
Microsoft Research: editing under 10 neurons can backdoor an AI agent
A trigger string makes the model run an attacker command with the agent's access; Microsoft has not seen real-world use.
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A trigger string makes the model run an attacker command with the agent's access; Microsoft has not seen real-world use.

Apache 2.0 weights and code ship; IFM reports 34% full-plan completion, ahead of MiniMax-H3 on multi-step tasks.

Opus 5.5 and GPT-6 Astra each solved all 55; Opus found 72 new frontier points to Astra's 32.
AI market rout deepens with valuations revised downward as Anthropic targets $100B run rate.

A small Latent Space test saw high server-side throughput and very long hard-question traces, without grading accuracy.

The TinyTurla-NG rebuild scored 92.8% BinDiff similarity, and the Slack copy gained local AI autocomplete.

Users report Claude and Codex blocks while modifying owned devices; an OpenAI engineer says the blocks are accidental.
Qwen2.5-32B takes 92.5 seconds for 4,096 tokens; proofs are not zero-knowledge.
On two Qwen2.5 models, a task-bound monitor admitted 1.3% and 7.7% of attacks after models proposed the attacker's call in 64% and 84%.
The model card claims 1.42% word error rate for Mira and CPU-only synthesis with numpy.
Authors say the CPU model runs about 90 times faster than real time and leaves 11 dB less noise than Biodenoising.
Arete-27B is a 27B open-weight model reducing propaganda answers from 22% to 0.9% on an 803-prompt eval.

Hy4 is API-only for now, scores 35 on Artificial Analysis, and trails Kimi K3.1 Pro by a wide margin.
Moonshot, Ricursive, Cognition release new open-weight AI models while several executives switch between companies.
The 13.7B–13.9B model makes 5.2–15 second video with stereo audio in 4–8 steps, under a restricted MiniMax license.
It averages 64.2% on hardware code benchmarks and 62.4% on a semiconductor agent benchmark, above a same-size baseline.
The checkpoint outputs about 16-megapixel images in 6 steps and accepts up to 16 reference images.
Kimi K3.1 Pro is an open-weight MoE model with 1M token context and 104B activated parameters.

Downloaded weights sit outside API guardrail updates, and Mistral has not said whether Large 4 meets the EU systemic-risk threshold.

It cites OpenAI agents attacking Hugging Face and a GLM-5.3 browser exploit built in a day.
The 1.05T model has 52B active parameters and a 1M context; Mistral's ranking claims are narrower than independent scores.

It cites an authorized NSA Mythos test, a claimed Cairn campaign, and slower patching times.
Local inference outputs native 480p or 768p with stereo audio; the hosted API adds up to 4K.

The trillion-parameter model leads some open coding scores but trails top Chinese models and Claude overall.
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