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Major milestones over time

Solving Open Research Problems Together: Six Papers from Meta AI and Mathematicians

Solving Open Research Problems Together Mathematicians and Muse Spark collaborate on six research papers Earlier this year, our models achieved gold-medal-level performance across five high-school Olympiad competitions in mathematics, physics, and chemistry. Those results inspired us to see whether AI could also help scientists solve open research problems. Competition problems can be incredibly difficult, but those

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AIhub monthly digest: September 2026 – tracking animal populations, recommender systems, and an interview with Ken Goldberg

Welcome to our monthly digest, where you can catch up with any AIhub stories you may have missed, peruse the latest news, recap recent events, and more. This month, we meet AI pioneer Ken Goldberg, use AI techniques to track animal populations, investigate how to improve recommender systems, and find out how external knowledge is used in AI systems. Combining cultures, from code to canvas: an interview with Ken Goldb

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Hidden Dates in System Prompts Shift LLM Evaluation Results

Reproducibility is essential for scientific research, yet prior work shows that LLM outputs vary with hardware and batching. We identify an overlooked factor: the hidden injection of the current date into system prompts, which users cannot control and which changes every day. Across 9 recent LLMs and 6 datasets spanning multiple-choice QA (MCQA), math reasoning, code generation, and machine translation, performance v

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What a crowdsourced game revealed about steering Olmo 3

AI models need to do more than produce correct answers. How they respond matters too: whether they’re helpful, fair, safe, respectful, and responsive to the people using them. For model builders, the challenge is knowing whether those “prosocial” behaviors hold up in practice—and whether evaluations capture how a model behaves when people interact with it in unexpected ways. Northeastern University MS student Soham P

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Building Custom Batched Ensemble Weather Forecasting with NVIDIA Earth2Studio

In this tutorial, we build an ensemble weather forecasting workflow with NVIDIA Earth2Studio. We install the required Earth2Studio components while preserving Colab’s existing CUDA-enabled PyTorch environment, load the FCN prognostic model, and retrieve atmospheric initial conditions from GFS. We then implement a custom wind-power diagnostic that converts 10-meter wind components into turbine capacity factors, along

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Auditing the Synthetic Memoir: Measuring Scene-Level Confabulation in LLM-Generated Autobiography Against the Documented Record

When a large language model (LLM) is asked to write a person's life, how much of what it writes actually happened? We present a scene-level case-study audit - the first quantified audit of LLM-generated autobiography against a subject-specific ground-truth corpus that we are aware of, based on an unsystematic literature search. The subject and the author of this paper are the same person: a 366-day "page-a-day" book

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#IJCAI-ECAI 2026 Distinguished Paper Award Winners Announced

The 35th International Joint Conference on Artificial Intelligence and the 29th European Conference on Artificial Intelligence (IJCAI-ECAI 2026) named three distinguished papers. One paper, titled "Approximate Strategyproofness in Approval-Based Budget Division" by Haris Aziz et al., proves that the Nash product rule (NASH) has an incentive ratio of 2, thereby circumventing the impossibility theorem by Brandl et al.

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