The shift toward AI-driven decision frameworks is not simply a technological trend but a fundamental necessity for life ...

RNA has emerged as one of the most promising molecules in modern medicine, enabling advances from mRNA vaccines and gene ...

That admission is what some in the field call recursive self-improvement (RSI), the point at which large language models ...

Combinatorial optimization problems are often encountered in real-world applications, including logistics, scheduling and ...

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 ...

Machine learning models are increasingly applied across scientific disciplines, yet their effectiveness often hinges on heuristic decisions such as data transformations, training strategies, and model ...

Tumor Site–Specific Radiation-Induced Lymphocyte Depletion Models After Fractionated Radiotherapy: Considerations of Model Structure From an Aggregate Data Meta-Analysis Lymphocytes play critical ...