
AI Agent Failures Need Escrow, Not Just Safety Training
Researchers from Google DeepMind, Microsoft, and Columbia propose financial guardrails for AI agents, with simulations showing up to 61% reduction in user losses.

Researchers from Google DeepMind, Microsoft, and Columbia propose financial guardrails for AI agents, with simulations showing up to 61% reduction in user losses.

Gemma 4 is Google DeepMind's most capable open model family: four variants from 2B to 31B, Apache 2.0 license, multimodal across text/image/video/audio, and the 31B Dense ranking #3 on Chatbot Arena against all open-weight models globally.

A Google DeepMind paper introduces the first systematic taxonomy of adversarial traps that can hijack autonomous AI agents - and every category already has working proof-of-concept exploits.

Google's Gemini 3.1 Flash Live beats GPT-4 Realtime 1.5 on Scale AI's Audio MultiChallenge and takes Search Live to 200+ countries - but it doesn't lead every benchmark.

Google invested $1 million in Animaj, an AI animation studio making YouTube kids content, just seven weeks after YouTube CEO Neal Mohan declared war on AI slop - with early access to Veo, Gemini, and Imagen.

Alphabet folds robotics software company Intrinsic into Google after five years as an independent moonshot, giving it access to Gemini models, DeepMind research, and Google Cloud - plus a Foxconn joint venture building AI-driven factories.

Google DeepMind's reasoning mode scores 84.6% on ARC-AGI-2, 3455 Codeforces Elo, and solves 18 previously unsolved research problems - outpacing Claude Opus 4.6 and GPT-5.2 on reasoning-heavy tasks.

Google DeepMind's Nano Banana 2, built on Gemini 3.1 Flash, delivers Pro-quality image generation and editing at twice the speed and half the price, rolling out free to all Gemini users across 141 countries.

Google DeepMind's natively multimodal image generation and editing model built on Gemini 3.1 Flash - Pro-level quality at Flash speed, free for all Gemini users.

AlphaEvolve evolved two novel game theory algorithms - VAD-CFR and SHOR-PSRO - that outperform human-designed baselines across 11 games, using mechanisms no researcher would have designed.

Detailed comparison of Moonshot AI's Kimi K2.5 and Google DeepMind's Gemini 3.1 Pro - a trillion-parameter open MoE against Google's flagship multimodal model.

Comparing Moonshot AI's 1T-parameter Kimi K2.5 with Google DeepMind's Gemma 3 27B - two multimodal open-weight models separated by 37x in parameter count but sharing a vision-first design philosophy.