We’re sharing a solution to the Navier-Stokes Millennium Prize Problem, one of the deepest problems at the frontier of mathematics.
The proof was produced by a group of agents, using an OpenAI next-generation model significantly more capable than GPT-6 Astra.
The problem
New preprint arxiv.org/abs/2502.05392
Open Challenges in Time Series Anomaly Detection: An Industry Perspective
This is a vision paper about what I think it missing from current research in time series anomaly detection, and how it could align better with practical applications.
I'm pretty frustrated with the current review process in ML (both from an author, reviewer and meta-reviewer perspective). There's possible solutions or at least experiments and changes, but I feel like business as usual is no longer feasible.
I'm excited to share our results on MotherNet, a new hyper-network architecture based on TabPFN that can learn an MLP in-context using a single forward pass. This substantially improves prediction times over predicting with TabPFN directly: arxiv.org/abs/2312.08598