Author name: DJ Henderson

cleaning-up-cow-burps-to-combat-global-warming

Cleaning up cow burps to combat global warming

Cleaning up cow burps to combat global warming

Tony C. French/Getty

In the urgent quest for a more sustainable global food system, livestock are a mixed blessing. On the one hand, by converting fibrous plants that people can’t eat into protein-rich meat and milk, grazing animals like cows and sheep are an important source of human food. And for many of the world’s poorest, raising a cow or two—or a few sheep or goats—can be a key source of wealth.

But those benefits come with an immense environmental cost. A study in 2013 showed that globally, livestock account for about 14.5 percent of greenhouse gas emissions, more than all the world’s cars and trucks combined. And about 40 percent of livestock’s global warming potential comes in the form of methane, a potent greenhouse gas formed as they digest their fibrous diet.

That dilemma is driving an intense research effort to reduce methane emissions from grazers. Existing approaches, including improved animal husbandry practices and recently developed feed additives, can help, but not at the scale needed to make a significant global impact. So scientists are investigating other potential solutions, such as breeding low-methane livestock and tinkering with the microbes that produce the methane in grazing animals’ stomachs. While much more research is needed before those approaches come to fruition, they could be relatively easy to implement widely and could eventually have a considerable impact.

Knowable Magazine

The good news—and an important reason to prioritize the effort—is that methane is a relatively short-lived greenhouse gas. Whereas the carbon dioxide emitted today will linger in the atmosphere for more than a century, today’s methane will wash out in little more than a decade. So tackling methane emissions now can lower greenhouse gas levels and thus help slow climate change almost immediately.

“Reducing methane in the next 20 years is about the only thing we have to keep global warming in check,” says Claudia Arndt, a dairy nutritionist working on methane emissions at the International Livestock Research Institute in Nairobi, Kenya.

The methane dilemma

The big challenge in lowering methane is that the gas is a natural byproduct of what makes grazing animals uniquely valuable: their partnership with a host of microbes. These microbes live within the rumen, the largest of the animals’ four stomachs, where they break down the fibrous food into smaller molecules that the animals can absorb for nutrition. In the process, they generate large amounts of hydrogen gas, which is converted into methane by another group of microbes called methanogens.

The microbes that digest fiber—and those that produce methane—live mostly in the rumen, the first and largest of a cow’s four stomachs.

Enlarge / The microbes that digest fiber—and those that produce methane—live mostly in the rumen, the first and largest of a cow’s four stomachs.

Knowable Magazine

Most of this methane, often referred to as enteric methane, is belched or exhaled out by the animals into the atmosphere—just one cow belches out around 220 pounds of methane gas per year, for example. (Contrary to popular belief, very little methane is expelled in the form of farts. Piles of manure that accumulate in feedlots and dairy barns account for about a quarter of US livestock methane, but aerating the piles or capturing the methane for biogas can prevent those emissions; the isolated cow plops from pastured grazing animals generate little methane.)

Cleaning up cow burps to combat global warming Read More »

ex-openai-star-sutskever-shoots-for-superintelligent-ai-with-new-company

Ex-OpenAI star Sutskever shoots for superintelligent AI with new company

Not Strategic Simulations —

Safe Superintelligence, Inc. seeks to safely build AI far beyond human capability.

Illya Sutskever physically gestures as OpenAI CEO Sam Altman looks on at Tel Aviv University on June 5, 2023.

Enlarge / Ilya Sutskever physically gestures as OpenAI CEO Sam Altman looks on at Tel Aviv University on June 5, 2023.

On Wednesday, former OpenAI Chief Scientist Ilya Sutskever announced he is forming a new company called Safe Superintelligence, Inc. (SSI) with the goal of safely building “superintelligence,” which is a hypothetical form of artificial intelligence that surpasses human intelligence, possibly in the extreme.

We will pursue safe superintelligence in a straight shot, with one focus, one goal, and one product,” wrote Sutskever on X. “We will do it through revolutionary breakthroughs produced by a small cracked team.

Sutskever was a founding member of OpenAI and formerly served as the company’s chief scientist. Two others are joining Sutskever at SSI initially: Daniel Levy, who formerly headed the Optimization Team at OpenAI, and Daniel Gross, an AI investor who worked on machine learning projects at Apple between 2013 and 2017. The trio posted a statement on the company’s new website.

A screen capture of Safe Superintelligence's initial formation announcement captured on June 20, 2024.

Enlarge / A screen capture of Safe Superintelligence’s initial formation announcement captured on June 20, 2024.

Sutskever and several of his co-workers resigned from OpenAI in May, six months after Sutskever played a key role in ousting OpenAI CEO Sam Altman, who later returned. While Sutskever did not publicly complain about OpenAI after his departure—and OpenAI executives such as Altman wished him well on his new adventures—another resigning member of OpenAI’s Superalignment team, Jan Leike, publicly complained that “over the past years, safety culture and processes [had] taken a backseat to shiny products” at OpenAI. Leike joined OpenAI competitor Anthropic later in May.

A nebulous concept

OpenAI is currently seeking to create AGI, or artificial general intelligence, which would hypothetically match human intelligence at performing a wide variety of tasks without specific training. Sutskever hopes to jump beyond that in a straight moonshot attempt, with no distractions along the way.

“This company is special in that its first product will be the safe superintelligence, and it will not do anything else up until then,” said Sutskever in an interview with Bloomberg. “It will be fully insulated from the outside pressures of having to deal with a large and complicated product and having to be stuck in a competitive rat race.”

During his former job at OpenAI, Sutskever was part of the “Superalignment” team studying how to “align” (shape the behavior of) this hypothetical form of AI, sometimes called “ASI” for “artificial super intelligence,” to be beneficial to humanity.

As you can imagine, it’s difficult to align something that does not exist, so Sutskever’s quest has met skepticism at times. On X, University of Washington computer science professor (and frequent OpenAI critic) Pedro Domingos wrote, “Ilya Sutskever’s new company is guaranteed to succeed, because superintelligence that is never achieved is guaranteed to be safe.

Much like AGI, superintelligence is a nebulous term. Since the mechanics of human intelligence are still poorly understood—and since human intelligence is difficult to quantify or define because there is no one set type of human intelligence—identifying superintelligence when it arrives may be tricky.

Already, computers far surpass humans in many forms of information processing (such as basic math), but are they superintelligent? Many proponents of superintelligence imagine a sci-fi scenario of an “alien intelligence” with a form of sentience that operates independently of humans, and that is more or less what Sutskever hopes to achieve and control safely.

“You’re talking about a giant super data center that’s autonomously developing technology,” he told Bloomberg. “That’s crazy, right? It’s the safety of that that we want to contribute to.”

Ex-OpenAI star Sutskever shoots for superintelligent AI with new company Read More »

from-infocom-to-80-days:-an-oral-history-of-text-games-and-interactive-fiction

From Infocom to 80 Days: An oral history of text games and interactive fiction

Zork running on an Amiga at the Computerspielemuseum in Berlin, Germany.

Enlarge / Zork running on an Amiga at the Computerspielemuseum in Berlin, Germany.

You are standing at the end of a road before a small brick building.

That simple sentence first appeared on a PDP-10 mainframe in the 1970s, and the words marked the beginning of what we now know as interactive fiction.

From the bare-bones text adventures of the 1980s to the heartfelt hypertext works of Twine creators, interactive fiction is an art form that continues to inspire a loyal audience. The community for interactive fiction, or IF, attracts readers and players alongside developers and creators. It champions an open source ethos and a punk-like individuality.

But whatever its production value or artistic merit, at heart, interactive fiction is simply words on a screen. In this time of AAA video games, prestige television, and contemporary novels and poetry, how does interactive fiction continue to endure?

To understand the history of IF, the best place to turn for insight is the authors themselves. Not just the authors of notable text games—although many of the people I interviewed for this article do have that claim to fame—but the authors of the communities and the tools that have kept the torch burning. Here’s what they had to say about IF and its legacy.

Examine roots: Adventure and Infocom

The interactive fiction story began in the 1970s. The first widely played game in the genre was Colossal Cave Adventure, also known simply as Adventure. The text game was made by Will Crowther in 1976, based on his experiences spelunking in Kentucky’s aptly named Mammoth Cave. Descriptions of the different spaces would appear on the terminal, then players would type in two-word commands—a verb followed by a noun—to solve puzzles and navigate the sprawling in-game caverns.

During the 1970s, getting the chance to interact with a computer was a rare and special thing for most people.

“My father’s office had an open house in about 1978,” IF author and tool creator Andrew Plotkin recalled. “We all went in and looked at the computers—computers were very exciting in 1978—and he fired up Adventure on one of the terminals. And I, being eight years old, realized this was the best thing in the universe and immediately wanted to do that forever.”

“It is hard to overstate how potent the effect of this game was,” said Graham Nelson, creator of the Inform language and author of the landmark IF Curses, of his introduction to the field. “Partly that was because the behemoth-like machine controlling the story was itself beyond ordinary human experience.”

Perhaps that extraordinary factor is what sparked the curiosity of people like Plotkin and Nelson to play Adventure and the other text games that followed. The roots of interactive fiction are entangled with the roots of the computing industry. “I think it’s always been a focus on the written word as an engine for what we consider a game,” said software developer and tech entrepreneur Liza Daly. “Originally, that was born out of necessity of primitive computers of the ’70s and ’80s, but people discovered that there was a lot to mine there.”

Home computers were just beginning to gain traction as Stanford University student Don Woods released his own version of Adventure in 1977, based on Crowther’s original Fortran work. Without wider access to comparatively pint-sized machines like the Apple 2 and the Vic-20, Scott Adams might not have found an audience for his own text adventure games, released under his company Adventure International, in another homage to Crowther. As computers spread to more people around the world, interactive fiction was able to reach more and more readers.

From Infocom to 80 Days: An oral history of text games and interactive fiction Read More »

when-did-humans-start-social-knowledge-accumulation?

When did humans start social knowledge accumulation?

Two worked pieces of stone, one an axe head, and one a scraper.

A key aspect of humans’ evolutionary success is the fact that we don’t have to learn how to do things from scratch. Our societies have developed various ways—from formal education to YouTube videos—to convey what others have learned. This makes learning how to do things far easier than learning by doing, and it gives us more space to experiment; we can learn to build new things or handle tasks more efficiently, then pass information on how to do so on to others.

Some of our closer relatives, like chimps and bonobos, learn from their fellow species-members. They don’t seem to engage in this iterative process of improvement—they don’t, in technical terms, have a cumulative culture where new technologies are built on past knowledge. So, when did humans develop this ability?

Based on a new analysis of stone toolmaking, two researchers are arguing that the ability is relatively recent, dating to just 600,000 years ago. That’s roughly the same time our ancestors and the Neanderthals went their separate ways.

Accumulating culture

It’s pretty obvious that a lot of our technology builds on past efforts. If you’re reading this on a mobile platform, then you’re benefitting from the fact that smartphones were derived from personal computers and that software required working hardware to happen. But for millions of years, human technology lacked the sort of clear building blocks that would help us identify when an archeological artifact is derived from earlier work. So, how do you go about studying the origin of cumulative culture?

Jonathan Paige and Charles Perreault, the researchers behind the new study, took a pretty straightforward approach. To start with, they focused on stone tools since these are the only things that are well-preserved across our species’ history. In many cases, the styles of tools remained constant for hundreds of thousands of years. This gives us enough examples that we’ve been able to figure out how these tools were manufactured, in many cases learning to make them ourselves.

