AI models like OpenAI’s ChatGPT and Google’s Gemini have run out of training data, according to Goldman Sachs’ data chief.

Every company wants to make breakthroughs with AI. But if your data is bad, your AI initiatives are doomed from the start.

The downsides are real, but these aren't deal-breakers. Scaling data AI monetization with free models means owning the full ...

One of the biggest risks to any AI tool is data integrity. Cybersecurity is built on the CIA triad of confidentiality, ...

The most advanced Granite 4 model, Granite-4.0-H-Small, includes 32 billion parameters. It has a mixture-of-experts design ...

Cheaper AI models may be trained on outputs of older systems instead of fresh human data.

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 ...

Long-term weather forecasting is a difficult task, partly because weather systems are inherently chaotic. Though mathematical ...

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 ...

Even a wrong answer is right some of the time AI models often produce false outputs, or "hallucinations." Now OpenAI has admitted they may result from fundamental mistakes it makes when training its ...

Top U.S. cancer centers have launched a federated AI platform, letting models learn from patient data securely to accelerate ...

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.