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.

CERES program updates include operational satellite instruments, algorithm advancements, machine learning applications, and ongoing missions measuring Earth’s energy budget and climate system changes.

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 ...

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 Timeliness and currency: Outdated information undermines AI performance.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 ...

As data privacy collides with AI’s rapid expansion, the Berkeley-trained technologist explains how a new generation of models is learning without crossing ethical lines.

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

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

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

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

Research reveals why AI systems can't become conscious—and what radically different computing substrates would be needed to ...