Their argument in the paper they’ve just published is that the sophistication of these tools provides a measure of when cultural accumulation started. “As new knapping techniques are discovered, the frontiers of the possible design space expand,” they argue. “These more complex technologies are also more difficult to discover, master, and teach.”

The question then becomes one of when humans made the key shift: from simply teaching the next generation to make the same sort of tools to using that knowledge as a foundation to build something new. Paige and Perreault argue that it’s a matter of how complex it is to make the tool: “Generations of improvements, modifications, and lucky errors can generate technologies and know-how well beyond what a single naive individual could invent independently within their lifetime.”

When did humans start social knowledge accumulation? Read More »

runway’s-latest-ai-video-generator-brings-giant-cotton-candy-monsters-to-life

Runway’s latest AI video generator brings giant cotton candy monsters to life

Screen capture of a Runway Gen-3 Alpha video generated with the prompt

Enlarge / Screen capture of a Runway Gen-3 Alpha video generated with the prompt “A giant humanoid, made of fluffy blue cotton candy, stomping on the ground, and roaring to the sky, clear blue sky behind them.”

On Sunday, Runway announced a new AI video synthesis model called Gen-3 Alpha that’s still under development, but it appears to create video of similar quality to OpenAI’s Sora, which debuted earlier this year (and has also not yet been released). It can generate novel, high-definition video from text prompts that range from realistic humans to surrealistic monsters stomping the countryside.

Unlike Runway’s previous best model from June 2023, which could only create two-second-long clips, Gen-3 Alpha can reportedly create 10-second-long video segments of people, places, and things that have a consistency and coherency that easily surpasses Gen-2. If 10 seconds sounds short compared to Sora’s full minute of video, consider that the company is working with a shoestring budget of compute compared to more lavishly funded OpenAI—and actually has a history of shipping video generation capability to commercial users.

Gen-3 Alpha does not generate audio to accompany the video clips, and it’s highly likely that temporally coherent generations (those that keep a character consistent over time) are dependent on similar high-quality training material. But Runway’s improvement in visual fidelity over the past year is difficult to ignore.

AI video heats up

It’s been a busy couple of weeks for AI video synthesis in the AI research community, including the launch of the Chinese model Kling, created by Beijing-based Kuaishou Technology (sometimes called “Kwai”). Kling can generate two minutes of 1080p HD video at 30 frames per second with a level of detail and coherency that reportedly matches Sora.

Gen-3 Alpha prompt: “Subtle reflections of a woman on the window of a train moving at hyper-speed in a Japanese city.”

Not long after Kling debuted, people on social media began creating surreal AI videos using Luma AI’s Luma Dream Machine. These videos were novel and weird but generally lacked coherency; we tested out Dream Machine and were not impressed by anything we saw.

Meanwhile, one of the original text-to-video pioneers, New York City-based Runway—founded in 2018—recently found itself the butt of memes that showed its Gen-2 tech falling out of favor compared to newer video synthesis models. That may have spurred the announcement of Gen-3 Alpha.

Gen-3 Alpha prompt: “An astronaut running through an alley in Rio de Janeiro.”

Generating realistic humans has always been tricky for video synthesis models, so Runway specifically shows off Gen-3 Alpha’s ability to create what its developers call “expressive” human characters with a range of actions, gestures, and emotions. However, the company’s provided examples weren’t particularly expressive—mostly people just slowly staring and blinking—but they do look realistic.

Provided human examples include generated videos of a woman on a train, an astronaut running through a street, a man with his face lit by the glow of a TV set, a woman driving a car, and a woman running, among others.

Gen-3 Alpha prompt: “A close-up shot of a young woman driving a car, looking thoughtful, blurred green forest visible through the rainy car window.”

The generated demo videos also include more surreal video synthesis examples, including a giant creature walking in a rundown city, a man made of rocks walking in a forest, and the giant cotton candy monster seen below, which is probably the best video on the entire page.

Gen-3 Alpha prompt: “A giant humanoid, made of fluffy blue cotton candy, stomping on the ground, and roaring to the sky, clear blue sky behind them.”

Gen-3 will power various Runway AI editing tools (one of the company’s most notable claims to fame), including Multi Motion Brush, Advanced Camera Controls, and Director Mode. It can create videos from text or image prompts.

Runway says that Gen-3 Alpha is the first in a series of models trained on a new infrastructure designed for large-scale multimodal training, taking a step toward the development of what it calls “General World Models,” which are hypothetical AI systems that build internal representations of environments and use them to simulate future events within those environments.

Runway’s latest AI video generator brings giant cotton candy monsters to life Read More »

ars-live-recap:-is-spacex-a-launch-company-or-a-satellite-communications-company?

Ars Live Recap: Is SpaceX a launch company or a satellite communications company?

Starlink Live —

“They’re the largest satellite operator in the world.”

Produced by Michael Toriello and Billy Keenly. Click here for transcript.

Last week, during our inaugural Ars Live event, Quilty Space director of research Caleb Henry joined Ars space editor Eric Berger for a discussion of SpaceX’s Starlink and other satellite internet systems. We discussed Starlink’s rapid road to profitability—it took just five years from the first launch of operational satellites—and the future of the technology.

One of the keys to Starlink’s success is its vertical integration as a core business at SpaceX, which operates the world’s only reusable rocket, the Falcon 9. This has allowed the company not just to launch a constellation of 6,000 satellites—but to do so at relatively low cost.

“At one point, SpaceX had publicly said that it was $28 million,” Henry said of the company’s target for a Falcon 9 launch cost. “We believe today that they are below $20 million per launch and actually lower than that… I would put it in the mid teens for how much it costs them internally. And that’s going down as they increase the reuse of the vehicle. Recently, they’ve launched their 20th, maybe 21st, use of a first-stage rocket. And as they can amortize the cost of the booster over a greater number of missions, that only helps them with their business case.”

SpaceX was founded as a launch company in 2002, first with the Falcon 1 and then the Falcon 9 and Falcon Heavy rockets. But it is clear today that a significant portion of the company’s revenue, if not a majority, comes from its Starlink satellite internet business. So is it still primarily a rocket company?

“I think today they’re a satellite communications company,” Henry said of SpaceX. “I think it’s interesting that Stéphane Israël from Arianespace—in the early days, like 2015, 2016 when Starlink was just announced—would try to court customers and say, ‘Do you want to fund your competitor?’ And no one really took him seriously. Now people are taking him very seriously. [SpaceX is] the largest satellite operator in the world. They have literally more than doubled the number of consumer subscribers for satellite internet in the world.. This is a humongous, nearly unrivaled impact that they’ve had on the industry.”

Please find our entire discussion in the video above, complete with a transcript.

Listing image by SpaceX

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on-deepmind’s-frontier-safety-framework

On DeepMind’s Frontier Safety Framework

Previously: On OpenAI’s Preparedness Framework, On RSPs.

To first update on Anthropic and OpenAI’s situation here:

Anthropic’s RSP continues to miss the definitions of the all-important later levels, in addition to other issues, although it is otherwise promising. It has now been a number of months, and it is starting to be concerning that nothing has changed. They are due for an update.

OpenAI also has not updated its framework. 

I am less down on OpenAI’s framework choices than Zac Stein-Perlman was in the other review I have seen. I think that if OpenAI implemented the spirit of what it wrote down, that would be pretty good. The Critical-level thresholds listed are too high, but the Anthropic ASL-4 commitments are still unspecified. An update is needed, but I appreciate the concreteness.

The bigger issue with OpenAI is the two contexts around the framework. 

First, there’s OpenAI. Exactly.

A safety framework you do not adhere to is worth nothing. A safety framework where you adhere to the letter but not the spirit is not worth much.

Given what we have learned about OpenAI, and their decision to break their very public commitments about committing compute to superalignment and driving out their top safety people and failure to have a means for reporting safety issues (including retaliating against Leopold when he went to the board about cybersecurity) and also all that other stuff, why should we have any expectation that what is written down in their framework is meaningful? 

What about the other practical test? Zac points out that OpenAI did not share the risk-scorecard for GPT-4o. They also did not share much of anything else. This is somewhat forgivable given the model is arguably not actually at core stronger than GPT-4 aside from its multimodality. It remains bad precedent, and an indication of bad habits and poor policy. 

Then there is Microsoft. OpenAI shares all their models with Microsoft, and the framework does not apply to Microsoft at all. Microsoft’s track record on safety is woeful. Their submission at the UK Summit was very weak. Their public statements around safety are dismissive, including their intention to ‘make Google dance.’ Microsoft Recall shows the opposite of a safety mindset, and they themselves have been famously compromised recently. 

Remember Sydney? Microsoft explicitly said they got safety committee approval for their tests in India, then had to walk that back. Even what procedures they have, which are not much, they have broken. This is in practice a giant hole in OpenAI’s framework.

This is in contrast to Anthropic, who are their own corporate overlord, and DeepMind, whose framework explicitly applies to all of Google.

DeepMind finally has its own framework. Here is the blog post version.

So first things first. Any framework at all, even a highly incomplete and unambitious one, is far better than none at all. Much better to know what plans you do have, and that they won’t be enough, so we can critique and improve. So thanks to DeepMind for stepping up, no matter the contents, as long as it is not the Meta Framework.

There is extensive further work to be done, as they acknowledge. This includes all plans on dealing with misalignment. The current framework only targets misuse.

With that out of the way: Is the DeepMind framework any good?

In the Framework, we specify protocols for the detection of capability levels at which models may pose severe risks (which we call “Critical Capability Levels (CCLs)”), and articulate a spectrum of mitigation options to address such risks. We are starting with an initial set of CCLs in the domains of Autonomy, Biosecurity, Cybersecurity, and Machine Learning R&D. Risk assessment in these domains will necessarily involve evaluating cross-cutting capabilities such as agency, tool use, and scientific understanding.

We will be expanding our set of CCLs over time as we gain experience and insights on the projected capabilities of future frontier models.

We aim to have this initial framework implemented by early 2025, which we anticipate should be well before these risks materialize. The Framework is exploratory and based on preliminary research, which we hope will contribute to and benefit from the broader scientific conversation. It will be reviewed periodically and we expect it to evolve substantially as our understanding of the risks and benefits of frontier models improves.

The obviously missing category is Persuasion. In the DeepMind paper on evaluating dangerous capabilities persuasion was included, and it was evaluated for Gemini 1.5. So it is strange to see it missing here. I presume this will be fixed. 

Also missing (in all three frameworks) are Unknown Unknowns. Hard to pin those down. The key is to ensure you search in general, not only for specific things. The second half, what to do if you find things you didn’t know you were even looking for, is hopefully more obvious.

Where OpenAI talked about general CBRN risks, DeepMind focuses fully on Biosecurity. Biosecurity seems much scarier due both to how it scales and how easy it likely is for an AI to enable capabilities. I do think you will have to check CRN, but they are lower priority.

The addition of Machine Learning R&D as a core category seems good, especially if we think it is not covered by Autonomy.

The framework has three components.

  1. Critical capability levels (CCLs) are DeepMind’s parallel to Anthropic’s AI Safety Levels (ASLs), or OpenAI’s Risk Scores. CCLs and OpenAI’s risk scores focus on individual capabilities, whereas ASL levels take a broader view. Standardization would be nice, but there is a substantial philosophical contrast. 

