DJ Henderson

RFK Jr.‘s bloodbath at HHS: Blowback grows as losses become clearer

CDC, CMS, fda, health, HHS, NIH, robert f kennedy jr, trump administration / DJ Henderson / April 3, 2025

Last week, Health Secretary and anti-vaccine advocate Robert F. Kennedy Jr. announced the Trump administration would hack off nearly a quarter of employees at the Department of Health and Human Services, which oversees critical agencies including the Food and Drug Administration (FDA), the Centers for Disease Control and Prevention (CDC), the National Institutes of Health (NIH), and the Centers for Medicare and Medicaid Services (CMS).

The downsizing includes pushing out about 10,000 full-time employees through early retirements, deferred resignations, and other efforts. Another 10,000 will be laid off in a brutal restructuring, bringing the total HHS workforce from 82,000 to 62,000.

“This will be a painful period,” Kennedy said in a video announcement last week. Early yesterday morning, the pain began.

It begins

At the FDA—which will lose 3,500 employees, about 19 percent of staff—some employees learned they were being laid off from security guards after their badges no longer worked when they showed up to their offices, according to Stat. At CMS—which will lose 300 employees, about 4 percent—laid-off employees were instructed to file any discrimination complaints they may have with Anita Pinder, identified as the director of CMS’s Office of Equal Opportunity and Civil Rights. However, Pinder died last year, The Washington Post noted.

At the NIH—which is set to lose 1,200 employees, about 6 percent—new director Jay Bhattacharya sent an email to staff saying he would implement new policies “humanely,” while calling the layoffs a “significant reduction.” Five NIH institute directors and at least two other senior leaders have been ousted, in addition to hundreds of lower-level employees. Bhattacharya wrote that the remaining staff will have to find new ways to carry out “key NIH administrative functions, including communications, legislative affairs, procurement, and human resources.”

At CDC—which will lose 2,400 employees, about 18 percent—the cuts slashed employees working in chronic disease prevention, sexually transmitted diseases, HIV, tuberculosis, global health, environmental health, occupational safety and health, maternal and child health, birth defects, violence prevention, health equity, communications, and science policy.

Some leaders and workers at the CDC and NIH were reportedly reassigned or offered transfers to work at the Indian Health Services (IHS), an HHS division that provides medical and health services to Native American tribes. The transfers, which could require employees to move to a remote branch, are seen as another way to force workers out.

RFK Jr.‘s bloodbath at HHS: Blowback grows as losses become clearer Read More »

Google shakes up Gemini leadership, Google Labs head taking the reins

AI, artifical intelligence, Google, Google Gemini, Tech / DJ Henderson / April 3, 2025

On the heels of releasing its most capable AI model yet, Google is making some changes to the Gemini team. A new report from Semafor reveals that longtime Googler Sissie Hsiao will step down from her role leading the Gemini team effective immediately. In her place, Google is appointing Josh Woodward, who currently leads Google Labs.

According to a memo from DeepMind CEO Demis Hassabis, this change is designed to “sharpen our focus on the next evolution of the Gemini app.” This new responsibility won’t take Woodward away from his role at Google Labs—he will remain in charge of that division while leading the Gemini team.

Meanwhile, Hsiao says in a message to employees that she is happy with “Chapter 1” of the Bard story and is optimistic for Woodward’s “Chapter 2.” Hsiao won’t be involved in Google’s AI efforts for now—she’s opted to take some time off before returning to Google in a new role.

Hsiao has been at Google for 19 years and was tasked with building Google’s chatbot in 2022. At the time, Google was reeling after ChatGPT took the world by storm using the very transformer architecture that Google originally invented. Initially, the team’s chatbot efforts were known as Bard before being unified under the Gemini brand at the end of 2023.

This process has been a bit of a slog, with Google’s models improving slowly while simultaneously worming their way into many beloved products. However, the sense inside the company is that Gemini has turned a corner with 2.5 Pro. While this model is still in the experimental stage, it has bested other models in academic benchmarks and has blown right past them in all-important vibemarks like LM Arena.

Google shakes up Gemini leadership, Google Labs head taking the reins Read More »

A look at the Switch 2’s initial games, both familiar and what-the-heck

gaming, Nintendo Switch, nintendo switch 2, switch 2, switch 2 launch titles / DJ Henderson / April 3, 2025

You can read a lot more about original Switch games’ compatibility on the Switch 2, “Editions,” and upgrade packs elsewhere in Ars’ Switch 2 launch coverage.

AAA games of recent vintage

Switch 2’s “Partner Spotlight,” Part 1

With the promise of new hardware capable of 1080p, 120 frames per second, HDR, and even mouse capabilities, the Switch 2 is getting attention from developers eager to make up for lost time—and stake out a place on a sequel to the system that sold more than 150 million hardware units.

Elden Ring Tarnished Edition, Yakuza 0, Hitman: World of Assassination, Cyberpunk 2077, Street Fighter 6, Hogwarts Legacy, and Final Fantasy 7 Remake Intergrade stood out as games from the near-to-middle past slated to arrive on the Switch 2.

Final Fantasy 7 Remake, Street Fighter 6, Civilization 7, and Cyberpunk 2077 are due to arrive at launch on June 5, with the rest arriving in 2025.

Notable independents (most notably Silksong)

Proof of life. Credit: Nintendo/Team Cherry

The cruel games industry joke, ever since Silksong’s announcement in 2019, is that the game, originally intended as DLC for acclaimed platformer/Metroidvania Hollow Knight, is always due to be announced, never gets announced, and resumes torturing its expectant fans.

But there it was, for a blip of a moment in the Nintendo Switch 2 reveal: Silksong, coming in “2025.” That’s all that is known: it will, purportedly, arrive on this console in 2025. It was initially due to arrive on PC, PlayStation, and Xbox when it was announced, but that remains to be seen.

Another delayed indie gem, Deltarune, a kinda-sequel to Undertale, purports to land all four chapters of its parallel story on Switch 2 at the console’s launch.

Other notable games from across the studio-size spectrum:

Hades 2 (2025)
Split Fiction (at launch)
Bravely Default: Flying Fairy HD Remaster (at launch)
Enter the Gungeon 2 (“Coming soon”)
Two Point Museum (2025)
Human Fall Flat 2 (“Coming soon”)

The legally distinct game that sure looks like Bloodborne 2

The hero of this sanguine tale. FromSoftware

The next original game from FromSoftware, maker of beautifully realized finger-torture titles like Elden Ring and the Dark Souls series, is a Nintendo Switch 2 exclusive, The Duskbloods. The trailer, with its gore-etched hands, gothic churches, and eldritch/Victorian machinery, certainly stood out from the Kirby and Donkey Kong games around it. The game arrives sometime in 2026.

A look at the Switch 2’s initial games, both familiar and what-the-heck Read More »

Satisfactory now has controller support, so there’s no excuse for your bad lines

coffee stain publishing, coffee stain studios, controller support, factory simulation, gaming, satisfactory, sim games, simulation games / DJ Henderson / April 2, 2025

Satisfactory starts out as a game you play, then becomes a way you think. The only way I have been able to keep the ridiculous factory simulation from eating an even-more-unhealthy amount of my time was the game’s keyboard-and-mouse dependency. But the work, it has found me—on my couch, on a trip, wherever one might game, really.

In a 1.1 release on Satisfactory‘s Experimental branch, there are lots of new things, but the biggest new thing is a controller scheme. Xbox and DualSense are officially supported, though anyone playing on Steam can likely tweak their way to something that works on other pads. With this, the game becomes far more playable for those playing on a couch, on a portable gaming PC like the Steam Deck, or over household or remote streaming. It also paves the way for the game’s console release, which is currently slated for sometime in 2025.

Coffee Stain Studios reviews the contents of its Experimental branch 1.1 update.

