In recent years, machine learning (ML) algorithms have proved themselves to be remarkably useful in helping people deal with different tasks: data classification and clustering, pattern revealing, ...

Source: Created by Alex Danvers on Canva. Replicating studies is key to gaining confidence in them. We don’t just want psychological effects that happened once in a lab, we want effects that are ...

Large language models have captured the news cycle, but there are many other kinds of machine learning and deep learning with many different use cases. Amid all the hype and hysteria about ChatGPT, ...

Trading used to be about gut feelings and reading charts. Traders sat at desks watching screens, trying to spot patterns that meant prices would go up or down. That world exists still but machines can ...

The algorithms that underlie modern artificial-intelligence (AI) systems need lots of data on which to train. Much of that data comes from the open web which, unfortunately, makes the AIs susceptible ...

Inspired by how the human brain consolidates memory, the 'Nested Learning' framework allows different parts of a model to learn and update at different speeds.

eSpeaks host Corey Noles sits down with Qualcomm's Craig Tellalian to explore a workplace computing transformation: the rise of AI-ready PCs. Matt Hillary, VP of Security and CISO at Drata, details ...

Machine-learning algorithms are transforming the search for extraterrestrial intelligence, finding candidate signals faster and better than ever before, but the development of artificial general ...

Classical machine learning (ML) is a powerful subset of artificial intelligence. Machine learning has advanced from simple pattern recognition in the 1960s to today's advanced use of massive datasets ...

Can we ever really trust algorithms to make decisions for us? Previous research has proved these programs can reinforce society’s harmful biases, but the problems go beyond that. A new study shows how ...