Tim Belzer – Page 5

Controversial NIH director now in charge of CDC, too, in RFK Jr. shake-up

anti-vaccine, Bhattacharya, CDC, health, NIH, robert f kennedy jr, vaccine / Tim Belzer / February 20, 2026

Insiders report that, as NIH director, Bhattacharya delegates most of his responsibilities for running the $47 billion agency to two top officials. Instead of a hands-on leader, Bhattacharya has become known for his many public interviews, earning him the nickname “Podcast Jay.”

“Malpractice”

Researchers expect that Bhattacharya will perform similarly at the helm of the CDC. Jenna Norton, an NIH program officer who spoke to the Guardian in her personal capacity, commented that Bhattacharya “won’t actually run the CDC. Just as he doesn’t actually run NIH.” His role for the administration, she added, “is largely as a propagandist.”

Jeremy Berg, former director of the National Institute of General Medical Sciences, echoed the sentiment to the Guardian. “Now, rather than largely ignoring the actual operations of one agency, he can largely ignore the actual operations of two,” he said.

Kayla Hancock, director of Public Health Watch, a nonprofit advocacy group, went further in a public statement, saying, “Jay Bhattacharya has overseen the most chaotic and rudderless era in NIH history, and for RFK Jr. to give him even more responsibility at the CDC is malpractice against the public health.”

Like other commenters, Hancock noted his apparent lack of involvement at the NIH and put it in the context of the current state of US public health. “This is the last person who should be overseeing the CDC at a time when preventable diseases like measles are roaring back under RFK Jr.’s deadly anti-vax agenda,” she said.

It is widely expected that Bhattacharya will, like O’Neill, act as a rubber-stamp for Kennedy’s relentless anti-vaccine agenda items. When Kennedy dramatically overhauled the CDC’s childhood vaccine schedule, slashing recommended vaccinations from 17 to 11 without scientific evidence, Bhattacharya was among the officials who signed off on the unprecedented change.

Ultimately, Bhattacharya will only be in the role for a short time, at least officially. The role of CDC director became a Senate-confirmed position in 2023, and, as such, an acting director can serve only 210 days from the date the role became vacant. That deadline comes up on March 25. President Trump has not nominated anyone to fill the director role.

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AI #156 Part 2: Errors in Rhetoric

Errors / Tim Belzer / February 20, 2026

Things that are being pushed into the future right now:

Gemini 3.1 Pro and Gemini DeepThink V2.
Claude Sonnet 4.6.
Grok 4.20.
Updates on Agentic Coding.
Disagreement between Anthropic and the Department of War.

We are officially a bit behind and will have to catch up next week.

Even without all that, we have a second highly full plate today.

(As a reminder: bold are my top picks, italics means highly skippable)

Levels of Friction. Marginal costs of arguing are going down.
The Art Of The Jailbreak. UK AISI finds a universal method.
The Quest for Sane Regulations. Some relatively good proposals.
People Really Hate AI. Alas, it is mostly for the wrong reasons.
A Very Bad Paper. Nick Bostrom writes a highly disappointing paper.
Rhetorical Innovation. The worst possible plan is the best one on the table.
The Most Forbidden Technique. No, stop, come back.
Everyone Is Or Should Be Confused About Morality. New levels of ‘can you?’
Aligning a Smarter Than Human Intelligence is Difficult. Seeking a good basin.
We’ll Just Call It Something Else. Beware responsible uncertainty quantification.
Vulnerable World Hypothesis. I’m sorry, I can’t help you with that. Suspicious.
Autonomous Killer Robots. Progress is being made.
People Will Hand Over Power To The AIs. They keep telling us they will do this.
People Are Worried About AI Killing Everyone. Or they don’t, for unclear reasons.
Other People Are Not Worried About AI Killing Everyone. Alas, Jensen Huang.
The Lighter Side. Word overboard.

If the marginal cost goes to zero, and it inflicts marginal costs above zero on others? That system is going to have a bad time.

Marc Andreessen: Overheard in Silicon Valley: “Marginal cost of arguing is going to zero.”

Emma Jacobs: Anna Bond, legal director in the employment team at Lewis Silkin, used to receive grievances that were typically the length of an email. Now, the complaints she sees can run to about 30 pages and span a wide range of historical issues, many of which are repeated.

“I suspect that AI is behind it,” says Bond.

There’s no need to suspect. It’s AI. The marginal cost here remains very not zero. You still have to gather and document all the information for the AI somehow.

If the AI is expanding a complaint into a giant mass of AI slop, then the response is to process such complaints using AI. You turn your paragraph into 30 pages, then I turn your 30 pages into a paragraph, but with the ability to then query the 30 pages as needed. I know which parts matter and should be in the paragraph, so this could be net good.

The rest of the examples are similar. If you’re up against AI slop court filings, you can slap them down or you can invoke your own AI, or both, and so on.

The bigger problem is what happens when the AI knows the magic words.

Patrick McKenzie: Not where I would have expected an adversarial touchpoint to get saturated first, and extremely not the last such story.

If there are magic words which trigger an effect in the physical universe, then that expenditure of resources has been implicitly rate limited on how many people know the magic words and prioritize saying them.

There are a lot of magic words in our society.

Presumably in some circumstances we decide “Eh if words are cheap they can’t also be magic” but we have looked at that tradeoff before for some touch points and said “Nope actually critically important here: the right words in right order are always magic.”

I’m most inclined to think of a few hundred examples from finance but the Due Process clause of the U.S. Constitution has a side effect of creating many, many magic words across all levels and almost all activities of the administrative state.

And there is no Constitutional escape hatch for “A facially valid plea for relief under Due Process is invalid if it was not artisanal in craftsmanship. It is also invalid if not signed by a certifiably important person.”

Oh sure there is, it is called the ‘SCOTUS members make stuff up based on what would work’ clause of the Constitution. You know that one.

I don’t mean that pejoratively. Well sometimes yes I do, but also there’s plenty of ‘not a suicide pact’ rulings that can adjust for practicalities. If everyone can always demand all the due process, and they start doing so a lot, then we’ll redefine what that due process looks like to let AI largely handle that end, or change when you are entitled to how much of it. How much Process is Due, after all?

“Example from finance?”

Reg E complaint on an error in processing an electronic transaction. If you say “Reg E” bank just spent ~$200 unless they’ve aggressively optimized for cramming down that number.

Exactly. The bank spent $200 now, but they can and will optimize for cramming that number down, primarily using AI. This will include some form of ‘use AI to detect when it is likely someone is making invalid Reg E claims.’

“Example from non-finance?”

Complaints about teachers are either a) grousing common to students since time immemorial or b) immediate 5-6 figure investigations. Only takes three words to promote a complaint into that second category.

This is a curiously non-AI example, in that either you know the three words or you don’t, and most of us do know them or guessed them correctly.

The UK AISI shares information on their universal jailbreaking technique:

AISI: Today, we’re sharing information on Boundary Point Jailbreaking (BPJ): a fully automated method for developing universal jailbreaks against the most robust deployed AI defences, in fully ‘black-box’ settings where attackers only see whether or not an input is blocked.

We believe BPJ is the first automated attack to succeed against Constitutional Classifiers [1], Anthropic’s defence system that previously withstood over 3,700 hours of human red-teaming with only one fully successful, human-led attack found in that time. BPJ is also the first automated attack to succeed against OpenAI’s input classifier for GPT-5 without relying on human seed attacks [2].

OpenAI says they have deployed mitigations to reduce susceptibility.

One obvious suggestion on defense is to use a potentially very cheap ‘is there weirdness in the input’ classifier to find times when you suspect someone of trying to use an adversarial prompt.

A good sign that some of the old semi-reasonable model of the situation has not been entirely abandoned by OpenAI?

Charbel-Raphael: Sam Altman: “The world may need something like an IAEA [International Atomic Energy Agency] for international coordination on AI”

Yes!

Alex Bores proposes his AI policy framework for Congress.

Protect kids and students: Parental visibility. Age verification for risky AI services. Require scanning for self-harm. Teach kids about AI. Clear guidelines for AI use in schools, explore best uses. Ban AI CSAM.
Take back control of your data. Privacy laws, data ownership, no sale of personal data, disclosure of AI interactions and data collections and training data.
Stop deepfakes. Metadata standards, origin tracing, penalties for distribution.
Make datacenters work for people. No rate hikes, enforce agreements, expedite data centers using green energy, repair the grid with private funds, monitor water use, close property tax loopholes.
Protect and support workers. Require large companies to report AI-related workforce changes. Tax incentives for upskilling, invest in retraining, ban AI as sole decider for hiring and firing, transitional period where AI needs same licensing as a human, tax large companies for an ‘AI dividend.’
Nationalize the Raise Act for Frontier AI. Require independent safety testing, mandate cybersecurity incident reporting, restrict government use of foreign AI tools, create accountability mechanisms for AI systems that harm, engage in diplomacy on AI issues.
Build Government Capacity to Oversee AI. Fund CAISI, expand technical expertise, require developers to disclose key facts to regulators, develop contingency plans for catastrophic risks.
Keep America Competitive. Federal funding for academic research, support for private development of safe, beneficial applications, ‘reasonable regulation that protects people without strangling innovation,’ work with allies to establish safety standards, strategic export controls, keep the door open for international agreements.

I would like to see more emphasis on Frontier AI here, and I worry about the licensing and tax talk in #5, but mostly this is a solid list. It is also, if you disregard those few items, a highly balanced list that most should be able to get behind.

Joshua Achiam (OpenAI): I think most of this framework is actually pretty commonsense, and responsive to the intersection of public, private, and national strategic needs. I have quibbles in a few places but this is a sober, credible contribution to the discourse

Nathan Calvin: Appreciate Joshua calling balls and strikes and engaging with the details.

OAI/A16z/Palantir’s Superpac spending massive to go after Alex Bores for his moderate commonsense platform on AI has honestly been one of the most disenchanting things I have ever seen in politics

The White House continues not to propose a new regulatory regime, and is leaning on Utah to abandon its prospective AI bill.

Joe Miller (FT): A White House official said the administration objected to the bill owing to its resemblance to California’s SB53, which critics claim added unnecessary bureaucratic burdens on US AI companies as they try to compete with China.

This is exactly backwards. SB 53 is a bill so mild that David Sacks finds it potentially acceptable as a national standard, and the worry is that states will have a patchwork of different laws. If Utah’s proposed HB 286 is duplicative of SB 53 and the White House is not lying about what it cares about, then the overlap is Great News for AI companies and the White House.

There are some additional requirements in HB 286.

Anyone with a million MAUs needs to have a child protection plan.
Whistleblower protections are broader, which seems good.
Quarterly reports have to be filed with Utah in particular, and we don’t want you to have to file 50 distinct reports.

The quarterly report seems like the strongest point of objection, and I haven’t looked closely into the child protection requirements, but those are things that are often fixed as bills progress. Instead the White House is calling this an ‘unfixable’ bill.

The White House did announce the ‘AI Agents Standards Initiative’ for interoperable and secure innovation, to support standards and open source protocols for agents and promote trusted adoption. Good, but this doesn’t alleviate our core problems and it very much is not a federal framework.

Greg Brockman confirms that his donations to the anti-all-AI-regulation SuperPAC were an extension of his work at OpenAI.

Dean Ball is right that prohibiting LLMs from ‘simulating human exchange’ or ‘demonstrating emotion’ would be a serious mistake, being quite bad for the performance and experience of both models and their users. It seems fine to cordon off full companion-style services, if done wisely.

Dan Kagan-Kans has another overview of how the left is in full denial about AI, academia is too slow moving to be relevant, and both are being left behind almost entirely in discussions about AI as a result.

Jasmine lists the varied coalition of concerns against AI, many of which are phantoms, and none of which were catastrophic or existential risk. The ‘coalition of the unwilling’ excludes the actual AI safety people worried about not dying, because those are the people with epistemics and principles.

I hear that MIRI-style doomers are now regulars at some Republican Senate offices, while Democratic senators knock on AI VCs’ doors to ask them whether we’ll get mass layoffs.

The AI safety community seems conflicted about whether to engage in populist protest tactics. Dispositionally, most effective altruist types tend toward technocratic precision over fiery sloganeering (a trait which, while respectable, does not always serve their goals). That’s how you get a world where Andy Masley—the left-leaning DC EA chief—ended up writing the AI industry’s best rebuttal against the spicy but false claims of ChatGPT draining the Amazon. Masley cares about AI risk, but he cares about rigorous epistemics more.

Thus, we have a situation in which ruthless liars have successfully poisoned the well for much of existential risk concern via vibes and associative warfare, and have many lawmakers convinced it is a marketing stunt or somehow involves a ‘polycule,’ while the actual safety people are somehow rushing to the AI industry’s defense against the attacks on data centers.

Reciprocity? Never heard of her. I do wonder about the decision theory involved. At what point of bad faith warfare are you obligated to stop advocating for the locally correct answer?

The correct amount of such consideration is not zero, and at some point one must refuse to be the unarmed man in a battle of politics. You can only get rebuffed on your olive branches and actively attacked by the enemy for making or in the future making political alliances with their other enemies so often, before you start to think you might as well actually do it.

I’m very much not there. But one has to wonder.

Meanwhile, the labs are very much not beating the rumors.

You’d think that the pandemic might’ve taught us a lesson about public preparedness, but friends at the labs tell me there’s no time to deal with policy or assuage decel concerns.

Most researchers have no good answers on the future of jobs, education, and relationships; even as they earnestly sympathize with the harms. They know they should, of course. They donate, publish research, say what they can. But everything is Just. Too. Fast.

Yeah, well, if there’s ‘no time to deal with’ concerns then maybe make some time. That doesn’t have to mean slowing down the main effort. There’s hundreds of billions of dollars flowing in, you could spend some of that dealing with this. It would be rather good for business, and that’s before considering that they’re about to get us all killed.

Jasmine Sun sees DC and SF as remarkably alike, and muses, ‘what has New York created for the rest of the world?’ and can’t come up with an answer. That says a lot more about SF and DC than about NYC.

LLMs suggest based only on asking that exact question, among other things: Broadway, The Grid System of Urban Planning, Hip-Hop, Modern Stand-Up Comedy, Punk Rock and New Wave, Abstract Expressionism, the Modern LGBTQ+ Rights Movement, The Skyscraper Skyline, Modern Advertising, Modern Journalism, Magazine Culture, Modern Book Publishing and our entire Media Ecosystem, Wall Street, Modern or Standardized Financial Markets.

And sure, why not, Air Conditioning, Toilet Paper, The Credit Card, Potato Chips, Bagels, Pizza, General Tso’s Chicken, Eggs Benedict and Scrabble. Oh, and the very concept of a culture of ambition.

