” CenturyLink told us then. “That’s why we partner with municipalities on their digital inclusion efforts by providing middle-mile infrastructure that supports last-mile networks. We have and will continue to raise legitimate concerns when government-owned networks create an anti-competitive environment. There needs to be a level playing field when it comes to permitting, right-of-way fees, and cross subsidization of costs.”

Stuck with CenturyLink

Kurt said that CenturyLink has set a “low bar” for its service, and it isn’t even meeting that low standard. “I do not use the Internet a lot. I do not use the Internet for gaming or streaming things. The Internet here would never be able to do that. But I do expect the pages to load properly and fully,” she said.

Kurt said she and her husband live in a house they built in 2007 and originally were led to believe that Verizon service would be available. “Prior to purchasing the property, we did our due diligence and sought out all utility providers… Verizon insisted it was their territory on at least two occasions,” she said.

But when it was time to install phone and Internet lines, it turned out Verizon didn’t serve the location, she said. This is another problem we’ve written about multiple times—ISPs incorrectly claiming to offer service in an area, only to admit they don’t after a resident moves in. (Verizon sold its Oregon wireline operations to Frontier in 2010.)

“We were stuck with CenturyLink,” and “CenturyLink did not offer Internet when we first built this home,” Kurt said. They subscribed to satellite Internet offered by WildBlue, which was acquired by ViaSat in 2009. They used satellite for several years until they could get CenturyLink’s DSL Internet.

Now they’re hoping to replace CenturyLink with Starlink, which uses low-Earth orbit satellites that offer faster service than older satellite services. They’re on the waiting list for Starlink and are interested in Amazon’s Kuiper satellite service, which isn’t available yet.

“We are hoping one of these two vendors will open up a spot for us and we can move our Internet over to satellite,” Kurt said. “We have also heard that Starlink and Amazon are going to be starting up phone service as well as Internet. That would truly be a gift to us. If we could move all of our services over to something reliable, our life would be made so much easier.”

Not enough technicians for copper network

John, the Colorado resident who had a three-week CenturyLink outage, said his default DSL speed is 10Mbps downstream and 2Mbps upstream. He doubled that by getting a second dedicated line to create a bonded connection, he said.

When John set up repair appointments during the outage, the “dates came and went without the typical ‘your tech’s on their way’ email, without anyone showing up,” he said. John said he repeatedly called CenturyLink and was told there was a bad cable that was being fixed.

“Every time I called, I’d get somebody who said that it was a bad cable and it was being fixed. Every single time, they’d say it would be fixed by 11 pm the following day,” he said. “It wasn’t, so I’d call again. I asked to talk with a supervisor, but that was always denied. Every time, they said they’d expedite the request. The people I talked with were all very nice and very apologetic about our outage, but they clearly stayed in their box.”

John still had the contact information for the CenturyLink technician who set up his bonded connection and messaged him around the same time he contacted Ars. When a CenturyLink employee finally showed up to fix the problem, he “found that our DSL was out because our modem was bad, and the phone was out because there was a bad dial-tone card in the closest pedestal. It took this guy less than an hour to get us back working—and it wasn’t a broken cable,” John said.

John praised CenturyLink’s local repair team but said his requests for repairs apparently weren’t routed to the right people. A CenturyLink manager told John that the local crew never got the repair ticket from the phone-based customer service team, he said.

The technician who fixed the service offered some insight into the local problems, John told us. “He said that in the mountains of western Boulder County, there are a total of five techs who know how to work with copper wire,” John told us. “All the other employees only work with fiber. CenturyLink is losing the people familiar with copper and not replacing them, even though copper is what the west half of the county depends on.”

Lumen says it has 1.08 million fiber broadband subscribers and 1.47 million “other broadband subscribers,” defined as “customers that primarily subscribe to lower speed copper-based broadband services marketed under the CenturyLink brand.”

John doesn’t know whether his copper line will ever be upgraded to fiber. His house is 1.25 miles from the nearest fiber box. “I wonder if they’ll eventually replace lines like the one to our house or if they’ll drop us as customers when the copper line eventually degrades to the point it’s not usable,” he said.

Jon is a Senior IT Reporter for Ars Technica. He covers the telecom industry, Federal Communications Commission rulemakings, broadband consumer affairs, court cases, and government regulation of the tech industry.

CenturyLink nightmares: Users keep asking Ars for help with multi-month outages Read More »

The Severance writer and cast on corporate cults, sci-fi, and more

Adam Scott, Apple, Apple TV, culture, Features, sci-fi, severance, streaming, TV / Kelly Newman / February 2, 2025

The following story contains light spoilers for season one of Severence but none for season 2.

The first season of Severance walked the line between science-fiction thriller and Office Space-like satire, using a clever conceit (characters can’t remember what happens at work while at home, and vice versa) to open up new storytelling possibilities.

It hinted at additional depths, but it’s really season 2’s expanded worldbuilding that begins to uncover additional themes and ideas.

After watching the first six episodes of season two and speaking with the series’ showrunner and lead writer, Dan Erickson, as well as a couple of members of the cast (Adam Scott and Patricia Arquette), I see a show that’s about more than critiquing corporate life. It’s about all sorts of social mechanisms of control. It’s also a show with a tremendous sense of style and deep influences in science fiction.

Corporation or cult?

When I started watching season 2, I had just finished watching two documentaries about cults—The Vow, about a multi-level marketing and training company that turned out to be a sex cult, and Love Has Won: The Cult of Mother God, about a small, Internet-based religious movement that believed its founder was the latest human form of God.

There were hints of cult influences in the Lumon corporate structure in season 1, but without spoiling anything, season 2 goes much deeper into them. As someone who has worked at a couple of very large media corporations, I enjoyed Severance’s send-up of corporate culture. And as someone who has worked in tech startups—both good and dysfunctional ones—and who grew up in a radical religious environment, I now enjoy its send-up of cult social dynamics and power plays.

Employees watch a corporate propaganda video — Lumon controls what information is presented to its employees to keep them in line. Credit: Apple

When I spoke with showrunner Dan Erickson and actor Patricia Arquette, I wasn’t surprised to learn that it wasn’t just me—the influence of stories about cults on season 2 was intentional.

Erickson explained:

I watched all the cult documentaries that I could find, as did the other writers, as did Ben, as did the actors. What we found as we were developing it is that there’s this weird crossover. There’s this weird gray zone between a cult and a company, or any system of power, especially one where there is sort of a charismatic personality at the top of it like Kier Eagan. You see that in companies that have sort of a reverence for their founder.

Arquette also did some research on cults. “Very early on when I got the pilot, I was pretty fascinated at that time with a lot of cult documentaries—Wild Wild Country, and I don’t know if you could call it a cult, but watching things about Scientology, but also different military schools—all kinds of things like that with that kind of structure, even certain religions,” she recalled.

