Using generative AI to design, train, or perform steps within a machine-learning system is risky, argues computer scientist Micheal Lones in a paper appearing in Patterns. Though large language models ...
Discovering and characterizing new materials is important for unlocking advances in fields like clean energy, advanced ...
In recent years, artificial intelligence has become more accessible than ever before. Powerful libraries, automated platforms ...
The study, titled “Teach AI What It Doesn’t Know,” published in AI Magazine, presents a detailed research agenda by Sean Du of Nanyang Technological University, focused on building reliable machine ...
Engineers develop a system that captures all the elements of trial and error in material design, enabling reliable ...
AI is already changing the way healthcare looks in the US. Artificial intelligence is slowly being integrated into almost ...
Using artificial-intelligence to teach other models can be cheaper and faster than building them from scratch, but this ...
Researchers used the world's fastest supercomputer for open science to train an artificial intelligence model that captures ...
The researchers argue that traditional centralized learning platforms are no longer equipped to handle the scale, speed, and ...
In today’s modern financial landscape, markets are increasingly driven by automated systems rather than traditional intuitive ...
Stanford's 2026 AI Index: frontier models fail one in three attempts, lab transparency is declining, and benchmarks are ...
Previously trained with text-based data, the AI is now a model that learns from videos and real-world simulations.
Some results have been hidden because they may be inaccessible to you
Show inaccessible results