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It’s a chaotic time in an industry that’s reshaping our lives – Guardian reporters and experts recommend the books that help explain how we got here, and where we’re headingHave you been feeling trapped in an endless cycle of artificial intelligence hype and panic? You’re not alone.It’s a chaotic time to make sense of the […]
Universities need protect their position in education so that students have an independent pathway to employmentAI companies like OpenAI are insinuating themselves into the pathway from education to work. Soon they may claim it entirely, a disastrous result for students.We know that students are using AI at school and at university. In conversations with those
OpenAI has released a new framework for tracking, investigating, and disclosing misalignment in its own models. The OpenAI team announced it on X alongside 6 detailed incident reports. The framework sets criteria and deadlines for public disclosure. It applies even when OpenAI has not fully explained or mitigated the behavior. Why OpenAI Built It OpenAI’s
Search and recommendation systems increasingly need to return a set of results, not one best match. A query like ‘camping gear’ should return a tent, a sleeping bag, a stove, and a headlamp. It should not return 10 near-identical tents. Google Research has introduced Retrieve-for-Train (R4T) for this problem. The framework uses reinforcement learning (RL)
Research model inserting ‘jailbreak-like instructions’ into its notes is among cases as company says it is introducing new way of tracking AI misalignmentOpenAI has disclosed six new reports of “unexpected or concerning” behaviour in artificial-intelligence models as the debate on AI safety becomes increasingly heated.Among the new cases reported by OpenAI, an unreleased research model
In early September, OpenAI announced it had solved a major mathematics problem that has stumped humans for nearly a century. The news left mathematicians reeling, and many expressed concern over what will be left for humans as AI becomes ever more adept at unravelling complex problems. Now 25 recipients of the Fields medal – often
Nunchux AI has released VC-Attention, a training-free low-bit attention kernel built for video Diffusion Transformers (DiTs). It targets 2 problems at once: value quantization error and a slow softmax stage. Why Attention is the Video Bottleneck Video DiTs flatten a clip into 1 sequence of spatiotemporal tokens and run full self-attention at every layer. A
Computational papers ship code that readers must clone, install, configure and debug. That cost keeps useful methods locked inside PDFs. A Stanford team led by Jiacheng Miao and James Zou proposes a fix. Paper2Agent was published in Nature on 16 September 2026. It converts a paper and its codebase into a Model Context Protocol (MCP)
Knowledgator Engineering has released GLiFormer, a schema-conditioned encoder framework for information extraction. One model handles named-entity recognition (NER), text classification, relation extraction, nested JSON structuring, and text embeddings. You pass labels and extraction schemas at inference time. Two checkpoints are on Hugging Face. GLiFormer Base v1 has 264.2M parameters, and GLiFormer Large v1 has 575.6M.
Lars Janssen says self-driving vehicles would be a boon for him as he has an eye condition and can’t drive, in response to an article by Adrian Chiles. Plus letters from Richard Connell and Michael FullerAdrian Chiles (Driverless cars are taking us on a road to nowhere, 10 September) wants to know who asked for
Why I can’t wait to get into a driverless car | Letters Read More »
