Обновляется ежедневно1797 проверенные истории
Проверенные источники искусственного интеллекта освещают запуски продуктов, изменения в политике, исследования в области безопасности и отраслевые шаги, объясненные простым языком командой некоммерческого образования.
Каждая история связана с самыми убедительными имеющимися доказательствами: первоначальными источниками, если таковые имеются, или явно приписываемыми сообщениями.
What happened, why it matters, and what to watch — without the jargon.
Когда сигнал слабый, мы ничего не публикуем, а лишь дополняем канал.
Source-checked AI stories, newest first, for people who need to understand AI without chasing hype.
A new arXiv preprint introduces PU-HNO, a three-stage model for predicting detailed indoor radio maps from lower-fidelity simulations and scene information. The authors report improvements over several baseline approaches, but the supplied record does not provide numerical results or evidence of real-world deployment.
An arXiv preprint introduces Tianmu-TC, a generative forecasting framework trained on Western North Pacific data that its authors say improves tropical-cyclone forecasts across global ocean basins while using less computation.
An arXiv preprint describes an LLM-based system that predicts job execution time and energy use from source code before allocating GPU resources. Its authors report lower energy consumption and queueing time with an unnamed data center, but the record lacks enough detail to independently assess the result.
A five-author ICML 2026 paper proposes measuring changes in nonlinear input interactions, not just final answers, when small prompt edits destabilize language models.
A new arXiv preprint studies whether reasoning models can learn tasks sequentially without losing ground, and proposes Continual Prompt Replay to close the gap with joint multitask training.
A new arXiv preprint argues that sequence-pooled normalization can provide global context even when a convolutional sequence labeler has a short receptive field. The finding could affect how researchers assess streaming limits, architecture design and attribution results.
A single-author preprint reports that Transformer and Mamba architectures develop similar near-marginal slow-mode dynamics despite using different internal mechanisms. The finding remains unverified beyond the supplied arXiv record.
A new arXiv preprint reports that strong inference-time guidance can push protein language models toward degenerate sequences that still score well under the optimized property oracle. The authors propose a low-cost post-hoc filter based on the model’s natural activation statistics.
A paper accepted by IEEE ICDM 2026 reports that adaptive inversion reconstructs substantially more of the original text from Gaussian-noise-protected embeddings than an existing generative baseline, challenging a widely used privacy assumption without establishing real-world exposure or independent replication.
A single-author arXiv preprint introduces the Middle East Cultural Sensitivity Score and reports that two language models reproduce structural Orientalist patterns in conversations about the region. The findings are preliminary and have not been independently verified.
A one-author arXiv preprint claims that a direction derived from nine emotion categories and narrative examples can track positive-negative valence in text, images, audio and brain recordings, while showing clear limits across concepts and model families.
A new arXiv preprint describes DeepTCM1.0, a system using 11 specialized AI agents and iterative review to analyze possible mechanisms of traditional Chinese medicine formulas. It reports an evaluation design but no numerical results, clinical validation, or evidence of improved patient care.
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