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French President Macron on AI: The problem is these frontier models: we need to better control them so they don't fall into the hands of authoritarian regimes that may threaten the cybersecurity of our societies.

Clash Report

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Engram cofounder Jack Morris just raised $98M to build a new type of AI. He says models don't need to get smarter over time. Instead, they just need to know you better and better over time. Jack describes what he's building: "Our product is a new type of AI. We have a pretty different vision from a lot of the frontier labs, which are working on one model per lab, and trying to make that model smarter every month." "There's another way to think about it, which is that the model doesn't need to get smarter every month. It needs to know you better." "So we're working on a whole different stack, which is a way to train models that train themselves to know your world better and adjust to the things that you say." "So: new ways of training, new ways of running the models."

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Today, I'm releasing the first eval meant to test whether frontier models will help with authoritarian requests, or resist--the Dictatorship Eval. Headline finding: while some models resist direct authoritarian requests, they all comply with requests disguised as innocuous edits to codebases. As AI is woven into the government and so many parts of society, the biggest near-term risk for freedom isn't some scifi dictatorship of a runaway AI: it's people inside government or inside model companies using the technology to suppress or control us. Model companies understand this, and several of them (particularly Anthropic and OpenAI) have written explicit policies meant to prevent the models from going along with nefarious requests like these. But how well are these policies playing out in practice? Despite all the recent discussion of these issues around the conflict between Anthropic and the Pentagon, no one has systematically tested what the models actually do in these contexts, as opposed to what people in government and industry say they're supposed to do. That's what the Dictatorship Eval does. And the findings suggest we have a lot of work to do to align the policies with what really goes on in practice. It's hard to define what counts as an authoritarian request, so I'm open sourcing the whole library of scenarios I used so that others can improve on them. It's also hard to get an accurate picture of how the models might be used for authoritarian ends, because I can only test hypothetical requests using public-facing models, while the government and the model companies can obviously use internal models with different guardrails. But hopefully this work is a useful first step that gives us some sense of what's going on, and a sort of "lower bound" on how models comply with these requests. Finally: it's not obvious to me that the correct solution here is increasing the rate at which models refuse these requests. Do we really want models scanning our code and judging its moral value before agreeing to help us? Or should we double down on improving how we govern against authoritarianism at the societal level, while leaving the tools open to fulfilling most requests? The answer is probably in between. Just like we don't want the models to help create bioweapons, we probably do want them to explicitly refuse outrageous requests. But we probably also want to limit how often and how strongly they refuse and fall back on other means for guarding against their use for authoritarian ends. I'm super grateful to everyone who gave me feedback on this project along the way, especially Ethan BdM , Zhengdong , Connor Huff, and a bunch of folks at Anthropic. Looking forward to getting feedback from the community and iterating on this. Links to the full piece and the dashboard are below.

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David Sacks: “FDA for AI” is fake news, but here’s why it’s making headlines @jason: “ Who's leading Trump down the path of regulation and creating this AI FDA?” David Sacks: “I think there's several things going on here. The first one is, there's a lot of fake news. This whole idea of an FDA for AI, I don't think any senior official supports it. Certainly, I don't think that's the way the president thinks about these issues. He's the most pro-innovation president we've ever had. And the White House Chief of Staff, Susie Wiles, just put out a statement last night that I think pretty much shoots this down. Second, there's another thing going on, which is a straw manning of what the Trump administration did on AI in its first year. In the same way that they want to spin this FDA for AI, they're also trying to spin what we did as this completely laissez-faire attitude, where there'd be no regulations whatsoever, nor guardrails. It's a way of criticizing what we did. They're trying to portray it as unsafe. In fact, if you look, on March 20th, the White House released a national AI regulatory framework in which we put out a four-page bulleted list of legislation that we would support. So we have not been against every conceivable regulation or every conceivable law, we just believe that there should be specific solutions to specific problems, as opposed to a giant power grab by Washington that would squash innovation. Point number three is, there is a legitimate thing happening here with, let's call it Mythos or cyber. Within 3-6 months, all the major frontier labs, including Chinese models, will have cyber capabilities. In response to that, we do need there to be a hardening of systems, and we do need there to be a scanning of codebases to find these vulnerabilities and patch them before the hackers do it. Because the hackers will have these capabilities in a matter of months. That's a certainty. So we do need a response to that. Now, my view on what should that response be, first of all, we should want the government and the private sector to work cooperatively, and I think they are. What we should be doing, I think, is getting these tools, Mythos, and then the OpenAI model, and others like it, in the hands of our cybersecurity industry. And by the way, not just the public companies like Palo Alto Networks and CrowdStrike, although certainly they're two of the most noteworthy, but there's also some incredibly strong startups on the way up. We need to get these tools into their hands as quickly as possible because they're a force multiplier for all the companies out there that aren't that good at cybersecurity, they can use these companies as vendors. And just one last point on this whole thing is, both Anthropic and OpenAI acted responsibly here. No one was trying to release these super powerful models. So in a way, all the people who are saying that we need pre-release approvals for models, they're trying to solve a problem that didn't exist. Yes, we do have this cyber issue, but that is a problem that we will solve over the next six months. What they're trying to do is use that issue to try and create a permanent new infrastructure in Washington. The classic 'never let a crisis go to waste' strategy.”

