Many "AI experts" have sprung up in the machine learning space since the advent of ChatGPT and other advanced generative AI constructs late last year, but Dr. James McCaffrey of Microsoft Research is ...

Learn about the most prominent types of modern neural networks such as feedforward, recurrent, convolutional, and transformer networks, and their use cases in modern AI. Neural networks are the ...

In real applications of Reinforcement Learning (RL), such as robotics, low latency, energy-efficient and high-throughput inference is very desired. The use of sparsity and pruning for optimizing ...

AI thrives on data but feeding it the right data is harder than it seems. As enterprises scale their AI initiatives, they face the challenge of managing diverse data pipelines, ensuring proximity to ...

Supervised learning, a popular tool in modern science and technology, thrives on huge amounts of labeled data. Physics-enhanced deep neural networks offer an effective solution to alleviate the data ...

An MIT spinoff co-founded by robotics luminary Daniela Rus aims to build general-purpose AI systems powered by a relatively new type of AI model called a liquid neural network. The spinoff, aptly ...