Sara Hooker, CEO of Adaption Labs, argues that the future of AI lies in adaptive learning rather than simply increasing model size.

Advances in machine learning and shape-memory polymers are enabling engineers to design for mechanical performance first and ...

A new study introduces a global probabilistic forecasting model that predicts when and where ionospheric disturbances—measured by the Rate of total electron content (TEC) Index (ROTI)—are likely to ...

The researchers have developed a new approach to making biometric presentation attack detection (PAD) resistant to demographic bias.

Dr. James McCaffrey presents a complete end-to-end demonstration of decision tree regression from scratch using the C# language. The goal of decision tree regression is to predict a single numeric ...

Abstract: To address the significant overhead of the beam training in millimeter wave (mmWave) wireless communications, we propose a balanced multimodal fusion network with bi-directional enhancement ...

Abstract: In order to effectively suppress the phenomenon of whistling in hearing aids, we propose the convex combination scheme of the proportionate adaptive feedback cancellation algorithm with ...

This study presents a bio-inspired control framework for soft robots, enhancing tracking accuracy by over 44% under disturbances while maintaining stability.

The integration of deep reinforcement learning with PD control in humanoid robots enhances gait stability and patient comfort ...

Reasoning large language models (LLMs) are designed to solve complex problems by breaking them down into a series of smaller ...

With the introduction of adaptive deep brain stimulation (aDBS) for Parkinson's disease, new questions emerge regarding who, why, and how to treat. This paper outlines the pathophysiological rationale ...