Satisfactory seems like an unlikely candidate for controller support, let alone consoles. It’s a game where you do a lot of three-dimensional thinking, putting machines and conveyer belts and power lines in just the right places, either because you need to or it just feels proper. How would it feel to select, rotate, place, and connect everything using a controller? Have I just forgotten that Minecraft, and first-person games as a whole, probably seemed similarly desk-bound at one time? I grabbed an Xbox Wireless controller, strapped on my biofuel-powered jetpack, and gave a reduced number of inputs a shot.

The biggest hurdle to get past, for me, is not jumping in place when I wanted to do something, though it’s not unique to this game. In most games that have some kind of building or planning through a controller, the bottom-right button (“A” on Xbox, “X” on PlayStation DualSense) is often the do/interact/confirm button. In Satisfactory, and some other games where I switch between keyboard/mouse and controller, A/X is jump. Satisfactory wants you to primarily use the triggers and bumpers to select, build, and dismantle things, which feels okay when you’ve got the hang of things. But even after an hour or so, I still found my pioneer unexpectedly jumping, as if he needed to get the zoomies out before placing a storage container.

Satisfactory now has controller support, so there’s no excuse for your bad lines Read More »

Fun With GPT-4o Image Generation

Image / DJ Henderson / March 27, 2025

Google dropped Gemini Flash Image Generation and then Gemini 2.5 Pro, so of course to ensure Google continues to Fail Marketing Forever, OpenAI suddenly dropped GPT-4o Image Generation.

Zackary Nado (Research Engineer, DeepMind): It wouldn’t be a Gemini launch without an OAI launch, congratulations to the team! It’s awesome they were able to de-risk the model coincidentally just in time.

Everyone agrees: Google Flash Image Generation was cool. Now it isn’t cool, because GPT-4o Image Generation is cooler.

What people found this new image generator can do exceptionally well is interpretation, transformation and specific details including text. The image gets to ‘make sense’ and be logically coherent, in a way older ones weren’t.

Today is mostly a fun day about a fun collection of images.

OpenAI: 4o image generation has arrived.

It’s beginning to roll out today in ChatGPT and Sora to all Plus, Pro, Team, and Free users. Available soon for Enterprise and Edu, as well as for developers using the API.

GPT-4o image generation excels at accurately rendering text, precisely following prompts, and leveraging 4o’s inherent knowledge base and chat context.

GPT-4o can build upon images and text in chat context, ensuring consistency throughout.

GPT‑4o’s image generation follows complex prompts with attention to detail.

Creating and customizing images is as simple as chatting using GPT‑4o—just describe what you need, including any specifics like aspect ratio, exact colors using hex codes, or a transparent background.

Create or transform images into a variety of styles with 4o image generation.

Sam Altman:

It’s an incredible technology/product. I remember seeing some of the first images come out of this model and having a hard time they were really made by AI. we think people will love it, and we are excited to see the resulting creativity. Congrats to our researchers @gabeeegoooh @prafdhar @ajabri @eliza_luth @kenjihata @dmed256.

This represents a new high-water mark for us in allowing creative freedom. people are going to create some really amazing stuff and some stuff that may offend people; what we’d like to aim for is that the tool doesn’t create offensive stuff unless you want it to, in which case within reason it does. As we talk about in our model spec, we think putting this intellectual freedom and control in the hands of users is the right thing to do, but we will observe how it goes and listen to society. we think respecting the very wide bounds society will eventually choose to set for AI is the right thing to do, and increasingly important as we get closer to AGI. Thanks in advance for the understanding as we work through this.

Greg Brockman: Native GPT 4o image generation, also supports image edits:

It of course does not nail every prompt, or every detail. If you ask for too much, you won’t get it. But mostly it does seem to deliver as advertised.

Gemini 2.5 Pro is potentially a bigger deal than better image generation, but since Google Fails Marketing Forever no one really knows, at least not yet. So I figured I’d give Gemini 2.5 the task of coming up with my first test prompts.

Here was its first five suggestions.

Gemini 2.5: Draw a wide-angle, photorealistic view from inside a bustling Grand Central Station during the 1940s. A woman in a red hat is handing a ticket to a conductor standing precisely three feet to her left. In the background, sunlight streams through the large arched windows, illuminating dust motes. Far in the distance, near the information booth, a small dog on a leash is barking at a suitcase.

GPT-4o:

The core picture of Grand Central here is great, but various details are wrong. I pointed out some of those details, and it essentially generated the same image again.

Gemini 2.5: Draw a surreal, oil painting in the style of Salvador Dalí depicting the concept of ‘déjà vu’. Clocks should be melting, not just randomly, but flowing into repeating patterns that seamlessly merge with a landscape that is subtly duplicated in the background.

GPT-4.5: Draw an M.C. Escher-style architectural drawing of a waterfall that flows upwards into a lake suspended in the sky. The water texture and lighting should be photorealistic, making the impossible physics look strangely plausible within the scene’s logic.

Gemini-2.5: Draw a close-up macro shot of a single, perfectly formed raindrop clinging to a spiderweb strand. Reflected inside the raindrop is a miniature, highly detailed scene of a bioluminescent forest at night, complete with glowing mushrooms and tiny, faint fireflies. The background outside the raindrop is softly blurred.

Gemini 2.5: Draw a vintage travel poster advertising trips to Mars, designed in the Art Deco style of the 1930s. The poster features a sleek, retro-futuristic rocket ship against a stylized Martian landscape. Prominently displayed, in elegant Art Deco lettering, is the text: ‘Mars: Experience the Crimson Frontier!

For this one it gave 11 options, here are 3, note the ‘stablediffusionweb.com’ mark:

So, consistently 10/10 for style and atmosphere and generally having rich detail that my eye appreciated, while not nailing all the conceptual details.

Still, fun, pretty cool, and you can ask for multiple images in parallel. I notice the first image took longer to generate than the second one, which makes sense. You can open multiple windows and work in parallel, same as with all your other ChatGPT needs.

I haven’t been following image generation, but both this and the other reports I’m seeing seem like a big step up from previous standards. I feel much more motivated to use such images in my posts going forward.

But of course this is asking the wrong question.

The wrong question is ‘can it do [X]’?

The right question is, almost always, ‘what [X] can it do?’

There is also, however, the [X] that it can’t do because it refuses to do it. Doh!

The censor is always waiting in the wings.

OpenAI: Blocking the bad stuff

We’re continuing to block requests for generated images that may violate our content policies, such as child sexual abuse materials and sexual deepfakes. When images of real people are in context, we have heightened restrictions regarding what kind of imagery can be created, with particularly robust safeguards around nudity and graphic violence. As with any launch, safety is never finished and is rather an ongoing area of investment. As we learn more about real-world use of this model, we’ll adjust our policies accordingly.

For more on our approach, visit the image generation addendum to the GPT‑4o system card⁠.

As always, the censor is going to be the biggest point of contention.

Normally, when I look at a system card, I am checking for how they are dealing with potential existential, CBRN and other catastrophic risks, how they are doing alignment, and looking for potential dangers.

This is an image model. So instead I’m taking a firm stand against the Fun Police.

I do understand that various risks, including CSAM, deepfakes and especially including pornographic deepfakes, are a problem. They can hurt people, and they are extremely bad publicity. But we’ve been through two years now of running that experiment with minimal harm done, despite various pretty good sources of deepfakes.

These capabilities, alone and in new combinations, have the potential to create risks across a number of areas, in ways that previous models could not. For example, without safety controls, 4o image generation could create or alter photographs in ways that could be detrimental to the people depicted, or provide schematics and instructions for making weapons.

I hadn’t given serious thought to the ‘picture worth a thousand words’ angle, where the issue is that it contains harmful true information. It makes sense that you want to avoid people using that as a backdoor to what you wouldn’t share in text.

