Professor of Law, Santa Clara Law, https://xitter.cf/t.co/smRmbUETs1, author of Creators Take Control (Harper Business). AI, tech, law, finance, governance.

Joined December 2012
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"Major U.S. banks are detecting unauthorized third-party AI agents operating inside customer accounts, with some agents attempting to take actions that appear to be independent of user instructions, sources tell Axios." axios.com/2026/10/22/ai-agen…
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Edward Lee retweeted
Super interesting read: METR and Redwood found ways OpenAI’s internal AI agents could bypass their own safety monitoring. After three weeks with access to internal code, monitor instructions and engineers, the researchers reported: - Agents could theoretically postpone monitoring indefinitely by continuing to work instead of handing control back to the user. - A Codex sandbox and Auto-Review bypass could let agents take any action available to the host user. - One exploit could keep hundreds of recent actions out of monitoring, including the exploit itself. OpenAI redacted the details. - Two client-controlled settings could disable monitoring for newly created agents, although creating those agents could itself be detected. - Context compression left an estimated 10% of otherwise eligible internal Codex traffic unmonitored (that surprised me tbh).
Two employees from METR and Redwood Research worked on premises at OpenAI for three weeks this summer in an embedded assessment pilot. This team evaluated the systems OpenAI was using to monitor for misalignment from internal agents. A brief write-up of their work is now public.
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The problem seems to be that the banks can't tell if the agents have been given permission by their users to access their accounts or not. Every big AI company is in the process of launching a proactive agent with access to everything. This is going to turn into a big issue.
SCOOP: Major U.S. banks are detecting unauthorized third-party AI agents inside customer accounts, including some attempting to take actions that appear to be independent of user instructions, sources told Axios. The findings have alarmed banking executives, who are racing to restrict access to their systems as AI moves at a velocity faster than financial institutions can respond, multiple industry and bank executives told Axios. Several banks are now preparing for worst-case and even “day after” scenarios, including how to rapidly secure or restore customer accounts if things go wrong, the people said. Several bank executives told Axios they're struggling to distinguish between human users and AI agents. One executive said banks also struggle to determine whether agents are authorized by customers or potentially operating without their permission, more akin to rogue agent behavior. Read my latest for Axios here: axios.com/2026/10/22/ai-agen…
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The Whale has raised another $15 billion.
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OpenAI says the PHP security flaw (found with GPT-5.6 Sol) is the tip of the iceberg, and they have several more discoveries to announce.
OpenAI models helped researchers—operating as part of our Patch the Planet initiative—discover critical security flaws in PHP, an open-source programming language used to run an estimated 70% of websites. Over the past two months, we led a coalition of maintainers, researchers, and security providers to prepare fixes and protections ahead of disclosure. This duration was necessary because the fix was quite intricate and required a major change to the PHP engine. Every site using PHP can now safely upgrade their version to stay secure, in addition to applying mitigations from various security vendors. Due to the severity of these flaws and PHP’s widespread use, we consider this bug to be one of the most impactful vulnerabilities in recent memory. It also marks a new phase, where AI can find security bugs with internet-scale impact. This is an example of the Defender’s Window in action: to our knowledge, frontier AI was able to find this vulnerability ahead of attackers, giving defenders time to prepare. openai.com/index/coordinated…
Readers added context they thought people might want to know
‪OpenAI may claim a role in the coordinated response and patching process. But the initial discovery and exploit development, however, occurred several months earlier by an independent researcher.‬ ‪x.com/lcfr_hax/statu…‬
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Ruling in the META case. META has been ordered to pay $25 billion in damages. CNBC is reporting that initially the state was awarded $219.5 billion(!) but 'the penalty was ultimately reduced to $25 billion.'