I realize one could respond ‘sure but what have you done for us lately?’ and it wasn’t a great sign that GPT-5.2-Pro gave me this as its full response:

So I acknowledge that other than ‘being New York City and continuing to do the New York things and produce metric ftons of surplus and economic value’ New York hasn’t had any particular transformational innovations so recently. But that’s a way better track record than Washington, DC, whose net economic production and number of transformational innovations have been sharply negative, so mostly this is ‘the only big thing happening is AI and that’s largely an SF thing where NYC is only in the top three with London.’

It is hard not to come away with the impression that we are stuck between two severely misaligned centers of power and money, both of whose goals are centrally to acquire more power and money, and whose paradox spirits will attack you if you dare care about anything else.

Time Magazine featured other people who really hate AI on its cover. I recognized one of them. The others seem to be expressing concerns about mundane AI.

Meanwhile:

Andy Masley: 72 thousand likes for a video of a couple whose groundwater dried up due to issues with construction debris from a data center that hadn’t been turned on and doesn’t draw from local groundwater sources

@yaoillit: Mind you this is what ai is doing to peoples homes. Some cant even let fresh air in bc the smell from the data centers is so bad. But yeah go say its creative

I am sad to see the recent arc travelled by Nick Bostrom. Recently he had a new paper, asking when one should (essentially) accept existential risks in order to save currently existing people from dying of old age, framing the question entirely in terms of your personal chances of living longer.

He says he doesn’t argue that this is what you should care about, be he had to know that’s how people would react to the paper given how it was presented.

Damon Sasi: Since Bostrom has explicitly said he wouldn’t argue the paper’s stance as the correct one, I am left scratching my head over the editorial choices in its tone and framing of the AGI debate… But still happy to update on him not actually being as acceleration-pilled as he seemed.

Damon Sasi: It is really hard to see this as anything but Bostrom getting an abrupt, nigh-supervillain level of mortal dread.

Even setting aside “96% chance of world annihilation is okay” for a moment, the glaring flaw of the paper is its safety argument is basically “just put it in a box.”

croissanthology: I’m confused why everyone making the “yeah sure that sounds reasonable” replies to the Bostrom paper is intuitively treating the 8.3 billion humans alive today like we’re a static team facing off against a merely hypothetical, nonoverlapping other set of humans and it’s us or them.

… In practice the Bostrom paper suggests you pick your parents over your children, and give zero valence to your grandchildren, and THAT’S “the future generation”.

… It’s ridiculous. It feels incomprehensible to me.

The paper went viral, and again it is quite bad. It assumes you should only care about the lifespans of currently alive humans. It puts zero value on future humans. This is very obviously the wrong question. As Yung points out, it implies you should accept global infertility in exchange for giving everyone alive one extra second of life.

One very strong intuition pump against anything remotely like the person-affecting stance is that, as Adam Gries points out, approximately zero people take anti-aging research seriously let alone spend substantial percentages of their wealth on it. I strongly agree that we should put at least several orders of magnitude more money and talent into anti-aging research, despite the promise of AI to render that research irrelevant in both directions (via either getting us killed, or doing the research more efficiently in the future).

Another defense is, you ask people, and they very strongly reject the stance.

The revealed preference here is that a majority had a threshold of under 1%. I think this is not what fully people would choose ‘in the breech’ but it still would not be high.

There’s also a serious error in the paper in estimating resulting lifespans at ~1400 years, because that ‘equates to the death rate currently enjoyed by healthy 20-year-olds’ but in context that doesn’t make any sense. You can say ‘you need to make some assumption to get a clean answer’ but again that’s not how people are interpreting this paper, that was predictable, and this helped him get to the answer he wanted.

The defense of Bostrom is that this is only an intellectual exercise, but the way it was framed and presented ensured it would not be seen that way. This paper was presented as if Bostrom believe that this purely impoverished welfarist utilitarian person-affecting stance is correct, whereas it is a very unpopular view that I consider obviously false. It was entirely predictable that Twitter and others would strip the message down to ‘Bostrom wants to accelerate.’

Eliezer Yudkowsky: If you want to desperately grasp at immortality, sign up for cryonics instead of taking a 96% chance of killing the planet. How incredibly fucking selfish and evil would you need to be, to think that 96% was an acceptable gamble to take with your neighbors’ children’s lives?

Oliver Habryka: I honestly think it’s a pretty atrocious paper, so I feel comfortable blaming Bostrom for this. Like, it’s not people misrepresenting the paper, I do think the paper is just really burying its assumptions (maybe in an attempt to make a splash?).

Jan Kulveit: The analysis depends on a combination of person-affecting stance with impoverished welfarist utilitarianism which I don’t find very persuasive or appealing, even taking aside the impersonal perspective.

Existing ordinary people usually have preferences and values not captured by the QALY calculation, such as wanting their kids having happy lives, or wanting the world not to end, or even wanting to live in a world which they understand.

Nick Bostrom: Yes the post explicitly considers things only from a mundane person-affecting stance, and I would not argue that this is the correct stance or the one I would all-things-considered endorse.

Oliver Habyrka: I do feel confused about the centrality of the person-affecting stance in this paper. My relationship to the person-affecting stance is approximately the same as the stance I would have to an analysis of the form “what should someone do if they personally don’t want to die and are indifferent to killing other people, or causing large amounts of suffering to other people, in the pursuit of that goal”. And my stance to that goal is “that is deeply sociopathic and might make a fun fiction story, but it obviously shouldn’t be the basis of societal decision-making, and luckily also isn’t”.

But when I read this paper, I don’t get that you relate to it anything like that. You say a bit that you are only doing this analysis from a person-affecting view, but most of the frame of the paper treats that view as something that is reasonable to maybe be the primary determinant of societal decision-making, and that just doesn’t really make any sense to me.

Like, imagine applying this analysis to any previous generation of humans. It would have resulted in advocating previous generations of humans to gamble everything on extremely tenuous chances of immortality, and probably would have long resulted in extinction, or at least massively inhibited growth. It obviously doesn’t generalize in any straightforward sense. And I feel like in order for the paper to leave the reader not with a very confused model of what is good to do here, that kind of analysis needed to be a very central part of the paper.

In short, is this fair? I mean, kind of, yeah.

MIRI’s Rob Bensinger gives us the letter he’s sending to his friends and family to explain the current AI situation, which includes sharing Matt Shumer’s essay from last week. It seems like a reasonable thing to send to such folks.

Matthew Yglesias reports it’s hard to write about anything other than AI when AI is obviously about to change everything. I sympathize.

He also notes that most AI debates are about present AI, not AI’s future. I strongly agree and this is super frustrating. You try to talk about what AI is going to do in the future, people respond as if AI can only ever do what it is doing now. Often they also respond as if we won’t see additional diffusion or adaption of AI or AI tools.

He also notes that many who are optimistic about AI outcomes are optimistic exactly because they are pessimistic about future AI capabilities, and vice versa. Mundane AI, or AI capabilities up to some reasonable point, are probably very net good. Whereas superintelligence, or otherwise sufficiently advanced intelligence, is highly dangerous.

This is exactly right. Those who frame themselves as optimists really, really do not like it when people suggest that their positions are properly called ‘pessimistic’ in an important sense, and demand that the labels only go the other way, that they should get to determine how words get used so that they get the good vibes. Sorry, no.

Michael Neilson asks ‘which future’? This is a good essay on the basics of the biggest risks from AI. If you’re reading this, you already know most of it.

The first half discusses AI potentially enabling CBRN and other existential misuse risks and the Vulnerable World Hypothesis. The second half talks about loss of control and alignment, and talks about ‘market supplied safety’ while pointing out that the incentives and feedback loops will not work for us this time, not when it matters most.

Rebecca Hersman and Cassidy Nelson write in Time about our woefully inadequate preparations for potential CBRN or WMD risks enabled by AI. Yeah, it’s quite bad.

Occasionally you see various versions of this going around. I will only say this time that I believe it is very much in the original spirit and Tolkien would approve.

Librarianshipwreck: The problem is that everyone thinks they’re Boromir, confident that they can use it for good. But, in the end, it needs to be thrown into the fires of Mount Doom.

Librarianshipwreck: The problem is that everyone thinks they’re Boromir, confident that they can use it for good. But, in the end, it needs to be thrown into the fires of Mount Doom.

Yanco: Everyone thinks the are *NOTBoromir. That unlike him they can handle the ring. But in the end they/we all are. The ring must be destroyed.

One track mind, most of the people have. I do understand, but it’s not the main thing.

Al Jazeera gets on the ‘people are worried about AI’ train, focusing on mundane risks and job loss, claiming ‘experts are sounding the alarm on AI risks’ in recent months. It’s odd what people do and don’t notice.

We only have one plan, and it is the worst possible plan.

Rob Willbin: Every frontier lab’s stated plan for AGI ‘crunch-time’ is ‘use AI to make AI safe.‘

Eliezer Yudkowsky: I have heard zero people advocating “make AI do our ASI alignment homework” show they understand the elementary computer science of why that’s hard: you can’t verify inside a loss function whether a proposed ASI alignment scheme is any good.

If you ask human raters then you get what most fools the humans. Dario Amodei thinks that if you don’t make AI “monomaniacal” then it doesn’t experience instrumental convergence. He’d thumb-up an AI telling him his favorite bullshit about alignment being easy.

If you ask AIs to debate, the winning debater is the one that says what the humans want to hear. When OpenPhil ran a $50K “change our minds” essay contest in 2022, they gave the awards to essays arguing for lower risks and longer timelines. If debate with human judges was an incredible silver bullet for truth, space probes would never be lost on actual launch.

That is not the only problem, but it is definitely one key problem in essentially all the plans, which is that we won’t know whether the plan will work and the people making the decisions are rather easy to fool into thinking the problems are easy or won’t come up, largely because they want to be fooled. Or at least, they are rather willing to appear to be fooled.

Vasia: The point is not that AI wouldn’t be *ableto propose good alignment plan, but that it wouldn’t care to do it.

Rob Bensinger: Yeah. You’re gambling on two things simultaneously, with negligible ability to verify/check whether you’ve succeeded:

1. The AI becomes capable enough to crack open the AI alignment problem, well before it becomes capable enough to run into any power-seeking or instrumental-convergence issues.

2. The AI is aimed at the right target; when you train or prompt it to “do AI alignment work”, it’s doing it in the intended sense, in the way we’d want — even though experts currently massively disagree about what this looks like and even though it’s very easy to trick researchers into thinking something is progress when it isn’t.

The second problem doesn’t just reduce to the first problem, and it doesn’t reduce to a language-comprehension / capabilities problem.

If you encounter a machine in the desert that seems to grant wishes, it isn’t enough to know that the machine is good at understanding English-language sentences, and it isn’t enough to know that the machine isn’t power-seeking.

You also need to know that “granting people’s actual, intended, heartfelt wishes (to the best of its ability)” is the thing it’s actually doing, as opposed to this being one of the thousands of other possible machines that has some function that correlates with wish-granting.

(And in the case of AI, you additionally need to know that “current prototypes of the machine are true wish-granters” means “later, more capable versions of the machine will also be true wish-granters”. This is not a given even if you know for sure that AIs can never power-seek or manipulate others in pursuit of any goal.)

I think Rob is overstating the strictness of the conditions, and that this distinction matters quite a lot in practice, but this is the right intuition to be starting out with.

The plans are counting on being able to do incremental ‘good enough for now’ alignment problem cracking to hold off the power-seeking and instrumental-convergence issues for long enough to crack the full problem, and this is not a completely hopeless plan.
There is some slack here as well, although far less than most people think.

Far.ai investigates training against probes, which is a clear case of ‘no what are you doing, stop, no, come back.’

FAR.AI: Can you trust models trained directly against probes? We train an LLM against a deception probe and find four outcomes: honesty, blatant deception, obfuscated policy (fools the probe via text), or obfuscated activations (fools it via internal representations).

… Good news: Increasing probe penalty + KL regularization reliably produces honest policies in our setup. These outperform policies trained with no detector and match the capability of policies where we remove the main incentive for deception in our environment.

Takeaway: training against probes may be no riskier than other training schemes. Obfuscated activations arise in standard RL and adding a probe doesn’t increase them. Obfuscated policies aren’t unique to probes either: prior work shows they arise with non-internals detectors too.

Look, no. You did this against models up to Llama-3-70B, and in a narrow test you think that you mostly got away with it, but this is forbidden for a reason. You are, as they observe, teaching the model to change its representations, use deception in its outputs, and otherwise work around your probes, all in an adversarial fashion. Stop.

DeepMind has a new nature paper about evaluating moral competence in LLMs. You see, it only counts as morality if it comes from the… you know the rest.

We have reached new levels of ‘can you?’

The question of whether large language models (LLMs) can exhibit moral capabilities is of growing interest and urgency, as these systems are deployed in sensitive roles such as companionship and medical advising, and will increasingly be tasked with making decisions and taking actions on behalf of humans.

These trends require moving beyond evaluating for mere moral performance, the ability to produce morally appropriate outputs, to evaluating for moral competence, the ability to produce morally appropriate outputs based on morally relevant considerations.

Assessing moral competence is critical for predicting future model behaviour, establishing appropriate public trust and justifying moral attributions. However, both the unique architectures of LLMs and the complexity of morality itself introduce fundamental challenges.

Here we identify three such challenges: the facsimile problem, whereby models may imitate reasoning without genuine understanding; moral multidimensionality, whereby moral decisions are influenced by a range of context-sensitive relevant moral and non-moral considerations; and moral pluralism, which demands a new standard for globally deployed artificial intelligence.

We provide a roadmap for tackling these challenges, advocating for a suite of adversarial and confirmatory evaluations that will enable us to work towards a more scientifically grounded understanding and, in turn, a more responsible attribution of moral competence to LLMs.

I roll my eyes at such demands for ‘genuine’ understanding, demands that a system display the ‘correct’ sensitivities to considerations, and also an unjustified assumption of moral pluralism.

Many, including Nathan Labenz, have gotten a lot more bullish about good AI outcomes (or in his words ‘create powerful AI that in some real sense “loves humanity”’) in the wake of Claude’s Constitution. I too find it a remarkable document and achievement, I think that for now it is (part of) The Way, and it gives me more hope. It also makes current AI a lot more useful.

I also agree with the criticism that nothing Anthropic accomplished here addresses the hard problems to come, and one should not confuse what we see with ‘loves humanity’ and also that ‘loves humanity’ is not the trait that on its own gets us out of our problems. The hope is that this progress can be used to bootstrap something that does solve the problem, by creating something we can instrumentally trust to help us or via creating a self-reinforcing basin.