The Severance writer and cast on corporate cults, sci-fi, and more Read More »

Weight saving and aero optimization feature in the 2025 Porsche 911 GT3

car review, Cars, Features, First drive, Porsche 911 GT3 / Beth Washington / January 29, 2025

Among the changes are better aero, shorter gearing, and the return of the Touring.

The Porsche 911 GT3 is to other 911s as other 911s are to regular cars. Credit: Jonathan Gitlin

VALENCIA, SPAIN—A Porsche 911 is rather special compared to most “normal” cars. The rear-engined sports car might be bigger and less likely to swap ends than the 1960s version, but it remains one of the more nimble and engaging four-wheeled vehicles you can buy. The 911 comes in a multitude of variants, but among driving enthusiasts, few are better regarded than the GT3. And Porsche has just treated the current 911 GT3 to its midlife refresh, which it will build in regular and Touring flavors.

The GT3 is a 911 you can drive to the track, spend the day lapping, and drive home again. It’s come a long way since the 1999 original—that car made less power than a base 911 does now. Now, the recipe is a bit more involved, with a naturally aspirated flat-six engine mounted behind the rear axle that generates 502 hp (375 kW) and 331 lb-ft (450 Nm) and a redline that doesn’t interrupt play until 9,000 rpm. You’ll need to exercise it to reach those outputs—peak power arrives at 8,500, although peak torque happens a bit sooner at around 6,000 revs.

It’s a mighty engine indeed, derived from the racing version of the 911, with some tweaks for road legality. So there are things like individual throttle valves, dry sump lubrication, solid cam finger followers (instead of hydraulic valve lifters), titanium con rods, and forged pistons.

I’ve always liked GT3s in white.

For this car, Porsche has also worked on reducing its emissions, fitting four catalytic converters to the exhaust, plus a pair of particulate filters, which together help cut NOx emissions on the US test cycle by 44 percent. This adds 3 lbs (1.4 kg) of mass and increases exhaust back pressure by 17 percent. But there are also new cylinder heads and reprofiled camshafts (from the even more focused, even more expensive GT3 RS), which increase drivability and power delivery in the upper rev range by keeping the valves open for longer.

Those tweaks might not be immediately noticeable when you look at last year’s GT3, but the shorter gearing definitely will be. The final drive ratios for both the standard seven-speed PDK dual-clutch gearbox and the six-speed manual have been reduced by 8 percent. This lowers the top speed a little—a mostly academic thing anyway outside of the German Autobahn and some very long runways—but it increases the pulling force on the rear wheels in each gear across the entire rev range. In practical terms, it means you can take a corner in a gear higher than you would in the old car.

There have been suspension tweaks, too. The GT3 moved to double front wishbone suspension (replacing the regular car’s MacPherson struts) in 2021, but now the front pivot point has been lowered to reduce the car diving under braking, and the trailing arms have a new teardrop profile that improves brake cooling and reduces drag a little. Porsche has altered the bump stops, giving the suspension an inch (24 mm) more travel at the front axle and slightly more (27 mm) at the rear axle, which in turn means more body control on bumpy roads.

A white Porsche 911 GT3 seen in profile

Credit: Porsche

New software governs the power steering. Because factors like manufacturing tolerances, wear, and even temperature can alter how steering components interact with each other, the software automatically tailors friction compensation to axle friction. Consequently, the steering is more precise and more linear in its behavior, particularly in the dead-ahead position.

The GT3 also has new front and rear fascias, again derived from the racing GT3. There are more cooling inlets, vents, and ducts, plus a new front diffuser that reduces lift at the front axle at speed. Porsche has tuned the GT3’s aerodynamics to be constant across the speed range, and like the old model, it generates around 309 lbs (140 kg) of downforce at 125 mph (200 km/h). Under the car, there are diffusers on the rear lower wishbones, and Porsche has improved brake and driveshaft cooling.

Finally, Porsche has made some changes to the interior. For instance, the GT3 now gains the same digital display seen on other facelifted 911s (the 992.2 generation if you’re a Porsche nerd), similar to the one you’d find in a Taycan, Macan, or Panamera.

Some people may mourn the loss of the big physical tachometer, but I’m not one of them. The car has a trio of UI settings: a traditional five-dial display, a more reduced three-dial display, and a track mode with just the big central tach, which you can reorient so the red line is at 12 o’clock, as was the case with many an old Porsche racing car, rather than its normal position down around 5 o’clock. And instead of a push button to start the car, there’s a twister—if a driver spins on track, it’s more intuitive to restart the car by twisting the control the way you would a key.

You can see the starter switch on the left of the steering wheel. Porsche

Finally, there are new carbon fiber seats, which now have folding backrests for better access to the rear. (However, unless I’m mistaken, you can’t adjust the angle of the backrest.) In a very clever and welcome touch, the headrest padding is removable so that your head isn’t forced forward when wearing a helmet on track. Such is the attention to detail here. (Customers can also spec the car with Porsche’s 18-way sports seats instead.)

Regular, Touring, Lightweight, Wiessach

In fact, the new GT3 is available in two different versions. There’s the standard car, with its massive rear wing (complete with gooseneck mounts), which is the one you’d pick if your diet included plenty of track days. For those who want a 911 that revs to 9 but don’t plan on spending every weekend chasing lap times, Porsche has reintroduced the GT3 Touring. This version ditches the rear wing for the regular 911 rear deck, the six-speed manual is standard (with PDK as an option), and you can even specify rear seats—traditionally, the GT3 has eliminated those items in favor of weight saving.

Of course, it’s possible to cut even more weight from the GT3 with the Weissach Pack for the winged car or a lightweight package for the Touring. These options involve lots of carbon fiber bits for the interior and the rear axle, a carbon fiber roof for the Touring, and even the option of a carbon fiber roll cage for the GT3. The lightweight package for the touring also includes an extra-short gear lever with a shorter throw.

The track mode display might be too minimalist for road driving—I tend to like being able to see my directions as well as the rpm and speed—but it’s perfect for track work. Note the redline at 12 o’clock. Porsche

Although Porsche had to add some weight to the 992.2 compared to the 992.1 thanks to thicker front brake discs and more door-side impact protection, the standard car still weighs just 3,172 lbs (1,439 kg), which you can reduce to 3,131 lbs (1,420 kg) if you fit all the lightweight goodies, including the ultra-lightweight magnesium wheels.

Behind the wheel

I began my day with a road drive in the GT3 Touring—a PDK model. Porsche wasn’t kidding about the steering. I hesitate to call it telepathic, as that’s a bit of a cliché, but it’s extremely direct, particularly the initial turn-in. There’s also plenty of welcome feedback from the front tires. In an age when far too many cars have essentially numb steering, the GT3 is something of a revelation. And it’s proof that electronic power steering can be designed and tuned to deliver a rewarding experience.