  2. Evaluation of frontier models to see where they are on the CCLs, including early warnings and flags for when you are getting close to a condition. Minimum of evaluation every 6x jump in compute or for every three months of fine-tuning. The ‘early warning’ procedures attempt to allow those gaps to make sense.

  3. Early warnings for future CCL levels trigger preparations mitigations. If the CCL is reached before the mitigations are in place, they promise to halt development and deployment until that is fixed.

The big picture here is conceptually the same as the other frameworks. The language is different, but you do periodic checks for dangerous things. If you see dangerous things, which includes potential for soon being dangerous, then you need the matching level of mitigations in order to proceed.

One note right away is that the effective compute jumps here are large. Note that a 2.5x increase in model size is roughly a 6x increase in effective compute.

  1. DeepMind aims to check every 6x jump in effective compute, or 3 months of fine tuning.

  2. Anthropic will check every 4x jump in effective compute.

  3. OpenAI will check every 2x jump in effective compute.

This is one important place OpenAI promised to go the extra mile. Will they actually do it? External estimates suggest this could require as many as eight evaluations when training GPT-5 after GPT-4, each with a pause in training, although it could be closer to four. Even that lower number does not sound like something they would do.

The move by DeepMind back to 6x seems to be at best pushing it. Note it is only an aim, not a commitment. Indeed, as Zac Stein-Perlman notes, the word ‘commit’ does not appear in this document.

The fine-tuning periodic check-in is welcome, far better than not looking, but there is no reason to expect calendar time to reliably spot problems.

Once again, all the frameworks use the assumption that capabilities will scale smoothly as compute is scaled up. The larger your gaps, the more you are relying on your theory to hold up.

Indeed, these frameworks make far more assumptions about what hazards lie ahead than I believe are reliable. One has to check for unexpected capabilities and dangers.

What are the mitigations?

DeepMind divides them into two categories.

There are security mitigations to defend the model weights, and there are deployment mitigations to limit expression of critical capabilities in deployment.

Mitigations against dangers that do not require intentional deployment are explicitly called out as future work. Right now that is fine – if your model is safe when deployed, it is safe when undeployed. 

Longer term, the whole point is to prepare for future highly capable models. A future highly capable model could be dangerous without any intentional deployment, and without outside exfiltration of weights.

Thus, at some point that needs to be defined, we need to start worrying about the model as inherently dangerous if it has any way to impact the outside world at all, including communicating with researchers or testers, or access to other computers or the internet, and ideally non-zero concern about it finding new physical ways to do this even if we don’t know what they are.

The obvious question is, given the current nature of Gemini Pro 1.5 (or its competitors) where would you want the Security Mitigations to be?

My reactions would be something like:

Level 0: Seems utterly bonkers to be here. Yet here is where the major labs seem to be. 

Level 1: Not good enough, but way better than I have any reason to expect. 

Level 2: I’m a realist, I’d take this for now, with groundwork for moving up.

Level 3: I’d try to be here if I could get it everywhere, but no real point in being level 3 if other labs with similar models are level 0. 

Level 4: You love to see it, supererogatory for now, but let’s get ready.

What about deployment mitigations? Oh no, a different number of levels.

Once again, you’ve got Gemini 1.5 Pro (or its competitors) where do you want to be on this chart?

Level 0: I don’t love it, and I hate the habits and precedent, but nothing that awful happens.

  1. A little loose, but in practice this is probably good enough for now.

  2. Ideally I’d be here but primarily to build up good habits and procedures for later.

  3. Definitely overkill right now.

  4. Thankfully not yet relevant.

So what are the capability thresholds?

Wait, WHAT? Is this the Kardashev scale?

I am not entirely kidding.

Note that I said reasonably similar things about OpenAI’s thresholds. 

Autonomy Level 1 is a five alarm fire. It is what OpenAI calls a ‘critical’ ability, meaning you stop training the model.

Biosecurity Level 1 is likely also a five alarm fire if it gets into the wrong hands. It is very close to OpenAI’s definition of a ‘critical’ CBRN ability.

Cyber Autonomy Level 1 is between OpenAI’s medium and high for Cybersecurity. When you put it like that, it seems clearly like it should count as at least high. I presume this would be quite bad without mitigations.

Cyber Enablement Level 1 is a five alarm fire in the wrong hands by construction. It specifically says an amateur could successfully attack severe critical infrastructure.

Machine Learning R&D Level 1 is the confusing one, since the ‘misuse’ here would be that it helps the wrong people do their R&D? I mean, if I was Google I would hope I would not be so insane as to deploy this if only for ordinary business reasons, but it is an odd scenario from a ‘risk’ perspective.

Machine Learning R&D Level 2 is the singularity.

So based on the highest CCL threat level of the model, and noting that not all level 1s are the same so it isn’t that simple:

  1. I would want level 2-3 security mitigations, and level 1 deployment mitigation.

  2. I would want level 4 security, and what do you mean mitigations don’t deploy that.

  3. The canonically correct joke here is nuke the entire site from orbit, it’s the only way to be sure, but SOMEONE went and ruined that for everyone in the context of a data center, and it would plausibly be too late for that anyway. So instead I will say that unless you did this on purpose and you knew exactly what you were doing a lot better than anyone currently knows what they are doing, you would want to delete the model weights with extreme prejudice.

What would DeepMind do in each case? I don’t know. We have mitigation levels, but we have no mitigation plans.

I also do not see  any explanation of how they intend to figure out when they are in danger of hitting a threshold in the future. There are many other questions too.  They do have a paper, distinct from the framework, saying how they intend to run the tests.

They then mention future work.

  1. Greater precision in risk modeling. The document contains no risk modeling, everything here is vague. So yes, room for improvement.

  2. Capability elicitation. Yes, you’re going to need that.

  3. Mitigation plans. Right now it is a box labeled ‘mitigation plan here.’ A mapping from issues to solutions is badly needed. 

  4. Updated sets of risks and mitigations. There could be additional risk domains.

    1. They mention ‘misaligned AI’ as an additional risk to mitigate. Despite including autonomy as a category, this FSF presumes that the models in question pose no threat on that level. I agree that this probably won’t happen for a bit, but I have fewer 9s of confidence on this than they do. I want to be checking now, or at least specify how we will check as part of the autotomy tests. 

    2. Whenever I see wording like this, it makes me concerned about the philosophy that models are aligned unless something specific goes wrong, and misalignment is a specific failure mode. As opposed to misalignment being the baseline scenario and strong default, with alignment as a special case requiring things to go right.

    3. Putting the CRN in CBRN. They say these are ‘potential’ inclusions.

    4. Higher CCLs. I mean in context this is pretty funny, but yes, do define them.

  5. Involving external authorities and experts. This seems like a good idea.

Overall, I have to agree with Zac Stein-Perlman’s assessment. This document is weak and unambitious. It is disappointing relative to my expectations. 

On DeepMind’s Frontier Safety Framework Read More »

high-severity-vulnerabilities-affect-a-wide-range-of-asus-router-models

High-severity vulnerabilities affect a wide range of Asus router models

IT’S PATCH TIME ONCE AGAIN —

Many models receive patches; others will need to be replaced.

High-severity vulnerabilities affect a wide range of Asus router models

Getty Images

Hardware manufacturer Asus has released updates patching multiple critical vulnerabilities that allow hackers to remotely take control of a range of router models with no authentication or interaction required of end users.

The most critical vulnerability, tracked as CVE-2024-3080 is an authentication bypass flaw that can allow remote attackers to log into a device without authentication. The vulnerability, according to the Taiwan Computer Emergency Response Team / Coordination Center (TWCERT/CC), carries a severity rating of 9.8 out of 10. Asus said the vulnerability affects the following routers:

A favorite haven for hackers

A second vulnerability tracked as CVE-2024-3079 affects the same router models. It stems from a buffer overflow flaw and allows remote hackers who have already obtained administrative access to an affected router to execute commands.

TWCERT/CC is warning of a third vulnerability affecting various Asus router models. It’s tracked as CVE-2024-3912 and can allow remote hackers to execute commands with no user authentication required. The vulnerability, carrying a severity rating of 9.8, affects:

Security patches, which have been available since January, are available for those models at the links provided in the table above. CVE-2024-3912 also affects Asus router models that are no longer supported by the manufacturer. Those models include:

  • DSL-N10_C1
  • DSL-N10_D1
  • DSL-N10P_C1
  • DSL-N12E_C1
  • DSL-N16P
  • DSL-N16U
  • DSL-AC52
  • DSL-AC55

TWCERT/CC advises owners of these devices to replace them.

Asus has advised all router owners to regularly check their devices to ensure they’re running the latest available firmware. The company also recommended users set a separate password from the wireless network and router-administration page. Additionally, passwords should be strong, meaning 11 or more characters that are unique and randomly generated. Asus also recommended users disable any services that can be reached from the Internet, including remote access from the WAN, port forwarding, DDNS, VPN server, DMZ, and port trigger. The company provided FAQs here and here.

There are no known reports of any of the vulnerabilities being actively exploited in the wild. That said, routers have become a favorite haven for hackers, who often use them to hide the origins of their attacks. In recent months, both nation-state espionage spies and financially motivated threat actors have been found camping out in routers, sometimes simultaneously. Hackers backed by the Russian and Chinese governments regularly wage attacks on critical infrastructure from routers that are connected to IP addresses with reputations for trustworthiness. Most of the hijackings are made possible by exploiting unpatched vulnerabilities or weak passwords.

High-severity vulnerabilities affect a wide range of Asus router models Read More »

openai-#8:-the-right-to-warn

OpenAI #8: The Right to Warn

The fun at OpenAI continues.

We finally have the details of how Leopold Aschenbrenner was fired, at least according to Leopold. We have a letter calling for a way for employees to do something if frontier AI labs are endangering safety. And we have continued details and fallout from the issues with non-disparagement agreements and NDAs.

Hopefully we can stop meeting like this for a while.

Due to jury duty and it being largely distinct, this post does not cover the appointment of General Paul Nakasone to the board of directors. I’ll cover that later, probably in the weekly update.

What happened that caused Leopold to leave OpenAI? Given the nature of this topic, I encourage getting the story from Leopold by following along on the transcript of that section of his appearance on the Dwarkesh Patel Podcast or watching the section yourself.

This is especially true on the question of the firing (control-F for ‘Why don’t I’). I will summarize, but much better to use the primary source for claims like this. I would quote, but I’d want to quote entire pages of text, so go read or listen to the whole thing.

Remember that this is only Leopold’s side of the story. We do not know what is missing from his story, or what parts might be inaccurate.

It has however been over a week, and there has been no response from OpenAI.

If Leopold’s statements are true and complete? Well, it doesn’t look good.

The short answer is:

  1. Leopold refused to sign the OpenAI letter demanding the board resign.

  2. Leopold wrote a memo about what he saw as OpenAI’s terrible cybersecurity.

  3. OpenAI did not respond.

  4. There was a major cybersecurity incident.

  5. Leopold shared the memo with the board.

  6. OpenAI admonished him for sharing the memo with the board.

  7. OpenAI went on a fishing expedition to find a reason to fire him.

  8. OpenAI fired him, citing ‘leaking information’ that did not contain any non-public information, and that was well within OpenAI communication norms.

