AI’s biggest constraint isn’t algorithms anymore. It’s data…specifically, high-quality, forward-looking data. It is the “Rare ...

So-called “unlearning” techniques are used to make a generative AI model forget specific and undesirable info it picked up from training data, like sensitive private data or copyrighted material. But ...

As AI adoption accelerates, enterprises are rethinking fragmented data architectures in favor of unified intelligence operating models.

Data access empowerment operating models enable public health leaders to make timely, informed decisions with trusted intelligence and faster insights.

A team of computer scientists at UC Riverside has developed a method to erase private and copyrighted data from artificial intelligence models—without needing access to the original training data.

Climate scientists are confronting a hard truth: some of the most widely used models are struggling to keep up with the pace and texture of real‑world warming. The physics at their core remains sound, ...

Is it possible for an AI to be trained just on data generated by another AI? It might sound like a harebrained idea. But it’s one that’s been around for quite some time — and as new, real data is ...

To feed the endless appetite of generative artificial intelligence (gen AI) for data, researchers have in recent years increasingly tried to create "synthetic" data, which is similar to the ...

Artificial intelligence (AI) systems are computational models that can learn to identify patterns in data, make accurate predictions or generate content (e.g., texts, images, videos or sound ...

The artificial intelligence industry is obsessed with size. Bigger algorithms. More data. Sprawling data centers that could, in a few years, consume enough electricity to power whole cities. This ...