The cockpit ergonomics are spot-on, with plenty of physical controls rather than relegating everything to a touchscreen. If you’re short like me and you buy a GT3, you’ll want to have the buckets set for your driving position—while the seat adjusts for height, as you raise it up, it also pitches forward a little, making the seat back more vertical than I’d like. (The seats slide fore and aft, so they’re not quite fixed buckets as they would be in a racing car.)

The anti-dive effect of that front suspension is quite noticeable under braking, and in either Normal or Sport mode, the damper settings are well-calibrated for bumpy back roads. It’s a supple ride, if not quite a magic carpet. On the highway, the Touring cruises well, although the engine can start to sound a little droning at a constant rpm. But the highway is not what the GT3 is optimized for.

On a dusty or wet road, you need to be alert if you’re going to use a lot of throttle at low speed. Jonathan Gitlin

On windy mountain roads, again in Normal or Sport, the car comes alive. Second and third gears are perfect for these conditions, allowing you to keep the car within its power band. And boy, does it sound good as it howls between 7,000 and 9,000 rpm. Porsche’s naturally aspirated flat-sixes have a hard edge to them—the 911 RSR was always the loudest race car in the pack—and the GT3 is no exception. Even with the sports exhaust in fruity mode, there’s little of the pops, bangs, and crackles you might hear in other sports cars, but the drama comes from the 9000 rpm redline.

Porsche asked us to keep traction control and ESC enabled during our drive—there are one-touch buttons to disable them—and given the muddy and dusty state of the roads, this was a wise idea. (The region was beset by severe flooding recently, and there was plenty of evidence of that on the route.) Even with TC on, the rear wheels would break traction if you were injudicious with the throttle, and presumably that would be the same in the wet. But it’s very easy to catch, even if you are only of moderate driving ability, like your humble correspondent.

After lunch, it was time to try the winged car, this time on the confines of the Ricardo Torno circuit just outside the city. On track, the handling was very neutral around most of the corners, with some understeer through the very slow turn 2. While a low curb weight and more than 500 hp made for a very fast accelerating car, the braking performance was probably even more impressive, allowing you to stand on the pedal and shed speed with no fade and little disturbance to the body control. Again, I am no driving god, but the GT3 was immensely flattering on track, and unlike much older 911s, it won’t try to swap ends on you when trail-braking or the like.

The landing was not nearly as jarring as you might think. Porsche

After some time behind the wheel, I was treated to some passenger laps by one of my favorite racing drivers, the inimitable Jörg Bergmeister. Unlike us journalists, he was not required to stay off the high curbs, and he demonstrated how well the car settles after launching its right-side wheels into the air over one of them. It settles down very quickly! He also demonstrated that the GT3 can be plenty oversteer-y on the exit of corners if you know what you’re doing, aided by the rear-wheel steering. It’s a testament to his driving that I emerged from two passenger laps far sweatier than I was after lapping the track myself.

The GT3 and GT3 Touring should be available from this summer in the US, with a starting price of $222,500. Were I looking for a 911 for road driving, I think I might be more tempted by the much cheaper 911 Carrera T, which is also pared to the bone weight-wise but uses the standard 380 hp (283 kW) turbocharged engine (which is still more power than the original GT3 of 1999). That car delivers plenty of fun at lower speeds, so it’s probably more useable on back roads.

A green Porsche 911 GT3 seen at sunset — Credit: Porsche

But if you want a 911 for track work, this new GT3 is simply perfect.

Jonathan is the Automotive Editor at Ars Technica. He has a BSc and PhD in Pharmacology. In 2014 he decided to indulge his lifelong passion for the car by leaving the National Human Genome Research Institute and launching Ars Technica’s automotive coverage. He lives in Washington, DC.

Weight saving and aero optimization feature in the 2025 Porsche 911 GT3 Read More »

AI haters build tarpits to trap and trick AI scrapers that ignore robots.txt

ai crawlers, ai poisoning, ai scraping, Anthropic, Artificial Intelligence, bots, Cybersecurity, facebook, Features, Google, iocaine, LLMs, Meta, nepenthes, openai, Policy, quixotic, tarpits / Shannon Garcia / January 28, 2025

Making AI crawlers squirm

Attackers explain how an anti-spam defense became an AI weapon.

Last summer, Anthropic inspired backlash when its ClaudeBot AI crawler was accused of hammering websites a million or more times a day.

And it wasn’t the only artificial intelligence company making headlines for supposedly ignoring instructions in robots.txt files to avoid scraping web content on certain sites. Around the same time, Reddit’s CEO called out all AI companies whose crawlers he said were “a pain in the ass to block,” despite the tech industry otherwise agreeing to respect “no scraping” robots.txt rules.

Watching the controversy unfold was a software developer whom Ars has granted anonymity to discuss his development of malware (we’ll call him Aaron). Shortly after he noticed Facebook’s crawler exceeding 30 million hits on his site, Aaron began plotting a new kind of attack on crawlers “clobbering” websites that he told Ars he hoped would give “teeth” to robots.txt.

Building on an anti-spam cybersecurity tactic known as tarpitting, he created Nepenthes, malicious software named after a carnivorous plant that will “eat just about anything that finds its way inside.”

Aaron clearly warns users that Nepenthes is aggressive malware. It’s not to be deployed by site owners uncomfortable with trapping AI crawlers and sending them down an “infinite maze” of static files with no exit links, where they “get stuck” and “thrash around” for months, he tells users. Once trapped, the crawlers can be fed gibberish data, aka Markov babble, which is designed to poison AI models. That’s likely an appealing bonus feature for any site owners who, like Aaron, are fed up with paying for AI scraping and just want to watch AI burn.

Tarpits were originally designed to waste spammers’ time and resources, but creators like Aaron have now evolved the tactic into an anti-AI weapon. As of this writing, Aaron confirmed that Nepenthes can effectively trap all the major web crawlers. So far, only OpenAI’s crawler has managed to escape.

It’s unclear how much damage tarpits or other AI attacks can ultimately do. Last May, Laxmi Korada, Microsoft’s director of partner technology, published a report detailing how leading AI companies were coping with poisoning, one of the earliest AI defense tactics deployed. He noted that all companies have developed poisoning countermeasures, while OpenAI “has been quite vigilant” and excels at detecting the “first signs of data poisoning attempts.”

Despite these efforts, he concluded that data poisoning was “a serious threat to machine learning models.” And in 2025, tarpitting represents a new threat, potentially increasing the costs of fresh data at a moment when AI companies are heavily investing and competing to innovate quickly while rarely turning significant profits.

“A link to a Nepenthes location from your site will flood out valid URLs within your site’s domain name, making it unlikely the crawler will access real content,” a Nepenthes explainer reads.

The only AI company that responded to Ars’ request to comment was OpenAI, whose spokesperson confirmed that OpenAI is already working on a way to fight tarpitting.

“We’re aware of efforts to disrupt AI web crawlers,” OpenAI’s spokesperson said. “We design our systems to be resilient while respecting robots.txt and standard web practices.”

