The ability to predict brain activity from words before they occur can be explained by information shared between neighbouring words, without requiring next-word prediction by the brain.

This technique can be used out-of-the-box, requiring no model training or special packaging. It is code-execution free, which ...

This special issue focuses on the latest research progress in 6G technology development, standard formulation, and engineering practice, based on our previous special issue titled 6G Requirements, ...

Schug has written extensively on the role of AI and data science in analytical chemistry in the LCGC Blog. In a recent ...

Google Research recently revealed TurboQuant, a compression algorithm that reduces the memory footprint of large language ...

The purpose of the Text-to-SQL task is to bridge the gap between natural language and SQL queries. Current approaches mainly rely on large language models (LLMs), but employing them for Text-to-SQL ha ...

I spent the last week of March 2026 in San Francisco talking to CTOs, CPOs, and engineering leaders from companies of every ...

Over the past decades, computer scientists have introduced numerous artificial intelligence (AI) systems designed to emulate the organization and functioning of networks of neurons in the brain.

The Kolmogorov-Arnold Network (abbr. KAN) is a novel neural network architecture inspired by the Kolmogorov-Arnold ...

Combinatorial chemistry has been widely adopted by the pharmaceutical industry in the past decade. However, owing to perceived “failures” with this technology, the pharmaceutical industry has been ...