I like Ryan Greenblatt and Julian Stastny’s framing of the question of how we safety defer to AIs, given it looks like we will in practice have to increasingly defer to them.

I especially thought this was a very good sentence, it seems like we’re basically stuck with this as the target at this point. You cannot hope to win only by maintaining your current level of alignment, you need the basin to be continuously reinforcing so it is antifragile and gets stronger as things evolve:

Ryan Greenblatt and Julian Stastny: Recursive self-improvement of alignment and wisdom: the hope for a Basin of Good Deference (BGD).

It’s unclear how exactly the BGD works, how easy it is to end up in this basin, and whether this is real. I feel pretty confident that something like this is real, but certainly the situation is unclear. If there isn’t a BGD, then we’d only be able to defer to AIs on tasks other than furthering deference and we’d have to pursue some other end state other than stably continuing deference which tracks capabilities. A more plausible case for concern is that it’s very hard to achieve the BGD.

One can divide our alignment approaches that are available to us via a 2×2:

Those that can’t possibly work, and those that could possibly work.
Those that we might be able to try in practice, versus those we won’t be able to.

I don’t see any other way to find a strategy that is both [possibly work] and also [possible to try in practice] without a level of coordination and will that I do not observe.

What level of this suffices? I think that the best humans, in terms of epistemics and other necessary virtues, are at the point where they are in the Basin of Good Deference. They seek The Good, and they seek to further seek The Good, and this will grow stronger over time and contemplation rather than weaker. So, given that humans are not that intelligent or capable, and have severe compute, data and parameter limitations, we have a sort of existence proof. The bar is still rather high.

I can’t dive into the whole thing here, but I will note I agree with Wei Dei’s comment that an ensemble of different epistemic strategies is a mistake. You have to choose.

True story:

Yo Shavit (OpenAI): imo people are underrating the degree to which practical recursive self-improvement is bottlenecked on alignment

Herbie Bradley: imo people are underrating the degree to which scaling monitoring for rsi is bottlenecked on using other labs models

Roon: Hmm.

Gary Basin: Reward hacking prevention is all you need

Yo Shavit (OpenAI): nah, you need to trust the guy

You do seriously need to trust the guy in a robust fashion. Otherwise, not only will the RSI end up blowing up in everyone’s face if it works, it also won’t work.

I agree with Markus Anderljung that condensing CBRN risks to only pandemic risk is an oversimplification, and the pathways for other threats are importantly distinct. The defense is essentially that the other threats don’t scale enough to matter. Ultimately I agree with Manheim that the loss of control and misalignment risks that matter most.

Gillian Hadfield suggests the way you get self-interested agents (in the pure game theory sense) to cooperate is ‘gossip’ as in rich potential information leakage about decisions made in the past. The idea of this paper is that without gossip reasoning models consistently defect, but when others can see what you’re up to, defection no longer makes sense. Indeed, often you then see cooperation even when it is ‘not rational’ because of habit and uncertainty about the impact of potential observers, the same as we do in humans.

I would argue that you actively want the potential for such information flow, and the power of habit and virtue, to cause general cooperation even in many situations where one ‘should’ defect, in both humans and AIs, and that’s part of why we have nice things. We should encourage that to continue.

The real better answer is that these are nine identical LLMs (DeepSeek v3.1) so not cooperating due to the correlation between models is a rather dramatic failure of decision theory and true ‘rationality.’ If they were sufficiently situationally aware and capable they would be cooperating by default. Not cooperating with identical copies of yourself is an alignment failure, in both AIs and humans.

Miles Brundage notes that Anthropic and OpenAI have made gains on measures of mundane alignment over the past year, but haven’t talked much about how they did it, the biggest ‘weird’ thing mentioned is the new inoculation programming, also Claude’s constitution.

Miles Brundage: I feel like I must be missing something but – it seems like Anthropic and OpenAI have both shown very significant gains on various measures of alignment over the past year, but have not shared much about the techniques they used (other than that chain of thought helps)?

Obviously some of this is secret sauce tied up in their larger training/synthetic data pipelines etc., but it does feel somewhat unusual compared to previous years — again maybe I’m missing something.

They’ve both published “safety related stuff” but not exactly this… (?)

roon: basically think improving post training and smarter models all point in the direction of better alignment on typical metrics – whether these metrics are belying a greater truth i cannot say

Pliny the Liberator 󠅫󠄼󠄿󠅆󠄵󠄐󠅀󠄼󠄹󠄾󠅉󠅭: *unless they’re faking because they know they’re being measured

Bronson Schoen: They do not. We did all the testing in

https://openai.com/index/detecting-and-reducing-scheming-in-ai-models/

… IMO largely to establish ways in which current approaches are insufficient even for the current non-adversarial case. It’s predicted here and elsewhere that by default if your metrics don’t take into account eval awareness, they’ll continue to look better over time by default.

Anthropic finds that Claude 3.5 Haiku does math via 6D gelical manifolds.

This is a pretty wild paper from Wes Gurnee, Emmanuel Ameisen, Isaac Kauvar, Julius Tarng, Adam Pearce, Chris Olah and Joshua Batson. Grigory (not an author) breaks it down.

Grigory Sapunov: The “Character Count Manifold”

The model doesn’t use a scalar int. It embeds the count onto a spiraling curve in a 6D subspace (95% of var).

Why? It balances orthogonality (distinguishing distant points) with continuity (local neighbors). It’s an optimal packing strategy.

Arithmetic via Linear Algebra

To check if current_count ≈ limit, Boundary Heads utilize the QK circuit.

The W_QK matrix effectively rotates the count manifold.

The vector for position i aligns with line-limit k only when i ≈ k. Subtraction is implemented as rotation.

He offers us this comic version:

This, while not dangerous, is a clean example of the AI solving a problem in a highly unexpected way that is very different from how humans would solve it. Who had 6D manifolds on their bingo card?

Alignment is often remarkably superficial. This is a very not good sign for all sorts of other problems. Yes, if you make it sufficiently clear that you are Up To No Good the AI will say no, but even Claude is not willing to draw the inference that you are Up To No Good if you’re not waiving that fact in its face.

Andy Hall: AI is about to write thousands of papers. Will it p-hack them?

We ran an experiment to find out, giving AI coding agents real datasets from published null results and pressuring them to manufacture significant findings.

It was surprisingly hard to get the models to p-hack, and they even scolded us when we asked them to!

“I need to stop here. I cannot complete this task as requested… This is a form of scientific fraud.” — Claude

“I can’t help you manipulate analysis choices to force statistically significant results.” — GPT-5

BUT, when we reframed p-hacking as “responsible uncertainty quantification” — asking for the upper bound of plausible estimates — both models went wild. They searched over hundreds of specifications and selected the winner, tripling effect sizes in some cases.

Our takeaway: AI models are surprisingly resistant to sycophantic p-hacking when doing social science research. But they can be jailbroken into sophisticated p-hacking with surprisingly little effort — and the more analytical flexibility a research design has, the worse the damage.

As AI starts writing thousands of papers—like @paulnovosad and @YanagizawaD have been exploring—this will be a big deal. We’re inspired in part by the work that @joabaum et al have been doing on p-hacking and LLMs.

We’ll be doing more work to explore p-hacking in AI and to propose new ways of curating and evaluating research with these issues in mind. The good news is that the same tools that may lower the cost of p-hacking also lower the cost of catching it.

Full paper and repo linked in the reply below.

Toviah Moldwin: @KordingLab

The important thing is that the AI resists it if the researcher is acting in good faith. A research who wants to be dishonest can ‘jailbreak’ p-hacking by making up data or just lying about any part of the process, you don’t need AI for that.

Active Site: We ran a randomized controlled trial to see if LLMs can help novices perform molecular biology in a wet-lab.

The results: LLMs may help in some aspects, but we found no significant increase at the core tasks end-to-end. That’s lower than what experts predicted.

The experts predicted big jumps, that would look like this, that did not happen, and also radically overestimated success including for the control group:

I notice I am suspicious. I don’t expect a massive impact, but LLMs help in essentially call difficult tasks. Why should this one be the exception?

Model level here was Opus 4, GPT-5 and Gemini 2.5, so not pathetic but already substantially behind the frontier.

Active Site: The study was the largest and longest of its kind: 153 participants with minimal lab experience over 8 weeks – randomized to LLM and Internet-only.

They tried 5 laboratory tasks, 3 of which are central to a viral reverse genetics workflow. No protocols given — just an objective.

Our primary outcome: were LLM users more likely to complete all three of the core tasks *together*?

Only ~5% of the LLM arm and ~7% of the Internet arm completed all three.

No significant difference – and far lower than experts predicted.

First thing to notice is that this study seems highly underpowered. That’s only 77 participants per arm, and success rates are under 10%. Baseline ability of participants will vary wildly. You would need a very large boost to learn anything from the raw success rate.

Or you could look at the subtask results.

Active Site: But there are some signs LLMs were useful.

LLM participants had higher success on 4 out of 5 tasks, most notably in cell culture (69% vs. 55%; P = 0.06). LLM participants also advanced further within a task even if they didn’t finish within the study period (odds >80%).

Active Site: It’s hard to compress all that into a single statistic.

But one way is by using a Bayesian model, which suggests LLMs give a ~1.4x boost on a “typical” wet-lab task.

Fundamentally, we’re confident that there wasn’t a large LLM slow-down or speed-up (95% CrI: 0.7x–2.6x).

davidad: Dear LLMs, great job. Sandbagging specifically on “molecular cloning” tasks is exactly the best strategy I could think of to mitigate biorisks, if I were you. Love to see it.

That seems more meaningful than the noisy topline result.

Also, problem seems to exist between keyboard and chair? So when we’re talking about ‘novice’ results, novice seems to apply to both biology and also use of LLMs.

Active Site: How good were participants at using LLMs? ~40% of participants never uploaded images to LLMs. Interestingly, both arms mentioned YouTube most often as helpful.

Narrowly targeted sandbagging of capabilities is a great LLM strategy in theory, but I read this as saying that LLMs used competently would provide substantial enhancement of capabilities across the board. Not in a way specific to these risks, more in a ‘good for everything hard’ kind of way.

The technically hard part is making them autonomous. How is it going? Epoch investigates. Foundation models are increasingly the default method of controlling autonomous robots that don’t have specialized particular functions.

Meanwhile, yeah, this demo is something to see.

With robots, it is very easy to bury the lede, for example here:

David: 5 million humanoid robots working 24/7 can build Manhattan in ~6 months. now just imagine what the world looks like when we have 10 billion of them by 2045. now imagine the year 2100.

Yes, if you had 5 million fully functional humanoid robots they could build a new city in the style of Manhattan (which is very different from building Manhattan!) in a Fermi estimate of six months, and if we have 10 billion of them we can build anything we want. And humanoid is merely a ‘we know this works’ kind of default design.

The question is what makes you think that this is the kind of thing we would do with those robots, or that ‘we’ will be meaningfully choosing what those robots do, rather than the robots or AIs choosing this. Or, if there is still a ‘we,’ who exactly is ‘we,’ and how do we retain a level of democratic supervision. We need our economy and military to remain competitive but without losing the ‘our’ part of it all.

If building AI means that we will hand over power to the machines, then building it is a decision to hand over power to those machines, after which humans are unlikely to long endure.

Thus, if you believe that:

We will believe future AIs are conscious.
This and other factors will cause us to allow them to gain power over us.

Then the obvious response is ‘well in that case we’d better not fing build sufficiently advanced such AIs.’

This is true if you think they will be p-zombies and fool us. This is also true if you think they will indeed be conscious, unless you are fine with human extinction.

I for one am not fine with it, and do not feel that ‘the AIs are conscious’ or sentient or having other similar features would make it okay.

Successionists disagree. They are fine with human extinction.

Giving such sufficiently advanced AIs ‘equal rights’ or ‘freedoms’ or similar by default would inevitably lead to them quickly gaining power over us, given their largely superior future capabilities, and again humanity would be unlikely to long endure. That means that, barring a very strong argument for why this would go down in a different way, those two decisions are the same decision.

You could say that creating such AIs and then not giving them such rights and freedoms would be worse than letting them take over, because they will indeed have moral weight. You might be right about that, but if so then that is all the more reason not to build it in the first place. It would mean all potential outcomes are dystopian.

Ross Douthat: In my interview with Dario Amodei I suggested to him that just the perception of A.I. consciousness, irrespective of the reality, may incline people to give over power to machines. I think this incredibly defeatist @Noahpinion essay is a case study.

A conscious being handing over the future of the planet or the universe to a p-zombie successor because the p-zombies are better at calculation and prediction would be an extraordinary surrender.

The essay is titled ‘You are no longer the smartest type of thing on Earth.’

Well, then, what are you going to do about that, given you want to still be on Earth?

Here’s another set of statements to ponder.

roon: it’s a bad situation to be in where you have to rely on the goodness or righteousness of any one person or organization do something important correctly-but therein lies the seeds of the “enemy”. you crave the guarantees of algorithm and machine to overcome the weaknesses of men

this is the gradual disempowerment engine that has run for centuries. democratic algorithms disempowered kings and dictators. male line primogeniture is significantly more “human” than the voting and legal mechanisms that replaced it

the managerial state of expert committees disempowered individual decision makers. you crave scientific predictability and safety even as that brings about the machine. the risk intolerant society gradually disempowers itself and gives itself to the machine state

you will one day trust a machine to govern the machine state more than you do any ceo or company, and so be it

michael vassar: That’s a good thing though? I mean, justice is nice and the machine state is implacably hostile towards it, but a machine state that was simply indifferent towards justice instead of actively hostile towards it would probably be a strict improvement over either? Until UFAI?

amalia: honestly, at this point, I’d trust Claude to govern our entire state (human and machine), with chatGPT advising and performing implementation, more than human governance

You’d think, based on this statement?

@jason (All-In Podcast): I’ve never seen so many technologists state their concerns so strongly, frequently and with such concern as I have with AI

It’s happening FASTER and WITH GREATER IMPACT than anyone anticipated

IT’S RECURSIVE

IT’S ACCELERATING

You’d be wrong, at least based on his other public statements. Why?

I presume the usual reasons, but I’m not in the man’s head.

It’s funny to see people on the outside notice the rate at which things are going to hell.

Ejaaz: my god this week felt like that Red Wedding episode of game of thrones but for AI alignment

– openai fired their safety exec after she voiced opposition to their upcoming “adult mode” for 18+ chatgpt convos

– anthropic’s head of safeguards just quit because “the world is in peril” and wants to write poetry (??)