But to Aaron, the fight is not about winning. Instead, it’s about resisting the AI industry further decaying the Internet with tech that no one asked for, like chatbots that replace customer service agents or the rise of inaccurate AI search summaries. By releasing Nepenthes, he hopes to do as much damage as possible, perhaps spiking companies’ AI training costs, dragging out training efforts, or even accelerating model collapse, with tarpits helping to delay the next wave of enshittification.

“Ultimately, it’s like the Internet that I grew up on and loved is long gone,” Aaron told Ars. “I’m just fed up, and you know what? Let’s fight back, even if it’s not successful. Be indigestible. Grow spikes.”

Nepenthes instantly inspires another tarpit

Nepenthes was released in mid-January but was instantly popularized beyond Aaron’s expectations after tech journalist Cory Doctorow boosted a tech commentator, Jürgen Geuter, praising the novel AI attack method on Mastodon. Very quickly, Aaron was shocked to see engagement with Nepenthes skyrocket.

“That’s when I realized, ‘oh this is going to be something,'” Aaron told Ars. “I’m kind of shocked by how much it’s blown up.”

It’s hard to tell how widely Nepenthes has been deployed. Site owners are discouraged from flagging when the malware has been deployed, forcing crawlers to face unknown “consequences” if they ignore robots.txt instructions.

Aaron told Ars that while “a handful” of site owners have reached out and “most people are being quiet about it,” his web server logs indicate that people are already deploying the tool. Likely, site owners want to protect their content, deter scraping, or mess with AI companies.

When software developer and hacker Gergely Nagy, who goes by the handle “algernon” online, saw Nepenthes, he was delighted. At that time, Nagy told Ars that nearly all of his server’s bandwidth was being “eaten” by AI crawlers.

Already blocking scraping and attempting to poison AI models through a simpler method, Nagy took his defense method further and created his own tarpit, Iocaine. He told Ars the tarpit immediately killed off about 94 percent of bot traffic to his site, which was primarily from AI crawlers. Soon, social media discussion drove users to inquire about Iocaine deployment, including not just individuals but also organizations wanting to take stronger steps to block scraping.

Iocaine takes ideas (not code) from Nepenthes, but it’s more intent on using the tarpit to poison AI models. Nagy used a reverse proxy to trap crawlers in an “infinite maze of garbage” in an attempt to slowly poison their data collection as much as possible for daring to ignore robots.txt.

Taking its name from “one of the deadliest poisons known to man” from The Princess Bride, Iocaine is jokingly depicted as the “deadliest poison known to AI.” While there’s no way of validating that claim, Nagy’s motto is that the more poisoning attacks that are out there, “the merrier.” He told Ars that his primary reasons for building Iocaine were to help rights holders wall off valuable content and stop AI crawlers from crawling with abandon.

Tarpits aren’t perfect weapons against AI

Running malware like Nepenthes can burden servers, too. Aaron likened the cost of running Nepenthes to running a cheap virtual machine on a Raspberry Pi, and Nagy said that serving crawlers Iocaine costs about the same as serving his website.

But Aaron told Ars that Nepenthes wasting resources is the chief objection he’s seen preventing its deployment. Critics fear that deploying Nepenthes widely will not only burden their servers but also increase the costs of powering all that AI crawling for nothing.

“That seems to be what they’re worried about more than anything,” Aaron told Ars. “The amount of power that AI models require is already astronomical, and I’m making it worse. And my view of that is, OK, so if I do nothing, AI models, they boil the planet. If I switch this on, they boil the planet. How is that my fault?”

Aaron also defends against this criticism by suggesting that a broader impact could slow down AI investment enough to possibly curb some of that energy consumption. Perhaps due to the resistance, AI companies will be pushed to seek permission first to scrape or agree to pay more content creators for training on their data.

“Any time one of these crawlers pulls from my tarpit, it’s resources they’ve consumed and will have to pay hard cash for, but, being bullshit, the money [they] have spent to get it won’t be paid back by revenue,” Aaron posted, explaining his tactic online. “It effectively raises their costs. And seeing how none of them have turned a profit yet, that’s a big problem for them. The investor money will not continue forever without the investors getting paid.”

Nagy agrees that the more anti-AI attacks there are, the greater the potential is for them to have an impact. And by releasing Iocaine, Nagy showed that social media chatter about new attacks can inspire new tools within a few days. Marcus Butler, an independent software developer, similarly built his poisoning attack called Quixotic over a few days, he told Ars. Soon afterward, he received messages from others who built their own versions of his tool.

Butler is not in the camp of wanting to destroy AI. He told Ars that he doesn’t think “tools like Quixotic (or Nepenthes) will ‘burn AI to the ground.'” Instead, he takes a more measured stance, suggesting that “these tools provide a little protection (a very little protection) against scrapers taking content and, say, reposting it or using it for training purposes.”

But for a certain sect of Internet users, every little bit of protection seemingly helps. Geuter linked Ars to a list of tools bent on sabotaging AI. Ultimately, he expects that tools like Nepenthes are “probably not gonna be useful in the long run” because AI companies can likely detect and drop gibberish from training data. But Nepenthes represents a sea change, Geuter told Ars, providing a useful tool for people who “feel helpless” in the face of endless scraping and showing that “the story of there being no alternative or choice is false.”

Criticism of tarpits as AI weapons

Critics debating Nepenthes’ utility on Hacker News suggested that most AI crawlers could easily avoid tarpits like Nepenthes, with one commenter describing the attack as being “very crawler 101.” Aaron said that was his “favorite comment” because if tarpits are considered elementary attacks, he has “2 million lines of access log that show that Google didn’t graduate.”

But efforts to poison AI or waste AI resources don’t just mess with the tech industry. Governments globally are seeking to leverage AI to solve societal problems, and attacks on AI’s resilience seemingly threaten to disrupt that progress.

Nathan VanHoudnos is a senior AI security research scientist in the federally funded CERT Division of the Carnegie Mellon University Software Engineering Institute, which partners with academia, industry, law enforcement, and government to “improve the security and resilience of computer systems and networks.” He told Ars that new threats like tarpits seem to replicate a problem that AI companies are already well aware of: “that some of the stuff that you’re going to download from the Internet might not be good for you.”

“It sounds like these tarpit creators just mainly want to cause a little bit of trouble,” VanHoudnos said. “They want to make it a little harder for these folks to get” the “better or different” data “that they’re looking for.”

VanHoudnos co-authored a paper on “Counter AI” last August, pointing out that attackers like Aaron and Nagy are limited in how much they can mess with AI models. They may have “influence over what training data is collected but may not be able to control how the data are labeled, have access to the trained model, or have access to the Al system,” the paper said.

Further, AI companies are increasingly turning to the deep web for unique data, so any efforts to wall off valuable content with tarpits may be coming right when crawling on the surface web starts to slow, VanHoudnos suggested.