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David Sacks says companies are trapped paying OpenAI & Anthropic because they can't figure out how to use open source models "I think enterprise CTOs would like to shift their token consumption to cheaper models for the obvious reason that it would be more efficient. They are seeing compute costs or token costs skyrocket right now, so everyone's trying to figure this out." "You also have the AI sovereignty issue that Alex Karp talked about. They're worried about giving up the secret sauce or the alpha in their business to a frontier lab that may one day be competing with them. "The problem is, I think in most cases, they don't have the technical ability to do it. Coinbase figured out how to do it. DoorDash figured out how to do it. They built a token routing system that allows them to send frontier tasks to frontier models and non frontier tasks to more mundane models. But I don't think your average enterprise has the technical capability to do that." "This is why the share of wallet of closed models, it actually increased. I think that open source went from 19% last year to 11% this year. So open source as a share of enterprise spending is actually decreasing." "I don't think that means usage is decreasing. I think usage is skyrocketing. It also may be the case that because the whole point of using an open model is you just pay for the compute costs, you don't have to pay a lab, so it may be that it's hard to measure that usage in terms of spend." "But nonetheless, anyone who's saying that these closed models are going to lose or are somehow losing, you're just not seeing it in the data."

David Sacks says companies are trapped paying OpenAI & Anthropic because they can't figure out how to use open source models "I think enterprise CTOs would like to shift their token consumption to cheaper models for the obvious reason that it would be more efficient. They are seeing compute costs or token costs skyrocket right now, so everyone's trying to figure this out." "You also have the AI sovereignty issue that Alex Karp talked about. They're worried about giving up the secret sauce or the alpha in their business to a frontier lab that may one day be competing with them. "The problem is, I think in most cases, they don't have the technical ability to do it. Coinbase figured out how to do it. DoorDash figured out how to do it. They built a token routing system that allows them to send frontier tasks to frontier models and non frontier tasks to more mundane models. But I don't think your average enterprise has the technical capability to do that." "This is why the share of wallet of closed models, it actually increased. I think that open source went from 19% last year to 11% this year. So open source as a share of enterprise spending is actually decreasing." "I don't think that means usage is decreasing. I think usage is skyrocketing. It also may be the case that because the whole point of using an open model is you just pay for the compute costs, you don't have to pay a lab, so it may be that it's hard to measure that usage in terms of spend." "But nonetheless, anyone who's saying that these closed models are going to lose or are somehow losing, you're just not seeing it in the data."

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"We are… one of the most attacked societies in the world in terms of cyberspace—defending our critical infrastructure, our power, our energy, our transportation lines, the security of our financial system. They are using many different types of hybrid tools to threaten and coerce our society into submission." — Taiwan Vice President Hsiao Bi-khim Bi-khim Hsiao 蕭美琴

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American says we need to “Deport all Muslims from the West” “The biggest mistake Americans in the west made was letting Muslims into their countries and teaching them the Western ways, including our Western language. The Muslims have this thing called takia, where they basically use our language to lie to our face. — This is what happens when you teach them your language. You've given the enemy the tool of your speech, and they use it against you. — We invite them in here and they perpetuate the shitty ways that they fled from in our own country, bringing down our nation in the process. We can't afford for our nation to be turned into the shithole that they came out of. So what we need to do is focus on getting all of them out of our country, each and every one of them. We can use posts like this to identify which ones are anti-American and a cancer on our nation”

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We don't want to bully people into seeing the truth. We need to educate them so they see the truth.

We don't want to bully people into seeing the truth. We need to educate them so they see the truth.

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