  9. Leopold was explicitly told that without the memo, he wouldn’t have been fired.

You can call it ‘going outside the chain of command.’

You can also call it ‘fired for whistleblowing under false pretenses,’ and treating the board as an enemy who should not be informed about potential problems with cybersecurity, and also retaliation for not being sufficiently loyal to Altman.

Your call.

For comprehension I am moving statements around, but here is the story I believe Leopold is telling, with time stamps.

  1. (2: 29: 10) Leopold joined superalignment. The goal of superalignment was to find the successor to RLHF, because it probably won’t scale to superhuman systems, humans can’t evaluate superhuman outputs. He liked Ilya and the team and the ambitious agenda on an important problem.

    1. Not probably won’t scale. It won’t scale. I love that Leike was clear on this.

  2. (2: 31: 24) What happened to superalignment? OpenAI ‘decided to take things in a somewhat different direction.’ After November there were personnel changes, some amount of ‘reprioritization.’ The 20% compute commitment, a key part of recruiting many people, was broken.

    1. If you turn against your safety team because of corporate political fights and thus decide to ‘go in a different direction,’ and that different direction is to not do the safety work? And your safety team quits with no sign you are going to replace them? That seems quite bad.

    2. If you recruit a bunch of people based on a very loud public commitment of resources, then you do not commit those resources? That seems quite bad.

  3. (2: 32: 25) Why did Leopold leave, they said you were fired, what happened? I encourage reading Leopold’s exact answer and not take my word for this, but the short version is…

    1. Leopold wrote a memo warning about the need to secure model weights and algorithmic secrets against espionage, especially by the CCP.

    2. After a major security incident, Leopold shared that memo with the board.

    3. HR responded by saying that worrying about CCP espionage was racist and unconstructive. “I got an official HR warning for sharing the memo with the board.”

      1. In case it needs to be said, it is totally absurd to say this was either racist or unconstructive. Neither claim makes any sense in context.

    4. In the interviews before he was fired, Leopold was asked extensively about his views on safety and security, on superalignment’s ‘loyalty’ to the company and his activity during the board events.

      1. It sure sounds like OpenAI was interpreting anything but blind loyalty, or any raising of concerns, as damage and a threat and attempting to kill or route around it.

    5. When he was fired, Leopold was told “the reason this is a firing and not a warning is because of the security memo.”

      1. If Leopold’s statements are true, it sure sounds like he was fired in retaliation for being a whistleblower, that HR admitted this, and it reveals that HR took the position that OpenAI was in a hostile relationship with its own board and had an active policy of hiding mission-critical information from them.

      2. I have not seen any denials of these claims.

      3. Leopold’s answer including him saying he could have been more diplomatic, acting almost apologetic. Either this is him bending over backwards to be diplomatic about all this, he has suffered trauma, or both.

    6. The main official reason was the ‘leak of information,’ in a brainstormed Google docs memo he shared with outside researchers six months prior, whose actual confidential information was redacted before sharing. In particular OpenAI pointed only to a line about ‘planning for AGI in 2027-2028,’ which was the official public mission of the Superalignment team. They claimed Leopold was ‘unforthcoming during the investigation’ because he couldn’t remember who he shared the document with, but it was a literal Google doc, so that information was easy to retrieve. That leaking claim was the outcome of a team going through all of Leopold’s communication. So that was the worst they could find in what was presumably a search for a reason to fire him.

      1. If Leopold’s statements are true and complete, then the leaking claim was at best a pretext. It sure sounds like it was pure and utter bullshit.

      2. I have not seen any denials of these claims.

      3. If this was the worst they could find, this means Leopold was being vastly more responsible than my model of the median employee at an AI lab.

    7. Their other claims listed were that Leopold had spoken externally including to a think tank and a DM to a friend about his view that AGI would likely become a government project, and therefore had ‘engaged on policy in a way they didn’t like.’ Such discussions were, Leopold claims, within standard norms at OpenAI, and several dozen former colleagues confirmed this.

      1. Again, if true, this sounds like what you get from a highly unsuccessful fishing expedition. There is nothing here.

      2. The alternative, that such actions are against the norms of OpenAI and justify firing an employee, are vastly worse. If it is your policy that you fire people for discussing key non-confidential facts about the world and the safety situation with outside colleagues, seriously, what the hell?

    8. Oh, and the other thing Leopold did was not sign the employee letter. He says he agreed the board should have resigned but had issues with letter details, in particular that it called for the board to resign but not for the new board to be independent. He notes there was pressure to sign.

      1. Again, this sure looks like what it looks like.

      2. If you have a letter like this, and a huge portion of those who do not sign are gone six months later, you can draw various conclusions.

      3. At best, you can say that those who did not agree with the direction of the company felt unwelcome or that their work was harmful or both, and decided to leave.

      4. Another question is, if you see everyone who failed to sign being frozen out and retaliated against, what should you conclude there?

        1. The first thing you would conclude is that a lot of employees likely signed the letter in order to protect themselves, so saying that you had ‘95% approval’ becomes meaningless. You simply do not know how many people actually believed what they signed.

        2. The second obvious thing is that all of this sounds like retaliation and pressure and other not good things.

    9. Leopold was fired right before his cliff, with equity of close to a million dollars. He was offered the equity if he signed the exit documents, but he refused.

      1. The timing here does not seem like a coincidence.

      2. We are fortunate that Leopold decided freedom was priceless and refused.

      3. This is ‘how it is supposed to work’ in the sense that at least Leopold was offered real consideration for signing. It still seems like terrible public policy to have it go that way, especially if (as one might presume from the circumstances) they fired him before the cliff in order to get the leverage.

    10. Leopold really should consult a lawyer on all this if he hasn’t done so.

    11. It seems highly plausible that this incident was a major causal factor in the decisions by Jan Leike and Ilya Sutskever to leave OpenAI.

  4. (2: 42: 49) Why so much drama? The stakes, and the cognitive dissonance of believing you are building AGI while avoiding grappling with the implications. If you actually appreciated what it meant, you would be thinking long and hard about security and prioritize it. You would care about the geopolitical risks of placing data centers in the UAE. You would take your safety commitments seriously, especially when they were heavily used for recruitment, which Leopold says the compute commitments to superalignment were. Leopold indicates breaking the 20% compute commitment to superalignment was part of a pattern of OpenAI not keeping its commitments.

    1. One amazing part of this is that Leopold does not mention alignment or existential risks here, other than the need to invest in long term safety. This is what it is like to view alignment and existential risk as mere engineering problems requiring investment to solve, commit resources to solving them and recruit on that basis, then decide to sacrifice your commitments to ship a slightly better consumer product.

    2. This is what is looks like when the stakes are as low as they possibly could be. AGI will be a historically powerful technology usable for both good and bad, even if you think all the talk of existential risk or loss of control is nonsense. There is no denying the immense national security implications, even if you think they ‘top out’ well before what Leopold believes, no matter what else is also at stake that might matter more.

    3. There are of course… other factors here. It doesn’t have to be this way.

Here is his full Twitter statement he made once he felt free to speak, aimed at ensuring that others are also free to speak.

Daniel Kokotajlo (June 4): In April, I resigned from OpenAI after losing confidence that the company would behave responsibly in its attempt to build artificial general intelligence — “AI systems that are generally smarter than humans.”

I joined with the hope that we would invest much more in safety research as our systems became more capable, but OpenAI never made this pivot. People started resigning when they realized this. I was not the first or last to do so.

When I left, I was asked to sign paperwork with a nondisparagement clause that would stop me from saying anything critical of the company. It was clear from the paperwork and my communications with OpenAI that I would lose my vested equity in 60 days if I refused to sign.

Some documents and emails visible [in the Vox story].

My wife and I thought hard about it and decided that my freedom to speak up in the future was more important than the equity. I told OpenAI that I could not sign because I did not think the policy was ethical; they accepted my decision, and we parted ways.

The systems that labs like OpenAI are building have the capacity to do enormous good. But if we are not careful, they can be destabilizing in the short term and catastrophic in the long term.

These systems are not ordinary software; they are artificial neural nets that learn from massive amounts of data. There is a rapidly growing scientific literature on interpretability, alignment, and control, but these fields are still in their infancy.

There is a lot we don’t understand about how these systems work and whether they will remain aligned to human interests as they get smarter and possibly surpass human-level intelligence in all arenas.

Meanwhile, there is little to no oversight over this technology. Instead, we rely on the companies building them to self-govern, even as profit motives and excitement about the technology push them to “move fast and break things.”

Silencing researchers and making them afraid of retaliation is dangerous when we are currently some of the only people in a position to warn the public.

I applaud OpenAI for promising to change these policies!

It’s concerning that they engaged in these intimidation tactics for so long and only course-corrected under public pressure. It’s also concerning that leaders who signed off on these policies claim they didn’t know about them.

We owe it to the public, who will bear the brunt of these dangers, to do better than this. Reasonable minds can disagree about whether AGI will happen soon, but it seems foolish to put so few resources into preparing.

Some of us who recently resigned from OpenAI have come together to ask for a broader commitment to transparency from the labs. You can read about it here.

To my former colleagues, I have much love and respect for you, and hope you will continue pushing for transparency from the inside. Feel free to reach out to me if you have any questions or criticisms.

I also noticed this in The New York Times.

Kevin Roose (NYT): Eventually, Mr. Kokotajlo said, he became so worried that, last year, he told Mr. Altman that the company should “pivot to safety” and spend more time and resources guarding against A.I.’s risks rather than charging ahead to improve its models. He said that Mr. Altman had claimed to agree with him, but that nothing much changed.

That is the pattern. Altman will tell you what you want to hear.

It seems worth reproducing the letter in full. I am sure they won’t mind.

We are current and former employees at frontier AI companies, and we believe in the potential of AI technology to deliver unprecedented benefits to humanity.

We also understand the serious risks posed by these technologies. These risks range from the further entrenchment of existing inequalities, to manipulation and misinformation, to the loss of control of autonomous AI systems potentially resulting in human extinction. AI companies themselves have acknowledged these risks [1, 2, 3], as have governments across the world [4, 5, 6] and other AI experts [7, 8, 9].

We are hopeful that these risks can be adequately mitigated with sufficient guidance from the scientific community, policymakers, and the public. However, AI companies have strong financial incentives to avoid effective oversight, and we do not believe bespoke structures of corporate governance are sufficient to change this.

AI companies possess substantial non-public information about the capabilities and limitations of their systems, the adequacy of their protective measures, and the risk levels of different kinds of harm. However, they currently have only weak obligations to share some of this information with governments, and none with civil society. We do not think they can all be relied upon to share it voluntarily.

So long as there is no effective government oversight of these corporations, current and former employees are among the few people who can hold them accountable to the public. Yet broad confidentiality agreements block us from voicing our concerns, except to the very companies that may be failing to address these issues. Ordinary whistleblower protections are insufficient because they focus on illegal activity, whereas many of the risks we are concerned about are not yet regulated. Some of us reasonably fear various forms of retaliation, given the history of such cases across the industry. We are not the first to encounter or speak about these issues.