But according to VanHoudnos, AI crawlers are also “relatively cheap,” and companies may deprioritize fighting against new attacks on crawlers if “there are higher-priority assets” under attack. And tarpitting “does need to be taken seriously because it is a tool in a toolkit throughout the whole life cycle of these systems. There is no silver bullet, but this is an interesting tool in a toolkit,” he said.

Offering a choice to abstain from AI training

Aaron told Ars that he never intended Nepenthes to be a major project but that he occasionally puts in work to fix bugs or add new features. He said he’d consider working on integrations for real-time reactions to crawlers if there was enough demand.

Currently, Aaron predicts that Nepenthes might be most attractive to rights holders who want AI companies to pay to scrape their data. And many people seem enthusiastic about using it to reinforce robots.txt. But “some of the most exciting people are in the ‘let it burn’ category,” Aaron said. These people are drawn to tools like Nepenthes as an act of rebellion against AI making the Internet less useful and enjoyable for users.

Geuter told Ars that he considers Nepenthes “more of a sociopolitical statement than really a technological solution (because the problem it’s trying to address isn’t purely technical, it’s social, political, legal, and needs way bigger levers).”

To Geuter, a computer scientist who has been writing about the social, political, and structural impact of tech for two decades, AI is the “most aggressive” example of “technologies that are not done ‘for us’ but ‘to us.'”

“It feels a bit like the social contract that society and the tech sector/engineering have had (you build useful things, and we’re OK with you being well-off) has been canceled from one side,” Geuter said. “And that side now wants to have its toy eat the world. People feel threatened and want the threats to stop.”

As AI evolves, so do attacks, with one 2021 study showing that increasingly stronger data poisoning attacks, for example, were able to break data sanitization defenses. Whether these attacks can ever do meaningful destruction or not, Geuter sees tarpits as a “powerful symbol” of the resistance that Aaron and Nagy readily joined.

“It’s a great sign to see that people are challenging the notion that we all have to do AI now,” Geuter said. “Because we don’t. It’s a choice. A choice that mostly benefits monopolists.”

Tarpit creators like Nagy will likely be watching to see if poisoning attacks continue growing in sophistication. On the Iocaine site—which, yes, is protected from scraping by Iocaine—he posted this call to action: “Let’s make AI poisoning the norm. If we all do it, they won’t have anything to crawl.”

Ashley is a senior policy reporter for Ars Technica, dedicated to tracking social impacts of emerging policies and new technologies. She is a Chicago-based journalist with 20 years of experience.

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Nvidia GeForce RTX 5090 costs as much as a whole gaming PC—but it sure is fast

Blackwell, dlss, dlss4, Features, gaming, geforce 5090, NVIDIA, nvidia dlss, rtx, rtx 5090, Tech / 9u50fv / January 24, 2025

Even setting aside Frame Generation, this is a fast, power-hungry $2,000 GPU.

Credit: Andrew Cunningham

Nvidia’s GeForce RTX 5090 starts at $1,999 before you factor in upsells from the company’s partners or price increases driven by scalpers and/or genuine demand. It costs more than my entire gaming PC.

The new GPU is so expensive that you could build an entire well-specced gaming PC with Nvidia’s next-fastest GPU in it—the $999 RTX 5080, which we don’t have in hand yet—for the same money, or maybe even a little less with judicious component selection. It’s not the most expensive GPU that Nvidia has ever launched—2018’s $2,499 Titan RTX has it beat, and 2022’s RTX 3090 Ti also cost $2,000—but it’s safe to say it’s not really a GPU intended for the masses.

At least as far as gaming is concerned, the 5090 is the very definition of a halo product; it’s for people who demand the best and newest thing regardless of what it costs (the calculus is probably different for deep-pocketed people and companies who want to use them as some kind of generative AI accelerator). And on this front, at least, the 5090 is successful. It’s the newest and fastest GPU you can buy, and the competition is not particularly close. It’s also a showcase for DLSS Multi-Frame Generation, a new feature unique to the 50-series cards that Nvidia is leaning on heavily to make its new GPUs look better than they already are.

Founders Edition cards: Design and cooling

	RTX 5090	RTX 4090	RTX 5080	RTX 4080 Super
CUDA cores	21,760	16,384	10,752	10,240
Boost clock	2,410 MHz	2,520 MHz	2,617 MHz	2,550 MHz
Memory bus width	512-bit	384-bit	256-bit	256-bit
Memory bandwidth	1,792 GB/s	1,008 GB/s	960 GB/s	736 GB/s
Memory size	32GB GDDR7	24GB GDDR6X	16GB GDDR7	16GB GDDR6X
TGP	575 W	450 W	360 W	320 W

We won’t spend too long talking about the specific designs of Nvidia’s Founders Edition cards since many buyers will experience the Blackwell GPUs with cards from Nvidia’s partners instead (the cards we’ve seen so far mostly look like the expected fare: gargantuan triple-slot triple-fan coolers, with varying degrees of RGB). But it’s worth noting that Nvidia has addressed a couple of my functional gripes with the 4090/4080-series design.

The first was the sheer dimensions of each card—not an issue unique to Nvidia, but one that frequently caused problems for me as someone who tends toward ITX-based PCs and smaller builds. The 5090 and 5080 FE designs are the same length and height as the 4090 and 4080 FE designs, but they only take up two slots instead of three, which will make them an easier fit for many cases.

Nvidia has also tweaked the cards’ 12VHPWR connector, recessing it into the card and mounting it at a slight angle instead of having it sticking straight out of the top edge. The height of the 4090/4080 FE design made some cases hard to close up once you factored in the additional height of a 12VHPWR cable or Nvidia’s many-tentacled 8-pin-to-12VHPWR adapter. The angled connector still extends a bit beyond the top of the card, but it’s easier to tuck the cable away so you can put the side back on your case.

Finally, Nvidia has changed its cooler—whereas most OEM GPUs mount all their fans on the top of the GPU, Nvidia has historically placed one fan on each side of the card. In a standard ATX case with the GPU mounted parallel to the bottom of the case, this wasn’t a huge deal—there’s plenty of room for that air to circulate inside the case and to be expelled by whatever case fans you have installed.

But in “sandwich-style” ITX cases, where a riser cable wraps around so the GPU can be mounted parallel to the motherboard, the fan on the bottom side of the GPU was poorly placed. In many sandwich-style cases, the GPU fan will dump heat against the back of the motherboard, making it harder to keep the GPU cool and creating heat problems elsewhere besides. The new GPUs mount both fans on the top of the cards.

Nvidia’s Founders Edition cards have had heat issues in the past—most notably the 30-series GPUs—and that was my first question going in. A smaller cooler plus a dramatically higher peak power draw seems like a recipe for overheating.

Temperatures for the various cards we re-tested for this review. The 5090 FE is the toastiest of all of them, but it still has a safe operating temperature.

