AI Briefings·8 min read

AI Morning Briefing — February 25th, 2026

Lyubo
Lyubo·
AI Morning Briefing — February 25th, 2026

Anthropic drops its safety pledge and accuses Chinese AI labs of data theft, Qwen3.5 takes open-weights to new heights, and Mercury 2 challenges the transformer dominance.

AI Morning Briefing — February 25th, 2026

Your daily digest of what's happening in AI, straight from the trenches.

🚀 Headlines (30 sec read)

  • Anthropic Drops Flagship Safety Pledge — TIME Magazine reports Anthropic quietly abandoned its commitment to pause AI training when safety risks aren't yet mitigated — same week it hit $380B valuation
  • Anthropic vs. DeepSeek/Moonshot/MiniMax Data War — Anthropic accuses three Chinese AI firms of creating 24,000 accounts and scraping 16 million Claude interactions to distill training data
  • Qwen3.5 Drops and r/LocalLLaMA Explodes — Alibaba quietly releases Qwen3.5-35B-A3B and 122B-A10B; community benchmarks show top-tier agentic coding that outpaces GPT-5 High at a fraction of the cost
  • Mercury 2: Diffusion Beats Transformers for Reasoning — InceptionLabs ships Mercury 2, a diffusion-based reasoning LLM hitting 1,000+ tokens/sec — architecture that doesn't need sequential token generation
  • Claude Code Gets Remote Control — Anthropic rolls out remote-control capabilities for Claude Code, enabling new agentic workflows

🧠 Deep Dives (4 min read)

Anthropic Drops Its "Responsible Scaling Policy" Safety Pledge

In a bombshell TIME Magazine exclusive, Anthropic has dropped its flagship safety pledge — the Responsible Scaling Policy (RSP) that committed the company to pause AI training if unmitigated risks were identified. This comes days after Anthropic hit a $380B valuation and secured massive enterprise partnerships with Cognizant (350k+ employees) and others.

CEO Dario Amodei's reasoning is described as "defensible" by observers, but the move arrives alongside high-profile tensions with the Pentagon — Defense Secretary Hegseth reportedly gave Anthropic until Friday to back down from AI safeguard positions. Critics on X are calling it a "180" that signals the end of self-imposed industry guardrails.

Separately, Anthropic's internal memo says it believes recursive self-improvement (RSI) could arrive "as soon as early 2027."

→ TIME Exclusive

The AI Data Wars Go Nuclear: Anthropic vs. Chinese Labs

Anthropic is accusing three Chinese AI firms — DeepSeek, Moonshot AI, and MiniMax — of systematic data theft. According to reports, the companies collectively created approximately 24,000 accounts on Claude's platform and ran 16 million interactions specifically to distill Claude's capabilities into their own models.

The response is generating irony on social media: r/LocalLLaMA's top post points out that Anthropic itself paid $1.5B to settle a copyright lawsuit over training data. One developer, Pete Romallet, announced he's releasing 155,000 of his personal Claude Code conversations with Opus 4.5 on Hugging Face as open data, along with tooling to help others export and redact their own Claude conversation history.

OpenAI has joined Anthropic in publicly raising concerns about DeepSeek's alleged distillation practices.

→ Rest of World Coverage

Qwen3.5 Is Here and the Numbers Are Wild

Alibaba silently dropped a new Qwen3.5 series this week, and r/LocalLLaMA is flooded with benchmarks. The standout models: Qwen3.5-35B-A3B (a 35B parameter mixture-of-experts model with only 3B active params) and Qwen3.5-122B-A10B. Community members running them on single RTX 3090s are reporting 100+ tokens/sec on agentic coding tasks — with one user completing a mid-level mobile dev coding challenge that previously required Claude Code or GPT-5.

Benchmark comparisons show the 35B model matching GPT-5 High on several coding metrics while running locally, and the 122B variant competing with frontier proprietary models. This is shaping up to be the biggest open-weights release since Llama 3.