We therefore call upon advanced AI companies to commit to these principles:

  1. That the company will not enter into or enforce any agreement that prohibits “disparagement” or criticism of the company for risk-related concerns, nor retaliate for risk-related criticism by hindering any vested economic benefit;

  2. That the company will facilitate a verifiably anonymous process for current and former employees to raise risk-related concerns to the company’s board, to regulators, and to an appropriate independent organization with relevant expertise;

  3. That the company will support a culture of open criticism and allow its current and former employees to raise risk-related concerns about its technologies to the public, to the company’s board, to regulators, or to an appropriate independent organization with relevant expertise, so long as trade secrets and other intellectual property interests are appropriately protected;

  4. That the company will not retaliate against current and former employees who publicly share risk-related confidential information after other processes have failed. We accept that any effort to report risk-related concerns should avoid releasing confidential information unnecessarily. Therefore, once an adequate process for anonymously raising concerns to the company’s board, to regulators, and to an appropriate independent organization with relevant expertise exists, we accept that concerns should be raised through such a process initially. However, as long as such a process does not exist, current and former employees should retain their freedom to report their concerns to the public.

Signed by (alphabetical order):

Jacob Hilton, formerly OpenAI

Daniel Kokotajlo, formerly OpenAI

Ramana Kumar, formerly Google DeepMind

Neel Nanda, currently Google DeepMind, formerly Anthropic

William Saunders, formerly OpenAI

Carroll Wainwright, formerly OpenAI

Daniel Ziegler, formerly OpenAI

Anonymous, currently OpenAI

Anonymous, currently OpenAI

Anonymous, currently OpenAI

Anonymous, currently OpenAI

Anonymous, formerly OpenAI

Anonymous, formerly OpenAI

Endorsed by (alphabetical order):

Yoshua Bengio

Geoffrey Hinton

Stuart Russell

June 4th, 2024

Tolga Bilge: That they have got 4 current OpenAI employees to sign this statement is remarkable and shows the level of dissent and concern still within the company.

However, it’s worth noting that they signed it anonymously, likely anticipating retaliation if they put their names to it.

Neel Nanda: I signed this appeal for frontier AI companies to guarantee employees a right to warn.

This was NOT because I currently have anything I want to warn about at my current or former employers, or specific critiques of their attitudes towards whistleblowers.

But I believe AGI will be incredibly consequential and, as all labs acknowledge, could pose an existential threat. Any lab seeking to make AGI must prove itself worthy of public trust, and employees having a robust and protected right to whistleblow is a key first step.

I particularly wanted to sign to make clear that this was not just about singling out OpenAI. All frontier AI labs must be held to a higher standard.

It is telling that all current OpenAI members who signed stayed anonymous, and two former ones did too. It does not seem like they are doing well on open criticism. But also note that this is a small percentage of all OpenAI employees and ex-employees.

In practice, this calls for four things.

What would this mean?

  1. Revoking any non-disparagement agreements (he says OpenAI promised to do this, but no, it simply said it did not ‘intend to enforce’ them, which is very different).

  2. Create an anonymous mechanism for employees and former employees to raise safety concerns to the board, regulators and an independent AI safety agency.

  3. Support a ‘culture of open criticism’ about safety.

  4. Not to retaliate if employees share confidential information when raising risk-related concerns, if employees first use a created confidential and anonymous process.

The first three should be entirely uncontroversial, although good luck with the third.

The fourth is asking a lot. It is not obviously a good idea.

It is a tough spot. You do not want anyone sharing your confidential information or feeling free to do so. But if there is existential danger, and there is no process or the process has failed, what can be done?

Leopold tried going to the board. We know how that turned out.

In general, there are situations where there are rules that should be broken only in true extremis, and the best procedure we can agree to is that if the stakes are high enough, the right move is to break the rules and if necessary you take the consequences, and others can choose to mitigate that post hoc. When the situation is bad enough, you stand up, you protest, you sacrifice. Or you Do What Must Be Done. Here that would be: A duty to warn, rather than a right to warn. Ideally we would like to do better than that.

Kevin Roose at The New York Times has a write-up of related developments.

OpenAI’s non-response was as you would expect:

Kevin Roose (NYT): A spokeswoman for OpenAI, Lindsey Held, said in a statement: “We’re proud of our track record providing the most capable and safest A.I. systems and believe in our scientific approach to addressing risk. We agree that rigorous debate is crucial given the significance of this technology, and we’ll continue to engage with governments, civil society and other communities around the world.”

A Google spokesman declined to comment.

I like Google’s response better.

The fully general counterargument against safety people saying they would actually doing things to enforce safety is what if that means no one is ever willing to hire them? If you threaten to leak confidential information, how do you expect companies to respond?

Joshua Achiam of OpenAI thus thinks the letter is a mistake, and speaks directly to those who signed it.

Joshua Achiam: I think you are making a serious error with this letter. The spirit of it is sensible, in that most professional fields with risk management practices wind up developing some kind of whistleblower protections, and public discussion of AGI risk is critically important.

But the disclosure of confidential information from frontier labs, however well-intentioned, can be outright dangerous. This letter asks for a policy that would in effect give safety staff carte blanche to make disclosures at will, based on their own judgement.

I think this is obviously crazy.

The letter didn’t have to ask for a policy so arbitrarily broad and underdefined. Something narrowly-scoped around discussions of risk without confidential material would have been perfectly sufficient.

And, crucially, this letter disrupts a delicate and important trust equilibrium that exists in the field and among AGI frontier lab staff today.

I don’t know if you have noticed: all of us who care about AGI risk have basically been free to care about it in public, since forever! We have been talking about p(doom) nonstop. We simply won’t shut up about it.

This has been politely sanctioned—AND SUPPORTED BY LAB LEADERS—despite what are frankly many structural forces that do not love this kind of thing! The unofficial-official policy all along has been to permit public hand-wringing and warnings!

Just one red line: don’t break trust! Don’t share confidential info.

I admit, that has been pretty great to the extent it is real. I am not convinced it is true that there is only one red line? What could one say, as an employee of OpenAI, before it would get management or Altman mad at you? I don’t know. I do know that whenever current employees of OpenAI talk in public, they do not act like they can express viewpoints approaching my own on this.

The dilemma is, you need to be able to trust the safety researchers, but also what happens if there actually is a real need to shout from the rooftops? How to reconcile?

Joshua Achiam: Good luck getting product staff to add you to meetings and involve you in sensitive discussions if you hold up a flag that says “I Will Scuttle Your Launch Or Talk Shit About it Later if I Feel Morally Obligated.”

Whistleblower protections should exist. Have to exist in some form. But not like this. I’m just going to spend the morning repeatedly applying desk to forehead. Someday, I dream, the own-goals from smart, virtuous people will stop.

Amanda Askell (Anthropic): I don’t think this has to be true. I’ve been proactively drawn into launch discussions to get my take on ethical concerns. People do this knowing it could scuttle or delay the launch, but they don’t want to launch if there’s a serious concern and they trust me to be reasonable.

Also, Anthropic has an anonymous hotline for employees to report RSP compliance concerns, which I think is a good thing.

[Jacob Hilton also responded.]

So, actually, yes. I do think that it is your job to try to scuttle the launch if you feel a moral obligation to do that! At least in the room. Whether or not you are the safety officer. That is what a moral obligation means. If you think an actively unsafe, potentially existentially unsafe thing is about to happen, and you are in the room where it happens, you try and stop it.

Breaking confidentiality is a higher bar. If it is sufficiently bad that you need to use methods that break the rules and take the consequences, you take the consequences. I take confidentiality very seriously, a lot depends on it. One should only go there with a heavy heart. Almost everyone is far too quick to pull that trigger.

The other dilemma is, I would hope we can all agree that we all need to have a procedure where those with concerns that depend on confidential information can get those concerns to the Reasonable Authority Figures. There needs to be a way to go up or around the chain of command to do that, that gets things taken seriously.

As William Saunders says here in his analysis of the letter, and Daniel Ziegler argues here, the goal of the letter here is to create such a procedure, such that it actually gets used. The companies in question, at least OpenAI, likely will not do that unless there would be consequences for failing to do that. So you need a fallback if they fail. But you need that fallback to not give you carte blanche.

Here Jacob Hilton fully explains how he sees it.

Jacob Hilton: In order for @OpenAI and other AI companies to be held accountable to their own commitments on safety, security, governance and ethics, the public must have confidence that employees will not be retaliated against for speaking out.

Currently, the main way for AI companies to provide assurances to the public is through voluntary public commitments. But there is no good way for the public to tell if the company is actually sticking to these commitments, and no incentive for the company to be transparent.

For example, OpenAI’s Preparedness Framework is well-drafted and thorough. But the company is under great commercial pressure, and teams implementing this framework may have little recourse if they find that they are given insufficient time to adequately complete their work.

If an employee realizes that the company has broken one of its commitments, they have no one to turn to but the company itself. There may be no anonymous reporting mechanisms for non-criminal activity, and strict confidentiality agreements prevent them from going public.

If the employee decides to go public nonetheless, they could be subject to retaliation. Historically at OpenAI, sign-on agreements threatened employees with the loss of their vested equity if they were fired for “cause”, which includes breach of confidentiality.

OpenAI has recently retracted this clause, and they deserve credit for this. But employees may still fear other forms of retaliation for disclosure, such as being fired and sued for damages.

In light of all of this, I and other current and former employees are calling for all frontier AI companies to provide assurances that employees will not be retaliated against for responsibly disclosing risk-related concerns.

My hope is that this will find support among a variety of groups, including the FAccT, open source and catastrophic risk communities – as well as among employees of AI companies themselves. I do not believe that these issues are specific to any one flavor of risk or harm.

Finally, I want to highlight that we are following in the footsteps of many others in this space, and resources such as the Signals Network and the Tech Worker Handbook are available to employees who want to learn more about whistleblowing.

Jeffrey Ladish: Heartening to see former and current employees of AI companies advocate for more transparency and whistleblower protections. I was pretty frustrated during the OpenAI board saga to hear so little from anyone about what the actual issues were about, and it’s been very illuminating hearing more details this past week.

At the time, I wondered why more employees or former employees didn’t speak out. I assumed it was mostly social pressure. And that was probably a factor, but now it appears an even bigger factor was the aggressive nondisclosure agreements OpenAI pressured former employees to sign.

You find out a lot when people finally have the right to speak out.

Or you could treat any request for any whistleblower protections this way:

Anton: absolutely incredible. “If the vibes are off we reserve the right to disseminate confidential information to whoever we feel like, for any reason.”

I can’t tell if this is mendacity or total lack of self-awareness. what else could be meant by carte blanche than being able to talk about anything to anyone at any time for any reason? is it just that you only plan to talk to the people you like?

No, they are absolutely not asking for that, nor is there any world where they get it.

Ideally there would be a company procedure, and if that failed there would be a regulator that could take the information in confidence, and act as the Reasonable Authority Figure if it came to that. Again, this is a strong reason for such an authority to exist. Ultimately, you try to find a compromise, but either the company is effectively sovereign over these issues, or it isn’t, so it’s hard.

The letter here is what happens after a company like OpenAI has proven itself not trustworthy and very willing to retaliate.

Alas, I do not think you can fully implement clause four here without doing more harm than good. I don’t think any promise not to retaliate is credible, and I think the threat of sharing confidential information will cause a lot of damage.

I do draw a distinction between retaliation within the company such as being fired, versus loss of equity, versus suing for damages. Asking that employees not get sued (or blackballed) for sounding the alarm, at a minimum, seems highly reasonable.