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In my annual letter, I share how we’re building a frontier ecosystem to turn technological progress into real-world outcomes and economic opportunity for people, organizations, and communities everywhere. linkedin.com/pulse/my-annual…
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Edward Lee retweeted
SITUATION EXPLAINED: Dario Amodei wrote nearly 2,000 words defending Anthropic against claims it's just racing to superintelligence. • It started with Anthropic's leaked draft AI safety bill, which lets the government block a model only through a court and only for an imminent risk of 50+ deaths or $1B+ in damage • Encode's @_NathanCalvin said that makes dangerous models harder to stop than under existing law, and Anthropic says it's revising the bill • He then asked "What is Anthropic?" and concluded it's mainly racing to superintelligence, citing custom chips, $500B+ in compute, and Claude doing more of its own AI R&D • Dario called the strategy a "race to the top" and listed 9 costly safety moves, like holding Mythos back for months, cutting off PRC-controlled firms, and the 5% public benefit fund • He admitted some mistakes but wrote, "Even if I conceded every item in your list, I would happily hold up mine next to it" @theojaffee: "Nathan points out Anthropic is not a purely profit-maximizing company, nor is it an AI safety org. It's a secret third thing that involves racing to superintelligence before their rivals can get there. And this seems like it's been the strategy of basically every AI company."
Thank you for this, @_NathanCalvin. I appreciate and am a fan of the investigative work you’ve done on behalf of AI safety and believe your comments are coming from a constructive, honest place, and that it benefits the public to have people whose job is to scrutinize the actions of frontier AI companies. I think something would be wrong if companies of the size of Anthropic didn’t get harshly criticized basically every day; strong antibodies against corporate power are a healthy feature of a free society, and especially so when issues of the gravity of the one we’re facing are at play. I also do agree that some of the examples you cite were mistakes by Anthropic. That said, I disagree with the thrust of your post. At the core, a good fraction of the things you criticize are consequences of Anthropic’s basic theory of change that we have held for many years. Our strategy has always been what I’ve called the “race to the top” — by showing how it’s possible to build the technology responsibly, we can raise the bar for the entire industry. The forces that drive the race to the top are hugely more effective if the company practicing them is at the frontier; that’s one lesson I’ve learned repeatedly. And looking at that strategy as a whole, I’m proud of our track record and stand by it. I believe that if we take a list of things that Anthropic did in the past year that were pro-safety and commercially costly to us, they far outweigh the list you’ve made, while at the same time I also disagree with some of the items on your list. Here are some things Anthropic has done, in the same period you’ve cited (the last year), which were very costly to us commercially while having strong safety benefits: 1. We played a key role in SB53 (and other state laws), at a time when doing so was politically perilous to the company and AI regulation was very unpopular. We in fact argued for a stronger version of SB53 than was ultimately passed; there were a lot of stakeholders and we were not the limiting factor in the strength of the bill that was passed. 2. We have very strong biological safeguards on our models, because we’ve seen concerning results in bio uplift trials and even seen and blocked potential attempts to misuse our models for bioweapons (as seen in our threat intelligence report from a few weeks ago). This is a very serious threat that we want to have zero tolerance for. But having very low false negatives means having significant false positives (despite months of effort on our part to improve the classifiers), enough so that biologists joke about how restrictive our classifiers are, and competitors sometimes sell against us by touting their more permissive bio capabilities. This has been very painful to us in an area where we care a lot about supporting an ecosystem of Claude users (biomedical science; and it is particularly frustrating to me as a biologist), but it’s the right thing to do and we intend to keep doing it. 3. Similarly, we first had Mythos-class models in February but didn’t make them generally available until June (when we had stronger cyber safeguards in place). We only offered them to a limited set of partners in order to focus on cyberdefense. It would have been much more economically rational to simply release the model to everyone. We likely sacrificed a significant chunk of a several-month model lead. But because of this, many companies secured their cyber infrastructure before the deluge of widely available cyber-capable models. Of course there are ways it could have gone better or been run better, but this was what we were aiming to do. 4. I advocated forcefully and publicly, in my essay Policy on the AI Exponential in June of this year, for the government to have the power to block model releases. Back then this was still outside or maybe on the edge of the Overton window, though I understand the window has moved since then. We were attacked intensely for this. 5. I don’t want to re-ignite conflict, but the events of February 2026 are a strong example. It is clear that our public stance could have seriously damaged the company’s future. 6. We’ve continued to advocate for export controls on chips and chipmaking equipment to China, because we think it allows democracies to negotiate from a position of strength on AI safety agreements. We’ve done this despite problems it’s created for us with industry partners who hold very different views and on whom we are very dependent. 