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 ...

First, institutions must ensure that synthetic datasets are continuously recalibrated against fresh, real-world evidence. The ...

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 ...

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 ...

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 ...

This claim is made in the context of explaining that the limitation for AI (LLMs in particular) lies in the quality of data required to mimic intelligence—a limitation often referred to as the ...