Transformer architectures have facilitated the development of large-scale and general-purpose sequence models for prediction tasks in natural language processing and computer vision, e.g., GPT-3 and ...

A Singapore-led team has introduced a paired protein language model (PPLM) that learns from two interacting proteins simultaneously, boosting accuracy in predicting protein–protein interactions. The ...

Researchers from MIT, Harvard, and the Broad Institute have unveiled PUPS, an AI method capable of predicting the location of any protein in any human cell line, even when both are previously untested ...

Newly developed artificial intelligence (AI) programs accurately predicted the role of DNA's regulatory elements and three-dimensional (3D) structure based solely on its raw sequence, according to ...

Unlock the full InfoQ experience by logging in! Stay updated with your favorite authors and topics, engage with content, and download exclusive resources. Dany Lepage discusses the architectural ...

This article is part of Demystifying AI, a series of posts that (try to) disambiguate the jargon and myths surrounding AI. (In partnership with Paperspace) In recent years, the transformer model has ...

The difference between sequential decision-making tasks and prediction tasks, such as CV and NLP. (a) A sequential decision-making task is a cycle of agent, task, and world, connected by interactions.