I'm delighted to share that @mustafasuleyman, CEO of Microsoft AI, co-founder of Google DeepMind and Inflection AI, has signed the Pro-Human AI Declaration. If you too support it, please join him and over a million others by signing it here – the momentum is building! Let's build tools not beings & keep humans in charge. https://humanstatement.org

All-In Summit: Microsoft CEO Satya Nadella -- The AI Doomer Slowdown -- Common Sense AI Guardrails -- What "Slowdown" Means for New AI Products -- Microsoft’s Master Plan -- Who Wins AI (0:00) @satyanadella joins The Besties! (0:55) Dario's blog, "pacing the frontier," common sense AI safety (6:28) The failure of AI CEO messaging, monitoring agents, what will a slowdown mean for new AI products? (14:22) Economic incentives for frontier lab doomerism, where the AI profits are (22:45) Microsoft's master plan for AI, how they are allocating capital (31:00) China's slow down, changing AI perception, data center benefits $MSFT

Any pursuit of superintelligence has to be grounded in the core principle that if the AI we build is not helping humanity and under human control, it's not worth pursuing. We also need to accelerate and spread the benefits of AI, such that they are diffused broadly across countries, communities, and companies. This requires a frontier ecosystem in which both closed and open-source models can thrive. And for firms, it’s imperative that they retain full control over their unique and tacit knowledge. Every organization should be able to build its own continuous learning loop/hill climbing machine, without becoming dependent on any one model provider, and have the ability to embed its own knowledge into models and weights they control. So, in this context, we welcome the research, focus, and deliberate pacing needed to get alignment right as the design goal. We also welcome ideas like "embedded evaluators" and the broader efforts to develop the mechanisms to make this more than just talk. The key is that this cannot be controlled by a handful of entities, but must have broad representation across the ecosystem, countries, and fields, including academia. This is the approach we are taking: broad access and choice at every layer of the AI stack; enterprise control of learning loops and models; and the “Code of Conduct” that underlies our own first party MAI models that we’ll publish tomorrow for public consultation.