Mass General Brigham researchers are betting that the next big leap in brain medicine will come from teaching artificial ...

Humans are the species with both the greatest capacity for self-sabotage and the greatest capacity for learning. We see evidence of this constantly in everyday life and in world news. In this essay, I ...

The new reinforcement learning system lets large language models challenge and improve themselves using real-world data instead of curated training sets. Meta researchers have unveiled a new ...

The identification of wheat infections has always been a considerable problem in agricultural forecasting. This paper presents an automated classification framework for wheat illnesses utilising ...

Abstract: Insufficient labeled data is a common issue in state-of-health (SOH) estimation of Lithium-Ion battery. Self-supervised learning method provide a feasible direction to solve the problem of ...

Google’s recent whitepaper, “Welcome to the Era of Experience,” signals a shift in the way AI agents are trained. Google’s paper hypothesizes that allowing AI agents to learn from the experience of ...

Automatic classification of interior decoration styles has great potential to guide and streamline the design process. Despite recent advancements, it remains challenging to construct an accurate ...

When Jace Rossignol was in fifth grade, he was breezing through seventh grade math and scored on an 11th grade reading level in the statewide MCAS exam. His elementary school could not accommodate him ...

Elon Musk is teasing a new Tesla ‘Full Self-Driving Supervised’ (FSD) update with “10x improvements”, but historical performance compared to Musk’s announcements suggests that it’s safer to manage ...

Abstract: Graph contrastive learning (GCL) has emerged as a powerful method for dealing with noise and fluctuations in graph-structured data, and can be applied to social networks and knowledge graphs ...