NERVOSYS

"New AI models should pass rigorous safety tests before being released to the public... including by experts in government. It has to happen fast. I would target 2025, 2026... or we're gonna have a very bad time." Dario in 2023. Guess what happened in 2026.

This is a new paradigm for interacting with Claude that is significantly more "inline" with all the other human activity org-wide. Once you do all of the under the hood engineering work to make this "just work" (e.g. across tools, integrations, compute environments, memory, security, etc.), Claude basically joins the team in a seamless way - you can talk to it as you would talk to a person and it can help with a very large variety of workloads. Imo this is the 3rd major redesign of LLM UIUX. The first paradigm was that the LLM is a website you go to, the second was that it is an app you download to your computer. This third one is that it is a self-contained, persistent, asynchronous entity with org-wide tools and context, working alongside teams of humans. It really takes a while to wrap your head around it, but it works and it is awesome.

Right now, when you send a query to an LLM, it gets decrypted on the server. The LLM sees your data in plain text. Prof. Ajay Joshi (BU, @CipherSonicAI ) on fully homomorphic encryption, which may be key for the future of AI privacy: how we can compute on data without ever decrypting it. The catch: it's a brutally memory-bound workload. Exactly the bottleneck wafer-scale was built to solve.

AI is not ready for a boom like this.