We have explained the difference between Deep Learning and Machine Learning in simple language with practical use cases.

In late 1981, the legendary urban design expert Allan B. Jacobs was walking along a road in Tangshan, China, visiting a new housing development when he noticed improvised, hand-made grates covering ...

Key market opportunities in camera image signal processors include optimizing AI-driven processing for diverse conditions, meeting demands in automotive, medical, and smartphone sectors, and ...

The ability to anticipate what comes next has long been a competitive advantage -- one that's increasingly within reach for developers and organizations alike, thanks to modern cloud-based machine ...

AI (Artificial Intelligence) is a broad concept and its goal is to create intelligent systems whereas Machine Learning is a specific approach to reach the same goal.

This course covers three major algorithmic topics in machine learning. Half of the course is devoted to reinforcement learning with the focus on the policy gradient and deep Q-network algorithms. The ...

Machine learning is a subfield of artificial intelligence, which explores how to computationally simulate (or surpass) humanlike intelligence. While some AI techniques (such as expert systems) use ...

When a quantum computer processes data, it must translate it into understandable quantum data. Algorithms that carry out this 'quantum compilation' typically optimize one target at a time. However, a ...

Systems controlled by next-generation computing algorithms could give rise to better and more efficient machine learning products, a new study suggests. Systems controlled by next-generation computing ...

Artificial intelligence (AI) is transforming our world, but within this broad domain, two distinct technologies often confuse people: machine learning (ML) and generative AI. While both are ...