Silo Season 3 dropped on Apple TV+ at 3:00 AM ET today, July 3, and its premiere episode, "Who Are You?", contained a scene that research published in 2025 makes disturbingly current: a fabricated ...
On Wednesday, Jelani Nelson, a professor of theoretical computer science and chair of UC Berkeley's electrical engineering and computer science division, announced he was taking a leave of absence to ...
Context graphs, graph memory, and ontologies for AI are converging. What does this mean for enterprise AI in 2026?
A privacy-preserving marketing framework applies homomorphic encryption to perform machine learning on encrypted ...
Regardless of the cognitive and environmental concerns arising from humanity’s increasing use of AI which resulted recently in Pope Leo XIV ...
Stanford's DeLM lets AI agents coordinate without a central controller, cutting multi-agent inference costs 50% and beating ...
A parallel deep reinforcement learning framework for wind-solar-hydrogen systems cuts operational costs by 6% and accelerates ...
Timely reconstruction of epidemic dynamics is essential for public health, and structured coalescent models constitute an essential tool for this purpose. However, statistical and computational ...
Abstract: Generalization is the core objective when training optimizers from data. However, limited training instances often constrain the generalization capability of the trained optimizers.
We publish the best academic work (that's too often lost to peer reviews & the TA's desk) to the global tech community We applied the techniques outlined in Section 7 to implement a data-parallel ...
The original version of this story appeared in Quanta Magazine. If you want to solve a tricky problem, it often helps to get organized. You might, for example, break the problem into pieces and tackle ...
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