A max-plus neural architecture aligns deep learning with the polyhedral structure of phylogenetic tree space, cutting ...
DualQuant from AI inference startup d-Matrix eliminates the dataset requirement that prior W4A4 methods rely on, matching ...
AI open-source community achieved a breakthrough in solving OpenAI’s challenging integer multiplication problem within just ...
The threat of quantum computers to government systems, how AI is upending math and the ongoing Pentagon-Anthropic saga. All ...
Scientists have called out several math and computer science results as the most significant in the company’s overwhelming ...
A new paper claims the theoretical speed limit for matrix multiplication is much lower than anyone had proven. It hasn’t been ...
Mechanistic modeling of chemical transformations offers a compelling basis for understanding reactivity and allows for ...
Matrix multiplication is one of those foundational operations that silently runs the modern world. Every time a neural network trains, a physics simulation renders, or a search engine ranks pages, ...
Want only the AI that hits your stack? Build an agent that tracks your companies and topics, and skips everything else. DeepMind's AlphaEvolve now advances one of theoretical CS's most-tracked ...
MIT researchers have designed silicon structures that can perform calculations in an electronic device using excess heat instead of electricity. These tiny structures could someday enable more ...
Some results have been hidden because they may be inaccessible to you
Show inaccessible results