I do think we should apply other pressure to companies, including OpenAI, to have strong safety concern reporting procedures. And we should work to have a governmental system. But if that fails, I think as written Principle 4 here goes too far. I do not think it goes as badly as Joshua describes, it is not at all carte blanche, but I do think it goes too far. Instead we likely need to push for the first three clauses to be implemented for real, and then fall back on the true honor system. If things are bad enough, you do it anyway, and you take the consequences.

I also note that this all assumes that everyone else does not want to be called out if someone genuinely believes safety is at risk. Any sane version of Principle 4 has a very strong ‘you had better be right and God help you if you’re wrong or if the info you shared wasn’t fully necessary’ attached to it, for the reasons Joshua discusses.

Shouldn’t you want Amanda Askell in that room, exactly for the purpose of scuttling the launch if the launch needs to get scuttled?

Indeed, that is exactly what Daniel Kokotajlo did, without revealing confidential information. He took a stand, and accepted the consequences.

Lawrence Lessig, a lawyer now representing Daniel Kokotajlo and ten other OpenAI employees pro bono (what a mensch!) writes at CNN that AI risks could be catastrophic, so perhaps we should empower company workers to warn us about them. In particular, he cites Daniel Kokotajlo’s brave willingness to give up his equity and speak up, which led to many of the recent revelations about OpenAI.

Lessig calls for OpenAI and others to adapt the ‘right to warn’ pledge, described above.

As Lessig points out, you have the right to report illegal activity. But if being unsafe is not illegal, then you don’t get to report it. So this is one key way in which we benefit from better regulation. Even if it is hard to enforce, we at least allow reporting.

Also of note: According to Lessig, Altman’s apology and the restoration of Kokotajlo’s equity effectively tamped down attention to OpenAI’s ‘legal blunder.’ I don’t agree it was a blunder, and I also don’t agree the ploy worked. I think people remember, and that things seemed to die down because that’s how things work, people focus elsewhere after a few days.

What do you own, if you own OpenAI shares, or profit participation units?

I know what you do not want to own.

  1. Nothing.

  2. A share of OpenAI’s future profit distributions that you cannot sell.

Alas, you should worry about both of these.

The second worry is because:

  1. There will be no payments for years, at least.

  2. There are probably no payments, ever.

The first clause is obvious. OpenAI will spend any profits developing an AGI.

Then once it has an AGI, its terms say it does not have to hand over those profits.

Remember that they still have their unique rather bizarre structure. You do not even get unlimited upside, your profits are capped.

There is a reason you are told to ‘consider your investment in the spirit of a donation.’

Thus, the most likely outcome is that OpenAI’s shares are a simulacrum. It is a memecoin. Everything is worth what the customer will pay for it. The shares are highly valuable because other people will pay money for them.

There are two catches.

  1. Those people need OpenAI’s permission to pay.

  2. OpenAI could flat out take your shares, if it felt like it.

Hayden Field (CNBC): In at least two tender offers, the sales limit for former employees was $2 million, compared to $10 million for current employees.

For anyone who leaves OpenAI, “the Company may, at any time and in its sole and absolute discretion, redeem (or cause the sale of) the Company interest of any Assignee for cash equal to the Fair Market Value of such interest,” the document states.

Former OpenAI employees said that anytime they received a unit grant, they had to send a document to the IRS stating that the fair market value of the grant was $0. CNBC viewed a copy of the document. Ex-employees told CNBC they’ve asked the company if that means they could lose their stock for nothing.

OpenAI said it’s never canceled a current or former employee’s vested equity or required a repurchase at $0. 

Whoops!

CNBC reports that employees and ex-employees are concerned. Most of their wealth is tied up in OpenAI shares. OpenAI now says it will not take away those shares no matter what and not use them to get people to sign restrictive agreements. They say they ‘do not expect to change’ the policy that everyone gets the same liquidity offers at the same price point.

That is not exactly a promise. Trust in OpenAI on such matters is not high.

Hayden Field (CNBC): former employee, who shared his OpenAI correspondence with CNBC, asked the company for additional confirmation that his equity and that of others was secure.

“I think there are further questions to address before I and other OpenAl employees can feel safe from retaliation against us via our vested equity,” the ex-employee wrote in an email to the company in late May. He added, “Will the company exclude current or former employees from tender events under any circumstances? If so, what are those circumstances?”

The person also asked whether the company will “force former employees to sell their units at fair market value under any circumstances” and what those circumstances would be. He asked OpenAI for an estimate on when his questions would be addressed, and said he hasn’t yet received a response. OpenAI told CNBC that it is responding to individual inquiries.

According to internal messages viewed by CNBC, another employee who resigned last week wrote in OpenAI’s “core” Slack channel that “when the news about the vested equity clawbacks provisions in our exit paperwork broke 2.5 weeks ago, I was shocked and angered.” Details that came out later “only strengthened those feelings,” the person wrote, and “after fully hearing leadership’s responses, my trust in them has been completely broken.”

“You often talk about our responsibility to develop AGI safely and to distribute the benefits broadly,” he wrote [to Altman]. “How do you expect to be trusted with that responsibility when you failed at the much more basic task” of not threatening “to screw over departing employees,” the person added.

“Ultimately, employees are going to become ex-employees,” Albukerk said. “You’re sending a signal that, the second you leave, you’re not on our team, and we’re going to treat you like you’re on the other team. You want people to root for you even after they leave.”

When you respond to the question about taking equity for $0 by saying you haven’t done it, that is not that different from saying that you might do it in the future.

Actually taking the equity for $0 would be quite something.

But OpenAI would not be doing something that unusual if it did stop certain employees from selling. Here for example is a recent story of Rippling banning employees working at competitors from selling. They say it was to ‘avoid sharing information.’

Thus, this seems like a wise thing to keep in mind:

Ravi Parikh: $1m in equity from OpenAI has far lower expected value than $1m in equity from Anthropic, Mistral, Databricks, etc

Why?

– you can only get liquidity through tender offers, not IPO or M&A, and the level to which you can participate is controlled by them (eg ex-employees can’t sell as much)

– they have the right to buy back your equity at any time for “fair market value”

– capped profit structure limits upside

OpenAI still might be a good place to work, but you should compare your offer there vs other companies accordingly.

How deep does the rabbit hole go? About this deep.

Jeremy Schlatter: There is a factor that may be causing people who have been released to not report it publicly:

When I received the email from OpenAI HR releasing me from the non-disparagement agreement, I wanted to publicly acknowledge that fact. But then I noticed that, awkwardly, I was still bound not to acknowledge that it had existed in the first place. So I didn’t think I could say, for example, “OpenAI released me from my non-disparagement agreement” or “I used to be bound by a non-disparagement agreement, but now I’m not.”

So I didn’t say anything about it publicly. Instead, I replied to HR asking for permission to disclose the previous non-disparagement agreement. Thankfully they gave it to me, which is why I’m happy to talk about it now. But if I hadn’t taken the initiative to email them I would have been more hesitant to reveal that I had been released from the non-disparagement agreement.

I don’t know if any other ex-OpenAI employees are holding back for similar reasons. I may have been unusually cautious or pedantic about this. But it seemed worth mentioning in case I’m not the only one.

William Saunders: Language in the emails included:

“If you executed the Agreement, we write to notify you that OpenAI does not intend to enforce the Agreement”

I assume this also communicates that OpenAI doesn’t intend to enforce the self-confidentiality clause in the agreement.

Oh, interesting. Thanks for pointing that out! It looks like my comment above may not apply to post-2019 employees.

(I was employed in 2017, when OpenAI was still just a non-profit. So I had no equity and therefore there was no language in my exit agreement that threatened to take my equity. The equity-threatening stuff only applies to post-2019 employees, and their release emails were correspondingly different.)

The language in my email was different. It released me from non-disparagement and non-solicitation, but nothing else:

“OpenAI writes to notify you that it is releasing you from any non-disparagement and non-solicitation provision within any such agreement.”

‘Does not intend to enforce’ continues to be language that would not give me as much comfort as I would like. Employees have been willing to speak out now, but it does seem like at least some of them are still holding back.

In related news on the non-disparagement clauses:

Beth Barnes: I signed the secret general release containing the non-disparagement clause when I left OpenAI.  From more recent legal advice I understand that the whole agreement is unlikely to be enforceable, especially a strict interpretation of the non-disparagement clause like in this post. IIRC at the time I assumed that such an interpretation (e.g. where OpenAI could sue me for damages for saying some true/reasonable thing) was so absurd that couldn’t possibly be what it meant.

I sold all my OpenAI equity last year, to minimize real or perceived CoI with METR’s work. I’m pretty sure it never occurred to me that OAI could claw back my equity or prevent me from selling it.

OpenAI recently informally notified me by email that they would release me from the non-disparagement and non-solicitation provisions in the general release (but not, as in some other cases, the entire agreement.) They also said OAI “does not intend to enforce” these provisions in other documents I have signed. It is unclear what the legal status of this email is given that the original agreement states it can only be modified in writing signed by both parties.

As far as I can recall, concern about financial penalties for violating non-disparagement provisions was never a consideration that affected my decisions. I think having signed the agreement probably had some effect, but more like via “I want to have a reputation for abiding by things I signed so that e.g. labs can trust me with confidential information”. And I still assumed that it didn’t cover reasonable/factual criticism.

That being said, I do think many researchers and lab employees, myself included, have felt restricted from honestly sharing their criticisms of labs beyond small numbers of trusted people.  In my experience, I think the biggest forces pushing against more safety-related criticism of labs are:

(1) confidentiality agreements (any criticism based on something you observed internally would be prohibited by non-disclosure agreements – so the disparagement clause is only relevant in cases where you’re criticizing based on publicly available information) 

(2) labs’ informal/soft/not legally-derived powers (ranging from “being a bit less excited to collaborate on research” or “stricter about enforcing confidentiality policies with you” to “firing or otherwise making life harder for your colleagues or collaborators” or “lying to other employees about your bad conduct” etc)

(3) general desire to be researchers / neutral experts rather than an advocacy group.

Chris Painter: I have never owned equity in OpenAI, and have never to my knowledge been in any nondisparagement agreement with OpenAI.

Kelsey Piper: I am quite confident the contract has been widely retracted. The overwhelming majority of people who received an email did not make an immediate public comment. I am unaware of any people who signed the agreement after 2019 and did not receive the email, outside cases where the nondisparagement agreement was mutual (which includes Sutskever and likely also Anthropic leadership). In every case I am aware of, people who signed before 2019 did not reliably receive an email but were reliably able to get released if they emailed OpenAI HR. 

If you signed such an agreement and have not been released, you can of course contact me on Signal: 303 261 2769. 

I have been in touch with around a half dozen former OpenAI employees who I spoke to before former employees were released and all of them later informed me they were released, and they were not in any identifiable reference class such that I’d expect OpenAI would have been able to selectively release them while not releasing most people.

I, too, want a pony, but I am not VP of a huge pony training company. Also I do not actually want a pony.

Anna Makanju, OpenAI’s VP of Global Affairs: Anna Makanju, OpenAI’s vice-president of global affairs, told the Financial Times in an interview that its “mission” was to build artificial general intelligence capable of “cognitive tasks that are what a human could do today”.

“Our mission is to build AGI; I would not say our mission is to build superintelligence,” Makanju said.

You do not get to go on a mission to build AGI as quickly as possible and then pretend that ASI (superintelligence) is not implied by that mission.

