Super proud to win the 2026 mvp THOR award for the Geneva High School freshman team tonight at the end of year celebration. There was only one award given out on each of the Freshman, Sophmore and JV teams. The award is an MVP award that stands not only for your stats but also for your personal characteristics. THOR stands for Teammate, Honor, Optimistic and Relentless in your pursuit of Goals. This one is special!!!  @TXBaseballRanch @fastballusa @TEAMELITENATION @TeamEliteIL @PrepBaseballIL @TopPreps @GenVikBaseball @K25_Baseball @NBaldassano @jared_liebelt18 @TXBaseballRanch @Loco4life35 @prospectdugout @PipelineRank

Super excited to announce seven new world-class MAI models today. They represent what we consider a new era in AI designed to keep you in control and on the frontier. First is our text foundation model, MAI-Thinking-1, exceptionally strong on reasoning and SWE tasks. - It’s a 35B active parameter MoE with a 256K context window. Independent human raters on Surge prefer it for overall quality in blind side-by-sides versus Sonnet 4.6, and it’s achieved 97% on AIME 2025, the key measure of its general-purpose reasoning abilities. - It's at 53% on SWE Bench Pro, placing it right alongside Opus 4.6 on one of the toughest coding benchmarks. - And since we co-designed our models with our own silicon, MAI-Thinking-1 is optimized on our MAIA 200 chip. Benchmarking head-to-head against the GB200, we see 30% better performance per dollar as well as a 1.4x performance-per-watt gain when running our MAI models on the MAIA 200 end-to-end. Next is MAI-Image-2.5 and its Flash variant. Two super strong models now at #2# on the leaderboards, surpassing the score of Nano Banana 2 on image editing. Last for now is MAI-Code-1-Flash, our new inference efficient coding model, especially tuned for VS Code and GitHub Copilot CLI. - Code-1-Flash achieves 51% on SWE Bench Pro, despite having just 5B parameters, putting it closer to Haiku in size but cheaper in cost. All of this is the foundation for Microsoft Frontier Tuning. It lets you customize our models to create custom, company-specific agents that only you control. You can make our model, your model. Your data. Your agents. Your moat. Early adopters are already seeing a difference. When we tuned our models for McKinsey’s tasks, MAI delivered the highest win rate, outperforming GPT-5.5 on quality, while being 10x lower on cost. Also really excited to be collaborating with the amazing team at Mayo Clinic to jointly train a new frontier AI model for healthcare. Our announcements today mark another milestone on the road to humanist superintelligence. You can learn more and about our other new models in our latest blog:

Super interesting story that shows how the current state of @github is unable to protect open source maintainers from AI spam at any meaningful scale. @archestra_ai put up a $900 GitHub bounty. AI accounts blew the issue up to 253 comments and proceeded to flood the entire repo with untested PRs. Their fix was a contributor whitelist hack: go through and pass onboarding, then a GitHub Action authors a commit as you so GitHub lets you back in. GitHub needs better anti-bot and anti-spam mechanisms so people don't have to build these types of mechanisms themselves.