Anthropic CEO says spies are after $100M AI secrets in a ‘few lines of code’


Anthropic’s CEO Dario Amodei is worried that spies, likely from China, are getting their hands on costly “algorithmic secrets” from the U.S.’s top AI companies — and he wants the U.S. government to step in.

Speaking at a Council on Foreign Relations event on Monday, Amodei said that China is known for its “large-scale industrial espionage” and that AI companies like Anthropic are almost certainly being targeted.

“Many of these algorithmic secrets, there are $100 million secrets that are a few lines of code,” he said. “And, you know, I’m sure that there are folks trying to steal them, and they may be succeeding.”

More help from the U.S. government to defend against this risk is “very important,” Amodei added, without specifying exactly what kind of help would be required.

Anthropic declined to comment to TechCrunch on the remarks specifically but referred to Anthropic’s recommendations to the White House’s Office of Science and Technology Policy (OSTP) earlier this month.

In the submission, Anthropic argues that the federal government should partner with AI industry leaders to beef up security at frontier AI labs, including by working with U.S. intelligence agencies and their allies.

The remarks are in keeping with Amodei’s more critical stance toward Chinese AI development. Amodei has called for strong U.S. export controls on AI chips to China while saying that DeepSeek scored “the worst” on a critical bioweapons data safety test that Anthropic ran.

Amodei’s concerns, as he laid out in his essay “Machines of Loving Grace” and elsewhere, center on China using AI for authoritarian and military purposes.

This kind of stance has led to criticism from some in the AI community who argue the U.S. and China should collaborate more, not less, on AI, in order to avoid an arms race that results in either country building a system so powerful that humans can’t control it.

OpenAI co-founder John Schulman has left Anthropic after less than a year


Less than a year into his tenure at the company, OpenAI co-founder John Schulman is leaving Anthropic. The startup confirmed Schulman’s departure after The Information, Reuters and other publications reported on the exit.

“We are sad to see John go but fully support his decision to pursue new opportunities and wish him all the very best,” said Jared Kaplan, Anthropic’s chief science officer, in a statement the company shared with Engadget. Schulman left OpenAI last August alongside Peter Deng, the company’s former vice-president of consumer product. Schulman is considered one of the original architects of ChatGPT.

Following his departure from OpenAI, Schulman said he was joining Anthropic to focus on AI alignment — the process of making machine learning models safe to use — and a desire to return “to more hands-on technical work.” Schulman hasn’t publicly said why he decided to leave Anthropic, nor what he plans to do next. His X profile still says he “recently joined” Anthropic.

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Anthropic CEO goes full techno-optimist in 15,000-word paean to AI


Anthropic CEO Dario Amodei wants you to know he’s not an AI “doomer.”

At least, that’s my read of the “mic drop” of a ~15,000 word essay Amodei published to his blog late Friday. (I tried asking Anthropic’s Claude chatbot whether it concurred, but alas, the post exceeded the free plan’s length limit.)

In broad strokes, Amodei paints a picture of a world in which all AI risks are mitigated, and the tech delivers heretofore unrealized prosperity, social uplift, and abundance. He asserts this isn’t to minimize AI’s downsides — at the start, Amodei takes aim, without naming names, at AI companies overselling and generally propagandizing their tech’s capabilities. But one might argue that the essay leans too far in the techno-utopianist direction, making claims simply unsupported by fact.

Amodei believes that “powerful AI” will arrive as soon as 2026. By powerful AI, he means AI that’s “smarter than a Nobel Prize winner” in fields like biology and engineering, and that can perform tasks like proving unsolved mathematical theorems and writing “extremely good novels.” This AI, Amodei says, will be able to control any software or hardware imaginable, including industrial machinery, and essentially do most jobs humans do today — but better.

“[This AI] can engage in any actions, communications, or remote operations … including taking actions on the internet, taking or giving directions to humans, ordering materials, directing experiments, watching videos, making videos, and so on,” Amodei writes. “It does not have a physical embodiment (other than living on a computer screen), but it can control existing physical tools, robots, or laboratory equipment through a computer; in theory it could even design robots or equipment for itself to use.”

Lots would have to happen to reach that point.

Even the best AI today can’t “think” in the way we understand it. Models don’t so much reason as replicate patterns they’ve observed in their training data.

