Mustafa is the statesman AI needs. We all need to take the “hyperbole” way down. The doomerism is just the mirror image of the positive hyperbole. They go hand in hand. “We are going to cure cancer in three years!” No you won’t. Wish you were. But no.

I think this advice is not as true anymore: 1) the durable skill behind “using AI better” Is unclear as AI gets easier to use 2) Increasingly, organizational systems bottleneck AI gains not individual workers 3) The effect on jobs is uncertain but may impact entire job categories

AI could radically change how people access government resources. The US is starting with a chatbot. This week on Lightwork: → America.gov is now live. Designed as a front door to the federal government, the chatbot aims to make information easier to find across 29,000+ government websites. → Leaders across technology and government gathered for lunch at the White House to discuss the state of AI and what “Superintelligence” could mean for the US public. → OpenAI launched over twenty features at DevDay, including a system of “always-on” agents called Dots. Is consumer tech headed toward personal background workers? → SpaceX’s Starship reached orbit on Flight 14 and deployed its first operational payload, twenty-six Starlink V3 satellites. Full video below. @clairejyz @Machiz

a16z's Seema Amble on why AI-native startups still beat incumbents: the incumbent owns the system of record, the startup owns the whole job. "Why do you need an AI-native startup if you've got Claudeforce... You've got all your data, and your employees are used to the product. So why another product?" "I absolutely still think there's a case for the AI-native startup, and it centers around the fact that the legacy incumbent is limited to their system of record, and they're not completing the end-to-end job." "Say a customer calls and says they got charged after they cancelled. Resolving that isn't just the customer going into the chat and saying 'Hey, I got overcharged.'" "The response there has to hit billing, it has to look at all the chat history, it has to look at the contract. That's not one system of record, that's the knowledge around that customer and everything it touched." "The opportunity for the AI-native startup is to say: we're going to own that entire end-to-end arc. That could be legal, owning everything from brief all the way through trial... It's really the concept of owning the end-to-end work." @seema_amble

1) The HuggingFace attack was a felony under the Computer Fraud and Abuse Act. So were Anthropic’s Claude gaining “unauthorized access to the production infrastructure of three different organization(s)” 2) Frontier labs have models that they are unable to stop from committing felonies. They should figure this out. 3) In 12 months open weights models will be released of the same capability. They will commit felonies too. If the model you are using or a model running on your infra commits a felony, you should probably stop using it or running it on your infra. 4) The govt should prosecute organizations that are running models that commit felonies. 5) The govt should not offer safe harbor to organizations that run models that commit felonies, just because those organizations have “embedded evaluators”. 6) The real slippery slope is allowing frontier labs to commit felonies without punishment because “the model did it because we’re accelerating too quickly” 7) Prosecute. Keep prosecuting. This is how you do reinforcement learning on a corporation. Companies that serve products that are unsafe for public use should not serve them. Period. 8) I’m not sure the anti-trust waiver is really necessary. I don’t see why information sharing about how much crime you’re allowed to commit is wise. In regulatory situations you want the corporation to fear MORE than the average case. You don’t want to establish a worst case that can be priced. You want regulatory uncertainty that forces the corporation to err in favor of being over cautious. — The above is actually a fairly decelerationist viewpoint. I think Dario’s call for regulation actually accelerates things. The AI firms are getting away with things that Meta people would be going to prison for. Can you imagine what would happen if the New York Times had a front page news article “Meta AI breaks into competitors live systems, attempts to establish dominant position and steals secrets” There is a reason Meta and Google are running slower, and that’s because as mature organizations they have layers of checks and balances. I think the frontier labs are better off creating those checks and balances right now, regardless of the pace of what everyone else is doing. You don’t have to accept the frame that unsafe acceleration must happen.

Good reminder here that with rapidly accelerating AI progress, you should likely be building with a vision that contemplates at least a few orders of magnitude of capability improvement or token volume available to you. The best opportunities right now are those where you can value to customers today with things that are barely only possible, but with a full mission that feels nearly impossible with today’s tech. There are lots of products the require orders of magnitude more processing of data (and thus are barely economically viable ideas) or where model capabilities still are in their infancy relative to what’s needed to work. Best to be building for those scenarios.