Traditional approaches to autonomous vehicles (AVs) rely on using millions of miles of driving data in conjunction with even more miles of simulated data as inputs to supervised machine learning ...

Autonomous robots are moving beyond scripted motions and narrow task automation into a new era of adaptable, ...

Collaboration between materials scientists and data scientists helps identify patterns in growing thin films. (Nanowerk News) From cell phones to solar panels to quantum computers, thin films are ...

Advances in ADAS, from sensor fusion to AI integration to 4D radar, are being driven by cutting-edge SoCs facilitating the ...

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Abstract: Despite the advancements of autonomous systems from decades of engineering, there is always the need to make them even more efficient and reliable. Machine learning holds great potential to ...

Below are five AI-driven trends set to define telecom strategies in 2026. They collectively signal a shift from manual ...

Autonomous laboratories and AI-driven experimentation are increasingly transforming how scientific discovery is conducted in chemistry, materials science, ...