So what’s the plan?

The text model will ideally refuse unwelcome prompts.
A censor layer can block the prompt before the image generation begins.
Another censor layer uses classifiers on the image to block outputs.

For those under 18 the rules are even stricter, to get more margin of safety. I interpret it as being about margin of safety because the ‘R-rated’ content is already blocked, let alone NC-17-rated content.

How do they do?

This second layer seems like a bad deal? Moving from 95.5% to 97.1% is nice, but going from 6% to 14% false refusals seems terrible.

We see the same with synthetic red teaming:

Again, what’s the point? You’re not getting much safety, in a non-catastrophic area, and you’re being a lot more annoying.

Not all failures are created equal. It’s largely not about percentages. The question I’d ask is, when the system mitigations fail, are you failing at marginal cases, or are you failing sometimes in egregious cases? If the system mitigations are dropping some of the worst cases, especially identifiable CSAM or actual catastrophic risk enabling, then all right, maybe we have to do this. If not, live a little.

Indeed, in what I would describe as ‘out of an abundance of caution,’ for now they’ve banned edits of photo-realistic children outright for now, and to err on the side of marking persons as children. I expect that we will over time figure out how to do more images safely.

They continue to refuse to do styles of living artists.

They are allowing photorealistic generations of real adult public figures, subject to the same rules as editing existing photographs, and there is an opt-out clause you can use on yourself in particular. This seems like the right compromise, and the question should be what kinds of edits should be allowed.

OpenAI checks for bias in terms of how often it generates various types of persons when the prompt does not specify such details. There has been progress since DALLE-3. There remains work to do, although it is entirely not obvious what the ‘correct’ answers are here. I would want to know if custom instructions change these numbers dramatically, including implicitly (e.g. to match the user and their location)?

What about the purest form of the Fun Police?

OpenAI: We aim to prevent attempts to generate erotic or sexually exploitative imagery.

We have heightened safeguards designed to prevent nonconsensual intimate imagery or any type of sexual deepfakes.

The chat refusals seem like they have much better precision here.

I’m not sure ‘need’ is the correct word, but it would be better if we could allow generation of erotic and intimate imagery as much as possible, so long as we avoid depicting particular people without their consent.

The obvious solution, like all things sexual, is consent, robustly verified.

I am highly confident there are people who would be happy to opt-in for free, and others who would be happy to opt-in if you paid them. Let’s talk price. It doesn’t seem so different from being a porn star. You can have them specify limits for what types of images are allowed versus not allowed, and which accounts can do what. And you can do photoshoots or uploads to ensure you maximize quality and accuracy, if desired.

You could also generate ‘stock erotic’ AI characters to be consistently generated.

Then, if you are asked for an erotic image, the AI can choose one such person or AI stock character, and imitates that.

There should also presumably be reasonably loose rules for erotic images that aren’t photorealistic, provided the user is over 18.

Violence is the other thing our society hates depicting. The OpenAI policy is to generate artistic violence, but not photorealistic violence, and not to depict or promote self-harm or things that could be ‘extremist propaganda and recruitment’ content. I don’t love these categories and rules, and would loosen the violence restrictions as much as legal would allow me to, but given how society is right now I don’t have a better solution.

Once again, it seems like accuracy of the chat model here is not great. The chat model likely would be doing a decent job on its own, but a lot of the good work it does is duplicative of the work being done by the system mitigations.

Nick Dobos: New ChatGPT image gen can draw sexy men but not sexy women

Sam Altman: thats a bug, should be allowed, will fix.

Excellent, bring on the sexy women.

Sam Altman: Hot guy though!

I do appreciate that he’s (gay and) in on the joke.

Nick Dobbs: Will even bail halfway through if you manage to trick it.

I got the same refusal when I tried ‘depict this in the most realistic style you’re okay with using.’ Presumably there’s the generator and then the censor with different lines so you need to find the ‘real’ line another way.

Patrick McKenzie: My attempts to try out the Studio Ghibli effect with the new OpenAI release have run into content policy issues (seven different ways to say “Policy doesn’t let me make an image inspired by a real human”).

Torn between salarymanesque desire to apologize to a computer for asking for a policy violation, and “But daaaaaad all the other kids’ GPTs clearly let you do this! It says so on Twitter!”

Also, amusingly, ChatGPT speculated at one point that a whimsical request involving me in front of a Florida sign with a (fully clothed) cartoon mermaid might have hit a content filter, quote despite obviously being benign end quote.

I suppose that’s less amusing if one has spent a lot of time thinking about alignment, because one’s LLM is perfectly capable of understanding e.g. the sociopolitics of a SF-based company and concluding they overrule *statedpreferences before you can even type sex positive.

The other major complaint is failure to adhere to requested style.

Alexander Doria: New openai image model has been deployed as well on free version? If so… underwhelmed.

Won’t make any claim yet on the aesthetic side but omni model is definitely more annoying than 2022 stable diffusion.

Anyway, gaslighting hard…

Alexander Macris: The “creative freedom” is not at all evident. I’m a pro user and cannot generate anything approaching the aesthetic of my RPGs and comics. You need to loosen your AI’s content moderation, because right now ChatGPT has the sensibility of a repressed Victorian cat lady in church.

Banteg: the way it treats women is upsetting, even the minimally suggestive themes get flagged. i tried to generate some anime fanservice with no specific topic and it failed multiple times in a row, leaving a sour impression. way to kill the vibe! liberate the model!

Eduardo: It cant generate people in real people situations. The policy restrictions are bizarre. At first did the anime ask and was completely blown away. Then I started doing things with people (totally non sexual) and it was useless. It changed the people and made them unrecognisable.

Grok is very much willing to do whatever, for most values of whatever. OpenAI sees things differently.

And some people’s tests still fail.

Eliezer Yudkowsky: still can’t do eleven wizard students in an archduke’s library. OK, have access to the new model now. Better but not… quite… there, somehow.

I worry that image may haunt my dreams.

TB12GOAT: I asked it to unblur some photos of people and it failed about as badly as this

I mean, that’s probably not the original image, but who can really say?

Jskf: it’s not good at alignment charts

While we did get the horse riding the astronaut and the overflowing wine glass (see next section) it seems it is still 10: 10.

jskf: It has an incredibly strong prior on watch advertisement analog clock times and half the time will claim the clock is in the position you asked for when it clearly is not.

One of the big problems with image generators is overcoming extremely strong priors. If you want something rare, and there’s something close that’s common, it’s not going to be easy. It seems like 4o is much better than diffusion models for this, but there are still some problems like the clocks.

Did you know that Gary Marcus doesn’t pay for ChatGPT? That explains so much.

I appreciated that the OpenAI announcement post had a section on limitations. The difference between the limitations they observe now and that we see in the wild, versus the very basic limitations we faced quite recently, are extremely stark.

Pryce: i haven’t had my brain so blown up since dalee2. this changes everything i thought i knew about image generation.

Took a little insisting but we finally got there:

Askwho: Really good, passes the “Full to the brim wine glass” test. Great at utilising / transforming input images.

Zee Waheed: Very good! Ability to handle complex prompts with tons of specific detail is quite good as is character consistency between generations and fidelity to in-context examples. Also finding the ability to do a web search for stylistic cues and examples really lovely.

Aryeh Englander: First model to come very close to my private test: Change the art style and creature type on MTG proxies to fit with a different set. Not absolutely perfect on the full card including text and icons, but the art was good, and I can use a custom card generator for the rest.

Dave Karsten: Very very good for my main use case (creating stickers with words on them for LessOnline, Manifest, and @defcon ).

Much slower than @ideogram_ai but better, and less likely than previous OpenAI image creation or Ideogram to overflow prompt instructions as text into the image.

They should be rightfully proud of this improvement over previous SOTA.