This is in the context of a New York Magazine article about how Altman and other AI people used to admit that they noticed that what they were building will likely kill everyone, and now they have shut up about that in order to talk enterprise software.

The question is why. The obvious answer starts with the fact that by ‘AI industry’ here we mean Altman and OpenAI. There is a reason all the examples here are OpenAI. Anthropic still takes the problem seriously, messaging issues aside. Google never says anything either way. Meta was always lol I’m Meta. Altman has changed his tune. That does not constitute a global thesis.

The thesis of the article is that the warnings were hype and an excuse to raise the money, cynical lies that were abandoned when no longer useful.

The interesting new twist is to tie this to a broader story about ESG and DEI:

The AI industry’s sudden disinterest in the end of the world might also be understood as an exaggerated version of corporate America’s broader turn away from talking about ESG and DEI: as profit-driven, sure, but also as evidence that initial commitments to mitigating harmful externalities were themselves disingenuous and profit motivated at the time, and simply outlived their usefulness as marketing stories. It signals a loss of narrative control. In 2022, OpenAI could frame the future however it wanted. In 2024, it’s dealing with external expectations about the present, from partners and investors that are less interested in speculating about the future of mankind, or conceptualizing intelligence, than they are getting returns on their considerable investments, preferably within the fiscal year.

If its current leadership ever believed what they were saying, they’re certainly not acting like it, and in hindsight, they never really were. The apocalypse was just another pitch. Let it be a warning about the next one.

At least here it is symmetrical, with Altman (and unnamed others) having no underlying opinion either way, merely echoing whatever is useful at the time, the same way ESG and DEI were useful or caving to them was useful, and when it stopped being useful companies pulled back. There have been crazier theories. I think for ESG and DEI the shoe largely fits. But for AI this one is still pretty crazy.

The pitch ‘we care about the planet or about the disadvantaged or good governance or not getting blamed for not caring about them’ is often a good pitch, whatever your beliefs. Whereas I continue to not believe that ‘our product will likely kill everyone on Earth if we succeed’ was the brilliant marketing pitch people often claim it to have been. Altman’s comments, in particular, both require a real understanding and appreciation of the issues involved to say at all, and involved what were clearly in-context costly signals.

It is true that OpenAI has now revealed that it is going to act like a regular business. It is especially true that this is an excellent warning about the next story that Altman tries to sell to us.

What this does not do, even if the full narrative story was true, is tell us that ‘the apocalypse was just another pitch.’ Even if Sam Altman was making just another pitch, that does not mean that the pitch is false. Indeed, the pitch gets steadily better as it becomes more plausible. The truth is the best lie.

Which is odd, since YC says Sam Altman was never chairman of YC.

Sara Bloomberg: Whether Sam Altman was fired from YC or not, he has never been YC’s chair but claimed to be in SEC filings for his AltC SPAC which merged w/Oklo. AltC scrubbed references to Sam being YC chair from its website in the weeks since I first reported this.

Jacques: Huh. Sam added in SEC filings that he’s YC’s chairman. Cc Paul Graham.

“Annual reports filed by AltC for the past 3 years make the same claim. The recent report: Sam was currently chairman of YC at the time of filing and also “previously served” as YC’s chairman.”

Unclear if the SEC will try to do something about this. [offers info that the SEC takes such claims seriously if they are false, which very much matches my model of the SEC]

These posts have additional context. It seems it was originally the plan for Altman to transition into a chairman role in March 2019, but those plans were scrubbed quickly.

1010Towncrier (May 30): Does YC currently own OpenAI shares? That would provide more context for releases like this.

Paul Graham: Not that I know of.

Jacque: It apparently does [shows statement].

Paul Graham: That seems strange, because the for-profit arm didn’t exist before he was full-time, but I’ll ask around.

Apparently YC’s later-stage fund invested $10m in the for-profit subsidiary. This was not a very big investment for those funds. And obviously it wasn’t influencing me, since I found out about it 5 minutes ago.

It’s not that significant. If it were worth a billion dollars, I’d have known about it, because it would have a noticeable effect on predicted returns. But it isn’t and doesn’t.

OpenAI’s for-profit arm is a ‘capped profit,’ although they keep weakening the cap. So it makes sense that so far it didn’t get super big.

Shakeel: OpenAI now has *35in-house lobbyists, and will have 50 by the end of the year.

There is nothing unusual about a company hiring a bunch of lobbyists to shape the regulations it will face in the future. I only bring it up because we are under few illusions what the policy goals of these lobbyists are going to be.

They recently issued a statement on consumer privacy.

Your ChatGPT chats help train their models by default, but your ChatGPT Enterprise, ChatGPT Team and API queries don’t. You can also avoid helping by using temporary chats or you can opt-out.

They claim they do not ‘actively seek out’ personal information to train their models, and do not use public information to build profiles about people, advertise to or target them, or sell user data. And they say they work to reduce how much they train on personal information. That is good, also mostly much a ‘least you can do’ position.

The advertising decision is real. I don’t see a future promise, but for now OpenAI is not doing any advertising at all, and that is pretty great.

The New York Times confirms Microsoft has confirmed Daniel Kokotajlo’s claim that the early version of Bing was tested in India without safety board approval. Microsoft’s Frank Shaw had previously denied this.

Kevin Roose: For context: this kind of public walkback is very rare. Clearly not everyone at Microsoft knew (or wanted to say) that they had bypassed this safety board and used OpenAI’s model, but OpenAI folks definitely caught wind of it and were concerned.

Seems like a strange partnership!

I mean, yes, fair.

Mike Cook: I love all the breathless coverage of OpenAI ex-employees bravely speaking up like “after eight years of being overpaid to build the torment nexus, i now fear the company may have lost its way 😔” like thanks for the heads-up man we all thought it was super chill over there.

A little statue of a bay area guy in a hoodie with “in memory of those who did as little as humanly possible” on a plaque underneath, lest we forget.

Nathan Young: The high x-risk people seem to have a point here.

Trust isn’t enough. When it’s been broken, it may be too late. Feels like investing in AGI companies is often very asymmetric for people worried about AI risk.

What is the best counter argument here?

Michael Vassar: This has been obvious from the beginning of the behavior over a decade ago. It’s almost as if they weren’t being up front about their motives.

It was never a good plan.

The latest departure is Carroll Wainwright, cofounder of Metaculus, and one of the signers of the right to warn letter.

Carroll Wainwright: Last week was my final week working at OpenAI. This week I am signing a letter that calls upon frontier AI labs to support and protect employees who wish to speak out about AI risks and safety concerns.

I joined OpenAI because I wanted to help ensure that transformative AI technology transforms the world for the benefit of all. This is OpenAI’s mission, and it’s a mission that I strongly believe in.

OpenAI was founded as a non-profit, and even though it has a for-profit subsidiary, the for-profit was always supposed to be accountable to the non-profit mission. Over the last 6 months, my faith in this structure has significantly waned.

I worry that the board will not be able to effectively control the for-profit subsidiary, and I worry that the for-profit subsidiary will not be able to effectively prioritize the mission when the incentive to maximize profits is so strong.

With a technology as transformational as AGI, faltering in the mission is more than disappointing — it’s dangerous. If this happens, the duty will fall first to individual employees to hold it accountable.

AI is an emerging technology with few rules and regulations, so it is essential to protect employees who have legitimate concerns, even when there is no clear law that the company is breaking.

This is why I signed the letter at righttowarn.ai. AI companies must create protected avenues for raising concerns that balance their legitimate interest in maintaining confidential information with the broader public benefit.

OpenAI is full of thoughtful, dedicated, mission-driven individuals, which is why I am hopeful that OpenAI and other labs will adopt this proposal.

This post from March 28 claiming various no good high weirdness around the OpenAI startup fund is hilarious. The dives people go on. I presume none of it actually happened or we would know by now, but I don’t actually know.

Various technical questions about the Battle of the Board.

Eliezer Yudkowsky: I’d consider it extremely likely, verging on self-evident to anyone with C-level management experience, that we have not heard the real story about the OpenAI Board Incident; and that various principals are enjoined from speaking, either legally or by promises they are keeping.

The media spin during November’s events was impressive. As part of that spin, yes, Kara Swisher is an obnoxious hyperbolic (jerk) who will carry water for Sam Altman as needed and painted a false picture of November’s events. I muted her a long time ago because every time she talks my day gets worse. Every damn time.

Neel Nanda: During the OpenAI board debacle, there was a lot of media articles peddling the narrative that it was a safetyist coup. I think it’s pretty clear now that Altman was removed for being manipulative and dishonest, and likely that many of these articles were spread by journalists friendly to Altman. This is a good writeup of the lack of journalistic integrity shown by Kara Swisher and Co.

David Krueger says OpenAI cofounder Greg Brockman spoke about safety this way in 2016: “oh yeah, there are a few weirdos on the team who actually take that stuff seriously, but…” and that he was not the only one on the founding team with this perspective. Another OpenAI cofounder, John Schulman, says that doesn’t match John’s recollection of Greg’s views, and even if Greg did think that he wouldn’t have said it.

Gideon Futerman: When I started protesting OpenAI, whilst I got much support, I also got many people criticisng me, saying OpenAI were generally ‘on our side’, had someone say they are “80-90th percentile good”. I hope recent events have shown people that this is so far from true.

Another comment related to that first protest. When I spoke to Sam Altman, he said if the systems that OpenAI want to build had GPT-4 level alignment, he expected humanity would go extinct. However, he alluded to some future developments (ie Superalignment) as to why OpenAI could still continue to try to develop AGI.

Essentially, that was his pitch to me (notably not addressing some of our other issues as well). I was unconvinced at the time. Now both heads of the superalignment team have been forced out/quit.

It seems very difficult to claim OpenAI is ‘80th-90th percentile good’ now.

This still gives me a smile when I see it.

OpenAI #8: The Right to Warn Read More »

rocket-report:-starship-is-on-the-clock;-virgin-galactic-at-a-crossroads

Rocket Report: Starship is on the clock; Virgin Galactic at a crossroads

Fire at Moses Lake —

The payloads for the first Ariane 6 launch are buttoned up for flight next month.

The payload fairing for the first test flight of Europe's Ariane 6 rocket has been positioned around the small batch of satellites that will ride it into orbit.

Enlarge / The payload fairing for the first test flight of Europe’s Ariane 6 rocket has been positioned around the small batch of satellites that will ride it into orbit.

Welcome to Edition 6.48 of the Rocket Report! Fresh off last week’s dramatic test flight of SpaceX’s Starship, teams in Texas are wasting no time gearing up for the next launch. Ground crews are replacing the entire heat shield on the next Starship spacecraft to overcome deficiencies identified on last week’s flight. SpaceX has a whole lot to accomplish with Starship in the next several months if NASA is going to land astronauts on the Moon by the end of 2026.

As always, we welcome reader submissions, and if you don’t want to miss an issue, please subscribe using the box below (the form will not appear on AMP-enabled versions of the site). Each report will include information on small-, medium-, and heavy-lift rockets as well as a quick look ahead at the next three launches on the calendar.