Assuming for the purpose of Amodei’s argument that the AI industry does soon “solve” human-like thought, would robotics catch up to allow future AI to perform lab experiments, manufacture its own tools, and so on? The brittleness of today’s robots imply it’s a long shot.

Yet Amodei is optimistic — very optimistic.

He believes AI could, in the next 7-12 years, help treat nearly all infectious diseases, eliminate most cancers, cure genetic disorders, and halt Alzheimer’s at the earliest stages. In the next 5-10 years, Amodei thinks that conditions like PTSD, depression, schizophrenia, and addiction will be cured with AI-concocted drugs, or genetically prevented via embryo screening (a controversial opinion) — and that AI-developed drugs will also exist that “tune cognitive function and emotional state” to “get [our brains] to behave a bit better and have a more fulfilling day-to-day experience.”

Should this come to pass, Amodei expects the average human lifespan to double to 150.

“My basic prediction is that AI-enabled biology and medicine will allow us to compress the progress that human biologists would have achieved over the next 50-100 years into 5-10 years,” he writes. “I’ll refer to this as the ‘compressed 21st century’: the idea that after powerful AI is developed, we will in a few years make all the progress in biology and medicine that we would have made in the whole 21st century.”

These seem like stretches, too, considering that AI hasn’t radically transformed medicine yet — and may not for quite some time, or ever. Even if AI does reduce the labor and cost involved in getting a drug into pre-clinical testing, it may fail at a later stage, just like human-designed drugs. Consider that the AI deployed in healthcare today has been shown to be biased and risky in a number of ways, or otherwise incredibly difficult to implement in existing clinical and lab settings. Suggesting all these issues and more will be solved roughly within the decade seems, well, aspirational.

But Amodei doesn’t stop there.

AI could solve world hunger, he claims. It could turn the tide on climate change. And it could transform the economies in most developing countries; Amodei believes AI can bring the per-capita GDP of sub-Saharan Africa ($1,701 as of 2022) to the per-capita GDP of China ($12,720 in 2022) in 5-10 years.

These are bold pronouncements, although likely familiar to anyone who’s listened to disciples of the “Singularity” movement, which expects similar results. To Amodei’s credit, he acknowledges that such developments would require “a huge effort in global health, philanthropy, [and] political advocacy,” which he posits will occur because it’s in the world’s best economic interest.

That would be a dramatic change in human behavior if so, given people have shown time and again that their primary interest is in what benefits them in the shorter term. (Deforestation is but one example among thousands.) It’s also worth noting that many of the workers responsible for labeling the datasets used to train AI are paid far below minimum wage while their employers reap tens of millions — or hundreds of millions — in capital from the results.

Amodei touches, briefly, on the dangers of AI to civil society, proposing that a coalition of democracies secure AI’s supply chain and block adversaries who intend to use AI toward harmful ends from the means of powerful AI production (semiconductors, etc.). In the same breath, he suggests that AI, in the right hands, could be used to “undermine repressive governments” and even reduce bias in the legal system. (AI has historically exacerbated biases in the legal system.)

“A truly mature and successful implementation of AI has the potential to reduce bias and be fairer for everyone,” Amodei writes.

So, if AI takes over every conceivable job and does it better and faster, won’t that leave humans in a lurch economically speaking? Amodei admits that, yes, it would, and that at that point, society would have to have conversations about “how the economy should be organized.”

But he offers no solution.

“People do want a sense of accomplishment, even a sense of competition, and in a post-AI world it will be perfectly possible to spend years attempting some very difficult task with a complex strategy, similar to what people do today when they embark on research projects, try to become Hollywood actors, or found companies,” he writes. “The facts that (a) an AI somewhere could in principle do this task better, and (b) this task is no longer an economically rewarded element of a global economy, don’t seem to me to matter very much.”

Amodei advances the notion, in wrapping up, that AI is simply a technological accelerator — that humans naturally trend toward “rule of law, democracy, and Enlightenment values.” But in doing so, he ignores AI’s many costs. AI is projected to have — is already having — an enormous environmental impact. And it’s creating inequality. Nobel Prize-winning economist Joseph Stiglitz and others have noted the labor disruptions caused by AI could further concentrate wealth in the hands of companies and leave workers more powerless than ever.