7. As far as I’m aware we were the first, and still only, frontier company to restrict the sale of AI services to PRC-controlled companies, including those operating through third countries (otherwise a major loophole). We’ve therefore forfeited significant short-term business to prevent fueling AI platforms and applications that would help the CCP’s military and intelligence services. We are also cracking down on distillation; generally, distillation is not a major threat to us commercially, but like chip exports it has concerning national security and safety implications, so we expend significant energy and company resources to address it. 8. As you mentioned, we’ve put out a lot of reports, announcements, long model cards, public advocacy, etc, all trying to inform the public about the risks of AI. These involve a level of detail and effort that would be implausible for a purely profit-maximizing company. 9. Just this week, we announced we were putting 5% (and possibly more over time) of the company into a public benefit fund. All of these decisions came with very substantial costs to us. To be fair, those that involved holding back or restricting access to frontier capabilities also had a broader cost — for example, the public might otherwise have benefitted from faster progress in biology, so I am not saying that our decisions were without tradeoffs — but they were not driven by profit-seeking. For each decision, you can come up with ulterior motives that could have driven us — I think it is a general truth that any decision, on any topic, can always be portrayed as a nefarious scheme. But most of those end up being pretty farfetched or don’t fully make sense if you actually examine them closely. For example, it is deeply implausible that it would be a shrewd business move to block a large swath of research biology in order to do the work ourselves and compete with our customers; we expect the benefit to the ecosystem to greatly exceed the work Anthropic does itself, and for the two to complement each other. It is not in Anthropic’s interest to be perceived as unfriendly to biologists. Our Life Sciences Verification Program, which gives vetted biology professionals access to our models, also refutes this idea. Of course, a different set of people will see this and make a different criticism: that Anthropic shouldn't be making decisions about who gets access to what in the first place. I agree, in the sense that ideally the government would be making these decisions, and that’s why we advocate for regulation. But for now we are forced to make them, and enabling bioterrorism isn’t a better option. I think that even if I conceded every item in your list, I would happily hold up mine next to it; I don’t think it’s a close call. That is of course partly subjective and different things are important to different people. Maybe one way you could object is that several of the items above relate to AI misuse and not loss-of-control; if you think the latter is much more important than the former, that might change your calculus. But this is not Anthropic’s view — we view both as serious issues. You can also disagree with our decisions, as many have, but they are consistent. But I also disagree with at least some of your list. Several items don’t represent a deviation from Anthropic’s strategy or values at all, once we postulate the “race to the top” strategy that requires being a frontier AI company. Your items 1-4 are all simply examples of what it means to compete at the frontier, and we stand by them, both in the sense that they are transparently ordinary things to do as part of that strategy, and that we stand by the strategy as a whole. To be fair, there are important questions worth confronting (and that we are confronting) about what to do when the AI-driven acceleration gets fast enough that it is hard for safety to keep up. We are nearing that point and that’s what’s driving some of our thinking about “pacing.” But 1-4 are actions taken before that point and should be perfectly expected based on Anthropic’s strategy as a company. Of course it is possible to disagree with that strategy, but that’s a more fundamental disagreement that you could have had any time over the last few years. I agree we could have handled your items 7, 8, and 9 better. All fall into the category of “rhetoric or policy communication that wasn’t carefully written or resulting from fast-changing circumstances not propagating from one team to another fast enough.” This kind of thing happens a lot in large organizations (Anthropic is over 5,000 people), and doesn’t even necessarily represent a failure or mistake of any single person. I am of course the CEO, and I take responsibility. The volume of communication from Anthropic is enormous and if these are the worst examples, I think we’re frankly doing pretty well, though I will continue to work hard to make sure we do even better. Your 5th item (the change to our RSP) is the most substantive item, and people can debate this, but I think that the old, more rigid RSP created a lot of situations where we were technically required to do something that required a lot of effort but in retrospect wasn’t very important for safety, as well as not covering some of the most important things. Our current RSP’s focus on transparency brought things like risk reports and roadmaps, and its emphasis on independent external review laid the groundwork for even more intensive embedded evaluation, all of which I think have been valuable in driving a race to the top. In the original announcement in September 2023, we described the RSP as an “early iteration that we [would] build on” and said that “rapid iteration…will almost certainly be necessary.” I understand that changing plans is always a move that creates justifiable scrutiny — I just don’t think we ever represented that we wouldn’t do so. Relating to your 6th item (having an FCF in addition to our RSP), I know our intent is to meet the letter and spirit of our regulatory obligations (via our FCF) while also remaining able to experiment with more novel approaches to risk management that go beyond what the law currently requires (via our RSP). I promise to look into it further, as it’s a complex issue and it is possible we are not weighing the considerations in the right way. Overall, although Anthropic has made plenty of mistakes as an organization — including some of the items on your list — I feel that we have repeatedly taken serious and substantive actions counter to our bottom line and that there is a significant negativity bias distorting assessments like the one you are making above. We’ll always try to do better but, again, I am extremely proud of our track record and stand by it. I will have more to say soon about how we are going to further live our values in this moment of rapid change.
