Introducing Gemini 4 Argon, our new frontier model, rolling out to cyber defenders starting today, and more widely as soon as possible. I am really excited by the progress we have made here. Argon is priced at $2 in and $10 out during introductory pricing!

Lots of discussion out there about our next model(!), so I wanted to give an early look as soon as possible. Introducing Gemini 4 Argon! It shows frontier performance in complex workflows, cyber defense and software engineering. Teams are using it extensively at Google, from coding to quantum computing, great feedback. Here’s a look at the benchmarks:

Can we have a data quality index (DQI) just like how we have air, water, power and food quality indices? Everyone understands the importance of data, Is not a DQI badly needed?

After 10 incredible years at Google, I've left @GoogleDeepMind to join @thematthewosman and @FabioZB_I at Polyphron as a co-founder and explore the next frontier in my research passions. Together, we're training frontier models that autonomously explore, understand, and physically reproduce human tissue biology. It's our grand vision to grow tissues realistic enough to match human response to all drugs, and realistic enough to recover organ function when transplanted into living organisms. Other than the bitter lesson, I think another lesson remains true in the history of ML: the more directly you can optimize your end goal, the better your outcome will be. IMO this is one lesson largely missed in the drug discovery and computational biology space today, and one that Matt and Fabio understood very clearly (and why I joined them on this journey!). At the heart of our company is one giant RL problem: propose a recipe to grow tissue, sample life itself, reward directly against the functionality of the tissue. If this sounds exciting to you as either an AI or Life scientist, feel free to reach out! We're building the coolest lab in NYC :) I'll never forget all of the {pretraining, RL, self-improvement} projects I worked on with my brilliant friends at GDM over the years, but I'm even more excited to share the things we discover next! (p.s. this isn’t the first time i RL’d something based off of similarity, iykyk)

We’re sharing a solution to the Navier-Stokes Millennium Prize Problem, one of the deepest problems at the frontier of mathematics. The proof was produced by a group of agents, using an OpenAI next-generation model significantly more capable than GPT-6 Astra. The problem concerns whether the description of smooth three-dimensional fluid motion modeled by the Navier-Stokes equations can break down. It has remained unresolved for roughly 90 years.

AlphaGenome Atlas is an interactive resource, mapping the predicted impact of all 9 billion DNA variants. It works in a regular web browser, without any coding required, and is free for academic researchers. Excited for the discoveries to come.