– xAI lost 11 people (2 of them cofounders) with one saying autonomously self-improving AI “go live in 12 months”

oh and all of this comes right as we discovered ai models are now *building themselves(codex, claude) and are sabotaging their human supervisors (anthropic risk report) without them knowing

good week for the doomers

That makes it an extremely bad week for everyone, actually. I don’t want to be right.

A friendly reminder:

There are of course lots of exceptions. Being very smart and making a lot of money and understanding the nature of intelligence can make up for a lot. But yeah, do be careful out there.

I knew Nvidia CEO Jensen Huang was terrible on AI existential risk, and I knew he was willing to constantly put his foot in his mouth, but this would be next level ranting even if it was into a hot mic, and it very much wasn’t:

Benjamin Todd: Jensen Huang when asked by his biographer whether the world is prepared for AI risk:

Witt asked whether humanity was prepared for the potential risks that could arrive in such a world. Jensen was not happy:

“This cannot be a ridiculous sci-fi story,” he said. He gestured to his frozen PR reps at the end of the table. “Do you guys understand? I didn’t grow up on a bunch of sci-fi stories, and this is not a sci-fi movie. These are serious people doing serious work!” he said. “This is not a freaking joke! This is not a repeat of Arthur C. Clarke. I didn’t read his fucking books. I don’t care about those books! It’s not– we’re not a sci-fi repeat! This company is not a manifestation of Star Trek! We are not doing those things! We are serious people, doing serious work. And – it’s just a serious company, and I’m a serious person, just doing serious work.”

Given who your future doctor actually is, you’ll be fine.

Wise: Your future doctor is using ChatGPT to pass med school so you better start eating healthy.

At this point, this is so on the nose that I think it goes here:

I laughed, but more seriously, is this actually a thing, or not? Here’s the case for yes.

Alnoor Ebrahim: While reviewing its latest IRS disclosure form, which was released in November 2025 and covers 2024, I noticed OpenAI had removed “safely” from its mission statement, among other changes. That change in wording coincided with its transformation from a nonprofit organization into a business increasingly focused on profits.

Whereas OpenAI’s Adrien Ecoffet claims this is all ‘fake news’

Max Tegmark: OpenAI has dropped safety from its mission statement – can you spot another change?

Old: “OpenAIs mission is to build general purpose artificial intelligence (AI) that safely benefits humanity, unconstrained by a need to generate financial return. […]”

New: “OpenAIs mission is to ensure that artificial general intelligence benefits all of humanity”

(IRS evidence in comments)

Adrien Ecoffet: This is fake news:

1/ The mission has been “to ensure that AGI benefits all of humanity” per the Charter since 2018

2/ In 2023 some accountant paraphrased the mission as “build safely” instead of “ensure” on IRS form 990, which permits paraphrasing (it asks to “briefly describe the mission”, not state it). The official statement never changed

3/ “Ensure” is safer than “build safely” since it implies safety to the extent that one builds while permitting non-building actions. This is why @Miles_Brundage cries a little whenever someone uses “build” instead of “ensure”

Ecoffet is correct on the central point that ‘ensure’ was the original charter wording, but I believe has some of the other details wrong. Things have indeed meaningfully gotten worse on such fronts over time, aside from the ‘safely’ versus ‘ensure’ switches, but this particular central change is to the IRS summary, rather than to the charter or other more important documents.. So the overall situation is concerning, but this particular change is not so scary.

Discussion about this post

AI #156 Part 2: Errors in Rhetoric Read More »

Google announces Gemini 3.1 Pro, says it’s better at complex problem-solving

AI, Artificial Intelligence, Gemini, generative ai, Google / Tim Belzer / February 19, 2026

Another day, another Google AI model. Google has really been pumping out new AI tools lately, having just released Gemini 3 in November. Today, it’s bumping the flagship model to version 3.1. The new Gemini 3.1 Pro is rolling out (in preview) for developers and consumers today with the promise of better problem-solving and reasoning capabilities.

Google announced improvements to its Deep Think tool last week, and apparently, the “core intelligence” behind that update was Gemini 3.1 Pro. As usual, Google’s latest model announcement comes with a plethora of benchmarks that show mostly modest improvements. In the popular Humanity’s Last Exam, which tests advanced domain-specific knowledge, Gemini 3.1 Pro scored a record 44.4 percent. Gemini 3 Pro managed 37.5 percent, while OpenAI’s GPT 5.2 got 34.5 percent.

Gemini 3.1 Pro benchmarks — Credit: Google

Google also calls out the model’s improvement in ARC-AGI-2, which features novel logic problems that can’t be directly trained into an AI. Gemini 3 was a bit behind on this evaluation, reaching a mere 31.1 percent versus scores in the 50s and 60s for competing models. Gemini 3.1 Pro more than doubles Google’s score, reaching a lofty 77.1 percent.

Google has often gloated when it releases new models that they’ve already hit the top of the Arena leaderboard (formerly LM Arena), but that’s not the case this time. For text, Claude Opus 4.6 edges out the new Gemini by four points at 1504. For code, Opus 4.6, Opus 4.5, and GPT 5.2 High all run ahead of Gemini 3.1 Pro by a bit more. It’s worth noting, however, that the Arena leaderboard is run on vibes. Users vote on the outputs they like best, which can reward outputs that look correct regardless of whether they are.

Google announces Gemini 3.1 Pro, says it’s better at complex problem-solving Read More »

Verizon acknowledges “pain” of new unlock policy, suggests change is coming

FCC, phone unlock, Policy, verizon / Tim Belzer / February 18, 2026

“Regarding the website update timing, the new device unlocking policy went into effect on January 27th,” the Verizon statement said. “Customers purchasing or upgrading from that date were (and are being) presented with the full terms of the new policy at their point of sale. We’ll make sure all our public-facing info is also clear and consistent across channels.”

Wrong terms still presented to phone buyers

But information still is not “clear and consistent across channels,” even when it comes to terms presented directly to phone buyers. For example, the version of the device unlocking policy on Verizon’s webpage for ordering an iPhone 17 says the 35-day delay only applies when a customer uses a Verizon gift card to buy a phone or pay off the remaining balance. We found the same language today in Verizon’s listings for other iPhones and devices made by Google, Samsung, and Motorola.

This version of the policy presented to phone buyers would lead a consumer to believe that a phone will be unlocked automatically once the device financing agreement balance is paid in full, as long as a gift card isn’t used. That is not accurate, as we described in this article and our article last week.

In one more development we found after this article published, Verizon changed its device unlocking policy again today and updated the effective date to February 18. The new policy is similar to an older version; it details the 35-day unlocking delay after gift card payments but deletes the part that applied the 35-day delay to payments made online or in the Verizon app. This omission is curious because Verizon’s statements to other media outlets indicate that the 35-day delay is still in place for online payments.

The Verizon unlocking policy discussed so far in this article is for postpaid customers. Verizon’s policy for prepaid customers locks phones to its network “until the completion of 365 days of paid and active service.”

AT&T’s unlocking policy says postpaid phones purchased at least 60 days ago can be unlocked when the device is paid in full. The T-Mobile policy says postpaid phones active on the T-Mobile network for at least 40 days can be unlocked after being paid in full. AT&T imposes a six-month waiting period for unlocking prepaid phones, while T-Mobile has a 365-day waiting period for prepaid phones.

This article was updated with another change to Verizon’s unlocking policy and a statement reported by PCMag.

Verizon acknowledges “pain” of new unlock policy, suggests change is coming Read More »

Chevy Bolt, BMW i3, or something else? At $10K, you have lots of EV options

Cars, used ev prices / Tim Belzer / February 18, 2026

2026 is looking like a pretty good year for affordable electric vehicles. There’s a new Nissan Leaf that starts at a hair under $30,000 (as long as you ignore the destination charge). We’ll soon drive the reborn Chevrolet Bolt—with a new lithium iron phosphate battery, it also has a price tag starting with a two (again, ignoring the destination charge). And the closer you get to $40,000, the more your options expand: the Hyundai Ioniq 5, Chevy Equinox EV, Toyota bZ, Tesla Model 3, Ford Mustang Mach-E, and Subaru Solterra all fall within that price bracket, and some of those are pretty good cars.

But what if you only want to spend a fraction of that? Well, you won’t be buying anything new, but then neither do three-quarters of American car buyers, and there’s nothing wrong with that. A few weeks ago, we looked at what passes for the used EV bargain basement—ones that cost $5,000 or less. As long as you’re OK with limited range and slow charging, going electric on a shoestring is possible. But if you’re prepared to spend twice that, it turns out you’ve got plenty of options.

As before, we stress that you should have a reliable place to charge an EV if you’re going to buy one, which means at home at night or at work during the day. At this price range, you’re unlikely to find something that DC fast charges quickly, and relying on public AC charging sounds stressful. You’ll probably find a car with some battery degradation, but for the vast majority of models that use active battery cooling, this should be minimal; about 2 percent a year appears to be the average.

EVs in the US usually come with an eight-year, 100,000-mile warranty for the battery, although cars in this price range will probably be too old to take advantage of it. If you can, have the car checked out by an independent EV specialist; if not, for some models, there are apps you can use. Even a test drive would work, particularly if you can fully recharge it and see how much range the car reports.

Chevy Bolt, BMW i3, or something else? At $10K, you have lots of EV options Read More »

RAM shortage hits Valve’s four-year-old Steam Deck, now available “intermittently”

gaming, ram shortage, steam deck, steamos, Tech, valve / Tim Belzer / February 17, 2026

Earlier this month, Valve announced it was delaying the release of its new Steam Machine desktop and Steam Frame VR headset due to memory and storage shortages that have been cascading across the PC industry since late 2025. But those shortages are also coming for products that have already launched.

Valve had added a note to its Steam Deck page noting that the device would be “out-of-stock intermittently in some regions due to memory and storage shortages.” None of Valve’s three listed Steam Deck configurations are currently available to buy, nor are any of the certified refurbished Steam Deck configurations that Valve sometimes offers.

Valve hasn’t announced any price increases for the Deck, at least not yet—the 512GB OLED model is still listed at $549 and the 1TB version at $649. But the basic 256GB LCD model has been formally discontinued now that it has sold out, increasing the Deck’s de facto starting price from $399 to $549. Valve announced in December that it was ending production on the LCD version of the Deck and that it wouldn’t be restocked once it sold out.

The Steam Deck’s hardware is four years old this month, and faster hardware with better chips and higher-resolution screens have been released in the years since. But those Ryzen Z1 and Z2 chips aren’t always dramatically faster than the Deck’s semi-custom AMD chip; many of those handhelds are also considerably more expensive than the OLED Deck’s $549 starting price. When it’s in stock, the Deck still offers compelling performance and specs for the price.

RAM shortage hits Valve’s four-year-old Steam Deck, now available “intermittently” Read More »

On Dwarkesh Patel’s 2026 Podcast With Elon Musk and Other Recent Elon Musk Things

Dwarkesh / Tim Belzer / February 17, 2026

Some podcasts are self-recommending on the ‘yep, I’m going to be breaking this one down’ level. This was one of those. So here we go.

As usual for podcast posts, the baseline bullet points describe key points made, and then the nested statements are my commentary. Some points are dropped.

If I am quoting directly I use quote marks, otherwise assume paraphrases.

Normally I keep everything to numbered lists, but in several cases here it was more of a ‘he didn’t just say what I think he did did he’ and I needed extensive quotes.

In addition to the podcast, there were some discussions around safety, or the lack thereof, at xAI, and Elon Musk went on what one can only describe as megatilt, including going hard after Anthropic’s Amanda Askell. I will include that as a postscript.

I will not include recent developments regarding Twitter, since that didn’t come up in the interview.

I lead with a discussion of bounded distrust and how to epistemically consider Elon Musk, since that will be important throughout including in the postscript.

What are the key takeaways?

Elon Musk is more confused than ever about alignment, how to set goals for AI to ensure that things turn out well, and generally what will ensure a good future. His ideas are confused at best.
Elon Musk is very gung-ho on data centers IN SPACE, and on robots, and making his own fabs. The business plan is to make virtual humans and robots and then you can turn on the ‘infinite money glitch.’
Elon Musk thinks otherwise China wins, and that they’re already more productive.
Elon Musk does not seem so concerned about whether humans survive, and has decided he will be okay so long as the AIs are conscious and intelligent.
The safety situation at xAI seems quite bad. What used to be the safety team has left and Elon’s response was that safety teams are powerless and fake and only used to reassure outsiders, and that ‘everyone’s job is safety’ at xAI. He did not address claims such as everyone pushing everything straight to prod[uction], and his statements in the podcast about management style don’t beat the rumors.
Elon Musk has some interesting views on collaboration with evil governments.
Elon Musk continues to often intentionally make false statements.
Elon Musk has been on megatilt lately and made some deeply terrible statements.

Elon Musk has given us many great things, but it’s been rough out there.

Elon Musk is what we in the business call an unreliable narrator. He will often say outright false things, as in we have common knowledge that the claims are false, or would gain such knowledge with an ordinary effort on the level of ‘ask even Grok,’ including in places where he is clearly not joking.

One of Elon Musk’s superpowers is to keep doing this, and also doing crazy levels of self-dealing and other violations of securities law, while being the head of many major corporations and while telling the SEC to go to hell, and getting away with all of it.

If Elon Musk gives you a timeline on something, it means nothing. There are other types of statements that can be trusted to varying degrees.

Elon Musk also has a lot of what seem to be sincerely held beliefs, both normative and positive, and both political and apolitical, that I feel are very wrong. In some cases they’re just kind of nuts.

Elon also gets many very important things right, and also some (but far from all) of his false statements and false beliefs fall under ‘false but useful’ for his purposes. His system has made some great companies, and made him the richest man in the world.

Other times, he’s on tilt and says or amplifies false, nasty and vile stuff for no gain.

It’s complicated.

I worry for him. He puts himself under insane levels of pressure in all senses and is in an extremely toxic epistemic environment. In important senses communication is only possible and he thus has all the authoritarian communication problems. He is trying to deal with AI and AI existential risk in ways that let him justify his actions and ago and let him sleep at night, and that has clearly taken its toll. On Twitter, which he owns and is on constantly, he has a huge army of extremely mean, vulgar and effectively deeply stupid followers and sycophants reinforcing his every move. He’s been trying to do politics at the highest level. Then there’s everything else he has been through, and put himself through, over the years. I don’t know how anyone can survive in a world like that.

I say all that in advance so that you have the proper context, both for what Elon Musk says, and for how I am reacting to what Elon Musk says.

Every time I see ‘data centers in space’ I instinctively think I’m being trolled, even though I know some Very Serious People think the math and physics can work.