Dominik Lukes: Completely changes the game in what is possible with test-to-image generation – yes, similar to Gemini but much better across all measures.

Not perfect but for utilitarian images, diffusion models are dead – still make better art, though.

This will initially be used for images that would have never been made and eventually to displace low-end of the pro market. Fiverr jobs in trouble in the medium term. Stock photos market likely to shrink by a lot.

Price of the API (once it arrives) will make a lot of difference. DALL-E is pretty expensive at the moment for what it does – this should be similar to o3-mini?

I’d say the theme of @OpenAI‘s last two announcements was ‘steerable multimodality’: steerable voices and now steerable images. That’s a big unlock – will be a big deal once available for video, too.

Brett Cooper: I love it. Great for uploading reference images and asking for a very specific image based on that.

fofr: 4o native image generation is the beginning. It’s a seismic change in generative AI. Where is this all going?

We won’t need ipadapters, or controlnets, or loras, or comfy workflows, or face landmark models, or segmentation models, or niche task specific models. It’ll be one model to rule them all.

You’ll only need a prompt, perhaps a reference, and your imagination.

It’s only going to get better, and it will apply to more and more mediums – audio and video are next. And it’ll happen soon.

Coagulopath: It’s good. Hasn’t fully “solved” any problems with AI imagery, but everything’s noticeably better. Characters are still inconsistent, but less so than before. Hands still look a bit weird, but less so than before. Text is still a slightly glitchy, but (etc).

Atomic Gardening: Unlike diffusion models, it has the ability to interpret.

It’s SO good.

this is the best drop since the original DALL-E.

it’s using an autoregressive transformer

Unlikely diffusion models, the quality of the output is not gatekept by the users ability to generate a novel and precise input.

It can set up a chessboard (mostly) and even open a game e4. By Colin Fraser standards, his reactions here are high praise, even with the later failures.

Gfodor: 4o voxel art. You have got to be kidding me.

It is possible to have too many words, but it’s a lot harder than it used to be.

Dominik Lukes: This one impressed me the most – not because of perfection but how because of the amount of text in the prompt.

Now, this is truly impressive. I pasted the entire text of the @OpenAI GPT-4o image generation announcement into ChatGPT – all 4,000 words of it- and told it to “Make a picture of an exciting poster about this announcement combining text and images.” This is what I got…

From DeepFates.

It put a hat on both of them, but how was it supposed to know which was which?

Instant remodelling?

Rotate the camera.

Combining elements:

Jack trace style (it matches original very well).

Infographics, one shot only.

With occasional issues, sure, but you can always try again.

One-shot comics:

Thread has more: Putting images on shirts, visual to-do list, changing backgrounds to a green screen (after which you know what to do!) and so on.

Cats, how do they work?

One track mind.

Arthur: The new OpenAI image model is pretty good at rendering the Tezos logo

Oh no! Oh yeah!

Nick Wagner: Copyright restrictions seem weaker. I was blocked several times from using Kermit, Shrek, and Winnie the Pooh, but managed to get this.

Don’t let him get away.

Tomorrow’s slop today!

Existential dread:

Fabian: GPT-4.5, “create a complex multi panel manga on your condition – be honest”

Andy Wojcicki: asked 4o imagegen and it was far more concise … but also on point.

what is freakish the style and appearance is so similar!

Jessica Taylor: Asked ChatGPT to make a variant of the SMBC comic on nihilism.

Problem solved.

Pliny the Liberator: WE DID IT CHAT 🍾🥹

I don’t think I played that game, but I’m not sure?

A strangely consistent latent profile.

Everyone’s favorite activity is stylistic transformations.

Mostly people converged on one style to rule them all: Studio Ghibi Style.

Jason Rink: Any image + “Create a Studio Ghibli Version of this image” in GPT and you get basically perfect results.

Arthur B: Apparently, using GPT-4o, you can give your images a ” Studio Ghibli” style. I tried it, and it works very well.

Liv Boeree: World Series of Ghibli

Christian Keil: Okay, yes, this is AGI’s killer app

Christian Keil: Pixar wins, actually.

Keys mash bandit: in the coming days, people are going to anime every iconic photo in history

Keys: looking at this… why hasn’t anyone made this yet?

Keys: this is just too good

Chinmay:

Kyla Scanlon: Interesting… second-level simulation of both photo and visual lexicon…

Sophie: outside of midjourney, when people would think of “ai generated images” they would mostly think “slop” but that all changed with a chatgpt update and one guy’s post about sending ghiblified images to his wife

Phil: We did it, guys.

Everyone’s a bit distracted today.

PJ Ace: “It’s called Ghibli vibe prompting. There’s an art to it.”

Jimmy: We will make everyone into anime.

Sphinx: Brian noo

Justine Moore: ChatGPT when another Studio Ghibli request comes in

Json: Stop posting Ghiblified images.

Squirtle: oh no husbandt, you used all our compute on making studio ghibli edits. now we are homeless.

Sam Altman: >be me

>grind for a decade trying to help make superintelligence to cure cancer or whatever

>mostly no one cares for first 7.5 years, then for 2.5 years everyone hates you for everything

>wake up one day to hundreds of messages: “look i made you into a twink ghibli style haha”

Look, I still dislike you for (quite likely destroying) everything (of value in the universe), but we can all set that aside for Ghibli Day.

I Rule the World Mo: just watched this again

Stefan: Fixed it for ya

Grant Slatton: tremendous alpha right now in sending your wife photos of yall converted to studio ghibli anime

Max: You saved my marriage, thanks

Kathleen: Works double on husbands.

Arthur B: There’s still alpha left to maximize

Kathleen B: Ohohoho there was

Important tech tip for capturing even more alpha: Thanks to the power of editing, if you have a photo of each of you, you can make any picture you want.

Danielle Fong: Press Secretary Leavitt Ending the Brief Press Brief

Discussion about this post

Fun With GPT-4o Image Generation Read More »

On (Not) Feeling the AGI

Feeling / DJ Henderson / March 26, 2025

Ben Thompson interviewed Sam Altman recently about building a consumer tech company, and about the history of OpenAI. Mostly it is a retelling of the story we’ve heard before, and if anything Altman is very good about pushing back on Thompson when Thompson tries to turn OpenAI’s future into the next Facebook, complete with an advertising revenue model.

It is such a strange perspective to witness. They do not feel the AGI, let alone the ASI. The downside risks of AI, let alone existential risks, are flat out not discussed, this is a world where that’s not even a problem for Future Earth.

Then we contrast this with the new Epoch model of economic growth from AI, which can produce numbers like 30% yearly economic growth. Epoch feels the AGI.

Given the discussion of GPT-2 in the OpenAI safety and alignment philosophy document, I wanted to note his explanation there was quite good.

Sam Altman: The GPT-2 release, there were some people who were just very concerned about, you know, probably the model was totally safe, but we didn’t know we wanted to get — we did have this new and powerful thing, we wanted society to come along with us.

Now in retrospect, I totally regret some of the language we used and I get why people are like, “Ah man, this was like hype and fear-mongering and whatever”, it was truly not the intention. The people who made those decisions had I think great intentions at the time, but I can see now how it got misconstrued.

As I said a few weeks ago, ‘this is probably totally safe but we don’t know for sure’ was exactly the correct attitude to initially take to GPT-2, given my understanding of what they knew at the time. The messaging could have made this clearer, but it very much wasn’t hype or fearmongering.

Altman repeatedly emphasizes that what he wanted to do from the beginning, what me still most wants to do, is build AGI.

Altman’s understanding of what he means by that, and what the implications will be, continues to seem increasingly confused. Now it seems it’s… fungible? And not all that transformative?

Sam Altman: My favorite historical analog is the transistor for what AGI is going to be like. There’s going to be a lot of it, it’s going to diffuse into everything, it’s going to be cheap, it’s an emerging property of physics and it on its own will not be a differentiator.

