1. Pentagon Designates Anthropic a Supply-Chain Risk After Military AI Standoff "We don't need it, we don't want it, and will not do business with them again.

2. Three Rivals, One Cap Table: OpenAI's $110B Round Rewires AI's Alliance Map SoftBank committed $30 billion. Nvidia committed $30 billion. Amazon committed $50 billion.

3. Max Woolf Documented Every Step of His Conversion from AI Coding Skeptic Max Woolf decided to port Python's scikit-learn to Rust using a coding agent. Six months earlier, he wouldn't have trusted one to write a YouTube metadata scraper.

In Brief

• Anthropic Offers Free Claude Max to Open-Source Maintainers Anthropic now gives its $200/month Claude Max 20x plan at no cost to qualifying open-source maintainers for six months. Eligibility requires maintaining a public repo with 5,000+ GitHub stars or 1M+ monthly NPM downloads, with active commits or reviews in the past three months. Simon Willison

• Professional Go Players Are Rethinking Strategy Because of AI South Korea's top Go professionals have absorbed AI-derived tactics into their play, altering centuries-old strategic intuitions. The Korea Baduk Association, the sport's governing body, has watched training rooms shift from pure human study to hybrid sessions where players drill AI-suggested moves. MIT Technology Review

• DualPath Fixes the KV-Cache Bottleneck Slowing Agentic LLM Inference Multi-turn agentic inference spends most of its time loading KV-Cache from storage, not computing. DualPath rebalances the load by routing cache traffic through idle decoding-engine NICs, breaking the bandwidth asymmetry in disaggregated architectures. Hugging Face Papers

• Solaris Builds a Multiplayer Video World Model Inside Minecraft Existing video world models handle only single-agent views. Solaris generates consistent multi-view observations across multiple players using an automated data-collection pipeline built on Minecraft's multiplayer infrastructure. Hugging Face Papers

• MediX-R1 Trains Medical Vision-Language Models With Open-Ended RL MediX-R1 replaces multiple-choice evaluation with free-form medical answers, using group-based reinforcement learning and a composite reward combining LLM accuracy judgments with medical-embedding similarity scores. The framework fine-tunes a vision-language backbone for clinically grounded reasoning. Hugging Face Papers

• GUI-Libra Narrows the Gap Between Open-Source and Closed-Source GUI Agents Open-source GUI agents underperform proprietary systems on long-horizon navigation tasks. GUI-Libra addresses this with action-aware supervised fine-tuning and a partially verifiable RL method that handles steps where correctness cannot be automatically checked. Hugging Face Papers

• MolHIT Improves Molecular Graph Generation for Drug Discovery Graph-based diffusion models for molecular generation suffer from low chemical validity. MolHIT uses hierarchical discrete diffusion to generate 2D molecular graphs that meet validity and property constraints better than existing graph and sequence-based approaches. Hugging Face Papers

• Sphere Encoder Generates Images in One Forward Pass, Rivals Multi-Step Diffusion The Sphere Encoder maps images uniformly onto a spherical latent space, then decodes random points back into images. Trained only on reconstruction losses, it produces competitive results in under five steps — or a single pass. Hugging Face Papers

• SMTL Framework Swaps Deep Reasoning for Parallel Search in Agentic Systems Deep research agents typically scale by adding reasoning depth, increasing cost and latency. Search More, Think Less replaces sequential reasoning chains with parallel evidence retrieval, targeting both efficiency and cross-domain generalization. Hugging Face Papers

• OmniGAIA Benchmarks AI Agents Across Vision, Audio, and Language Together Most multimodal LLM benchmarks test only two modalities at a time. OmniGAIA evaluates agents on tasks requiring simultaneous vision, audio, and language perception combined with reasoning and tool use. Hugging Face Papers

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