Mistaken correlations: Why it's critical to move beyond overly aggregated machine-learning metrics
techxplore.com·18h
Experiments on Reward Hacking Monitorability in Language Models
lesswrong.com·4h
meta-pytorch/segment-anything-fast: A batched offline inference oriented version of segment-anything
github.com·43m
Use of Assertions
blog.regehr.org·18h
How Flavor Is Informed by More Than Just Taste
laughingsquid.com·15h
How Static Analysis Can Expose Personal Data Hidden in Source Code
hackernoon.com·21h
Publisher Correction: Multiple oestradiol functions inhibit ferroptosis and acute kidney injury
nature.com·18h
SandboxAQ Supercharges OpenFold3 with AQAffinity: High-Speed, Structure-Free Drug Potency Prediction
prnewswire.com·1d
An (Science) experiment and one questionable blackberry–mocha–banana smoothie ☕
notesonmydesk.top·15h
Causal analysis of ship inspection data and maritime accidents through causal neural networks
sciencedirect.com·17h
Building a Self-Healing Data Pipeline That Fixes Its Own Python Errors
towardsdatascience.com·20h
AI has a bias problem. Can we build something smarter?
news.berkeley.edu·1d
Learning from Models
rodney.bearblog.dev·1d
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