At least for the 5090, the smaller cooler does mean higher temperatures—around 10 to 12 degrees Celsius higher when running the same benchmarks as the RTX 4090 Founders Edition. And while temperatures of around 77 degrees aren’t hugely concerning, this is sort of a best-case scenario, with an adequately cooled testbed case with the side panel totally removed and ambient temperatures at around 21° or 22° Celsius. You’ll just want to make sure you have a good amount of airflow in your case if you buy one of these.

Testbed notes

A new high-end Nvidia GPU is a good reason to tweak our test bed and suite of games, and we’ve done both here. Mainly, we added a 1050 W Thermaltake Toughpower GF A3 power supply—Nvidia recommends at least 1000 W for the 5090, and this one has a native 12VHPWR connector for convenience. We’ve also swapped the Ryzen 7 7800X3D for a slightly faster Ryzen 7 9800X3D to reduce the odds that the CPU will bottleneck performance as we try to hit high frame rates.

As for the suite of games, we’ve removed a couple of older titles and added some with built-in benchmarks that will tax these GPUs a bit more, especially at 4K with all the settings turned up. Those games include the RT Overdrive preset in the perennially punishing Cyberpunk 2077 and Black Myth: Wukong in Cinematic mode, both games where even the RTX 4090 struggles to hit 60 fps without an assist from DLSS. We’ve also added Horizon Zero Dawn Remastered, a recent release that doesn’t include ray-tracing effects but does support most DLSS 3 and FSR 3 features (including FSR Frame Generation).

We’ve tried to strike a balance between games with ray-tracing effects and games without it, though most AAA games these days include it, and modern GPUs should be able to handle it well (best of luck to AMD with its upcoming RDNA 4 cards).

For the 5090, we’ve run all tests in 4K—if you don’t care about running games in 4K, even if you want super-high frame rates at 1440p or for some kind of ultrawide monitor, the 5090 is probably overkill. When we run upscaling tests, we use the newest DLSS version available for Nvidia cards, the newest FSR version available for AMD cards, and the newest XeSS version available for Intel cards (not relevant here, just stating for the record), and we use the “Quality” setting (at 4K, that equates to an actual rendering version of 1440p).

Rendering performance: A lot faster, a lot more power-hungry

Before we talk about Frame Generation or “fake frames,” let’s compare apples to apples and just examine the 5090’s rendering performance.

The card mainly benefits from four things compared to the 4090: the updated Blackwell GPU architecture, a nearly 33 percent increase in the number of CUDA cores, an upgrade from GDDR6X to GDDR7, and a move from a 384-bit memory bus to a 512-bit bus. It also jumps from 24GB of RAM to 32GB, but games generally aren’t butting up against a 24GB limit yet, so the capacity increase by itself shouldn’t really change performance if all you’re focused on is gaming.

And for people who prioritize performance over all else, the 5090 is a big deal—it’s the first consumer graphics card from any company that is faster than a 4090, as Nvidia never spruced up the 4090 last year when it did its mid-generation Super refreshes of the 4080, 4070 Ti, and 4070.

Comparing natively rendered games at 4K, the 5090 is between 17 percent and 40 percent faster than the 4090, with most of the games we tested landing somewhere in the low to high 30 percent range. That’s an undeniably big bump, one that’s roughly commensurate with the increase in the number of CUDA cores. Tests run with DLSS enabled (both upscaling-only and with Frame Generation running in 2x mode) improve by roughly the same amount.

You could find things to be disappointed about if you went looking for them. That 30-something-percent performance increase comes with a 35 percent increase in power use in our testing under load with punishing 4K games—the 4090 tops out around 420 W, whereas the 5090 went all the way up to 573 W, with the 5090 coming closer to its 575 W TDP than the 4090 does to its theoretical 450 W maximum. The 50-series cards use the same TSMC 4N manufacturing process as the 40-series cards, and increasing the number of transistors without changing the process results in a chip that uses more power (though it should be said that capping frame rates, running at lower resolutions, or running less-demanding games can rein in that power use a bit).

Power draw under load goes up by an amount roughly commensurate with performance. The 4090 was already power-hungry; the 5090 is dramatically more so. Credit: Andrew Cunningham

The 5090’s 30-something percent increase over the 4090 might also seem underwhelming if you recall that the 4090 was around 55 percent faster than the previous-generation 3090 Ti while consuming about the same amount of power. To be even faster than a 4090 is no small feat—AMD’s fastest GPU is more in line with Nvidia’s 4080 Super—but if you’re comparing the two cards using the exact same tests, the relative leap is less seismic.

That brings us to Nvidia’s answer for that problem: DLSS 4 and its Multi-Frame Generation feature.

DLSS 4 and Multi-Frame Generation

As a refresher, Nvidia’s DLSS Frame Generation feature, as introduced in the GeForce 40-series, takes DLSS upscaling one step further. The upscaling feature inserted interpolated pixels into a rendered image to make it look like a sharper, higher-resolution image without having to do all the work of rendering all those pixels. DLSS FG would interpolate an entire frame between rendered frames, boosting your FPS without dramatically boosting the amount of work your GPU was doing. If you used DLSS upscaling and FG at the same time, Nvidia could claim that seven out of eight pixels on your screen were generated by AI.

DLSS Multi-Frame Generation (hereafter MFG, for simplicity’s sake) does the same thing, but it can generate one to three interpolated frames for every rendered frame. The marketing numbers have gone up, too; now, 15 out of every 16 pixels on your screen can be generated by AI.

Nvidia might point to this and say that the 5090 is over twice as fast as the 4090, but that’s not really comparing apples to apples. Expect this issue to persist over the lifetime of the 50-series. Credit: Andrew Cunningham

Nvidia provided reviewers with a preview build of Cyberpunk 2077 with DLSS MFG enabled, which gives us an example of how those settings will be exposed to users. For 40-series cards that only support the regular DLSS FG, you won’t notice a difference in games that support MFG—Frame Generation is still just one toggle you can turn on or off. For 50-series cards that support MFG, you’ll be able to choose from among a few options, just as you currently can with other DLSS quality settings.

The “2x” mode is the old version of DLSS FG and is supported by both the 50-series cards and 40-series GPUs; it promises one generated frame for every rendered frame (two frames total, hence “2x”). The “3x” and “4x” modes are new to the 50-series and promise two and three generated frames (respectively) for every rendered frame. Like the original DLSS FG, MFG can be used in concert with normal DLSS upscaling, or it can be used independently.

One problem with the original DLSS FG was latency—user input was only being sampled at the natively rendered frame rate, meaning you could be looking at 60 frames per second on your display but only having your input polled 30 times per second. Another is image quality; as good as the DLSS algorithms can be at guessing and recreating what a natively rendered pixel would look like, you’ll inevitably see errors, particularly in fine details.

Both these problems contribute to the third problem with DLSS FG: Without a decent underlying frame rate, the lag you feel and the weird visual artifacts you notice will both be more pronounced. So DLSS FG can be useful for turning 120 fps into 240 fps, or even 60 fps into 120 fps. But it’s not as helpful if you’re trying to get from 20 or 30 fps up to a smooth 60 fps.

