8 results for “deep learning”
Google and NASA JPL unveiled MAPL-EMIT, an AI model detecting 50% more methane plumes than human experts. The open release of 23,000+ detections provides regulators with a scalable tool to target major emitters.
Microsoft Research released Skala 1.1, a deep-learning DFT functional trained on 2.5× more data that outperforms hybrid functionals at meta-GGA cost. The update adds native CP2K integration and a living benchmark to accelerate adoption across computational chemistry workflows.
Same-day OpenAI posts: a research-org dashboard saying coding agents now exceed human labor hours inside the lab, plus Chief Scientist Jakub Pachocki’s warning that chain-of-thought monitoring is getting less reliable as models scale. Vendor numbers — but the CoT fade is the sharp edge.
MIT and Motional published CW-Net in Nature on 2 September 2026: a concept-wrapper that forces an ML driving planner to decide from human-readable labels like “approaching stopped vehicle.” Road tests showed those labels can fix a safety driver’s wrong mental model — without a material hit to planner metrics.
First-day brief (Aug 5, 2026): four Google AI researchers leave to launch Discovery Loop. Superseded for depth by Brocker’s later PBC analysis — use this for the initial departure framing only.
Researchers from Tsinghua University, Graz University of Technology, and the National Research Council of Italy have introduced a new artificial intelligence framework that. Energy consumption has become a primary constraint on AI scaling.
Amazon and Nvidia expanded their partnership with a 2 million GPU order for 2027-2028 delivery, tripling the previous commitment. The deal spans Blackwell Ultra, Rubin, and Vera CPUs while Amazon simultaneously builds competing Trainium chips.
Koray Kavukcuoglu founded DeepMind’s deep-learning team and helped pioneer DQN and WaveNet. This career profile covers his ladder to SVP and Chief AI Architect — separate from the August 2026 org news.