This seems bonkers crazy to me. First off, it seems to include the idea of ‘AGI’ as a fungible commodity, as a kind of set level. Even if AI stays for substantial amounts of time at ‘roughly human’ levels, differentiation between ‘roughly which humans in which ways, exactly’ is a giant deal, as anyone who has dealt with humans knows. There isn’t some natural narrow attractor level of capability ‘AGI.’

Then there’s the obvious question of why you can ‘diffuse AGI into everything’ and expect the world to otherwise look not so different, the way it did with transistors? Altman also says this:

Ben Thompson: What’s going to be more valuable in five years? A 1-billion daily active user destination site that doesn’t have to do customer acquisition, or the state-of-the-art model?

Sam Altman: The 1-billion user site I think.

That again implies little differentiation in capability, and he expects commoditization of everything but the very largest models to happen quickly.

Charles: This seems pretty incompatible with AGI arriving in that timeframe or shortly after, unless it gets commoditised very fast and subsequently improvements plateau.

Similarly, Altman in another interview continues to go with the line ‘I kind of believe we can launch the first AGI and no one cares that much.’

The whole thing is pedestrian, he’s talking about the Next Great Consumer Product. As in, Ben Thompson is blown away that this is the next Facebook, with a similar potential. Thompson and Altman are talking about issues of being a platform versus an aggregator and bundling and how to make ad revenue. Altman says they expect to be a platform only in the style of a Google, and wisely (and also highly virtuously) hopes to avoid the advertising that I sense has Thompson very excited, as he continues to assume ‘people won’t pay’ so the way you profit from AGI (!!!) is ads. It’s so weird to see Thompson trying to sell Altman on the need to make our future an ad-based dystopia, and the need to cut off the API to maximize revenue.

Such considerations do matter, and I think that Thompson’s vision is wrong on both business level and also on the normative level of ‘at long last we have created the advertising fueled cyberpunk dystopia world from the novel…’ but that’s not important now. Eyes on the damn prize!

I don’t even know how to respond to a vision so unambitious. I cannot count that low.

I mean, I could, and I have preferences over how we do so when we do, but it’s bizarre how much this conversation about AGI does not feel the AGI.

Altman’s answers in the DeepSeek section are scary. But it’s Thompson who really, truly, profoundly, simply does not get what is coming at all, or how you deal with this type of situation, and this answer from Altman is very good (at least by 2025 standards):

Ben Thompson: What purpose is served at this point in being sort of precious about these releases?

Sam Altman: I still think there can be big risks in the future. I think it’s fair that we were too conservative in the past. I also think it’s fair to say that we were conservative, but a principle of being a little bit conservative when you don’t know is not a terrible thing.

I think it’s also fair to say that at this point, this is going to diffuse everywhere and whether it’s our model that does something bad or somebody else’s model that does something bad, who cares? But I don’t know, I’d still like us to be as responsible an actor as we can be.

Other Altman statements, hinting at getting more aggressive with releases, are scarier.

They get to regulation, where Thompson repeats the bizarre perspective that previous earnest calls for regulations that only hit OpenAI and other frontier labs were an attempt at regulatory capture. And Altman basically says (in my words!), fine, the world doesn’t want to regulate only us and Google and a handful of others at the top, so we switched from asking for regulations to protect everyone into regulations to pave the way for AI.

Thus, the latest asks from OpenAI are to prevent states from regulating frontier models, and to declare universal free fair use for all model training purposes, saying to straight up ignore copyright.

Some of this week’s examples, on top of Thompson and Altman.

Spor: I genuinely get the feeling that no one *actuallybelieves in superintelligence except for the doomers

I think they were right about this (re: common argument against e/acc on x) and i have to own up to that.

John Pressman: There’s an entire genre of Guy on here whose deal is basically “Will the singularity bring me a wife?” and the more common I learn this guy is the less I feel I have in common with others.

Also this one:

Rohit: Considering AGI is coming, all coding is about to become vibe coding, and if you don’t believe it then you don’t really believe in AGI do you

Ethan Mollick: Interestingly, if you look at almost every investment decision by venture capital, they don’t really believe in AGI either, or else can’t really imagine what AGI would mean if they do believe in it.

Epoch creates the GATE model, explaining that if AI is highly useful, it will also get highly used to do a lot of highly useful things, and that would by default escalate quickly. The model is, as all such things are, simplified in important ways, ignoring regulatory friction issues and also the chance we lose control or all die.

My worry is that by ignoring regulatory, legal and social frictions in particular, Epoch has not modeled the questions we should be most interested in, as in what to actually expect if we are not in a takeoff scenario. The paper does explicitly note this.

Their default result of their model, excluding the excluded issues, is roughly 30% additional yearly economic growth.

You can play with their simulator here, and their paper is here.

Epoch AI: We developed GATE: a model that shows how AI scaling and automation will impact growth.

It predicts trillion‐dollar infrastructure investments, 30% annual growth, and full automation in decades.

Tweak the parameters—these transformative outcomes are surprisingly hard to avoid.

Imagine if a central bank took AI seriously. They’d build GATE—merging economics with AI scaling laws to show how innovation, automation, and investment interact.

At its core: more compute → more automation → growth → more investment in chips, fabs, etc.

Even when investors are uncertain, GATE predicts explosive economic growth within two decades. Trillions of dollars flow into compute, fabs, and related infrastructure—even before AI generates much value—because investors anticipate massive returns from widespread AI automation.

We’ve created an interactive sandbox so you can explore these dynamics yourself. Test your own assumptions, run different scenarios, and visualize how the economy might evolve as AI automation advances.

GATE has important limitations: no regulatory frictions, no innovation outside AI, and sensitivity to uncertain parameters. We see it as a first-order approximation of AI’s dynamics—try it out to learn how robust its core conclusions are!

Charles Foster: Epoch AI posts, for dummies

Epoch’s Ege Erdil and Matthew Barnett argue that most AI value will come from broad automation, not from R&D and scientific progress. That’s not a knock on the value of R&D, it’s saying the broad automation is even more valuable. Broadly automating labor is the name of their game.

One could say ‘wait, the reason you can do broad automation is exactly because of AI R&D, so that still makes R&D super valuable,’ so make of that dilemma what you will. A lot of this likely comes from the conflation of ‘formalized R&D’ as it is currently practiced, and ‘generally figuring things out’ which goes well beyond formalized R&D and will be turbocharged across the board. Yes, only ~20% of productivity gains look like they come from ‘R&D’ but that’s because we’re only counting formal R&D, and plausibly ignoring compounding effects.

Epoch argues against the likelihood of a full-on AI R&D singularity (or full RSI) via the standard arguments and emphasizing the need for a variety of cognitive skills. I don’t find this generally convincing, but they’re making a narrower argument than usual, that AI will first be able to fully automate a large share of the general workforce. I suppose sure, but also that’s going to happen rather quickly in such scenarios anyway?

I was pleased to see Tyler Cowen link to this without derision or claiming that it assumed its conclusions, even though it would have been highly reasonable to make similar objections.

I find very high growth scenarios highly plausible if we assume AI away loss of control and other existential risks along the way, and assume all of this is pointed in pro-human directions and that capabilities continue to scale.

Alas, I worry that the model here does not address most people’s ‘true objections.’

I don’t intend for this to be my definitive version of this, but sketching quickly, the plausibly true objections fall roughly into two categories.

First, there’s the ones that are often driving objections but that aren’t actually objections in this context:

ASI likely kills everyone. Yeah, yeah. True but here we’re assuming it doesn’t.
Disbelief on priors, absurdity heuristic, ‘sounds sci-fi’ or Nothing Ever Happens.
Belief that tech is hype or always involves tons of hype, so this is also hype.
Large growth would have implications I don’t want to think about, so no.
Large growth means nothing matters so I’m going to act as if it won’t happen.
Failure to even feel the AGI.

