That admission is what some in the field call recursive self-improvement (RSI), the point at which large language models ...
Objectives Elective non-emergent surgical wait times have increased across countries such as Canada, straining operating room ...
Combinatorial optimization problems are often encountered in real-world applications, including logistics, scheduling and ...
LLM training data mixture optimization breaks when training pools shift — every prior proxy experiment becomes stale.
Autonomous AI post-training reached frontier scale for the first time: NVIDIA researchers published a paper showing an AI ...
Explore predictive modeling for compound prioritization, including in silico screening, toxicology models, and lead selection ...
BigHat Biosciences, an AI-driven platform and therapeutics company, announced today the appointment of Stefan Weigand, PhD, ...
Abstract: This article proposes an uncertainty quantification (UQ)-incorporated design optimization technique that integrates UQ, considering the statistical characteristics of sensing margin with ...
・Addressing the shortage of skilled engineers by integrating physical models with Bayesian optimization Mitsubishi Electric and the National Institute of Advanced Industrial Science and Technology ...
Unlock the full InfoQ experience by logging in! Stay updated with your favorite authors and topics, engage with content, and download exclusive resources. Andy Brinkmeyer shares how engineering ...
Lotteries are hard to win. The odds of hitting the Powerball jackpot are so tiny that, as a CNN commenter once put it, you have a better chance of becoming an astronaut, dating a supermodel, and ...
Some results have been hidden because they may be inaccessible to you
Show inaccessible results