Google Just Achieved True Intelligence With New AI

Google just fused two opposite training methods into one system — Supervised Reinforcement Learning (SRL) — and made small 7B models earn intelligence with dense, step-wise rewards. In tests on s1K 1.1 and code tasks, SRL beat standard SFT and held up when no rollout was correct. The winning recipe: SRL first, then RLVR. Meanwhile, Gemini 2.0’s multi-agent “AI co-scientist” helped researchers surface drug candidates for liver fibrosis and independently reconstructed a decade-long discovery about phage tail piracy in bacteria—in days. 📩 Brand Deals & Partnerships: me@faiz.mov ✉ General Inquiries: airevolutionofficial@gmail.com 🧠 What You’ll See (sources): Google SRL paper (arXiv): From Expert Trajectories to Step-wise Reasoning https://arxiv.org/pdf/2510.25992 • RLVR background (arXiv): Reinforcement Learning with Verifiable Rewards https://arxiv.org/abs/2506.14245 • Google Research blog: Accelerating scientific breakthroughs with an AI co-scientist https://research.google/blog/accelerating-scientific-breakthroughs-with-an-ai-co-scientist/ • Liver fibrosis study (Advanced Science, DOI): AI-Assisted Drug Re-Purposing for Human Liver Fibrosis https://advanced.onlinelibrary.wiley.com/doi/10.1002/advs.202508751 • PubMed record (Vorinostat details): https://pubmed.ncbi.nlm.nih.gov/40946179/ • Preprint (liver fibrosis): https://www.biorxiv.org/content/10.1101/2025.04.29.651320v1.full-text • Tail piracy explainer (Imperial College news): https://www.imperial.ac.uk/news/268213/microbial-piracy-uncovers-fight-drug-resistant-infections/ • Coverage (GEN / summary with AI angle): https://www.genengnews.com/topics/infectious-diseases/tail-swapping-pirate-phages-expose-new-route-for-amr/ 🚨 Why It Matters: Small AIs can now reason step by step without giant reward models, and multi-agent systems are doing real science—compressing years of discovery into days. This flips the script on scale vs. smarts.