Data keeps growing exponentially, driving demand for better memory storage solutions. Synthetic DNA is a strong candidate to ...

Across modern data-intensive disciplines, the union of numerical computation, statistics, and machine learning has become ...

AI medical imaging market is projected to exceed $20B by 2035. Generative models address class imbalances in medical imaging ...

Quantum exposure cuts across data, supplier contracts, capital allocation, customer commitments, regulatory adequacy and ...

Google's open-source diffusion language model generates 256 tokens in parallel and self-corrects, hitting 4x speed on one GPU ...

Regulators are accelerating oversight of algorithmic and personalized pricing with the Federal Trade Commission (FTC) and key states moving ...

Penn Engineers have developed an open-source algorithm that combines the speed of AI with the precision of geometry to ...

Algorithmic transparency requirements—which require organizations to disclose how their automated systems work—have expanded ...

Abstract: In the era of large-scale machine learning, large-scale clusters are extensively used for data processing jobs. However, the state-of-the-art heuristic-based and Deep Reinforcement Learning ...

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 ...

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 ...