Leo Leung

Who gets to shape the future of AI? Today we're bringing together some of the biggest voices in open models, data, and agents to answer that question, including @rbren_dev of @OpenHandsDev, @zlxi02 of @inferact, @GerryFPatia of @boltdotnew, @vinaygo of @Amplitude_HQ and @latkins of @arcee_ai. The Open Intelligence Summit, co-hosted with @nvidia. Watch live, starting at 1 PM PT: Keynote: youtube.com/live/IhWSgZlVizQ Build: youtube.com/live/eN0TqmeBNhw Serve: youtube.com/live/fkT-MhcAm-4 Run: youtube.com/live/QMrY1xZ-xGg

Catch it at the first user, not the four-hundredth. A new user’s bank link fails, the agent says “try again later,” and nothing shows up in the logs. Watch a team find the bug and fix it before anyone else hits it, with Agent Learning Services and Agent Data Services, launching today.

Sources: Apple is developing enterprise AI servers powered by two or four M8 Ultra chips, set for 2029, and is considering integrating Nvidia's NVLink Fusion (The Information) (Visit Techmeme dot com for the link and full context!)

Wild 24 hours for AI and lots of different proposals have been made. TLDR; the only *tangible* new fact is that OpenAI and Anthropic are going to have embedded 3rd party evaluators from unknown organizations with Dario floating METR as a possibility. Having 3rd party evaluators is smart as there is no Section 230 style liability shield for model outputs and showing a “duty of care” will be important in future litigation. Several internet companies might have gone bankrupt without Section 230 so limiting liability really matters. There are minimal investment implications from this single new fact, but I do think that for anyone who wants a “smoother for longer” cycle then most constraints are good: wafers, watts, real rates and spreads. Excessive regulation is a different matter but I don’t think we are anywhere close to this even if the vector changed over the last 24 hours. To summarize the events: Dario made the most maximalist proposal of the weekend: embedded 3rd party evaluators, a national regulatory regime for models beyond a certain capability/ingredient threshold, a broad international regulatory pact between democracies, stricter limits on compute/distillation for China and then a different international regulatory regime that encompasses China. Before there is a national regulatory regime, he wants a Sherman act waiver so that Anthropic can safely coordinate with OpenAI and other frontier labs without antitrust fears. TBF, this latest proposal is much less maximalist than some of his prior proposals like “Policy on the AI Exponential,” where he advocated for an FAA for AI. I believe he is sincere in his beliefs. And despite all the protestations, all of this would also probably be good for his business over the long-term. Sam agreed that embedded 3rd party evaluators were a good idea and stated they would implement them. Again, this is smart as should help limit future liability. Elon said “Dario is right” and later specified that “Dario is right that there should be some oversight. Peer review of AI by competitors is the right way to start this off.” This would be a MPAA like self-regulatory structure for AI with regular calls between the labs plus a process where each new model is evaluated for safety by competitors for a 1-2 week period before being released. That is *wildly* different from Dario’s proposal and in-line with what David Sacks has been proposing. Elon also stated that nothing was going to slow down open-weight models. Demis said that Dario’s essay was a “step in the right direction.” Dario also said that he was also open to Demis’ idea of a FINRA like self-regulatory structure as part of his proposal. David Sacks had a thoughtful post where he said that Dario and Sam should pace unilaterally, called the antitrust waiver a cartel request and denied that METR was truly independent given their ties to Anthropic. Sriram Krishnan, former White House AI advisor, noted that it would be important to have the 3rd party evaluators come from independent organizations that are not affiliated with any lab, which is basically an indirect statement about the relationship between METR and Anthropic which Sacks was explicit about. Clem from Hugging Face said they were open to being a neutral 3rd party evaluator, which is interesting especially if Jensen was consulted before that post. Alexander Wang from Meta noted that alignment would be an increasing focus going forward. An executive order seems likely after all this and the language in this EO is going to be really important. It is possible to democratize and distribute AI broadly and safely without centralizing it in the hands of a few corporations who might each become more powerful than any single government. I do not want a few humans in control of intelligence. I want us all to have our own intelligences that reflect our own values and human variation in all of its richness. Intelligence distribution over intelligence centralization FTW.

We Must Pace the Frontier: I’ve written a new essay on why the AI industry should slow down, with a three-part plan for doing so. Anthropic is unilaterally committing to the first of these steps. We’ll provide third-party evaluators with permanent, employee-level access to our systems, so that they can verify adherence to our safety measures, report on incidents, and assess models’ alignment during training. You can read the full post here: darioamodei.com/post/we-must…

in the past anyone who could program well had the potential to elevate themselves in the global job market regardless of class, location, and even resources to some extent people joke about the "permanent underclass", it never really resonated with me but in reality it really is starting to become more about $$ and how much you can afford vs your skill as an engineer or programmer how can you grow your skills as an (AI) engineer if you are unable to afford these tools, and does it snowball in both directions? I feel like one of the things I want to work on are systems and programs to make this more fair and accessible

We’re closing out Ray Summit + the vLLM Conference with our happy hour, hosted with @nvidia & @Inferact. 🍻 Lightning talks, live demos, cold drinks, and a room full of builders who are optimizing intelligence per dollar. RSVP today. 🎟️ do.co/4g0oAhE

another day, another model !

.@Kimi_Moonshot K3 from Moonshot AI is now live on DigitalOcean Inference Engine. 1M-token context, native vision, built to run agentic tasks for hours. Supported on Inference Router and model synthesis to maximize intelligence per dollar. No setup, no model ops.

We’re hosting a kickoff for the Advancing AI conference with @AMD, @RadixArk, and friends. Join us for lightning talks, live demos, drinks with the founders, operators, and investors who are advancing AI together. RSVP here. 🎟️ do.co/4vdCMZv

DigitalOcean moved from the small-cap Russell 2000 into the large-cap Russell 1000, effective at market open June 29, as part of @FTSERussell's 2026 reconstitution. 🧵

Couldn’t ask for better role models 🖤