New York University

Headlines · 4

1. 5d
   Study identifies six linguistic patterns that make AI text harder to read

   Researchers from New York University and the University of Texas at Austin analyzed text from 14 language models, including 120 conversations, 45 coding sessions and 980 essays, and compared it with human writing. They identified six recurring constructions that the models overused: unusual word combinations, widely separated related sentence elements, shortened references with dropped connectors, stacked nouns, nouns converted into verbs, and animate verbs applied to inanimate subjects. Llama and the Olmo base model were closest to human text. In a proof-of-concept experiment, a smaller model trained with a penalty for longer answers favored shorter phrasing under certain conditions.

   The Decoder · 🔥 0
2. Oct 22
   Altman Says Mathematicians Are Moving From Fear Toward Acceptance of AI

   According to media reports, OpenAI CEO Sam Altman told an audience of several hundred students at Stanford University that mathematicians’ attitudes toward AI have moved from disbelief and anger toward acceptance that AI can no longer be avoided in research and proof work. Altman described the progression as resembling stages of grief. His optimistic framing contrasts with mathematicians’ continuing concerns that AI systems may not show their derivations and leave researchers with difficult verification work. OpenAI’s announced solution to the Navier–Stokes equations and its claims about solving more than 700 other problems were not independently verified in the supplied material.

   36氪 人工智能 · 🔥 0
3. Oct 15
   Gary Marcus Says US-China AI Race Will End in a Tie, Not a Victory

   Speaking to Bloomberg on the sidelines of the Bloomberg New Economy Forum in New Delhi, New York University emeritus professor of psychology and neural science Gary Marcus said the US-China artificial intelligence race will end in a tie rather than a decisive victory for either side. He also discussed how the technology can be made safer. Bloomberg's written report headlined the remarks as an "unwinnable" war on AI.

   Bloomberg Technology · 🔥 0
4. Oct 10
   LeCun's AMI open-sources H-JEPA, a hierarchical world model for visual planning

   AMI (Advanced Machine Intelligence), the world-model startup chaired by Yann LeCun, released a paper with NYU, INRIA Paris and Brown University describing H-JEPA: multiple JEPA modules stacked so each layer predicts states at its own timescale, with a high level setting a coarse plan and lower levels refining predicted intermediate states into executable actions. The paper reports 73% success for a three-layer model versus 18% for a single-layer model on the Visual AntMaze simulated maze task, with better results at lower planning compute on several tasks; code and pretrained weights were released. The report also says AMI previously raised $1.03B at a $3.5B pre-money valuation, while its website still shows mainly research direction and hiring rather than a public product.

   36氪 人工智能 · 🔥 0

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