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 ...
Ranks among the top-performing agents on OpenAI's MLE-Bench and sets new performance milestones MUMBAI, India, Feb ...
When AI-powered prosthetic arms that move autonomously become widespread, understanding how people feel about them and accept them will be crucial. In a study appearing in Scientific Reports, ...
Advances in ADAS, from sensor fusion to AI integration to 4D radar, are being driven by cutting-edge SoCs facilitating the ...
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 ...
OneFii deploys customized AI-native enterprise systems for businesses, enabling 24/7 autonomous operations, scalable ...
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 ...