One computer scientist’s “stunning” proof is the first progress in 50 years on one of the most famous questions in computer ...

Machine learning models—especially large-scale ones like GPT, BERT, or DALL·E—are trained using enormous volumes of data.

When someone starts a new job, early training may involve shadowing a more experienced worker and observing what they do ...

In March 2025, IDC (International Data Corporation) released the report "AI-Powered Adaptive Education: Opportunities and Trends," which provides a comprehensive analysis of the current trends, ...

In order to solve the problem of non-ideal training sets (i.e., the less-complete or over-complete sets) and implement one-iteration learning, a novel efficient quantum perceptron algorithm based on ...

Abstract: Motivated by the observation that most neural architecture search (NAS) methods are time consuming because a “training process” is required to evaluate each searched neural architecture, ...

A Tesla owner sued Tesla over alleged inflated odometer readings that helped the carmaker dodge car repairs due to exceeding warranty mileage limits ...

An international team of scientists has used machine learning to help them develop perovskite solar cells with near-record efficiency. In their paper published in the journal Science, the group ...

The opportunity comes as creators seek to reclaim control over their audience relationships and shield themselves from the unpredictable tides of platform changes.

DisTrO has already been tested and shown in a Nous Research technical paper to yield an 857 times efficiency increase compared to one popular existing training algorithm, All-Reduce, as well as a ...