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 ...

Abstract: Reconfigurable Intelligent Surfaces (RIS) have gained significant attention as a promising solution to enhance wireless communication performance through controllable electromagnetic ...

Abstract: In this paper, a second-order Volterra adaptive filtering algorithm based on natural gradient descent (SOVNGD) is proposed. Compared to the conventional second-order Volterra (SOV) algorithm ...

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 ...

A new study reveals that the next generation of blockchain defenses will not rely on fixed rules alone but on adaptive, ...

More engineers are turning to reinforcement learning to incorporate adaptive and self-tuning control into industrial systems.