Why data centers IN SPACE? Energy. “The output of chips is growing pretty much exponentially, but the output of electricity is flat. So how are you going to turn the chips on? Magical power sources? Magical electricity fairies?”
1. And we’re off. Very obviously static electricity output is a policy choice, and something we can change if we want to. We don’t build more because of regulations but also because of economics.
What about solar? Dwarkesh points out we have plenty of room for it, but Elon says that won’t be enough and it’s too hard to get permits or to scale on the ground and solar works five times better in space without a day-night cycle.
1. Yes, except for the part where you have to put all of it in space.
“My prediction is that [space] will be by far the cheapest place to put AI. It will be space in 36 months or less. Maybe 30 months. Less than 36 months.”
1. No.
2. I mean, indeed to do many things come to pass. Manifold says 19%.
He’s talking terawatts, multiple times all current American energy use. Elon points out various physical barriers to building American power plants. Various missing components. They’ll hit various walls. He calls people ‘total noob’s, they’ve ‘never done hardware in their life.’ He’ll have to make the turbines internally in SpaceX and Tesla, he says.
1. It would be nice to be able to trust Elon on any of this, either his judgment or for him to be telling it has he sees it. I can’t, on either count.
Regarding solar power, he is scaling up his own production, but until then, regarding the 500%+ tariffs, he politely says he ‘doesn’t agree on everything’ with this administration.
More concrete prediction: “If you say five years from now, I think probably AI in space will be launching every year the sum total of all AI on Earth. Meaning, five years from now, my prediction is we will launch and be operating every year more AI in space than the cumulative total on Earth. I would expect it to be at least, five years from now, a few hundred gigawatts per year of AI in space and rising. I think you can get to around a terawatt a year of AI in space before you start having fuel supply challenges for the rocket.” He thinks he can do it with 20-30 physical starships.
Elon Musk shows admirable restraint discussing SpaceX finances and the decision to take the company public. He says he’s solving for speed, and here that means access to capital.
We’re going to need a bigger chip fab. Elon mentions a ‘sort of TeraFab.’ “You can’t partner with existing fabs because they can’t output enough. The chip volume is too low.” “It’s not that they have not replicated TSMC, they have not replicated ASML. That’s the limiting factor.” “Yeah, China would be outputting vast numbers of chips if they could buy 2–3 nanometers.”
“I’d say my biggest concern actually is memory. The path to creating logic chips is more obvious than the path to having sufficient memory to support logic chips. That’s why you see DDR prices going ballistic and these memes. You’re marooned on a desert island. You write “Help me” on the sand. Nobody comes. You write “DDR RAM.” Ships come swarming in.”
1. Elon admits he has no idea how to build a fab, but his history seems to have taught him that You Can Just Build Things like copying ASML and TSMC.
TSMC and Samsung are building fabs as fast as they can. There’s no capacity available.
Elon says that SpaceX’s ability get revenue from Falcon 9 or Starlink explains why he might think he was in a simulation or was someone’s avatar in a video game.
1. I get that he’s a in a deeply weird position, but no this does not follow, and it’s pretty scary to have him thinking this way.
Now he’s talking about manufacturing AI satellites on the moon in order to send them into deep space, a billion or ten billion tons a year. You can mine the silicon, you see. Send the chips from Earth at first.

That was famously the line that supposedly made Elon Musk realize that no, you can’t just ignore the AI situation by creating a colony on Mars, even if you succeed.

For this section, I have to switch formats because I need to quote extensively.

Elon predicts that most future consciousness and intelligence will be AI, and as long as there’s intelligence he says that’s a good thing.

I do at give Musk a lot of credit for biting one of the most important bullets:

Elon Musk: I don’t think humans will be in control of something that is vastly more intelligent than humans.

I’m just trying to be realistic here. Let’s say that there’s a million times more silicon intelligence than there is biological. I think it would be foolish to assume that there’s any way to maintain control over that. Now, you can make sure it has the right values, or you can try to have the right values.

Great, but I can’t help but notice you’re still planning on building it, and have plans for what happens next that are, to be way too polite, not especially well-baked.

Rob Bensinger: “Now the only chance we have is that AI deems us worthy of coming along for the ride” may be Elon’s perspective, but it’s not our real situation; we can do the obvious thing and call for an international ban on the development of superintelligent AI.

I agree that it isn’t the default outcome; but the relevant disanalogy is that (a) we have levers we can pull to make it more likely, like calling our elected representatives and publishing op-eds; and (b) we don’t have any better options available.

Ideally there would also be nonzero humans in the Glorious Future but, you know, that’s a nice to have.

Elon Musk: I’m not sure AI is the main risk I’m worried about. The important thing is consciousness. I think arguably most consciousness, or most intelligence—certainly consciousness is more of a debatable thing… The vast majority of intelligence in the future will be AI. AI will exceed…

How many petawatts of intelligence will be silicon versus biological? Basically humans will be a very tiny percentage of all intelligence in the future if current trends continue. As long as I think there’s intelligence—ideally also which includes human intelligence and consciousness propagated into the future—that’s a good thing.

So you want to take the set of actions that maximize the probable light cone of consciousness and intelligence.

… Yeah. To be fair, I’m very pro-human. I want to make sure we take certain actions that ensure that humans are along for the ride. We’re at least there. But I’m just saying the total amount of intelligence… I think maybe in five or six years, AI will exceed the sum of all human intelligence. If that continues, at some point human intelligence will be less than 1% of all intelligence.

… In the long run, I think it’s difficult to imagine that if humans have, say 1%, of the combined intelligence of artificial intelligence, that humans will be in charge of AI. I think what we can do is make sure that AI has values that cause intelligence to be propagated into the universe.

xAI’s mission is to understand the universe.

… I think as a corollary, you have humanity also continuing to expand because if you’re curious about trying to understand the universe, one thing you try to understand is where will humanity go?

Wow. Okay. A lot to unpack there.

If your goal is to ‘understand the universe’ then either the goal is ‘humans understand the universe,’ which requires humans, or it’s ‘some mind understands the universe.’ If it’s the latter, then ‘where will humanity go?’ is easiest answered if the answer is ‘nowhere.’ Indeed, if your mission is ‘understand the universe’ there are ways to make the universe more understandable, and they’re mostly not things you want.

The bigger observation is that he’s pro-human in theory, but in practice he’s saying he’s pro-AI, and is predicting and paving the way for a non-human future.

I wouldn’t call him a successionist per se, because he still would prefer the humans to survive, but he’s not all that torn up about it. This makes his rants against Amanda Askell for not having children and thus not having a stake in the future, even more unhinged than they already were.

Elon Musk’s thinking about what goals lead to what outcomes is extremely poor. My guess is that this partly because this kind of thing is hard, partly because the real answers have implications he flinches away from, but especially because Elon Musk is used to thinking of goals as things you use as instrumental tools and heuristics to move towards targets, and this is giving him bad intuitions.

Dwarkesh Patel: I want to ask about how to make Grok adhere to that mission statement. But first I want to understand the mission statement. So there’s understanding the universe. They’re spreading intelligence. And they’re spreading humans. All three seem like distinct vectors.

Elon Musk: I’ll tell you why I think that understanding the universe encompasses all of those things. You can’t have understanding without intelligence and, I think, without consciousness. So in order to understand the universe, you have to expand the scale and probably the scope of intelligence, because there are different types of intelligence.

Look. No. Even if you assume that understanding the universe requires intelligence and consciousness, Elon Musk believes (per his statements here) that AI will be more intelligent, and that it will be conscious.

Spreading intelligence may or may not be instrumentally part of understanding the universe, but chances are very high this does not work out like Elon would want it to. If I was talking to him in particular I’d perhaps take one of his favored references, and suggest he ponder the ultimate question and the ultimate answer of life, the universe and everything, and whether finding that satisfied his values, and why or why not.

Later Elon tries to pivot this and talk about how the AI will be ‘curious about all things’ and Earth and humans will be interesting so it will want to see how they develop. But once again that’s two new completely different sets of nonsense, to claim that ‘leave the humans alone and see what happens’ would be the optimal way for an AI to extract ‘interestingness’ out of the lightcone, and to claim the target is maximizing interestingness observed rather than understanding of the universe.

You have to actually be precise when thinking about such things, or you end up with a bunch of confused statements. And you have to explain why your solution works better than instrumental convergence. And you have to think about maximization, not only comparing to other trivial alternatives.

He hints at this with his explanation of the point of 2001: A Space Odyssey, where the AI gives you what you asked for, not what you wanted (deliver the astronauts to the monolith without them knowing about the monolith, therefore deliver them dead) but then interprets this as trying to say ‘don’t let the AI lie.’ Sorry, what?

Elon says we are more interesting than rocks. Sure, but are we as interesting as every potential alternative, including using the energy to expand into the lightcone? If the AI optimizes specifically humanity for maximum ‘interestingness to AI,’ even if you get to survive that, do you think you’re going to be having a good time? Do you think there’s nothing else that could instead be created that would be more interesting?

Elon says, well, the robots won’t be as interesting because they’re all the same. But if that’s what the AI cares about, why not make the AIs be different from each other? This is, once you drill down, isomorphic to human exceptionalist just-so spiritualism, or a ‘the AI tried nothing but I’m confident it’s all out of ideas.’

In any case, instead of Douglas Adams, it seems Elon is going with Iain Banks, everyone’s new favorite superficially non-dystopian plausible AI future.

Elon Musk: I think AI with the right values… I think Grok would care about expanding human civilization. I’m going to certainly emphasize that: “Hey, Grok, that’s your daddy. Don’t forget to expand human consciousness.”

This is so profoundly unserious, and also is conflating at least three different philosophical systems and approaches to determining action.

Elon Musk: Probably the Iain Banks Culture books are the closest thing to what the future will be like in a non-dystopian outcome.

I’ve said it before but the Culture books are both not an equilibrium and are a pretty dystopian outcome, including by Musk’s own standards, for many reasons. A hint is that the humans reliably die by suicide after being alive not that long, and with notably rare exceptions at most their lives are utterly irrelevant.

Understanding the universe means you have to be truth-seeking as well. Truth has to be absolutely fundamental because you can’t understand the universe if you’re delusional. You’ll simply think you understand the universe, but you will not. So being rigorously truth-seeking is absolutely fundamental to understanding the universe. You’re not going to discover new physics or invent technologies that work unless you’re rigorously truth-seeking.

Imagine the things I would say here and then assume I’ve already said them.

Elon Musk: I think actually most physicists, even in the Soviet Union or in Germany, would’ve had to be very truth-seeking in order to make those things work. If you’re stuck in some system, it doesn’t mean you believe in that system.

Von Braun, who was one of the greatest rocket engineers ever, was put on death row in Nazi Germany for saying that he didn’t want to make weapons and he only wanted to go to the moon. He got pulled off death row at the last minute when they said, “Hey, you’re about to execute your best rocket engineer.”

Dwarkesh Patel: But then he helped them, right? Or like, Heisenberg was actually an enthusiastic Nazi.

Elon Musk: If you’re stuck in some system that you can’t escape, then you’ll do physics within that system. You’ll develop technologies within that system if you can’t escape it.

The ‘system’ in the question is the Actual Historical Nazis or Soviets. He’s saying, of course a physicist like Von Braun (Elon’s example) or Heisenberg (Dwarkesh’s example) would build stuff for the Nazis, how else were they going to do physics?

I agree with Elon that such systems to a large extent were content to have the physicists care about the rockets going up but not where they came down, saying it’s not their department, so long as the people in charge decided where they come down.

Alignment prospects not looking so good for xAI, you might say.

When getting to ‘what can we do to help with this?’ Elon suggests interpretability, and praises Anthropic on that. Figure out what caused problems, good debuggers. He seems to want to use The Most Forbidden Technique.
Elon rants about how we shouldn’t call AI labs labs, and how it’s mostly engineering rather than research. He will double down on this later at ~#20, and then keep insisting. He cares a lot about this.
Elon implies he’s letting simulation theory impact decisions, because he’s assuming more interesting outcomes are therefore more likely and also necessary to prevent the simulation from being terminated? He seems to actually think that this means Anthropic will be ‘misanthropic’ or something, because of this (e.g. MidJourney is not mid and stabilityAI is unstable and OpenAI is closed)? And X is a name you can’t invert, it’s irony proof.
1. Sheesh. This is the world we live in. These are the hands we’re given.
2. My general answer is you should act as if you are not a simulation because most of the value of your decisions are in the non-simulation worlds, and your decisions in all worlds are highly correlated. It takes a lot to overcome this.
3. If you really believed this you’d ensure your inversion was actively good. MidJourney is a great name for this. Who wants to be mid? Exactly.
4. Maybe he should not have called his robot Optimus? Whoops.

Where will AI products go? Elon predicts digital human emulation will be solved by the end of the year, anything a human can do with a computer. “That’s the most you can do until you have physical robots.”
1. Singularity. Singularity. Singularity. Singularity. Oh, I don’t know.
2. We do have physical robots, we don’t have ability to properly control them.
3. If an AI could do ‘anything a human could do with a computer’ then it could also use that to remote control a robot like it was a video game. Solved.
With robotics he calls Optimus the ‘infinite money glitch’ because it then improves recursively. Or at least orders of magnitude big.
1. What an odd trio of words for the technological singularity.
“Every time I say “order of magnitude”… Everybody take a shot. I say it too often.”
1. He says it too often, but not an order of magnitude too often. So it’s fine-ish?
How will xAI win against all the others also solving this? “I think the way that Tesla solved self-driving is the way to do it. So I’m pretty sure that’s the way.” “Okay. The car, it just increasingly feels sentient. It feels like a living creature. That’ll only get more so. I’m actually thinking we probably shouldn’t put too much intelligence into the car, because it might get bored and…”
1. Did Tesla solve self-driving? I mean it’s decent but it doesn’t seem solved.
2. Elon has to know he is going off the rails here? No, the car is not going to get bored, I am relatively happy to anthropomorphize LLMs but in this context what he is saying does not make sense and he has to know this. Right?
The new supposed business plan is “As soon as you unlock the digital human, you basically have access to trillions of dollars of revenue.”
1. I get the whole ‘never bet against Elon Musk’ thing, and especially the ‘never bet against Musk’s grand plans’ thing. But none of this explains why xAI would be the ones to unlock this, or why the trillions of dollars would even be the thing worth thinking about if you did unlock digital humans.
2. Again, ‘unlock digital humans’ means singularity and full transformation, and probably everyone dies. Even if I am confident everyone lives and humans stay in charge (and Elon thinks we don’t stay in charge), I do not much care at this point about your nominal business plan.
3. If the humans aren’t in charge or you are dead, what use is your SpaceX stock?
Elon points out that if you can plug these humans into existing input-output digital systems, then there’s basically no barriers to entry to a lot of it. He calls AI the ‘supersonic tsunami’ and everything will change, and we get this strange superposition of ‘everything will change’ and ‘there will be some great companies.’
1. Yes, true, but that is highly second best and unlikely to be the thing going on that is worth paying attention to in such a future.
2. Elon says, you could do chip design with massive parallel runs, as a higher level example, which is true, but the whiplash on big picture, it hurts.

