
Tool Blindness, Tree Search, and the Road to ASI
Three new papers expose a 50-point gap in agent tool knowledge, show tree search tripling inference throughput, and map the research between AGI and superintelligence.
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Three new papers expose a 50-point gap in agent tool knowledge, show tree search tripling inference throughput, and map the research between AGI and superintelligence.

DiffusionGemma 26B is Google DeepMind's open-weight discrete diffusion language model that generates 256 tokens in parallel, reaching 1,100+ tokens/sec on H100 - roughly 4x faster than autoregressive models of the same size.

OpenAI published its first public compliance framework mapping internal safety practices to California's SB 53 and the EU AI Act - but critics note the underlying Preparedness Framework quietly dropped manipulation from its risk categories last April.

Google's Gemini 3.5 Flash is genuinely fast at 289 tok/s and competitive on agentic tasks - but the benchmark portfolio has gaps worth knowing before you build on it.

Google DeepMind's fastest frontier model, hitting 76.2% on Terminal-Bench 2.1 and 289 tok/s, now powering AI Mode in Search for over 1 billion monthly users.

Google DeepMind's May 2026 AlphaEvolve impact report shows the system running in production across infrastructure, quantum computing, genomics, and commercial partnerships spanning logistics to fintech.

David Silver, creator of AlphaGo and AlphaZero, closed a $1.1B seed round for Ineffable Intelligence - a London lab building AI that learns without human data.

Google's Gemini 3.1 Flash TTS ships in preview with 30 voices, 70-plus languages, 200-plus inline audio tags, and Elo 1,211 on the Artificial Analysis TTS Arena.

Google DeepMind's Veo 3.1 generates 4K video with native audio and is now free for every Google account at 10 clips per month via Google Vids.

Google DeepMind's Gemini Robotics-ER 1.6 hits 93% accuracy reading industrial gauges via agentic vision, a 70-point jump over ER 1.5, and launches inside Boston Dynamics' Spot today.

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.