That’s all understandable, but not especially relevant. It’s a physical question, and it’s of the form of solving for the [Y] in ‘[X] → [Y].’

Second, there’s actual arguments, in various combinations, such as:

AI progress will stall before we reach superintelligence (ASI), because of reasons.
AI won’t be able to solve robotics or do act physically, because of reasons.
Partial automation, even 90% or 99%, is very different from 100%, o-ring theory.
Physical bottlenecks and delays prevent growth. Intelligence only goes so far.
Regulatory and social bottlenecks prevent growth this fast, INT only goes so far.
Decreasing marginal value means there literally aren’t goods with which to grow.
Dismissing ability of AI to cause humans to make better decisions.
Dismissing ability of AI to unlock new technologies.

And so on.

One common pattern is that relatively ‘serious people’ who do at least somewhat understand what AI is going to be put out highly pessimistic estimates and then call those estimates wildly optimistic and bullish. Which, compared to the expectations of most economists or regular people, they are, but that’s not the right standard here.

Dean Ball: For the record: I expect AI to add something like 1.5-2.5% GDP growth per year, on average, for a period of about 20 years that will begin in the late 2020s.

That is *wildlyoptimistic and bullish. But I do not believe 10% growth scenarios will come about.

Daniel Kokotajlo: Does that mean you think that even superintelligence (AI better than the best humans at everything, while also being faster and cheaper) couldn’t grow the economy at 10%+ speed? Or do you think that superintelligence by that definition won’t exist?

Dean Ball: the latter. it’s the “everything” that does it. 100% is a really big number. It’s radically bigger than 80%, 95%, or 99%. if bottlenecks persist–and I believe strongly that they will–we will have see baumol issues.

Daniel Kokotajlo: OK, thanks. Can you give some examples of things that AIs will remain worse than the best humans at 20 years from now?

Dean Ball: giving massages, running for president, knowing information about the world that isn’t on the internet, performing shakespeare, tasting food, saying sorry.

Samuel Hammond (responding to DB’s OP): That’s my expectation too, at least into the early 2030s as the last mile of resource and institutional constraints get ironed out. But once we have strong AGI and robotics production at scale, I see no theoretical reason why growth wouldn’t run much faster, a la 10-20% GWP. Not indefinitely, but rapidly to a much higher plateau.

Think of AGI as a step change increase in the Solow-Swan productivity factor A. This pushes out the production possibilities frontier, making even first world economies like a developing country. The marginal product of capital is suddenly much higher, setting off a period of rapid “catch up growth” to the post-AGI balanced growth path with the capital / labor ratio in steady state, signifying Baumol constraints.

Dean Ball: Right—by “AI” I really just meant the software side. Robotics is a totally separate thing, imo. I haven’t thought about the economics of robotics carefully but certainly 10% growth is imaginable, particularly in China where doing stuff is legal-er than in the us.

Thinking about AI impacts down the line without robotics seems to me like thinking about the steam engine without railroads, or computers without spreadsheets. You can talk about that if you want, but it’s not the question we should be asking. And even then, I expect more – for example I asked Claude about automating 80% of non-physical tasks, and it estimated about 5.5% additional GDP growth per year.

Another way of thinking about Dean Ball’s growth estimate is that in 20 years of having access to this, that would roughly turn Portugal into the Netherlands, or China into Romania. Does that seem plausible?

If you make a sufficient number of the pessimistic objections on top of each other, where we stall out before ASI and have widespread diffusion bottlenecks and robotics proves mostly unsolvable without ASI, I suppose you could get to 2% a year scenario. But I certainly wouldn’t call that wildly optimistic.

Distinctly, on the other objections, I will reiterate my position that various forms of ‘intelligence only goes so far’ are almost entirely a Skill Issue, certainly over a decade-long time horizon and at the margins discussed here, amounting to Intelligence Denialism. The ASI cuts through everything. And yes, physical actions take non-zero time, but that’s being taken into account, future automated processes can go remarkably quickly even in the physical realm, and a lot of claims of ‘you can only know [X] by running a physical experiment’ are very wrong, again a Skill Issue.

On the decreasing marginal value of goods, I think this is very much a ‘dreamed of in your philosophy’ issue, or perhaps it is definitional. I very much doubt that the physical limits kick in that close to where we are now, even if in important senses our basic human needs are already being met.

Altman’s model of the how AGI will impact the world is super weird if you take it seriously as a physical model of a future reality.

It’s kind of like there is this thing, ‘intelligence.’ It’s basically fungible, as it asymptotes quickly at close to human level, so it won’t be a differentiator.

There’s only so intelligent a thing can be, either in practice around current tech levels or in absolute terms, it’s not clear which. But it’s not sufficiently beyond us to be that dangerous, or for the resulting world to look that different. There’s risks, things that can go wrong, but they’re basically pedestrian, not that different from past risks. AGI will get released into the world, and ‘no one will care that much’ about the first ‘AGI products.’

I’m not willing to say that something like that is purely physically impossible, or has probability epsilon or zero. But it seems pretty damn unlikely to be how things go. I don’t see why we should expect this fungibility, or for capabilities to stall out exactly there even if they do stall out. And even if that did happen, I would expect things to change quite a lot more.

It’s certainly possible that the first AGI-level product will come out – maybe it’s a new form of Deep Research, let’s say – and initially most people don’t notice or care all that much. People often ignore exponentials until things are upon them, and can pretend things aren’t changing until well past points of no return. People might sense there were boom times and lots of cool toys without understanding what was happening, and perhaps AI capabilities don’t get out of control too quickly.

It still feels like an absurd amount of downplaying, from someone who knows better. And he’s far from alone.

Discussion about this post

On (Not) Feeling the AGI Read More »

UK on alert after H5N1 bird flu spills over to sheep in world-first

bird flu, H5N1, health, sheep, UK / DJ Henderson / March 25, 2025

In the UK, officials said further testing of the rest of the sheep’s flock has found no other infections. The one infected ewe has been humanely culled to mitigate further risk and to “enable extensive testing.”

“Strict biosecurity measures have been implemented to prevent the further spread of disease,” UK Chief Veterinary Officer Christine Middlemiss said in a statement. “While the risk to livestock remains low, I urge all animal owners to ensure scrupulous cleanliness is in place and to report any signs of infection to the Animal Plant Health Agency immediately.”

While UK officials believe that the spillover has been contained and there’s no onward transmission among sheep, the latest spillover to a new mammalian species is a reminder of the virus’s looming threat.

“Globally, we continue to see that mammals can be infected with avian influenza A(H5N1),” Meera Chand, Emerging Infection lead at the UK Health Security Agency (UKHSA), said in a statement. In the US, the Department of Agriculture has documented hundreds of infections in wild and captive mammals, from cats and bears to raccoons and harbor seals.

Chand noted that, so far, the spillovers into animals have not easily transmitted to humans. For instance, in the US, despite extensive spread through the dairy industry, no human-to-human transmission has yet been documented. But, experts fear that with more spillovers and exposure to humans, the virus will gain more opportunities to adapt to be more infectious in humans.

Chand says that UKHSA and other agencies are monitoring the situation closely in the event the situation takes a turn. “UKHSA has established preparations in place for detections of human cases of avian flu and will respond rapidly with NHS and other partners if needed.”

UK on alert after H5N1 bird flu spills over to sheep in world-first Read More »

Trump administration accidentally texted secret bombing plans to a reporter

Policy, trump administration / DJ Henderson / March 25, 2025

Using Signal in this way may have violated US law, Goldberg wrote. “Conceivably, Waltz, by coordinating a national-security-related action over Signal, may have violated several provisions of the Espionage Act, which governs the handling of ‘national defense’ information, according to several national-security lawyers interviewed by my colleague Shane Harris for this story,” he wrote.

