I've posted two articles about synthetic data, both highly skeptical about the hype surrounding it. In Can synthetic data bridge the AI training data gap? (July 2021), I wrote: The problem of ...

In today’s data-driven world, enterprises face an ever-growing demand for data to fuel their operations, from testing to machine learning and AI. Yet, collecting high-quality, diverse and ...

While many organizations are experimenting with synthetic data, few are focusing on scalability and building AI-ready data ...

Meta CEO Mark Zuckerberg thinks 'feedback loops,' the process of AI learning from its own outputs, are more important than new data for developing AI.

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 ...

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 ...

* The Matrix analogy: Are we training AI inside simulations? Whether you're a data scientist, CTO, or just curious about how AI models learn, this episode offers a deep dive into one of the most ...