As artificial intelligence models continue to evolve at ever-increasing speed, the demand for training data and the ability to test capabilities grows alongside them. But in a world with equally ...

Slator’s Data-for-AI Market Report identifies this shift as a structural change in the AI value chain, where competitive ...

Enterprise AI deployment increasingly operates under strict governance constraints, where privacy regulation, data provenance ...

The weird, rare, surprising patterns that make data rich slowly get smoothed out when an AI model trains on outputs from a ...

Mantis takes disparate sources of data to make synthetic datasets that can be used to build so-called "digital twins" of the ...

Nvidia has once again solidified its position as the undisputed leader in AI innovation with the release of "Nemotron-4 340B," a groundbreaking family of open models that is set to revolutionize the ...

We used Tonic Fabricate to generate a fully synthetic email corpus, then RL fine-tuned an open-source model against it. The ...

As more companies invest in generative AI (gen AI) for bespoke use cases and products, proprietary data is becoming increasingly important to training large language models (LLMs). Unlike ChatGPT, ...

Companies can’t avoid working with data, but management of that data can pose serious challenges. Customer and other personal data keep escaping, courtesy of breaches that surged 78% last year in the ...

Sajal works at Kyndryl, advises startups, ex-Innovation Expert for UN Compact and member, EU Commission's Apply AI Alliance. The AI industry is bound to face a paradox. Synthetic data can democratize ...