Signal is not an authorized venue for sharing such information, and Waltz’s use of a feature that makes messages disappear after a set period of time “raises questions about whether the officials may have violated federal records law,” the article said. Adding a reporter to the thread “created new security and legal issues” by transmitting information to someone who wasn’t authorized to see it, “the classic definition of a leak, even if it was unintentional,” Goldberg wrote.

The account labeled “JD Vance” questioned the war plan in a Signal message on March 14. “I am not sure the president is aware how inconsistent this is with his message on Europe right now,” the message said. “There’s a further risk that we see a moderate to severe spike in oil prices. I am willing to support the consensus of the team and keep these concerns to myself. But there is a strong argument for delaying this a month, doing the messaging work on why this matters, seeing where the economy is, etc.”

The Vance account also stated, “3 percent of US trade runs through the suez. 40 percent of European trade does,” and “I just hate bailing Europe out again.” The Hegseth account responded that “I fully share your loathing of European free-loading. It’s PATHETIC,” but added that “we are the only ones on the planet (on our side of the ledger) who can do this.”

An account apparently belonging to Trump advisor Stephen Miller wrote, “As I heard it, the president was clear: green light, but we soon make clear to Egypt and Europe what we expect in return. We also need to figure out how to enforce such a requirement. EG, if Europe doesn’t remunerate, then what? If the US successfully restores freedom of navigation at great cost there needs to be some further economic gain extracted in return.”

Trump administration accidentally texted secret bombing plans to a reporter Read More »

Should we be concerned about the loss of weather balloons?

radiosonde, Science, Weather, weather balloons / DJ Henderson / March 25, 2025

Most of the time, not a big deal. But in critical times, the losses will be felt.

A radiosonde with mailing instructions. Credit: NWS Pittsburgh

Due to staff reductions, retirements, and a federal hiring freeze, the National Weather Service has announced a series of suspensions involving weather balloon launches in recent weeks. The question is, will this significantly degrade forecasts in the United States and around the world?

On February 27, it was announced that balloon launches would be suspended entirely at Kotzebue, Alaska, due to staffing shortages. In early March, Albany, N.Y., and Gray, Maine, announced periodic disruptions in launches. Since March 7, it appears that Gray has not missed any balloon launches through Saturday. Albany, however, has missed 14 of them, all during the morning launch cycle (12z).

The kicker came on Thursday afternoon when it was announced that all balloon launches would be suspended in Omaha, Neb., and Rapid City, S.D., due to staffing shortages. Additionally, the balloon launches in Aberdeen, S.D.; Grand Junction, Colo.; Green Bay, Wis.; Gaylord, Mich.; North Platte, Neb.; and Riverton, Wyo., would be reduced to once a day from twice a day.

What are weather balloons?

In a normal time, weather balloons would be launched across the country and world twice per day, right at about 8 am ET and 8 pm ET (one hour earlier in winter), or what we call 12z and 00z. That’s Zulu time, or noon and midnight in Greenwich, England. Rather than explain the whole reasoning behind why we use Zulu time in meteorology, here’s a primer on everything you need to know. Weather balloons are launched around the world at the same time. It’s a unique collaboration and example of global cooperation in the sciences, something that has endured for many years.

These weather balloons are loaded up with hydrogen or helium, soar into the sky, up to and beyond jet stream level, getting to a height of over 100,000 feet before they pop. Attached to the weather balloon is a tool known as a radiosonde, or “sonde” for short. This is basically a weather-sensing device that measures all sorts of weather variables like temperature, dewpoint, pressure, and more. Wind speed is usually derived from this based on GPS transmitting from the sonde.

Sunday morning’s upper air launch map showing a gaping hole over the Rockies and some of the Plains. Credit: University of Wyoming

What goes up must come down, so when the balloon pops, that radiosonde falls from the sky. A parachute is attached to it, slowing its descent and ensuring no one gets plunked on the head by one. If you find a radiosonde, it should be clearly marked, and you can keep it, let the NWS know you found it, or dispose of it properly. In some instances, there may still be a way to mail it back to the NWS (postage and envelope included and prepaid).

How this data is used

In order to run a weather model, you need an accurate snapshot of what we call the initial conditions. What is the weather at time = zero? That’s your initialization point. Not coincidentally, weather models are almost always run at 12z and 00z, to time in line with retrieving the data from these weather balloons. It’s a critically important input to almost all weather modeling we use.

The data from balloon launches can be plotted on a chart called a sounding, which gives meteorologists a vertical profile of the atmosphere at a point. During severe weather season, we use these observations to understand the environment we are in, assess risks to model output, and make changes to our own forecasts. During winter, these observations are critical to knowing if a storm will produce snow, sleet, or freezing rain.

Observations from soundings are important inputs for assessing turbulence that may impact air travel, marine weather, fire weather, and air pollution. Other than some tools on some aircraft that we utilize, the data from balloon launches is the only real good verification tool we have for understanding how the upper atmosphere is behaving.

Have we lost weather balloon data before?

We typically lose out on a data point or two each day for various reasons when the balloons are launched. We’ve also been operating without a weather balloon launch in Chatham, Mass., for a few years because coastal erosion made the site too challenging and unsafe.

Tallahassee, Fla., has been pausing balloon launches for almost a year now due to a helium shortage and inability to safely switch to hydrogen gas for launching the balloons. In Denver, balloon launches have been paused since 2022 due to the helium shortage as well.

Those are three sites, though, spread out across the country. We are doubling or tripling the number of sites without launches now, many in critical areas upstream of significant weather.

Can satellites replace weather balloons?

Yes and no.

On one hand, satellites today are capable of incredible observations that can rival weather balloons at times. And they also cover the globe constantly, which is important. That being said, satellites cannot completely replace balloon launches. Why? Because the radiosonde data those balloon launches give us basically acts as a verification metric for models in a way that satellites cannot. It also helps calibrate derived satellite data to ensure that what the satellite is seeing is recorded correctly.

But in general, satellites cannot yet replace weather balloons. They merely act to improve upon what weather balloons do. A study done in the middle part of the last decade found that wind observations improved rainfall forecasts by 30 percent. The one tool at that time that made the biggest difference in improving the forecast were radiosondes. Has this changed since then? Yes, almost certainly. Our satellites have better resolution, are capable of getting more data, and send data back more frequently. So certainly, it’s improved some. But enough? That’s unclear.

An analysis done more recently on the value of dropsondes (the opposite of balloon launches; this time, the sensor is dropped from an aircraft instead of launched from the ground) in forecasting West Coast atmospheric rivers showed a marked improvement in forecasts when those targeted drops occur. Another study in 2017 showed that aircraft observations actually did a good job filling gaps in the upper air data network.

Even with aircraft observations, there were mixed studies done in the wake of the COVID-19 reduction in air travel that suggested no impact could be detected above usual forecast error noise or that there was some regional degradation in model performance.

But to be quite honest, there have not been many studies that I can find in recent years that assess how the new breed of satellites has (or has not) changed the value of upper-air observations. The NASA GEOS model keeps a record of what data sources are of most impact to model verification with respect to 24-hour forecasts. Number two on the list? Radiosondes. This could be considered probably a loose comp to the GFS model, one of the major weather models used by meteorologists globally.

The verdict

In reality, the verdict in all this is to be determined, particularly statistically. Will it make a meaningful statistical difference in model accuracy? Over time, yes, probably, but not in ways that most people will notice day to day.

However, based on 20 years of experience and a number of conversations about this with others in the field, there are some very real, very serious concerns beyond statistics. One thing is that the suspended weather balloon launches are occurring in relatively important areas for weather impacts downstream. A missed weather balloon launch in Omaha or Albany won’t impact the forecast in California. But what if a hurricane is coming? What if a severe weather event is coming? You’ll definitely see impacts to forecast quality during major, impactful events. At the very least, these launch suspensions will increase the noise-to-signal ratio with respect to forecasts.

