Currently, deep learning is the most important technique for solving many complex machine vision problems. State-of-the-art deep learning models typically contain a very large number of parameters ...

As artificial intelligence researchers exhaust the supply of real data on the web and in digitized archives, they are ...

In a recent study published in the journal Nature Medicine, researchers used diffusion models for data augmentation to increase the robustness and fairness of medical machine learning (ML) models in ...

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 ...

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 ...

In a time when health systems are struggling to gain meaningful insights from data – and simultaneously aware that safeguarding patient privacy is essential – synthetic data offers a lot of potential.

Jēnna Reese is CEO of Connect Centric, a D.C.-based firm that helps Fortune 500s and large nonprofits execute technology initiatives. In the race to modernize with AI, a new kind of risk is quietly ...

This article is part of a VB special issue. Read the full series here: The quest for Nirvana: Applying AI at scale. Artificial intelligence (AI) relies heavily on large, diverse and ...

Strict data privacy regulations have compelled companies to transition to using synthetic data, the ideal substitute for real data, containing similar insights and properties yet is more privacy-safe ...

Content provided by IBM and TNW. Babies learn to talk from hearing other humans — mostly their parents — repeatedly produce sounds. Slowly, through repetition and discovering patterns, infants start ...