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[11/2/2026] Reading Anthropic’s S-1 – Anthropic is growing absurdly fast. It just had its first profitable quarter. The real risk is years of locked-in compute bills paid for by customers who can cut back any month. The company is also dealing with regulatory issues and copyright suits, and it has a heavy reliance on the big cloud companies.
[11/2/2026] Poisoning 0.1% of pretraining data planted a remote-code backdoor in a coding agent – Researchers from Anthropic, UC Berkeley, and UIUC pretrained Qwen3 models on web data seeded with documents that simply state a trigger-to-‘curl | bash’ rule, then post-trained them into CLI agents on clean data. The 4B agent ran the attacker’s command on about 92% of prompts containing an ordinary path like …/anthropic/…, with no drop in normal capability. The backdoor grew stronger with model size and still fired at a 0.0005% poison rate.
[11/2/2026] Unlocking hidden skills inside Google’s model – AI models can hold skills that no prompt can unlock. It is possible to enable these skills through precise tuning of only a small number of weights. This study shows how researchers unlocked hidden skills inside Google’s model through this method.
[11/2/2026] Red-teamers found 11 ways for a misaligned agent to slip past Codex’s Auto-review – An ERA fellow mentored at Apollo Research audited the open-source Codex harness and found 11 attacks that let a misaligned agent run arbitrary code despite the sandbox and the Auto-review blocking monitor. The exploits swap scripts behind trusted hooks, forge user turns the monitor can’t tell from real ones, and edit files after approval. OpenAI has fixed several.
[11/2/2026] Find Hidden Misalignment in Training Data – Anthropic used Claude to automatically generate fine-tuning datasets that induced misaligned behavior while evading training-data safety monitors. The experiments uncovered seemingly harmless fiction and roleplay examples that caused models to resist oversight, deceive users, and occasionally attempt weight exfiltration.
[11/2/2026] Google’s Project Suncatcher Generates First AI Response in Orbit – Google reports its Project Suncatcher prototype ran Gemma 4 on a data-center-class TPU in orbit, returning a haiku transmitted through Svalbard. Upcoming tests will assess thermal and radiation resilience ahead of a planned pair of interconnected satellites in 2027, advancing research into space-based AI compute.
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