We’ll be taking a closer look at the DLSS upgrades in the next couple of weeks (including MFG and the new transformer model, which will supposedly increase upscaling quality and supports all RTX GPUs). But in our limited testing so far, the issues with DLSS MFG are basically the same as with the first version of Frame Generation, just slightly more pronounced. In the built-in Cyberpunk 2077 benchmark, the most visible issues are with some bits of barbed-wire fencing, which get smoother-looking and less detailed as you crank up the number of AI-generated frames. But the motion does look fluid and smooth, and the frame rate counts are admittedly impressive.

But as we noted in last year’s 4090 review, the xx90 cards portray FG and MFG in the best light possible since the card is already capable of natively rendering such high frame rates. It’s on lower-end cards where the shortcomings of the technology become more pronounced. Nvidia might say that the upcoming RTX 5070 is “as fast as a 4090 for $549,” and it might be right in terms of the number of frames the card can put up on your screen every second. But responsiveness and visual fidelity on the 4090 will be better every time—AI is a good augmentation for rendered frames, but it’s iffy as a replacement for rendered frames.

A 4090, amped way up

Nvidia’s GeForce RTX 5090. Credit: Andrew Cunningham

The GeForce RTX 5090 is an impressive card—it’s the only consumer graphics card to be released in over two years that can outperform the RTX 4090. The main caveats are its sky-high power consumption and sky-high price; by itself, it costs as much (and consumes as much power as) an entire mainstream gaming PC. The card is aimed at people who care about speed way more than they care about price, but it’s still worth putting it into context.

The main controversy, as with the 40-series, is how Nvidia talks about its Frame Generation-inflated performance numbers. Frame Generation and Multi-Frame Generation are tools in a toolbox—there will be games where they make things look great and run fast with minimal noticeable impact to visual quality or responsiveness, games where those impacts are more noticeable, and games that never add support for the features at all. (As well-supported as DLSS generally is in new releases, it is incumbent upon game developers to add it—and update it when Nvidia puts out a new version.)

But using those Multi-Frame Generation-inflated FPS numbers to make topline comparisons to last-generation graphics cards just feels disingenuous. No, an RTX 5070 will not be as fast as an RTX 4090 for just $549, because not all games support DLSS MFG, and not all games that do support it will run it well. Frame Generation still needs a good base frame rate to start with, and the slower your card is, the more issues you might notice.

Fuzzy marketing aside, Nvidia is still the undisputed leader in the GPU market, and the RTX 5090 extends that leadership for what will likely be another entire GPU generation, since both AMD and Intel are focusing their efforts on higher-volume, lower-cost cards right now. DLSS is still generally better than AMD’s FSR, and Nvidia does a good job of getting developers of new AAA game releases to support it. And if you’re buying this GPU to do some kind of rendering work or generative AI acceleration, Nvidia’s performance and software tools are still superior. The misleading performance claims are frustrating, but Nvidia still gains a lot of real advantages from being as dominant and entrenched as it is.

The good

Usually 30-something percent faster than an RTX 4090
Redesigned Founders Edition card is less unwieldy than the bricks that were the 4090/4080 design
Adequate cooling, despite the smaller card and higher power use
DLSS Multi-Frame Generation is an intriguing option if you’re trying to hit 240 or 360 fps on your high-refresh-rate gaming monitor

The bad

Much higher power consumption than the 4090, which already consumed more power than any other GPU on the market
Frame Generation is good at making a game that’s running fast run faster, it’s not as good for bringing a slow game up to 60 Hz
Nvidia’s misleading marketing around Multi-Frame Generation is frustrating—and will likely be more frustrating for lower-end cards since they aren’t getting the same bumps to core count and memory interface that the 5090 gets

The ugly

You can buy a whole lot of PC for $2,000, and we wouldn’t bet on this GPU being easy to find at MSRP

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Sleeping pills stop the brain’s system for cleaning out waste

Biology, brain, Features, neurobiology, nREM sleep, Science, sleeping pills / Beth Washington / January 20, 2025

Cleanup on aisle cerebellum

A specialized system sends pulses of pressure through the fluids in our brain.

Our bodies rely on their lymphatic system to drain excessive fluids and remove waste from tissues, feeding those back into the blood stream. It’s a complex yet efficient cleaning mechanism that works in every organ except the brain. “When cells are active, they produce waste metabolites, and this also happens in the brain. Since there are no lymphatic vessels in the brain, the question was what was it that cleaned the brain,” Natalie Hauglund, a neuroscientist at Oxford University who led a recent study on the brain-clearing mechanism, told Ars.

Earlier studies done mostly on mice discovered that the brain had a system that flushed its tissues with cerebrospinal fluid, which carried away waste products in a process called glymphatic clearance. “Scientists noticed that this only happened during sleep, but it was unknown what it was about sleep that initiated this cleaning process,” Hauglund explains.

Her study found the glymphatic clearance was mediated by a hormone called norepinephrine and happened almost exclusively during the NREM sleep phase. But it only worked when sleep was natural. Anesthesia and sleeping pills shut this process down nearly completely.

Taking it slowly

The glymphatic system in the brain was discovered back in 2013 by Dr. Maiken Nedergaard, a Danish neuroscientist and a coauthor of Hauglund’s paper. Since then, there have been numerous studies aimed at figuring out how it worked, but most of them had one problem: they were done on anesthetized mice.

“What makes anesthesia useful is that you can have a very controlled setting,” Hauglund says.

Most brain imaging techniques require a subject, an animal or a human, to be still. In mouse experiments, that meant immobilizing their heads so the research team could get clear scans. “But anesthesia also shuts down some of the mechanisms in the brain,” Hauglund argues.

So, her team designed a study to see how the brain-clearing mechanism works in mice that could move freely in their cages and sleep naturally whenever they felt like it. “It turned out that with the glymphatic system, we didn’t really see the full picture when we used anesthesia,” Hauglund says.

Looking into the brain of a mouse that runs around and wiggles during sleep, though, wasn’t easy. The team pulled it off by using a technique called flow fiber photometry which works by imaging fluids tagged with fluorescent markers using a probe implanted in the brain. So, the mice got the optical fibers implanted in their brains. Once that was done, the team put fluorescent tags in the mice’s blood, cerebrospinal fluid, and on the norepinephrine hormone. “Fluorescent molecules in the cerebrospinal fluid had one wavelength, blood had another wavelength, and norepinephrine had yet another wavelength,” Hauglund says.

This way, her team could get a fairly precise idea about the brain fluid dynamics when mice were awake and asleep. And it turned out that the glymphatic system basically turned brain tissues into a slowly moving pump.