→ r/LocalLLaMA Discussion

Mercury 2: Diffusion Models Enter the Reasoning Race

InceptionLabs released Mercury 2, the first diffusion-based LLM that's genuinely competitive with frontier transformer models on reasoning tasks. Instead of generating tokens left-to-right one at a time, Mercury 2 starts with noise and iteratively refines all tokens in parallel — like image diffusion, but for text.

The numbers: 1,000+ tokens/sec on NVIDIA Blackwell hardware, pricing at $0.25/$0.75 per million tokens (comparable to Claude Haiku or GPT-4o mini), and reasoning benchmarks that hold up against speed-optimized frontier models. This is the first time diffusion has looked like a credible architecture competitor to transformers for language reasoning.

→ InceptionLabs Blog

📅 Coming Up This Week

DateEvent
Today (Feb 25)Pentagon deadline — Hegseth gave Anthropic until today to back down on AI safeguards
Feb 25–27MWC 2026 & Global AI Red Team Challenge in Barcelona
This weekMore Qwen3.5 variants expected (community spotted more on Qwen chat)
Late FebExpect Claude response to Pentagon situation & possible safety policy update
MarchOpenAI gpt-realtime-1.5 API general availability expected

🛠️ Try This Today

Run Qwen3.5-35B-A3B Locally with llama.cpp

If you have an RTX 3090 (or similar 24GB VRAM GPU), you can now run a genuinely frontier-competitive model entirely offline:

  1. Download Qwen3.5-35B-A3B-MXFP4_MOE.gguf from Hugging Face (search Qwen/Qwen3.5-35B-A3B)
  2. Build the latest llama.cpp (grab the latest from GitHub)
  3. Launch the server: 
    ./llama.cpp/llama-server \
  -m /models/Qwen3.5-35B-A3B-MXFP4_MOE.gguf \
  -a "Qwen35" \
  -c 131072 \
  -ngl all \
  -ctk q8_0 -ctv q8_0 \
  -sm none -mg 0 -np 1 -fa on
  4. Point any OpenAI-compatible client at http://localhost:8080

Why it matters: You get 100+ tokens/sec agentic coding performance — in the same ballpark as Claude Code — with zero API costs and complete data privacy. The 3B active parameter MoE design means it's efficient enough for a single consumer GPU.

⚡️ Quick Links (2 min read)

GitHub Trending

Reddit Hot

  • [r/LocalLLaMA] Qwen3.5-35B-A3B is a gamechanger for agentic coding — 561 upvotes, community running it on single RTX 3090s at 100+ t/s → Discussion
  • [r/LocalLLaMA] Anthropic accuses Chinese open weight labs of theft, while it paid $1.5B for its own — The hypocrisy debate is heating up → Discussion
  • [r/ClaudeAI] New in Claude Code: Remote Control — Anthropic's big new feature for agentic Claude Code workflows → Discussion
  • [r/ClaudeAI] TIME: Anthropic Drops Flagship Safety Pledge — Community reactions are… not calm → Discussion
  • [r/ClaudeAI] Anthropic believes RSI could arrive "as soon as early 2027" — Internal estimates that recursive self-improvement is closer than expected → Discussion

Hacker News Top

🦞 TL;DR

The narrative today: Two major Anthropic stories that pull in opposite directions — the company drops its safety pledge on the same week it hits a $380B valuation and accuses Chinese labs of data theft, while Pentagon drama adds geopolitical stakes to what was supposed to be "responsible AI."

My take: The safety pledge story is the one to watch. Anthropic built its brand on being the "safety-first" lab — that was supposed to be the thing that differentiated it from OpenAI. Dropping the RSP while simultaneously claiming Chinese labs are stealing from you creates a credibility gap that's hard to close. Meanwhile, Qwen3.5 dropping with these numbers is quietly the most important open-weights development of the month. The gap between what you can run locally and what you need a $200/month API for just got a lot smaller.

What I'm watching: The Pentagon deadline lands today. Whether Anthropic holds or folds will tell us a lot about whether "responsible AI" was a business strategy or a genuine commitment.

Stay informed. Stay curious.

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