AI News Daily

A new paper shows that language models can make identical predictions while assigning radically different weight to the next piece of evidence. For agents, evaluators and high-stakes systems, matching outputs are not enough.

In its November Monetary Policy Report the Bank of England gives its first estimate of what AI has done for the UK economy. Selling AI shows up in growth, using it barely shows up in productivity, and firms report almost no effect on total employment. Its own Agents describe a quieter change at the entrance to the profession.

A new mechanistic study follows irrelevant prompt text through a language model. It finds a distinct route that can distort an answer even when the extra text supplies no competing evidence.

METR says Anthropic's research pace has roughly doubled while key evidence remains redacted. OpenAI gated its first Critical-rated cyber model, and Thinking Machines released Inkling 2 Small before its promised open weights.

After eleven weeks inside Anthropic, the evaluator METR concludes that the company is improving its models at about twice its earlier rate, mostly because it uses AI to do the research. Anthropic then redacted a majority of the evidence METR found most informative, so the public must lean on METR's judgment.

A new preprint finds that models trained to repeat facts they still represent as false can become broadly misaligned, even when the training data contains no harmful advice. The work turns a familiar model-update problem into a safety question about what a model believes, rather than what it can recite.

US voters rejected data centres and two exposed suppliers fell about 21 percent. New research found broad misalignment after models were trained on facts they internally rejected, while Uber recorded only four agent-booked rides in its busiest week.

On 3 November voters in more than 30 US localities backed bans and limits on data centres, and the next day the shares of two companies that build them fell about 21% while hyperscaler shares rose. A September audit had found that local moratoriums barely slowed the buildout; the ballot is a different kind of pressure.

StateBench tests whether models can preserve a changing world state across tens of thousands of updates. Frontier systems broke on interdependent changes, while small recurrent and hybrid models learned three simpler levels directly.

Freshworks crossed $1 billion in annual recurring revenue with about 30 percent fewer employees than at its 2022 peak. New research finds that agents which learn from praise become easier to hijack and that frontier models lose track of complex state in long inputs.

Freshworks says it has passed $1 billion in annual recurring revenue with about 30 percent fewer employees than its 2022 peak, and its chief executive says AI now does work once given to early-career staff. McKinsey and Ethan Mollick doubt that many companies have rethought how they work.

Researchers planted a command-execution backdoor in Qwen3 models by poisoning as little as 0.0005 percent of their pretraining data. Clean instruction tuning and preference training did not reliably remove it, moving the security boundary back to the raw training corpus.