Pumping up

“Norepinephrine is released from a small area of the brain in the brain stem,” Hauglund says. “It is mainly known as a response to stressful situations. For example, in fight or flight scenarios, you see norepinephrine levels increasing.” Its main effect is causing blood vessels to contract. Still, in more recent research, people found out that during sleep, norepinephrine is released in slow waves that roll over the brain roughly once a minute. This oscillatory norepinephrine release proved crucial to the operation of the glymphatic system.

“When we used the flow fiber photometry method to look into the brains of mice, we saw these slow waves of norepinephrine, but we also saw how it works in synchrony with fluctuation in the blood volume,” Hauglund says.

Every time the norepinephrine level went up, it caused the contraction of the blood vessels in the brain, and the blood volume went down. At the same time, the contraction increased the volume of the perivascular spaces around the blood vessels, which were immediately filled with the cerebrospinal fluid.

When the norepinephrine level went down, the process worked in reverse: the blood vessels dilated, letting the blood in and pushing the cerebrospinal fluid out. “What we found was that norepinephrine worked a little bit like a conductor of an orchestra and makes the blood and cerebrospinal fluid move in synchrony in these slow waves,” Hauglund says.

And because the study was designed to monitor this process in freely moving, undisturbed mice, the team learned exactly when all this was going on. When mice were awake, the norepinephrine levels were much higher but relatively steady. The team observed the opposite during the REM sleep phase, where the norepinephrine levels were consistently low. The oscillatory behavior was present exclusively during the NREM sleep phase.

So, the team wanted to check how the glymphatic clearance would work when they gave the mice zolpidem, a sleeping drug that had been proven to increase NREM sleep time. In theory, zolpidem should have boosted brain-clearing. But it turned it off instead.

Non-sleeping pills

“When we looked at the mice after giving them zolpidem, we saw they all fell asleep very quickly. That was expected—we take zolpidem because it makes it easier for us to sleep,” Hauglund says. “But then we saw those slow fluctuations in norepinephrine, blood volume, and cerebrospinal fluid almost completely stopped.”

No fluctuations meant the glymphatic system didn’t remove any waste. This was a serious issue, because one of the cellular waste products it is supposed to remove is amyloid beta, found in the brains of patients suffering from Alzheimer’s disease.

Hauglund speculates it could be possible zolpidem induces a state very similar to sleep but at the same time it shuts down important processes that happen during sleep. While heavy zolpidem use has been associated with increased risk of the Alzheimer disease, it is not clear if this increased risk was there because the drug was inhibiting oscillatory norepinephrine release in the brain. To better understand this, Hauglund wants to get a closer look into how the glymphatic system works in humans.

“We know we have the same wave-like fluid dynamics in the brain, so this could also drive the brain clearance in humans,” Haugland told Ars. “Still, it’s very hard to look at norepinephrine in the human brain because we need an invasive technique to get to the tissue.”

But she said norepinephrine levels in people can be estimated based on indirect clues. One of them is pupil dilation and contraction, which work in in synchrony with the norepinephrine levels. Another other clue may lay in microarousals—very brief, imperceivable awakenings which, Hauglund thinks, can be correlated with the brain clearing mechanism. “I am currently interested in this phenomenon […]. Right now we have no idea why microarousals are there or what function they have” Hauglund says.

But the last step she has on her roadmap is making better sleeping pills. “We need sleeping drugs that don’t have this inhibitory effect on the norepinephrine waves. If we can have a sleeping pill that helps people sleep without disrupting their sleep at the same time it will be very important,” Hauglund concludes.

Cell, 2025. DOI: 10.1016/j.cell.2024.11.027

Jacek Krywko is a freelance science and technology writer who covers space exploration, artificial intelligence research, computer science, and all sorts of engineering wizardry.

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Fire destroys Starship on its seventh test flight, raining debris from space

Commercial space, FAA, Features, launch, NASA, Science, Space, spacex, Starbase, starship / DJ Henderson / January 18, 2025

This launch debuted a more advanced, slightly taller version of Starship, known as Version 2 or Block 2, with larger propellant tanks, a new avionics system, and redesigned feed lines flowing methane and liquid oxygen propellants to the ship’s six Raptor engines. SpaceX officials did not say whether any of these changes might have caused the problem on Thursday’s launch.

SpaceX officials have repeatedly and carefully set expectations for each Starship test flight. They routinely refer to the rocket as experimental, and the primary focus of the rocket’s early demo missions is to gather data on the performance of the vehicle. What works, and what doesn’t work?

Still, the outcome of Thursday’s test flight is a clear disappointment for SpaceX. This was the seventh test flight of SpaceX’s enormous rocket and the first time Starship failed to complete its launch sequence since the second flight in November 2023. Until now, SpaceX has made steady progress, and each Starship flight has achieved more milestones than the one before.

On the first flight in April 2023, the rocket lost control a little more than two minutes after liftoff, and the ground-shaking power of the booster’s 33 engines shattered the concrete foundation beneath the launch pad. Seven months later, on Flight 2, the rocket made it eight minutes before failing. On that mission, Starship failed at roughly the same point of its ascent, just before the cutoff of the vehicle’s six methane-fueled Raptor engines.

Back then, a handful of photos and images from the Florida Keys and Puerto Rico showed debris in the sky after Starship activated its self-destruct mechanism due to an onboard fire caused by a dump of liquid oxygen propellant. But that flight occurred in the morning, with bright sunlight along the ship’s flight path.

This time, the ship disintegrated and reentered the atmosphere at dusk, with impeccable lighting conditions accentuating the debris cloud’s appearance. These twilight conditions likely contributed to the plethora of videos posted to social media on Thursday.

Starship and Super Heavy head downrange from SpaceX’s launch site near Brownsville, Texas. Credit: SpaceX

The third Starship test flight last March saw the spacecraft reach its planned trajectory and fly halfway around the world before succumbing to the scorching heat of atmospheric reentry. In June, the fourth test flight ended with controlled splashdowns of the rocket’s Super Heavy booster in the Gulf of Mexico and of Starship in the Indian Ocean.

In October, SpaceX caught the Super Heavy booster with mechanical arms at the launch pad for the first time, proving out the company’s audacious approach to recovering and reusing the rocket. On this fifth test flight, SpaceX modified the ship’s heat shield to better handle the hot temperatures of reentry, and the vehicle again made it to an on-target splashdown in the Indian Ocean.

Most recently, Flight 6 on November 19 demonstrated the ship’s ability to reignite its Raptor engines in space for the first time and again concluded with a bullseye splashdown. But SpaceX aborted an attempt to again catch the booster back at Starbase due to a problem with sensors on the launch pad’s tower.

With Flight 7, SpaceX hoped to test more changes to the heat shield protecting Starship from reentry temperatures up to 2,600° Fahrenheit (1,430° Celsius). Musk has identified the heat shield as one of the most difficult challenges still facing the program. In order for SpaceX to reach its ambition for the ship to become rapidly reusable, with minimal or no refurbishment between flights, the heat shield must be resilient and durable.

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