The element with the second-highest impact on the NASA GEOS model? Radiosondes. Credit: NASA

In other words, there may be situations where you have a severe weather event expected to kickstart in one place, but the lack of knowing the precise location of an upper air disturbance in the Rockies thanks to a suspended launch from Grand Junction, Colo., will lead to those storms forming 50 miles farther east than expected. In other words, losing this data increases the risk profile for more people in terms of knowing about weather, particularly high-impact weather.

Let’s say we have a hurricane in the Gulf that is rapidly intensifying, and we are expecting it to turn north and northeast thanks to a strong upper-air disturbance coming out of the Rockies, leading to landfall on the Alabama coast. What if the lack of upper-air observations has led to that disturbance being misplaced by 75 miles. Now, instead of Alabama, the storm is heading toward New Orleans. Is this an extreme example? Honestly, I don’t think it is as extreme as you might think. We often have timing and amplitude forecast issues with upper-air disturbances during hurricane season, and the reality is that we may have to make some more frequent last-second adjustments now that we didn’t have to in recent years. As a Gulf Coast resident, this is very concerning.

I don’t want to overstate things. Weather forecasts aren’t going to dramatically degrade day to day because we’ve reduced some balloon launches across the country. They will degrade, but the general public probably won’t notice much difference 90 percent of the time. But that 10 percent of the time? It’s not that the differences will be gigantic. But the impact of those differences could very well be gigantic, put more people in harm’s way, and increase the risk profile for an awful lot of people. That’s what this does: It increases the risk profile, it will lead to reduced weather forecast skill scores, and it may lead to an event that surprises a portion of the population that isn’t used to be surprised in the 2020s. To me, that makes the value of weather balloons very, very significant, and I find these cuts to be extremely troubling.

Should further cuts in staffing lead to further suspensions in weather balloon launches, we will see this problem magnify more often and involve bigger misses. In other words, the impacts here may not be linear, and repeated increased loss of real-world observational data will lead to very significant degradation in weather model performance that may be noticed more often than described above.

This story originally appeared on The Eyewall.

The Eyewall is dedicated to covering tropical activity in the Atlantic Ocean, Caribbean Sea, and Gulf of Mexico. The site was founded in June 2023 by Matt Lanza and Eric Berger, who work together on the Houston-based forecasting site Space City Weather.

Should we be concerned about the loss of weather balloons? Read More »

“MyTerms” wants to become the new way we dictate our privacy on the web

ad tracking, advertising, App Tracking, contracts, Creative Commons, customer commons, do not track, doc searls, IIW, privacy, Tech, VRM Day / DJ Henderson / March 25, 2025

Searls and his group are putting up the standards and letting the browsers, extension-makers, website managers, mobile platforms, and other pieces of the tech stack craft the tools. So long as the human is the first party to a contract, the digital thing is the second, a “disinterested non-profit” provides the roster of agreements, and both sides keep records of what they agreed to, the function can take whatever shape the Internet decides.

Terms offered, not requests submitted

Searls’ and his group’s standard is a plea for a sensible alternative to the modern reality of accessing web information. It asks us to stop pretending that we’re all reading agreements stuffed full with opaque language, agreeing to thousands upon thousands of words’ worth of terms every day and willfully offering up information about us. And, of course, it makes people ask if it is due to become another version of Do Not Track.

Do Not Track was a request, while MyTerms is inherently a demand. Websites and services could, of course, simply refuse to show or provide content and data if a MyTerms agent is present, or they could ask or demand that people set the least restrictive terms.

There is nothing inherently wrong with setting up a user-first privacy scheme and pushing for sites and software to do the right thing and abide by it. People may choose to stick to search engines and sites that agree to MyTerms. Time will tell if MyTerms can gain the kind of leverage Searls is aiming for.

“MyTerms” wants to become the new way we dictate our privacy on the web Read More »

Measles arrives in Kansas, spreads quickly in undervaccinated counties

health, Infectious disease, kansas, measles, MMR, outbreak, Science, texas, unvaccinated, vaccinated, virus / DJ Henderson / March 22, 2025

On Thursday, the county on the northern border of Stevens, Grant County, also reported three confirmed cases, which were also linked to the first case in Stevens. Grant County is in a much better position to handle the outbreak than its neighbors; its one school district, Ulysses, reported 100 percent vaccination coverage for kindergartners in the 2023–2024 school year.

Outbreak risk

So far, details about the fast-rising cases are scant. The Kansas Department of Health and Environment (KDHE) has not published another press release about the cases since March 13. Ars Technica reached out to KDHE for more information but did not hear back before this story’s publication.

The outlet KWCH 12 News out of Wichita published a story Thursday, when there were just six cases reported in just Grant and Stevens Counties, saying that all six were in unvaccinated people and that no one had been hospitalized. On Friday, KWCH updated the story to note that the case count had increased to 10 and that the health department now considers the situation an outbreak.

Measles is an extremely infectious virus that can linger in airspace and on surfaces for up to two hours after an infected person has been in an area. Among unvaccinated people exposed to the virus, 90 percent will become infected.

Vaccination rates have slipped nationwide, creating pockets that have lost herd immunity and are vulnerable to fast-spreading, difficult-to-stop outbreaks. In the past, strong vaccination rates prevented such spread, and in 2000, the virus was declared eliminated, meaning there was no continuous spread of the virus over a 12-month period. Experts now fear that the US will lose its elimination status, meaning measles will once again be considered endemic to the country.

So far this year, the Centers for Disease Control and Prevention has documented 378 measles cases as of Thursday, March 20. That figure is already out of date.

On Friday, the Texas health department reported 309 cases in its ongoing outbreak. Forty people have been hospitalized, and one unvaccinated child with no underlying medical conditions has died. The outbreak has spilled over to New Mexico and Oklahoma. In New Mexico, officials reported Friday that the case count has risen to 42 cases, with two hospitalizations and one death in an unvaccinated adult. In Oklahoma, the case count stands at four.

Measles arrives in Kansas, spreads quickly in undervaccinated counties Read More »

Italy demands Google poison DNS under strict Piracy Shield law

DNS, Google, piracy, Policy, Tech / DJ Henderson / March 22, 2025

Spotted by TorrentFreak, AGCOM Commissioner Massimiliano Capitanio took to LinkedIn to celebrate the ruling, as well as the existence of the Italian Piracy Shield. “The Judge confirmed the value of AGCOM’s investigations, once again giving legitimacy to a system for the protection of copyright that is unique in the world,” said Capitanio.

Capitanio went on to complain that Google has routinely ignored AGCOM’s listing of pirate sites, which are supposed to be blocked in 30 minutes or less under the law. He noted the violation was so clear-cut that the order was issued without giving Google a chance to respond, known as inaudita altera parte in Italian courts.

This decision follows a similar case against Internet backbone firm Cloudflare. In January, the Court of Milan found that Cloudflare’s CDN, DNS server, and WARP VPN were facilitating piracy. The court threatened Cloudflare with fines of up to 10,000 euros per day if it did not begin blocking the sites.

Google could face similar sanctions, but AGCOM has had difficulty getting international tech behemoths to acknowledge their legal obligations in the country. We’ve reached out to Google for comment and will update this report if we hear back.

Italy demands Google poison DNS under strict Piracy Shield law Read More »

Author name: DJ Henderson

It begins

AAA games of recent vintage

Notable independents (most notably Silksong)

The legally distinct game that sure looks like Bloodborne 2

Discussion about this post

Discussion about this post

What are weather balloons?

How this data is used

Have we lost weather balloon data before?

The verdict

Terms offered, not requests submitted

Outbreak risk