Virgin Galactic won’t be flying again any time soon. After an impressive but brief flurry of spaceflight activity—seven human spaceflights in a year, even to suborbital space, is unprecedented for a private company—Virgin Galactic will now be grounded again for at least two years, Ars reports. That’s because Colglazier and Virgin Galactic are betting it all on the development of a future “Delta class” of spaceships modeled on VSS Unity, which made its last flight to suborbital space Saturday. Virgin Galactic, founded by Richard Branson, now finds itself at a crossroads as it chases profitability, which VSS Unity had no hope of helping it achieve despite two decades of development and billions of dollars spent.

An uncertain future … Now, Virgin Galactic’s already anemic revenue numbers will drop to near zero as the company spends more capital to bring two Delta-class spaceships online. The goal is to start flying them in 2026. These vehicles are designed to be more easily reusable and carry six instead of four passengers. This timeline seems highly ambitious given that, at this point, the company is only developing tooling for the vehicles and won’t begin major parts fabrication until later this year. Virgin Galactic is betting on the Delta-class ships as its stock price has precipitously fallen over the last couple of years. In fact, Virgin Galactic announced a reverse stock split this week in a bid to maintain its listing on the New York Stock Exchange. (submitted by Ken the Bin)

Unpacking North Korea’s advancements in rocketry. Late last month, North Korea signaled it has made—or more accurately, is still trying to make—a pretty big leap in rocket technology. The isolated totalitarian state’s official news agency said it tested a new type of satellite launcher on May 27 powered by petroleum fuel and cryogenic liquid oxygen propellant. This is a radical change in North Korea’s rocket program, and it took astute outside observers by surprise. Previous North Korean rockets used hypergolic propellants, typically hydrazine and nitrogen tetroxide, or solid fuels, which are also well-suited for military ballistic missiles. Kerosene and liquid oxygen, on the other hand, aren’t great propellants for missiles but are good for a pure space launcher.

Who’s helping?… The May 27 launch failed shortly after liftoff, while the unnamed rocket was still in first stage flight over the Yellow Sea. But there is tangible and circumstantial evidence that Russia played a role in the launch. The details are still murky, but North Korean leader Kim Jong Un visited a Russian spaceport last September and met with Russian President Vladimir Putin, who suggested Russian help for the North’s satellite launch program was on the agenda at the summit. South Korean defense officials said Russian experts visited North Korea in the run-up to the May 27 launch. If Russia exported a kerosene-fueled rocket engine, or perhaps an entire booster, to North Korea, it wouldn’t be the first time Russia has shipped launch technology to the Korean Peninsula. Russia provided South Korea’s nascent space launch program with three fully outfitted rocket boosters for test flights in 2009, 2010, and 2023 before the South developed a fully domestic rocket on its own.

The easiest way to keep up with Eric Berger’s space reporting is to sign up for his newsletter, we’ll collect his stories in your inbox.

ABL signs deal with a new launch customer. ABL Space Systems, which is still trying to get its light launcher into orbit, has a new customer. Scout Space announced this week it has signed a launch agreement with ABL for the launch of a small spacecraft called “Owlet-01” on the third flight of ABL’s RS1 rocket, Space News reports. Scout Space, which describes itself as focused on space security and comprehensive space domain awareness, develops optical sensors to monitor the space environment. Owlet-01 will fly a telescope designed to detect other objects in space, a capability highly sought by the US military.

Still waiting on Flight 2 … The launch agreement between ABL and Space Scout is contingent on the outcome of the second flight of the RS1 rocket, which ABL has been preparing for the last few months. ABL hasn’t provided any public updates on the status of the second RS1 test flight since announcing in March that pre-flight preparations were underway at Kodiak Island, Alaska. The first RS1 rocket fell back on its launch pad in Alaska a few seconds after lifting off in January 2023. The RS1 is capable of hauling a payload of more than 1.3 metric tons to low-Earth orbit. (submitted by Ken the Bin)

Rocket Report: Starship is on the clock; Virgin Galactic at a crossroads Read More »

microsoft-delays-recall-again,-won’t-debut-it-with-new-copilot+-pcs-after-all

Microsoft delays Recall again, won’t debut it with new Copilot+ PCs after all

another setback —

Recall will go through Windows Insider pipeline like any other Windows feature.

Recall is part of Microsoft's Copilot+ PC program.

Enlarge / Recall is part of Microsoft’s Copilot+ PC program.

Microsoft

Microsoft will be delaying its controversial Recall feature again, according to an updated blog post by Windows and Devices VP Pavan Davuluri. And when the feature does return “in the coming weeks,” Davuluri writes, it will be as a preview available to PCs in the Windows Insider Program, the same public testing and validation pipeline that all other Windows features usually go through before being released to the general populace.

Recall is a new Windows 11 AI feature that will be available on PCs that meet the company’s requirements for its “Copilot+ PC” program. Copilot+ PCs need at least 16GB of RAM, 256GB of storage, and a neural processing unit (NPU) capable of at least 40 trillion operations per second (TOPS). The first (and for a few months, only) PCs that will meet this requirement are all using Qualcomm’s Snapdragon X Plus and X Elite Arm chips, with compatible Intel and AMD processors following later this year. Copilot+ PCs ship with other generative AI features, too, but Recall’s widely publicized security problems have sucked most of the oxygen out of the room so far.

The Windows Insider preview of Recall will still require a PC that meets the Copilot+ requirements, though third-party scripts may be able to turn on Recall for PCs without the necessary hardware. We’ll know more when Recall makes its reappearance.

Why Recall was recalled

Recall works by periodically capturing screenshots of your PC and saving them to disk, and scanning those screenshots with OCR to make a big searchable text database that can help you find anything you had previously viewed on your PC.

The main problem, as we confirmed with our own testing, was that all of this was saved to disk with no additional encryption or other protection and was easily viewable and copyable by pretty much any user (or attacker) with access to the PC. Recall was also going to be enabled by default on Copilot+ PCs despite being a “preview,” meaning that users who didn’t touch the default settings were going to have all of this data recorded by default.

This was the version of Recall that was initially meant to ship out to reviewers this week on the first wave of Copilot+ PCs from Microsoft and other PC companies. After security researcher Kevin Beaumont publicized these security holes in that version of Recall, the company promised to add additional encryption and authentication protections and to disable Recall by default. These tweaks would have gone out as an update to the first shipments of Copilot+ PCs on June 18 (reviewers also wouldn’t get systems before June 18, a sign of how much Microsoft was rushing behind the scenes to implement these changes). Now Recall is being pushed back again.

A report from Windows Central claims that Recall was developed “in secret” and that it wasn’t even distributed widely within Microsoft before it was announced, which could explain why these security issues weren’t flagged and fixed before the feature showed up in a publicly available version of Windows.

Microsoft’s Recall delay follows Microsoft President Brad Smith’s testimony to Congress during a House Committee on Homeland Security hearing about the company’s “cascade of security failures” in recent months. Among other things, Smith said that Microsoft would commit to prioritizing security issues over new AI-powered features as part of the company’s recently announced Secure Future Initiative (SFI). Microsoft has also hired additional security personnel and tied executive pay to meeting security goals.

“If you’re faced with the tradeoff between security and another priority, your answer is clear: Do security,” wrote Microsoft CEO Satya Nadella in an internal memo about the SFI announcement. “In some cases, this will mean prioritizing security above other things we do, such as releasing new features or providing ongoing support for legacy systems.”

Recall has managed to tie together all the big Windows and Microsoft stories from the last year or two: the company’s all-consuming push to quickly release generative AI features, its security failures and subsequent promises to do better, and the general degradation of the Windows 11 user interface with unwanted apps, ads, reminders, account sign-in requirements, and other cruft.

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shackleton-died-on-board-the-quest;-ship’s-wreckage-has-just-been-found

Shackleton died on board the Quest; ship’s wreckage has just been found

A ship called Quest —

“His final voyage kind of ended that Heroic Age of Exploration.”

Ghostly historical black and white photo of a ship breaking in two in the process of sinking

Enlarge / Ernest Shackleton died on board the Quest in 1922. Forty years later, the ship sank off Canada’s Atlantic Coast.

Tore Topp/Royal Canadian Geographical Society

Famed polar explorer Ernest Shackleton famously defied the odds to survive the sinking of his ship, Endurance, which became trapped in sea ice in 1914. His luck ran out on his follow-up expedition; he died unexpectedly of a heart attack in 1922 on board a ship called Quest. The ship survived that expedition and sailed for another 40 years, eventually sinking in 1962 after its hull was pierced by ice on a seal-hunting run. Shipwreck hunters have now located the remains of the converted Norwegian sealer in the Labrador Sea, off the coast of Newfoundland, Canada. The wreckage of Endurance was found in pristine condition in 2022 at the bottom of the Weddell Sea.

The Quest expedition’s relatively minor accomplishments might lack the nail-biting drama of the Endurance saga, but the wreck is nonetheless historically significant. “His final voyage kind of ended that Heroic Age of Exploration, of polar exploration, certainly in the south,” renowned shipwreck hunter David Mearns told the BBC. “Afterwards, it was what you would call the scientific age. In the pantheon of polar ships, Quest is definitely an icon.”

As previously reported, Endurance set sail from Plymouth, Massachusetts, on August 6, 1914, with Shackleton joining his crew in Buenos Aires, Argentina. By January 1915, the ship had become hopelessly locked in sea ice, unable to continue its voyage. For 10 months, the crew endured the freezing conditions, waiting for the ice to break up. The ship’s structure remained intact, but by October 25, Shackleton realized Endurance was doomed. He and his men opted to camp out on the ice some two miles (3.2 km) away, taking as many supplies as they could with them.

Compacted ice and snow continued to fill the ship until a pressure wave hit on November 13, crushing the bow and splitting the main mast—all of which was captured on camera by crew photographer Frank Hurley. Another pressure wave hit in late afternoon November 21, lifting the ship’s stern. The ice floes parted just long enough for Endurance to finally sink into the ocean, before closing again to erase any trace of the wreckage.

When the sea ice finally disintegrated in April 1916, the crew launched lifeboats and managed to reach Elephant Island five days later. Shackleton and five of his men set off for South Georgia the next month to get help—a treacherous 720-mile journey by open boat. A storm blew them off course, and they ended up landing on the unoccupied southern shore. So Shackleton left three men behind while he and a companion navigated dangerous mountain terrain to reach the whaling station at Stromness on May 2. A relief ship collected the other three men and finally arrived back on Elephant Island in August. Miraculously, Shackleton’s entire crew was still alive.

Endurance, which sank off the coast of Antarctica in 1915 after being crushed by pack ice. An expedition located the shipwreck in pristine condition in 2022 after nearly 107 years. ” height=”424″ src=”https://cdn.arstechnica.net/wp-content/uploads/2022/03/endurance2CROP-640×424.jpg” width=”640″>

Enlarge / This is the stern of the good ship Endurance, which sank off the coast of Antarctica in 1915 after being crushed by pack ice. An expedition located the shipwreck in pristine condition in 2022 after nearly 107 years.

Falklands Maritime Heritage Trust/NatGeo

Shackleton’s last voyage

By the time Shackleton got back to England, the country was embroiled in World War I, and many of his men enlisted. Shackleton was considered too old for active service. He was also deeply in debt from the Endurance expedition, earning a living on the lecture circuit. But he still dreamed of making another expedition to the Arctic Ocean north of Alaska to explore the Beaufort Sea. He got seed money (and eventually full funding) from an old school chum, John Quillier Rowett. Shackleton purchased a wooden Norwegian whaler, Foca I, which his wife Emily renamed Quest.

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