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

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.

There is more than one way to describe a water molecule, especially when communicating with a machine learning (ML) model, says chemist Robert DiStasio. You can feed the algorithm the molecule's ...

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

3. Timeliness and currency: Outdated information undermines AI performance. In fast-changing fields, models that rely on ...

AI projects are not for the faint-hearted – they need to be properly resourced with the different skills required: data ...

This study presents SynaptoGen, a differentiable extension of connectome models that links gene expression, protein-protein interaction probabilities, synaptic multiplicity, and synaptic weights, and ...

Pathology has long been the cornerstone of cancer diagnosis and treatment. A pathologist carefully examines an ultrathin ...

That’s the aim of predictive cyber resilience (PCR)—an emerging approach to security built on intelligence, automation and ...

Digital Twin of the Ocean is a continuously updated virtual counterpart of the real ocean that exchanges data in real time ...

In 2026, owning a domain won’t just be about staking a claim on the web. It will mean establishing trust, flexibility, and ...

EPFL researchers have developed new software—now spun-off into a start-up—that eliminates the need for data to be sent to third-party cloud services when AI is used to complete a task. This could ...