AI Briefing — Tuesday, June 30, 2026
What mattered in AI on Tuesday, June 30, 2026 — curated from 15+ sources.
Top stories
The DeepMind trio who built a poker AI are now making money for quant hedge funds
EquiLibre Technologies, a Prague-based AI lab founded by three ex-DeepMind researchers, is now valued at more than $500 million.
New attack provides one more reason why AI browsers are a bad idea
Telling an LLM that 2 + 2 = 5 is enough to make it follow forbidden instructions.
Google introduces a faster, cheaper image generator with Nano Banana 2 Lite
Google is updating its image generator to make it faster and cheaper, making it a more useful tool for creators looking to make AI content.
ScarfBench: Benchmarking AI Agents for Enterprise Java Framework Migration
Nvidia competitor Etched hits $5B valuation, $1B in sales for AI chip
Nvidia AI chip competitor Etched says it has already booked $1 billion under contract for the inference systems powered by its chip.
Anthropic launches Claude Sonnet 5 as a cheaper way to run agents
Anthropic’s Claude Sonnet 5 brings stronger agentic capabilities, lower pricing, and improved safety, positioning the model as a cheaper alternative to Opus, GPT-5.5, and Gemini Pro.
Claude Sonnet 5
Claude Science
Anthropic’s Claude Science bets on workflow, not a new model, to win over scientists
Anthropic's Claude Science is a workbench that gives scientists one environment to do computational research, saving them from the need to bounce between databases, pipelines, and tools.
Deep dives worth reading
ScarfBench: Benchmarking AI Agents for Enterprise Java Framework Migration
Why Specialization Is Inevitable
Featuring Every Eval Ever Results on Hugging Face Model Pages
DiScoFormer: One transformer for density and score, across distributions
Run a vLLM Server on HF Jobs in One Command
Research paper of the day
VLK: Learning Humanoid Loco-Manipulation from Synthetic Interactions in Reconstructed Scenes
Perception-based humanoid loco-manipulation requires connecting egocentric observations and task instructions to whole-body motion. Learning this mapping requires synchronized egocentric images, language commands, and r…
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