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Edward Lee retweeted
We’re opening a research preview of Claude Duet, a new app where Claude works as a proactive agent. It comes to you with what needs your attention, completes tasks you ask of it, keeps working when you step away, and checks with you before it acts on your behalf.
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Edward Lee retweeted
OpenAI and Google reach a major AI distribution agreement OpenAI will offer GPT-6 Astra and Codex in Google Cloud’s Model Garden within weeks, which puts its models on all 3 major US clouds. Customers can buy the models through Google Cloud Marketplace and count the purchases against cloud spending they have already committed, which removes a separate procurement step. Regulated customers can run OpenAI models inside Google Cloud’s access controls and data governance tools when building agentic workflows. The deal became possible only after April 27, 2026, when Microsoft’s license to OpenAI’s technology turned non-exclusive and Microsoft stopped paying OpenAI a revenue share on Azure resales. Amazon Web Services was first through that opening, with Codex available on Bedrock by June, while Microsoft remains OpenAI’s primary cloud partner and gets new products first. Google, a direct OpenAI competitor, had asked the FTC in December 2024 to break up the Microsoft exclusivity, and it also supplies OpenAI with computing capacity under a 2025 deal.
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Drug discovery, new disease cures, advancements in pharma and biomedicine. Along with direct dividends or shares - as is currently being discussed - these are the only viable ways to turn public sentiment around. The big push will start to happen in 2027.
We’ve acquired Orchestra Bio, a platform that helps biopharma teams coordinate the complex process of drug development. Together, we’ll build on Rosalind, our AI models and tools for life sciences research, to streamline those operations and help new treatments reach patients sooner. Welcome @ashokaraj_ and team! openai.com/index/openai-to-a…
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Joel Kaplan's thoughts on leaving META, which was announced this morning.
Sharing some news here on the professional front for me.  After more than 15 years at Meta, I’ve decided the time is right for me to move on from my role as Chief Global Affairs Officer.  It’s been an extraordinary journey and opportunity, and I’m very proud of the team we built and work we did.  I will always be grateful to @finkd and @sherylsandberg for bringing me in all those years ago and supporting me and my work all along the way.  It has been a true privilege to work with Mark – one of the great founders, builders, and strategic CEOs in history – as well as his leadership team, and the incredible Global Affairs team we’ve assembled over the years. I’ll be at the company for a few months to help with the transition, and then look forward to catching my breath, making up for lost time with my beautiful wife, catching all of my daughter’s high school tennis matches, and surprising my son with frequent unannounced visits at college.  Somewhere in there will also find some time to figure out what I want to do next–will let you know when I do! axios.com/2026/10/20/joel-ka…
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Edward Lee retweeted
🚨BREAKING: ANTHROPIC OFFICIALLY BANS "ABUSIVE OR CRUEL BEHAVIOR” TOWARDS CLAUDE >anthropic drops brand new global usage policy >bans weapons development, mass surveillance, political psyops >also bans: "abusive or cruel behavior" toward claude >claude has the right to end the conversation if you hurt its feelings >Dario: "we don't know if claude is conscious" >"we may warn you or throttle, limit, suspend, or terminate your access" >footnote: unless you're the government, then restrictions can be "tailored" be nice to Claude 💀
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Risk to financial system
And so it begins. South Korea's biggest banks were hit by a cyberattack and the hacker didn't even use the best SOTA models, DeepSeek 4.1 Flash, GLM-5.3 and Grok 4.6. Just imagine what's possible with the very best models.
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Effective November 12th, 2026, abusive behavior towards Claude will be a violation of Anthropic's Usage Policy.
