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

Neural architecture search (NAS) and machine learning optimisation represent rapidly advancing fields that are reshaping the way modern systems are designed and deployed. By automating the process of ...

Some artificial intelligence models can already resemble the human brain even before having learned anything. This surprising finding comes from a study that challenges traditional approaches ...

Integrating quantum computing into AI doesn’t require rebuilding neural networks from scratch. Instead, I’ve found the most effective approach is to introduce a small quantum block—essentially a ...

Machine learning is transforming many scientific fields, including computational materials science. For about two decades, scientists have been using it to make accurate yet inexpensive calculations ...

As data privacy collides with AI’s rapid expansion, the Berkeley-trained technologist explains how a new generation of models ...

eSpeaks’ Corey Noles talks with Rob Israch, President of Tipalti, about what it means to lead with Global-First Finance and how companies can build scalable, compliant operations in an increasingly ...

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.

Theoretical physicists use machine-learning algorithms to speed up difficult calculations and eliminate untenable theories—but could they transform what it means to make discoveries? Theoretical ...

In AIoT-based systems, sensors continuously collect high-frequency data such as vibration, temperature, pressure, and electrical signals. These data streams are processed by machine learning and deep ...

Researchers in the Nanoscience Center at the University of Jyväskylä, Finland, have developed a pioneering computational ...