Daily AI Briefing — February 28, 2026

OpenAI announced a record-shattering $110 billion funding round at an $840 billion valuation, backed by Nvidia, Amazon, and others — cementing its position as the most valuable private tech company in history.

In a major AI policy confrontation, the Trump administration moved to ban Anthropic from U.S. government contracts after the company refused to remove military-use restrictions from its models. Meanwhile, Block (parent of Square and Cash App) announced 4,000 layoffs — nearly half its workforce — explicitly attributing the cuts to AI productivity gains, with shares surging 25%+.

On the technical front:

• ASML declared its High-NA EUV lithography tools production-ready, enabling next-generation AI chip fabrication
• Google released Nano Banana 2 (Gemini 3.1 Flash Image), now the #1 rated image model at half competitor pricing
• Sakana AI introduced Doc-to-LoRA and Text-to-LoRA for single-pass LLM adaptation
• Perplexity released pplx-embed, achieving SOTA on web-scale embedding/retrieval tasks
• Microsoft Research unveiled CORPGEN for managing multi-horizon agent tasks
• Goldman Sachs and Deutsche Bank began testing agentic AI for real-time trade surveillance
• Accenture partnered with Mistral AI to scale sovereign AI across Europe

Today's most impactful work spans AI safety research and a landmark governance crisis between frontier labs and the U.S. military.

• Model Incrimination (MATS 9.0 / Neel Nanda) introduces novel methods to diagnose *why* an LLM misbehaves—distinguishing scheming from sycophancy or capability failures—filling a critical gap in safety evaluation
• Unsupervised Elicitation research (MATS/Anthropic) delivers an important negative result: no existing easy-to-hard generalization technique reliably scales oversight to superhuman models across three realistic challenge settings
• The Dawn of AI Scheming provides the most comprehensive survey to date of empirical evidence on deceptive alignment across model organisms

On governance, Zvi's analysis of the Anthropic–Department of War standoff and Sam Altman's memo aligning OpenAI with Anthropic's red lines on autonomous weapons and mass surveillance represent a potential inflection point for military AI policy. New ARENA exercise sets package frontier interpretability topics (attribution graphs, emergent features) into accessible training material. Abram Demski's Coherent Care advances foundational arguments for Updateless Decision Theory, and a community-built RSP version comparison tool aids timely policy scrutiny.

The AI community was dominated by two seismic stories: OpenAI's unprecedented $110B funding round from Amazon, NVIDIA, and SoftBank, and the heated debate over AI labs refusing US government mass surveillance requests.

• Sam Altman announced the largest private funding round in history, detailing new Amazon partnership for a stateful runtime environment and continued Azure API exclusivity with Microsoft
• Ilya Sutskever praised Anthropic for not backing down on surveillance, warning of harder challenges ahead; Jan Leike sharply framed the government as seeking a new "mass domestic surveillance" supplier
• François Chollet argued AI performance remains fundamentally tied to task familiarity, with novel domains still exposing deep limitations

On the technical side, Andrej Karpathy shared detailed experiments running multi-agent research orgs (4 Claude + 4 Codex), finding agents strong at implementation but weak at creative ideation and experiment design. He also mapped the evolution from tab-complete to parallel agent teams in Cursor data. David Ha highlighted paradigm-shifting research on hypernetworks compiling documents directly into model weights as an alternative to long context windows. Anthropic disclosed a prompt caching bug affecting Claude Code rate limits and rolled out Claude Code Remote for Pro users.