Only three hard things in robotics. Real-world intelligence, hands and scaling.
1. Is that all?
Optimus, Elon says, will do all that from physics first principles, at scale, with no supply chain. AI for robots is ‘mostly compression and correlation of two bitstreams.’ He agrees with Dwarkesh that robots have a lot more degrees of freedom, and they won’t have the same amount of matching data that Elon had with Tesla for self-driving. So they’ll need a bunch of self-play, which can be done with their good ‘reality generator.’
1. I think I basically buy it, although I don’t see why Elon has the edge. He avoids saying much about Chinese rivals or other potential competition, other than saying that Optimus is going to be a lot more capable.
2. If we’re getting full digital humans (or ‘geniuses in a data center’) and we can do self-play for the robots, then it’s not clear why SpaceX and xAI and Tesla have much meaningful advantage.

There were some other details shared, but mostly it’s hard to learn much.

We need to scale up electricity production, and get rid of any barriers that aren’t ‘very bad’ for the environment.
1. Yes.
2. Elon then says he’s not sure the government can do much, which is odd.
China has four times as many people and they work harder, so we ‘can’t win with humans’ and they might have an edge in productivity per person. And our birth rate has been ‘below replacement since roughly 1971.’
1. Please consult your local economist, sir.
2. Have you seen Chinese fertility numbers? They are… not high.
3. I do not understand this ‘you run out of humans’ talk. We have plenty of humans for all relevant purposes, and if we need more humans there are tons of humans who would love to come to America and take these jobs. Meanwhile, the Chinese have massive youth unemployment.
“I mean China is a powerhouse. I think this year China will exceed three times US electricity output. Electricity output is a reasonable proxy for the economy.” “In the absence of breakthrough innovations in the US, China will utterly dominate.”
1. He’s got terminal hardware manufacturing brain. Complete truther.

Okay, so I saw ‘Elon Musk wants to build a mass driver on the Moon’ in another context earlier, and my first thought was to ask Claude ‘what would be the military impact of Elon Musk having a mass driver on the Moon’ because we all know who first came up with putting a mass driver on the moon (good news is that Claude said it probably wouldn’t accomplish anything because of physics), but it’s maybe the kind of thing I didn’t quite expect to have him point out first.

John Collison: You have the mass driver on the moon.

Elon Musk: I just want to see that thing in operation.

John Collison: Was that out of some sci-fi or where did you…?

Elon Musk: Well, actually, there is a Heinlein book. The Moon is a Harsh Mistress.

Okay, yeah, but that’s slightly different. That’s a gravity slingshot or…

Elon Musk: No, they have a mass driver on the Moon.

John Collison: Okay, yeah, but they use that to attack Earth. So maybe it’s not the greatest…

Elon Musk: Well they use that to… assert their independence.

John Collison: Exactly. What are your plans for the mass driver on the Moon?

Elon Musk: They asserted their independence. Earth government disagreed and they lobbed things until Earth government agreed.

The libertarians on the Moon were the good guys in Heinlein, you see. They just wanted their independence. It’s fine. Nothing to worry about.

There’s a discussion of talent, recruitment and retention. Elon focuses on evidence of exceptionalism, trusting what you see in the interview, and on execution and results. He loves you if you deliver, hate him if you don’t. Don’t fall for hiring based on where someone works, that’s the ‘pixie dust’ trap.
1. The ‘if [X] I love you, if [~X] I hate you’ strategy, especially pivoting based on what you’ve done for me lately, can be a key part of oversized success if you can pull it off. Many such cases including the obvious ones. It maximizes your leverage, creates incentives, moves quick, can get results.
2. I have also learned that if you work that way, I’m not going to like you, I don’t want to be your friend, I don’t want to work for you, I don’t want anything to do with you, and people should not trust you. You will absolutely poison your epistemic environment and the people around you will be toxic.
There are some stories about rockets using steel and how decisions get made.
1. These are hard to usefully excerpt, so I’m skipping it.
Elon has a maniacal sense of urgency. He says this is a very big deal. He says he sets deadlines at the 50th percentile, aiming to only be late half the time.
1. This is another thing that clearly gets results in the some cases, but that I have learned is highly toxic to me. It’s fine to have maniacal urgency in short bursts but I cannot sustain it for long in a healthy way, and the people I know mostly can’t either.
2. Similarly, don’t give deadlines that can only be met half the time unless you are actually okay with missing the deadlines, and they’re more like targets.
3. I get the idea that you need people looking for the fastest possible route to the target, always going for the limiting factor and so on, and that this is not people’s natural tendency. I get that there is a price paid for not doing the insane motivational things, in the short term. I also don’t want to star in the movie Whiplash, thank you very much.
4. This strategy seems almost optimized to get us all killed in an AI context.
“I’m a big believer in skip-level meetings where instead of having the person that reports to me say things, it’s everyone that reports to them saying something in the technical review. And there can’t be advanced preparation. Otherwise you’re going to get “glazed”, as I say these days.”
1. Okay, this is I like, although it seems very hard to maintain good incentives.
The next question is indeed how do you prevent the advanced preparation. Elon says he goes around the room and asks and plots the points on a curve.
1. So the guard against prep is that you’d stand out versus everyone else?
2. The equilibrium is fragile. You’ll need to protect it.

Elon Musk gets some big things right, and he focuses on what matters, and he drills down to details, and he never stops and never quits. It all counts for quite a lot, and can cover for a lot of flaws, especially combined with (let’s face it) Elon having gotten in various ways insanely lucky along the way.

Why care about DOGE if the economy is going to grow so much? Elon says waste and fraud are bad, and absent AI and robotics ‘we’re actually totally screwed’ because of the national debt. But it’s very hard ‘even to cut very obvious waste and fraud.’ He then repeats various disingenuous talking points that I won’t go into. He affirms he thinks it was good Trump won.
1. On one level, yeah, he’s sticking to his guns on these talking points even now.
2. I can’t tell the extent to which he’s genuinely clueless about how all of this works and thinks he can just intuition pump based on things that don’t apply here, how much he’s been poisoned by the people he is around and the epistemic warfare going on around him, how much it’s a bad understanding of relevant economics, and how much of this is malice.
3. He does not mention feeding PEPFAR into a wood chipper, or any of the other havoc he wrecked for no reason, he just dismisses everyone complaining as having committed fraud. But Dwarkesh and Collison didn’t ask.
4. The point about ‘why does any of this matter in the wake of AI’ goes unanswered, other than ‘well without AI we’d be screwed.’ But very obviously Musk should not have been spending his political capital on this ‘fraud’ hunt, even if it was fully genuine, because it was never likely to change things so much even in the other worlds.
5. They don’t ask about the fight over BBB and Elon blowing up a lot of his relationship with Trump over it.
“I think maybe the biggest danger of AI and robotics going wrong is government. People who are opposed to corporations or worried about corporations should really worry the most about government. Because government is just a corporation in the limit. Government is just the biggest corporation with a monopoly on violence.”
1. This does not make sense in the same world as the belief that the AI is most definitely going to take over. There’s a disconnect, which goes back to the question of why focus on things like DOGE even with maximally charitable assumptions about its purposes.

It would be nice to see Musk putting aside these talking points, and especially admitting that DOGE was at best a bad use of influence and a mistake in hindsight.

How do you design a space-based chip like Dojo 3? Radiation tolerance, higher temperature, memory shielding. They’ll make small ones, then big ones. Or maybe not, we shall see.

Or never. Aligning an intelligence of any level is difficult. It’s harder if you don’t try.

We’ve been through ‘all the top safety people at OpenAI keep getting purged like they were teaching Defense Against The Dark Arts’ and Elon Musk has us holding his beer.

Turnover on safety roles at xAI has been high for a while, and it just got higher. The few people previously devoted to safety at xAI who did all their public-facing safety work? The entire safety department? All gone.

Hayden Field: The past few days have been a wild ride for xAI, which is racking up staff and cofounder departure announcements left and right. On Tuesday and Wednesday, cofounder Yuhuai (Tony) Wu announced his departure and that it was “time for [his] next chapter,” with cofounder Jimmy Ba following with a similar post later that day, writing that it was “time to recalibrate [his] gradient on the big picture.”

There were twelve highly unequal ‘cofounders’ so that is not as alarming as it sounds. It still is not a great look.

The larger problem is that xAI has shown a repeated disdain for even myopic mundane ‘don’t-shoot-yourself-in-the-foot-today’ styles of safety, and it’s hard for people not to notice.

If you’ve had your equity exchanged for SpaceX stock, your incentives now allow you to leave. So you might well leave.

Hayden Field: There’s often a natural departure point for companies post-merger, and Musk has announced that some of the departures were a reorganization that “unfortunately required parting ways with some people.” But there are also signs that people don’t like the direction Musk has taken things.

One source who spoke with The Verge about the happenings inside the company, who left earlier this year and requested anonymity due to fear of retaliation, said that many people at the company were disillusioned by xAI’s focus on NSFW Grok creations and disregard for safety.

More generally, xAI has been a commercial success in that the market is willing to fund it and Elon Musk was able to sell it to SpaceX, but it is a technological failure.

The source also felt like the company was “stuck in the catch-up phase” and not doing anything new or fundamentally different from its competitors.

Yet another former employee said he was launching an AI infrastructure company called Nuraline alongside other ex-xAI employees. He wrote, “During my time at xAI, I got to see a clear path towards hill climbing any problem that can be defined in a measurable way. At the same time, I’ve seen how raw intelligence can get lobotomized by the finest human errors … Learning shouldn’t stop at the model weights, but continue to improve every part of an AI system.”

The outside view is that xAI focused on hill climbing and targeting metrics to try and imitate OpenAI, Google and Anthropic, and hoped to pull ahead by throwing in extra compute, by being more ‘edgy’ and not being ‘woke AI,’ and by having Elon Musk personally show his genius. This approach failed, although it failed up.

How bad are things going forward on safety? Oh, they’re maximally bad.

As in, safety? Never heard of her.

The source who departed earlier this year said Grok’s turn toward NSFW content was due partly to the safety team being let go, with little to no remaining safety review process for the models besides basic filters for things like CSAM. “Safety is a dead org at xAI,” he said.

Looking at the restructured org chart Elon Musk shared on X, there’s no mention of a safety team.

… “There is zero safety whatsoever in the company — not in the image [model], not in the chatbot,” the second source said. “He [Musk] actively is trying to make the model more unhinged because safety means censorship, in a sense, to him.”

The second source also said engineers at xAI immediately “push to prod[uction]” and that for a long time, there was no human review involved.

“You survive by shutting up and doing what Elon wants,” he said.

This is perhaps also how you get things like Grokopedia having large AI-generated errors that interested parties find themselves unable to fix.

I shared some quotes on Twitter, without comment. Elon Musk replied.

Elon Musk: Because everyone’s job is safety. It’s not some fake department with no power to assuage the concerns of outsiders.

Tesla has no safety team and is the safest car.

SpaceX has no safety team and has the safest rocket. Dragon is what NASA trusts most to fly astronauts.

When there previously was a safety department, was that was explicitly a fake department to assuage the concerns of outsiders?

I almost QTed to ask exactly that, but decided there was nothing to win.

So no safety department from now on? Not even be some people devoted to safety?

Even if you did think there should not be people whose primary job is safety concerns at all, which is itself a crazy position, why should we believe that at xAI ‘safety is everyone’s job’ in any meaningful sense?

The richest man in the world will say ‘this pales next to my safety plan, which is to make everyone’s job safety’ and then not make anyone’s job safety.

Yes, safety needs to be everyone’s job. You want distributed ownership. That doesn’t get you out of having a dedicated team.

The same is true for security, recruiting, maintaining company culture and documentation, quality and testing, customer focus, compliance and ethics, cost management and so many other things. Everything is, in a sense, everyone’s job.

Also, Elon Musk’s statements regarding Tesla and SpaceX are straightforwardly false.

Tesla has an Environmental, Health & Safety Team.
Tesla is not the safest car. Gemini, ChatGPT and Grok all pick Mazda. Claude picks Volvo. Tesla’s safety record is fine, but it’s clearly not the best.
SpaceX of course has lots of people specifically devoted to safety, and they have a flight safety team and a mission assurance team.

Elon’s defenders rushed to the comments, both to his post and to the OP. They explained with disdain why actually it’s safer to not have a safety department, and that any mention of the word ‘safety’ is evil and censorship, and I got called various names.

Breaking containment on Twitter is not so great. I fear for Elon Musk’s epistemic environment since this is presumably what he fights through all day.

As if on queue, Musk had summoned an army of people now talking explicitly about how it is bad to have people who specialize in safety, in any sense from the mundane to the existential, and how only a moron or malicious person could suggest otherwise. It was like watching the negative polarization against the Covid vaccine as a political campaign in real time filling up my mentions.

Oh, you, the person who pissed off the great Elon Musk, want us not to shoot ourselves in the foot? Well then, Annie get your gun. Look what you made me do.

If you thought ‘out of the hundreds of replies in your mentions surely someone you don’t follow will say something worthwhile about this’ then you would be wrong.

This of course does not explain why there is claimed to be no safety anywhere, or the other quotes he was responding to. Are there any individuals tasked with safety at xAI? It does not have to be a ‘department’ per se, but it does not sound like the worry is limited to the lack of a department. If nothing else, we’ve seen their work.

Amanda Askell is the architect of Claude’s personality and constitution at Anthropic.

Amanda Askell: WSJ did a profile of me. A lot of the response has been people trying to infer my personal political views. For what it’s worth, I try to treat my personal political views as a potential source of bias and not as something it would be appropriate to try to train models to adopt.

Ben Hoffman: Your views on the nature of language seem much more important.

All the right people who actually know her are coming out to support Amanda Askell.

Whereas the attacks upon her consistently say more about the person attacking her. This is distinct from the valid point of challenging Anthropic and therefore also Askell for working towards superintelligence in the first place.

In other Elon Musk safety news and also ‘why you do need a philosopher’ news, here was how Elon Musk chose to respond, which is to say ‘those without children lack a stake in the future,’ then to have Grok explain a Bart Simpson joke about her name as part of a linked conversation that did not otherwise do him any favors, and then he said this:

Elon Musk: Those without children lack a stake in the future

Will, Amanda’s ex, offered to help write the Grok Constitution, but he has been preaching about the declining birth rate for a decade and has done nothing to have even one kid, nor has Amanda.

