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 ...

How do you fix the very real problem of missing or flawed data in healthcare? Just make new data, says a leading academic. But is it as simple as that? In my previous reports on the challenges of ...

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 ...

As AI becomes more common and decisions more data-driven, a new(ish) form of information is on the rise: synthetic data. And some proponents say it promises more privacy and other vital benefits. Data ...

In the rapidly evolving landscape of the finance industry, the advent of synthetic data stands out as a groundbreaking development to revolutionize the way financial institutions harness data for ...

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 ...

As AI companies start running out of training data, many are looking into so-called “synthetic data” — but it remains unclear whether such a thing will ever work. But while companies like Anthropic, ...