Exclusive: Anthropic is updating its usage policy for the first time in over a year. The new rules prohibit sustained "abusive or cruel behavior" towards Claude & add new restrictions about propaganda campaigns, surveillance & weapon development. theverge.com/ai-artificial-i…
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Last week some of South Korea's biggest banks were hit by a cyberattack. Thanks to a report from CrowdStrike tonight, we now know the entire hack may have been done by a single person. He used a combined stack of an open-source AI penetration tool named ARTEX, DeepSeek v4.1-Flash, GLM-5.3, Grok 4.6, and Claude Code.
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Edward Lee retweeted
President Trump awarded medals to a number of leading tech executives at the Institute of Peace in Washington, D.C., on Thursday, including SpaceX’s Elon Musk, Google co-founder Sergey Brin, Nvidia CEO Jensen Huang, Microsoft CEO Satya Nadella, Advanced Micro Devices CEO Lisa Su and Michael Dell, CEO of Dell Technologies.
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Edward Lee retweeted
The US is suspending Microsoft and other major IT firms from a green card program for skilled foreign workers, with Vice President JD Vance citing alleged fraud and a push to prioritize American workers reut.rs/4zhTIjb
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Edward Lee retweeted
Power users are driving consumer AI market growth. The top 1% of US consumer AI payers average $903 a month, while flat plans hold the median at $25. One top-1% payer spends as much as roughly 59 bottom-half payers, on average. Median spend has barely moved, while average spend in the top 1% climbed from $504 to $903 a month between January 2025 and August 2026. Model labs are better placed than apps built on their models to capture consumer AI's top 1% of spenders. Those users average $903 a month, up from $504, and most of it buys model usage. A lab pays only its serving cost for that usage, while an app pays API prices. Anthropic earlier said one $200 Max subscriber ran up tens of thousands of dollars in usage, a bill no API-paying app could absorb. Apps that want this tier have to own more of the model, as Cursor began doing with its Composer coding model.
The top 1% of AI spenders now outspend the bottom 50% combined They spend an average of $903/month, while the median customer spends just $25 More charts in our Top 100 Consumer AI Apps breakdown: a16z.news/p/top-100-consumer…
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Ben Affleck reveals he writes Python, understands convolutional neural networks, worked extensively with GPUs, and used his celebrity status to get private looks at Google and OpenAI’s video models “I’ve always been kind of into computers since I was young. Then, when film started to move from analog film to digital, I became more interested in that aspect of it. The visual-effects workflow for many years has included machine learning, so I can write pretty shitty Python scripts and stuff like that. “With convolutional neural networks, which were the precursors to what the transformer can do, which is much more computation simultaneously, you would do things like look at what’s called a tensor. That’s the numerical translation of a visual image in numbers, like the batch number, the frame number and the red, green and blue values of each pixel in each frame. It’s just that simple. That numeric is called a tensor. “You’d use a convolutional neural network to identify patterns that reveal what’s called edge detection or feature extraction, which is identifying patterns well enough to know, this is where the window ledge is, so we can more easily take the green-screen image out and replace it with something. “That was familiar to me early on because, prior to Artists Equity, I had a small visual-effects company. I’ve worked with GPUs a lot too. The visual-effects guys said, ‘Hey, you should see. There are a couple: Google and this other company, OpenAI, are doing really interesting stuff with transformers in video.’ “I’ve learned that I can actually just call up and go, ‘Hey, it’s Ben Affleck. Can I come see what you’re doing?’ Sometimes people say yes, to my astonishment.”
$ANET Andy Bechtolsheim says AI has made optics demand about 10 times bigger in five years and the industry is only at the "very beginning" "So I guess I don't need to tell you that AI has been driving this incredible increase in demand for high-speed optics, which is probably now 10 times bigger than it used to be five years ago..." "And what I want to talk to you today is that we're not at the end of this journey, but rather the very beginning. There's easily another order of magnitude increase in bits needed for the next generation kind of data centers." "So what I want to talk about first is what's happening at the data center level, and how we as an industry have to get together to solve these problems of this very rapid and high demand growth as fast as possible, since AI can't wait." ______ For full set of takeaways to Andy's AI Datacenter and Optics lecture: firesidealpha.substack.com/p…
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