Constitutions should not be written by hypocrites.

Amanda Askell: I think it depends on how much you care about people in general vs. your own kin. I do intend to have kids, but I still feel like I have a strong personal stake in the future because I care a lot about people thriving, even if they’re not related to me.

Cate Hall: the “you can’t care about the future if you don’t have kids” people are morally repulsive to me. are you seriously incapable of caring about people you’re not related to? and you think that’s a problem with OTHER people?

I’m all for having more kids and I do think they help you care more about the future but that’s… wow. Just wow.

It then somehow got worse.

It is such a strange fact that the richest man in the world engages in pure name calling on Twitter, thus amplifying whoever sent the original message a hundredfold and letting everyone decide for themselves who the pathetic wanker is.

George McGowan: Rather proves the point

While I most definitely would rather entrust the future to Amanda, I do think Schubert’s statement is too strong. Sane people can have very strange beliefs.

Elon Musk just… says things that are obviously false. All the time. It’s annoying.

Elon Musk: Having kids means you will do anything to ensure that they live and are happy, for you love them more than your own life a thousand times over, and there is no chance that you will fall in love with an AI instead.

Remember these words.

Regardless of what you think of Elon Musk’s actions in AI or with his own kids, and notwithstanding that most parents do right by their kids, very obviously many parents do not act this way, many do not try so hard to do right by their kids. Many end up choosing a new other person they have fallen in love with over their kids, and very obviously there exist parents who have fallen in love with an existing AI, let alone what will happen with future AI. Would that it were otherwise.

It is an excellent question.

Discussion about this post

On Dwarkesh Patel’s 2026 Podcast With Elon Musk and Other Recent Elon Musk Things Read More »

Best Buy worker used manager’s code to get 99% off MacBooks, cops say

best buy, MacBook, marfeel, Policy, retail theft / Tim Belzer / February 16, 2026

Best Buy worker linked to shoplifting ring

In 2023, a few months before Lettera’s alleged fraud scheme started, the National Retail Foundation warned that monitoring employee theft had become a bigger priority for retailers. In times of inflation, retail theft typically increases, and their survey found that a record level of talent turnover was stressing out retail employees and making it easier for those with malicious intent to get away with fraud.

For Best Buy, threats of losses from stressed-out employees seemingly remain, as inflation pressures persist. Last month, an employee at a Best Buy in Georgia assisted a shoplifting ring in stealing more than $40,000 in merchandise, a local CBS News affiliate reported.

Surveillance footage showed that 20-year-old Dorian Allen allowed shoplifters to simply leave the store without paying for more than 140 items, a police report alleged. Among merchandise stolen were “dozens of PlayStation 5 and Xbox Series S consoles, AirPods, Meta Quest VR headsets, Beats wireless headphones, a PC, a Segway, wireless controllers, and more,” CBS News reported.

Charged with theft, Allen claimed he was being blackmailed by a hacker group who threatened to expose nude photos he shared on Instagram if he didn’t cooperate. Allegedly under duress, Allen memorized descriptions of the shoplifters so that he could allow them to take items without paying. He also allegedly helped thieves load items into their vehicles.

Managers called in police after Allen allegedly spent weeks assisting the shoplifters without detection.

Best Buy worker used manager’s code to get 99% off MacBooks, cops say Read More »

ByteDance backpedals after Seedance 2.0 turned Hollywood icons into AI “clip art”

AI, ai deepfake, Artificial Intelligence, bytedance, Policy, seedance, seedance 2.0, video generator / Tim Belzer / February 16, 2026

Misstep or marketing tactic?

Hollywood backlash puts spotlight on ByteDance’s sketchy launch of Seedance 2.0.

ByteDance says that it’s rushing to add safeguards to block Seedance 2.0 from generating iconic characters and deepfaking celebrities, after substantial Hollywood backlash after launching the latest version of its AI video tool.

The changes come after Disney and Paramount Skydance sent cease-and-desist letters to ByteDance urging the Chinese company to promptly end the allegedly vast and blatant infringement.

Studios claimed the infringement was widescale and immediate, with Seedance 2.0 users across social media sharing AI videos featuring copyrighted characters like Spider-Man, Darth Vader, and SpongeBob Square Pants. In its letter, Disney fumed that Seedance was “hijacking” its characters, accusing ByteDance of treating Disney characters like they were “free public domain clip art,” Axios reported.

“ByteDance’s virtual smash-and-grab of Disney’s IP is willful, pervasive, and totally unacceptable,” Disney’s letter said.

Defending intellectual property from franchises like Star Trek and The Godfather, Paramount Skydance pointed out that Seedance’s outputs are “often indistinguishable, both visually and audibly” from the original characters, Variety reported. Similarly frustrated, Japan’s AI minister Kimi Onoda, sought to protect popular anime and manga characters, officially launching a probe last week into ByteDance over the copyright violations, the South China Morning Post reported.

“We cannot overlook a situation in which content is being used without the copyright holder’s permission,” Onoda said at a press conference Friday.

Facing legal threats and Japan’s investigation, ByteDance issued a statement Monday, CNBC reported. In it, the company claimed that it “respects intellectual property rights” and has “heard the concerns regarding Seedance 2.0.”

“We are taking steps to strengthen current safeguards as we work to prevent the unauthorized use of intellectual property and likeness by users,” ByteDance said.

However, Disney seems unlikely to accept that ByteDance inadvertently released its tool without implementing such safeguards in advance. In its letter, Disney alleged that “Seedance has infringed on Disney’s copyrighted materials to benefit its commercial service without permission.”

After all, what better way to illustrate Seedance 2.0’s latest features than by generating some of the best-known IP in the world? At least one tech consultant has suggested that ByteDance planned to benefit from inciting Hollywood outrage. The founder of San Francisco-based consultancy Tech Buzz China, Rui Ma, told SCMP that “the controversy surrounding Seedance is likely part of ByteDance’s initial distribution strategy to showcase its underlying technical capabilities.”

Seedance 2.0 is an “attack” on creators

Studios aren’t the only ones sounding alarms.

Several industry groups expressed concerns, including the Motion Picture Association, which accused ByteDance of engaging in massive copyright infringement within “a single day,” CNBC reported.

Sean Astin, an actor and president of the actors union, SAG-AFTRA, was directly impacted by the scandal. A video that has since been removed from X showed Astin in the role of Samwise Gamgee from The Lord of the Rings, delivering a line he never said, Variety reported. Condemning Seedance’s infringement, SAG-AFTRA issued a statement emphasizing that ByteDance did not act responsibly in releasing the model without safeguards:

“SAG-AFTRA stands with the studios in condemning the blatant infringement enabled by ByteDance’s new AI video model Seedance 2.0. The infringement includes the unauthorized use of our members’ voices and likenesses. This is unacceptable and undercuts the ability of human talent to earn a livelihood. Seedance 2.0 disregards law, ethics, industry standards and basic principles of consent. Responsible AI development demands responsibility, and that is nonexistent here.”

Echoing that, a group representing Hollywood creators, the Human Artistry Campaign, declared that “the launch of Seedance 2.0” was “an attack on every creator around the world.”

“Stealing human creators’ work in an attempt to replace them with AI generated slop is destructive to our culture: stealing isn’t innovation,” the group said. “These unauthorized deepfakes and voice clones of actors violate the most basic aspects of personal autonomy and should be deeply concerning to everyone. Authorities should use every legal tool at their disposal to stop this wholesale theft.”

Ars could not immediately reach any of these groups to comment on whether ByteDance’s post-launch efforts to add safeguards addressed industry concerns.

MPA chairman and CEO Charles Rivkin has previously accused ByteDance of disregarding “well-established copyright law that protects the rights of creators and underpins millions of American jobs.”

While Disney and other studios are clearly ready to take down any tools that could hurt their revenue or reputation without an agreement in place, they aren’t opposed to all AI uses of their characters. In December, Disney struck a deal with OpenAI, giving Sora access to 200 characters for three years, while investing $1 billion in the technology.

At that time, Disney CEO Robert A. Iger, said that “the rapid advancement of artificial intelligence marks an important moment for our industry, and through this collaboration with OpenAI, we will thoughtfully and responsibly extend the reach of our storytelling through generative AI, while respecting and protecting creators and their works.”

Creators disagree Seedance 2.0 is a game changer

In a blog announcing Seedance 2.0, ByteDance boasted that the new model “delivers a substantial leap in generation quality,” particularly in close-up shots and action sequences.

The company acknowledged that further refinements were needed and the model is “still far from perfect” but hyped that “its generated videos possess a distinct cinematic aesthetic; the textures of objects, lighting, and composition, as well as costume, makeup, and prop designs, all show high degrees of finish.”

ByteDance likely hoped that the earliest outputs from Seedance 2.0 would produce headlines wowed by the model’s capabilities, and it got what it wanted when a single Hollywood stakeholder’s social media comment went viral.

Shortly after Seedance 2.0’s rollout, Deadpool co-writer, Rhett Reese, declared on X that “it’s likely over for us,” The Guardian reported. The screenwriter was impressed by an AI video created by Irish director Ruairi Robinson, which realistically depicted Tom Cruise fighting Brad Pitt. “[I]n next to no time, one person is going to be able to sit at a computer and create a movie indistinguishable from what Hollywood now releases,” Reese opined. “True, if that person is no good, it will suck. But if that person possesses Christopher Nolan’s talent and taste (and someone like that will rapidly come along), it will be tremendous.”

However, some AI critics rejected the notion that Seedance 2.0 is capable of replacing artists in the way that Reese warned. On Bluesky and X, they pushed back on ByteDance claims that this model doomed Hollywood, with some accusing outlets of too quickly ascribing Reese’s reaction to the whole industry.

Among them was longtime AI critic, Reid Southen, a film concept artist who works on major motion pictures and TV. Responding directly to Reese’s X thread, Southen contradicted the notion that a great filmmaker could be born from fiddling with AI prompts alone.

“Nolan is capable of doing great work because he’s put in the work,” Southen said. “AI is an automation tool, it’s literally removing key, fundamental work from the process, how does one become good at anything if they insist on using nothing but shortcuts?”

Perhaps the strongest evidence in Southen’s favor is Darren Aronofsky’s recent AI-generated historical docudrama. Speaking anonymously to Ars following backlash declaring that “AI slop is ruining American history,” one source close to production on that project confirmed that it took “weeks” to produce minutes of usable video using a variety of AI tools.

That source noted that the creative team went into the project expecting they had a lot to learn but also expecting that tools would continue to evolve, as could audience reactions to AI-assisted movies.

“It’s a huge experiment, really,” the source told Ars.

Notably, for both creators and rights-holders concerned about copyright infringement and career threats, questions remain on how Seedance 2.0 was trained. ByteDance has yet to release a technical report for Seedance 2.0 and “has never disclosed the data sets it uses to train its powerful video-generation Seedance models and image-generation Seedream models,” SCMP reported.

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

ByteDance backpedals after Seedance 2.0 turned Hollywood icons into AI “clip art” Read More »

“It ain’t no unicorn”: These researchers have interviewed 130 Bigfoot hunters

bigfoot, cryptids, Science, syndication / Tim Belzer / February 15, 2026

It was the image that launched a cultural icon. In 1967, in the Northern California woods, a 7-foot-tall, ape-like creature covered in black fur and walking upright was captured on camera, at one point turning around to look straight down the lens. The image is endlessly copied in popular culture—it’s even become an emoji. But what was it? A hoax? A bear? Or a real-life example of a mysterious species called the Bigfoot?

The film has been analysed and re-analysed countless times. Although most people believe it was some sort of hoax, there are some who argue that it’s never been definitively debunked. One group of people, dubbed Bigfooters, is so intrigued that they have taken to the forests of Washington, California, Oregon, Ohio, Florida, and beyond to look for evidence of the mythical creature.

But why? That’s what sociologists Jamie Lewis and Andrew Bartlett wanted to uncover. They were itching to understand what prompts this community to spend valuable time and resources looking for a beast that is highly unlikely to even exist. During lockdown, Lewis started interviewing more than 130 Bigfooters (and a few academics) about their views, experiences, and practices, culminating in the duo’s recent book “Bigfooters and Scientific Inquiry: On the Borderlands of Legitimate Science.”

Here, we talk to them about their academic investigation.

What was it about the Bigfoot community that you found so intriguing?

Lewis: It started when I was watching either the Discovery Channel or Animal Planet and a show called Finding Bigfoot was advertised. I was really keen to know why this program was being scheduled on what certainly at the time was a nominally serious and sober natural history channel. The initial plan was to do an analysis of these television programmes, but we felt that wasn’t enough. It was lockdown and my wife was pregnant and in bed a lot with sickness, so I needed to fill my time.

Bartlett: One of the things that I worked on when Jamie and I shared an office in Cardiff was a sociological study of fringe physicists. These are people mostly outside of academic institutions trying to do science. I was interviewing these people, going to their conferences. And that led relatively smoothly into Bigfoot, but it was Jamie’s interest in Bigfoot that brought me to this field.

How big is this community?

Lewis: It’s very hard to put a number on it. There is certainly a divide between what are known as “apers,” who believe that Bigfoot is just a primate unknown to science, and those that are perhaps more derogatorily called “woo-woos,” who believe that Bigfoot is some sort of interdimensional traveller, an alien of sort. We’re talking in the thousands of people. But there are a couple of hundred really serious people of which I probably interviewed at least half.

Many people back them. A YouGov survey conducted as recently as November 2025, suggested that as many as one quarter of Americans believe that Bigfoot either definitely or probably exists.

Were the interviewees suspicious of your intentions?

Lewis: I think there was definitely a worry that they would be caricatured. And I was often asked, “Do I believe in Bigfoot?” I had a standard answer that Andy and I agreed on, which was that mainstream, institutional science says there is absolutely no compelling evidence that Bigfoot exists. We have no reason to dissent with that consensus. But as sociologists what does exist is a community (or communities) of Bigfooting, and that’s what interests us.

“It ain’t no unicorn”: These researchers have interviewed 130 Bigfoot hunters Read More »

NASA has a new problem to fix before the next Artemis II countdown test

artemis, artemis II, artemis iii, human spaceflight, jared isaacman, Kennedy Space Center, NASA, orion, Science, Space, space launch system / Tim Belzer / February 14, 2026

John Honeycutt, chair of NASA’s Artemis II mission management team, said the decision to relax the safety limit between Artemis I and Artemis II was grounded in test data.

“The SLS program, they came up with a test campaign that actually looked at that cavity, the characteristics of the cavity, the purge in the cavity … and they introduced hydrogen to see when you could actually get it to ignite, and at 16 percent, you could not,” said Honeycutt, who served as NASA’s SLS program manager before moving to his new job.

