Researchers have developed photonic computing chips that overcome key limitations for a type of neural network known as a photonic spiking neural system. By enabling fast learning and decision making ...

As we move into the next era of digital ecosystems, the transition from automation to autonomy requires a complete ...

The rapid rise of electric vehicles combined with breakthroughs in autonomous driving technology is reshaping the future of ...

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 ...

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 ...

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 ...

The traditional approach to artificial intelligence development relies on discrete training cycles. Engineers feed models vast datasets, let them learn, then freeze the parameters and deploy the ...

Ranks among the top-performing agents on OpenAI's MLE-Bench and sets new performance milestones MUMBAI, India, Feb ...

How are AI Agents transforming DeFi? From autonomous risk management to liquidity optimization and smart contract security, ...

Ranks among the top-performing agents on OpenAI's MLE-Bench and sets new performance milestonesNEW YORK, Feb. 24, 2026 /PRNewswire/ -- Fractal ( a publicly listed global enterprise ...