These companies include Anthropic, as loath as Amodei is to admit it. Anthropic is a business, after all — one reportedly worth close to $40 billion. And those benefiting from its AI tech are, by and large, corporations whose only responsibility is to boost returns to shareholders, not better humanity.

A cynic might question the essay’s timing, in fact, given that Anthropic is said to be in the process of raising billions of dollars in venture funds. OpenAI CEO Sam Altman published a similarly technopotimist manifesto shortly before OpenAI closed a $6.5 billion funding round. Perhaps it’s a coincidence.

Then again, Amodei isn’t a philanthropist. Like any CEO, he has a product to pitch. It just so happens that his product is going to “save the world” — and those who think otherwise risk being left behind. Or so he’d have you believe.

Anthropic looks to fund a new, more comprehensive generation of AI benchmarks


Anthropic is launching a program to fund the development of new types of benchmarks capable of evaluating the performance and impact of AI models, including generative models like its own Claude.

Unveiled on Monday, Anthropic’s program will dole out payments to third-party organizations that can, as the company puts it in a blog post, “effectively measure advanced capabilities in AI models.” Those interested can submit applications to be evaluated on a rolling basis.

“Our investment in these evaluations is intended to elevate the entire field of AI safety, providing valuable tools that benefit the whole ecosystem,” Anthropic wrote on its official blog. “Developing high-quality, safety-relevant evaluations remains challenging, and the demand is outpacing the supply.”

As we’ve highlighted before, AI has a benchmarking problem. The most commonly cited benchmarks for AI today do a poor job of capturing how the average person actually uses the systems being tested. There are also questions as to whether some benchmarks, particularly those released before the dawn of modern generative AI, even measure what they purport to measure, given their age.

The very-high-level, harder-than-it-sounds solution Anthropic is proposing is creating challenging benchmarks with a focus on AI security and societal implications via new tools, infrastructure and methods.

The company calls specifically for tests that assess a model’s ability to accomplish tasks like carrying out cyberattacks, “enhance” weapons of mass destruction (e.g. nuclear weapons) and manipulate or deceive people (e.g. through deepfakes or misinformation). For AI risks pertaining to national security and defense, Anthropic says it’s committed to developing an “early warning system” of sorts for identifying and assessing risks, although it doesn’t reveal in the blog post what such a system might entail.

Anthropic also says it intends its new program to support research into benchmarks and “end-to-end” tasks that probe AI’s potential for aiding in scientific study, conversing in multiple languages and mitigating ingrained biases, as well as self-censoring toxicity.

To achieve all this, Anthropic envisions new platforms that allow subject-matter experts to develop their own evaluations and large-scale trials of models involving “thousands” of users. The company says it’s hired a full-time coordinator for the program and that it might purchase or expand projects it believes have the potential to scale.

“We offer a range of funding options tailored to the needs and stage of each project,” Anthropic writes in the post, though an Anthropic spokesperson declined to provide any further details about those options. “Teams will have the opportunity to interact directly with Anthropic’s domain experts from the frontier red team, fine-tuning, trust and safety and other relevant teams.”

Anthropic’s effort to support new AI benchmarks is a laudable one — assuming, of course, there’s sufficient cash and manpower behind it. But given the company’s commercial ambitions in the AI race, it might be a tough one to completely trust.

In the blog post, Anthropic is rather transparent about the fact that it wants certain evaluations it funds to align with the AI safety classifications it developed (with some input from third parties like the nonprofit AI research org METR). That’s well within the company’s prerogative. But it may also force applicants to the program into accepting definitions of “safe” or “risky” AI that they might not agree with.

A portion of the AI community is also likely to take issue with Anthropic’s references to “catastrophic” and “deceptive” AI risks, like nuclear weapons risks. Many experts say there’s little evidence to suggest AI as we know it will gain world-ending, human-outsmarting capabilities anytime soon, if ever. Claims of imminent “superintelligence” serve only to draw attention away from the pressing AI regulatory issues of the day, like AI’s hallucinatory tendencies, these experts add.

In its post, Anthropic writes that it hopes its program will serve as “a catalyst for progress towards a future where comprehensive AI evaluation is an industry standard.” That’s a mission the many open, corporate-unaffiliated efforts to create better AI benchmarks can identify with. But it remains to be seen whether those efforts are willing to join forces with an AI vendor whose loyalty ultimately lies with shareholders.