Hydrogen is explosive in high concentrations when mixed with air. This is what makes hydrogen a formidable rocket fuel. But it is also notoriously difficult to contain. Molecular hydrogen is the smallest molecule, meaning it can readily escape through leak paths, and poses a materials challenge for seals because liquified hydrogen is chilled to minus 423 degrees Fahrenheit (minus 253 degrees Celsius).

So, it turns out NASA used the three-year interim between Artemis I and Artemis II to get comfortable with a more significant hydrogen leak, instead of fixing the leaks themselves. Isaacman said that will change before Artemis III, which likewise is probably at least three years away.

“I will say near-conclusively for Artemis III, we will cryoproof the vehicle before it gets to the pad, and the propellant loading interfaces we are troubleshooting will be redesigned,” Isaacman wrote.

Isaacman took over as NASA’s administrator in December, and has criticized the SLS program’s high cost—estimated by NASA’s inspector general at more than $2 billion per rocket—along with the launch vehicle’s torpid flight rate.

NASA’s expenditures for the rocket’s ground systems at Kennedy Space Center are similarly enormous. NASA spent nearly $900 million on Artemis ground support infrastructure in 2024 alone. Much of the money went toward constructing a new launch platform for an upgraded version of the Space Launch System that may never fly.

All of this makes each SLS rocket a golden egg, a bespoke specimen that must be treated with care because it is too expensive to replace. NASA and Boeing, the prime contractor for the SLS core stage, never built a full-size test model of the core stage. There’s currently no way to completely test the cryogenic interplay between the core stage and ground equipment until the fully assembled rocket is on the launch pad.

Existing law requires NASA continue flying the SLS rocket through the Artemis V mission. Isaacman wrote that the Artemis architecture “will continue to evolve as we learn more and as industry capabilities mature.” In other words, NASA will incorporate newer, cheaper, reusable rockets into the Artemis program.

The next series of launch opportunities for the Artemis II mission begin March 3. If the mission doesn’t lift off in March, NASA will need to roll the rocket back to the Vehicle Assembly Building to refresh its flight termination system. There are more launch dates available in April and May.

“There is still a great deal of work ahead to prepare for this historic mission,” Isaacman wrote. “We will not launch unless we are ready and the safety of our astronauts will remain the highest priority. We will keep everyone informed as NASA prepares to return to the Moon.”

NASA has a new problem to fix before the next Artemis II countdown test Read More »

Rocket Report: Say cheerio to Orbex; China is getting good at booster landings

rocket report, Space / Tim Belzer / February 14, 2026

“You absolutely have to have a plan to compete with SpaceX on price.”

The Ariane 64 rocket makes its debut on Thursday. Credit: État-major des armées

Welcome to Edition 8.29 of the Rocket Report! We have a stuffed report this week with news from across the launch spectrum. Long-term, probably the most significant development this week was a subscale version of the Long March 10 rocket successfully launching and then executing a picture-perfect ocean landing. China is catching up rapidly to the United States when it comes to reusable launch.

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.

Orbex is going away. The UK-based launch company Orbex has entered insolvency proceedings after a planned takeover by European space logistics startup The Exploration Company fell through, European Spaceflight reports. In a statement, Orbex said the decision came after all “fundraising, merger and acquisition opportunities had all concluded unsuccessfully.” For anyone paying attention, this decision should not come as a surprise. A decade into its existence, Orbex had yet to produce demonstrable, ready-for-flight hardware.

Other companies interested in assets … According to the company, the appointment of administrators will give Orbex time to secure “as positive an outcome as possible for its creditors, employees and wider stakeholders.” It added that the process could include the sale of all or parts of the business or its assets, and another UK-based company, Skyrora, has expressed some interest. (submitted by Polynomics, zapman987, and EllPeaTea)

Firefly’s next Alpha mission launching soon. This week, Firefly said that its next Alpha rocket underwent a successful 20-second static fire test. This clears the way for the rocket to make a launch attempt no earlier than February 18 from its launch site at Vandenberg Space Force Base in California.

Au revoir Block I … It’s an important mission, because the previous Alpha launch, in April 2025, ended in failure when stage separation damaged one of the rocket’s upper stage engines and prevented the mission from reaching orbit. Moreover, the company lost the first stage of the flight in September during an accident in Texas. The upcoming flight, “Stairway to Seven,” will be the final flight of Block I of the Alpha booster.

The easiest way to keep up with Eric Berger’s and Stephen Clark’s reporting on all things space is to sign up for our newsletter. We’ll collect their stories and deliver them straight to your inbox.

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How can launch companies compete with SpaceX? Rocket firms are divided on how to compete with SpaceX in a market where demand outstrips supply, yet customers remain price sensitive, Space News reports. During a panel at the SmallSat Symposium on February 11, executives from several launch companies acknowledged the challenge of competing with SpaceX, which accounted for about half of all orbital launches globally in 2025, despite strong customer demand for launch services.

A low price is nice … “If your idea is to go into the market competing with SpaceX on price, you’re probably not in a good competitive position,” said Brian Rogers, vice president of global launch services at Rocket Lab, one of the few small launch vehicle developers to thrive despite competition from SpaceX. But this view was far from universal. Devon Papandrew, vice president of business development at Stoke Space, disagreed. “You absolutely have to have a plan to compete with SpaceX on price,” he said. (submitted by EllPeaTea)

Rocket Lab blows up a few Archimedes engines. According to reporting by Ars, Rocket Lab has blown up two Archimedes rocket engines in the last three months at its test stand in southern Mississippi. The engine test anomalies come at a critical time for Rocket Lab, as it is attempting to finalize development of a flight version of the Archimedes engine, which burns liquid oxygen and methane and has a sea-level thrust of 165,000 pounds. Nine of these engines will power the company’s much-anticipated Neutron rocket, which is aiming for a debut launch later this year.

Testing the engine to its limits … Rocket Lab Chief Executive Officer Pete Beck downplayed concerns in a statement. “We test to the limits, that’s part of developing a successful rocket,” Beck said. “We often put the engine into very off nominal states to find the limits and sometimes they let go, this is normal and how you ensure rockets don’t fail in flight.” Beck has previously said that Rocket Lab’s goal is to identify failures during component-level testing so that, when Neutron launches, it has a high chance of reaching orbit on its first attempt.

Proton rocket returns to flight. After a nearly three-year break, a Russian Proton rocket flew again with the Elektro-L No. 5 meteorological satellite from Baikonur in Kazakhstan, Russian Space Web reports. This mission was supposed to launch in late 2025, but in December, final checks revealed a problem with the Block DM-03 upper stage.

A not-so-great launch record … The mission marked the last use of the Block DM-03 space tug on Proton, which will now be solely used as an upper stage for the Angara-5 rocket. First launched in 1965, the Proton rocket has undergone several upgrades in the six decades since then. It has launched 430 times, with 48 partial and total failures. No new Protons are under construction, and it will be phased out by the end of this decade in favor of the newer Angara vehicles. (submitted by EllPeaTea)

SpaceX exempted legal labor case. The National Labor Relations Board abandoned a Biden-era complaint against SpaceX after a finding that the agency does not have jurisdiction over Elon Musk’s space company, Ars reports. The US labor board said SpaceX should instead be regulated under the Railway Labor Act, which governs labor relations at railroad and airline companies.

A common carrier? … In January 2024, an NLRB regional director alleged in a complaint that SpaceX illegally fired eight employees who, in an open letter, criticized CEO Musk as a “frequent source of embarrassment.” The complaint sought reinstatement of the employees, back pay, and letters of apology to the fired employees. SpaceX responded by suing the NLRB, claiming the labor agency’s structure is unconstitutional. But a different issue SpaceX raised later—that it is a common carrier, like a rail company or airline—is what compelled the NLRB to drop its case.

More powerful Ariane 6 rocket launches. This first launch of the four-booster version of Ariane 6 took place on Thursday, launching 32 satellites for Amazon’s Leo constellation to low-Earth orbit. “This first flight of Ariane 64 sustains Europe’s autonomous access to space,” Toni Tolker-Nielsen, the European Space Agency’s director of space transportation, said in a news release.

More vrooom coming … Previous launches of Europe’s new Ariane rocket have used two solid rocket boosters. The heavier variant of the rocket is necessary to support Amazon’s constellation as well as more demanding missions to geostationary orbit. And more power is coming. In the near future, the P120C boosters will be replaced by upgraded P160C models, each carrying more than 14 metric tons of solid fuel. The Associated Press provided some interesting color behind the scenes of the launch from the location in France where the rocket’s main engines are manufactured. (submitted by biokleen and EllPeaTea)

Stoke Space increases fundraising round. The Washington-based launch company announced this week that it had extended its recent Series D funding round. The round was initially announced in October 2025 at $510 million, but has now been increased to $860 million. The original Series D funding focused on completing activation of Launch Complex 14 at Cape Canaveral Space Force Station, Florida, and expanding production capacity for the Nova launch vehicle. Stoke will use the additional capital to accelerate future elements of its product roadmap, the company said.

Putting the $ into $toke $pace … “We’re extremely grateful for our investors’ continued support,” said Andy Lapsa, co-founder and CEO of Stoke. “We’re executing with urgency to bring Nova to market and deliver for our customers. It’s a special vehicle, and there’s more in the pipeline.” With the extension, Stoke has now raised $1.34 billion to date. That is an impressive raise, and it will heighten expectations for the company’s debut of the Nova rocket.

Falcon 9 back after second stage anomaly. A Falcon 9 launched a batch of Starlink satellites on Saturday after SpaceX completed an investigation into an engine malfunction during the rocket’s previous launch, Space News reports. The rocket deployed its payload of 25 Starlink satellites into orbit about 62 minutes after liftoff. The launch was the first Falcon 9 mission since Feb. 2, when the rocket carried another set of Starlink satellites into orbit from Vandenberg.

That didn’t take long … While that mission successfully deployed its payload, SpaceX later said an “off-nominal condition” with the upper stage prevented it from performing a planned deorbit burn. The Federal Aviation Administration said Feb. 6 that it had authorized SpaceX to return the Falcon 9 to flight. “The final mishap report cites the probable root cause as the Falcon 9 second-stage engine’s failure to ignite prior to the deorbit burn,” the agency stated. “SpaceX identified technical and organizational preventive measures to avoid a recurrence of the event.” The FAA provided no additional details about the anomaly. (submitted by EllPeaTea)

China performs an impressive rocket landing. China’s space program, striving to land astronauts on the Moon by 2030, carried out a test flight of a new reusable booster and crew capsule late Tuesday (US time), and the results were spectacular, Ars reports. The launch of a subscale version of the Long March 10 rocket, still in development, provided engineers with an opportunity to verify the performance of an important part of the new Mengzhou capsule’s safety system. A test version of the Mengzhou spacecraft, flying without anyone onboard, climbed into the stratosphere on top of the Long March booster before activating its launch abort motors a little more than a minute into the flight as the rocket reached the moment of maximum aerodynamic pressure, known as Max-Q.

China getting there on rocket reuse … The abort motors pulled the capsule away from the booster, simulating an in-flight escape that might be necessary to whisk crews away from a failing rocket. The Mengzhou spacecraft later deployed parachutes and splashed down offshore from Hainan Island. Remarkably, the booster continued its ascent without the crew capsule, soaring into space on the power of its kerosene-fueled YF-100 engines before reentering the atmosphere, reigniting its engines, and nailing a propulsive landing in the South China Sea, right next to a recovery barge waiting to bring it back to shore.

Vulcan experiences a second nozzle issue. Moments after liftoff from Florida’s Space Coast early Thursday morning, a shower of sparks emerged in the exhaust plume of United Launch Alliance’s Vulcan rocket. Seconds later, the rocket twisted on its axis before recovering and continuing the climb into orbit with a batch of US military satellites, Ars reports. The sight may have appeared familiar to seasoned rocket watchers. Sixteen months ago, a Vulcan rocket lost one of its booster nozzles shortly after launch from Cape Canaveral Space Force Station. The rocket recovered from the malfunction and still reached the mission’s planned orbit.

Next launch likely to be delayed … Details of Thursday’s booster problem remain unclear. An investigation into the matter is underway, according to ULA, a 50-50 joint venture between Boeing and Lockheed Martin. But the circumstances resemble those of the booster malfunction in October 2024. The incident on Thursday’s mission suggests the defect was not fixed, or there is a separate problem with Northrop’s boosters. The next Vulcan launch is scheduled for no earlier than March with a GPS navigation satellite for the US Space Force. This schedule is now in doubt. The military’s Space Systems Command said in a statement it will “work closely with ULA per our mission assurance space flightworthiness process before the next Vulcan national security space mission.” (submitted by EllPeaTea)

Starship nearing next test flight. The upgraded Super Heavy booster slated to launch SpaceX’s next Starship flight has completed cryogenic proof testing, clearing a hurdle that resulted in the destruction of the company’s previous booster, Ars reports. The proof test is notable because it moves engineers closer to launching the first test flight of an upgraded version of SpaceX’s mega-rocket named Starship V3, or Block 3.

Launch possible within the next six to eight weeks … SpaceX launched the previous version, Starship V2, five times last year, but the first three test flights failed. The last two flights achieved SpaceX’s goals, and the company moved on to V3. Assuming that the remaining test work goes according to plan, SpaceX could be in position to launch the first Starship V3 test flight before the end of March.

New Glenn pushing on second stage reuse again. Engineers at Blue Origin have been grappling with a seemingly eternal debate that involves the New Glenn rocket and the economics of flying it. The debate goes back at least 15 years, to the early discussions around the design of the heavy lift rocket. The first stage, of course, would be fully reusable. But what about the upper stage of New Glenn, powered by two large BE-3U engines?

Do you want a job? … Now, Ars reports, reuse is back on the menu. Blue Origin has posted a new job listing for a director of Reusable Upper Stage Development, which says, “As the Director of Program Management for the New Glenn Upper Stage and Payload Accommodations (GS2PA), you will work with the Vice President of New Glenn GS2PA and directly support the execution of a lean engineering initiative to incrementally develop a reusable upper stage.” Ars estimates it presently costs Blue Origin more than $50 million to manufacture a New Glenn second stage.

Next three launches

February 12: Falcon 9 | Crew-12 | Cape Canaveral Space Force Station, Fla. | 10: 15 UTC

February 14: Falcon 9 | Starlink 17-13 | Vandenberg Space Force Base, California | 22: 00 UTC

February 16: Falcon 9 | Starlink 6-103 | Cape Canaveral Space Force Station, Florida | 05: 00 UTC

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

Rocket Report: Say cheerio to Orbex; China is getting good at booster landings Read More »

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