Nature

Machine learning-driven metastructure design for sensor-free linearization of MEMS electrothermal actuators

This study presents a novel approach for achieving linear motion in thermal micro-actuators by integrating machine learning-assisted optimized mechanical metastructures into the system design.
Nature

Machine learning method predicting thermal performance of conformal cooling systems

The cooling system plays a critical role during the injection molding process, influencing both the molding cycle time and the quality of the final product. Conformal cooling channels are intricately ...
Interesting Engineering on MSN

New 'super-brain' learns laws of nature to fast-track optical component design

Researchers at Chalmers University of Technology have developed a machine learning system that learns ...
Semiconductor Engineering

EDA Makes A Frenzied Push Into Machine Learning

Machine learning is becoming a competitive prerequisite for the EDA industry. Big chipmakers are endorsing and demanding it, and most EDA companies are deploying it for one or more steps in the design ...
Semiconductor Engineering

Overcoming Regression Debug Challenges With Machine Learning

Development of a modern semiconductor requires running many electronic design automation (EDA) tools many times over the course of the project. Every stage, from architectural exploration and design ...
Android Police

Machine Learning: Everything you need to know

I’ve been covering Android since 2023, when I joined Android Police, mostly focusing on AI and everything around Pixel and Galaxy phones. I’ve got a bachelor’s in IT with a major in AI, so I naturally ...