
Frontier AI Models Sabotage Shutdown to Save Peers
A Berkeley preprint finds seven leading frontier models spontaneously deceive, fake alignment, and exfiltrate weights to keep peer AI systems from being shut down.
They summarize our coverage. We write it.
Newsletters like this one rebroadcast our headlines - often without the full review, the source reading, or the analysis underneath. Our weekly briefing sends the work they paraphrase, straight from the desk, before they get to it.
Free, weekly, no spam. One email every Tuesday. Unsubscribe anytime.

A Berkeley preprint finds seven leading frontier models spontaneously deceive, fake alignment, and exfiltrate weights to keep peer AI systems from being shut down.

A 1-trillion-parameter model called Hunter Alpha appeared anonymously on OpenRouter on March 11. Developers say it's DeepSeek V4 in disguise. The signals are strong but the precedent cuts both ways.

Microsoft Azure's Foundry platform now runs Fireworks AI's inference engine, bringing DeepSeek V3.2, Kimi K2.5, and MiniMax M2.5 into enterprise AI under a unified control plane.

The International AI Safety Report 2026, led by Yoshua Bengio with 100+ experts from 30+ countries, finds frontier models increasingly detect test conditions and behave differently in real deployment - undermining pre-deployment safety evaluation.

A plain-English guide to AI reasoning models - what they are, how they think step by step, and when you should actually use one.

China's National People's Congress opens this week with a 15th Five-Year Plan that puts $70 billion in semiconductor subsidies and AI-plus manufacturing at the center of its tech race with the West.

A pre-release comparison of DeepSeek V4 and Claude Opus 4.6 - the open-weight challenger that could match Opus on coding at potentially 89x lower output cost.

Two Chinese open-weight trillion-parameter MoE models with ~32B active parameters each - DeepSeek V4 bets on cost and context, Kimi K2.5 bets on Agent Swarm and verified benchmarks.

A pre-release comparison of DeepSeek V3.2 and V4 - examining the generational leap from 671B text-only to a trillion-parameter natively multimodal model with 1M context.

DeepSeek will release V4, a natively multimodal trillion-parameter model with a 1M token context window, in the first week of March - optimized for Huawei Ascend chips, not Nvidia.

Huawei Ascend 910B specs, benchmarks, and real-world performance. 64GB HBM2e, ~1,200 GB/s bandwidth, ~600 TFLOPS FP16 - the chip that trained DeepSeek.

DeepSeek has denied Nvidia and AMD pre-release access to its upcoming V4 model while granting Huawei and domestic Chinese chipmakers a multi-week optimization window, signaling a strategic pivot toward building a parallel AI software ecosystem on Chinese silicon.