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 ...

Synthetic data generation has emerged as a crucial technique for addressing various challenges, including data privacy, scarcity and bias. By creating artificial data that mimics real-world datasets, ...

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.

AI scaling faces diminishing returns due to the growing scarcity of high-quality, high-entropy data from the internet, pushing the industry towards richer, synthetic data. Nvidia is strategically ...

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 ...

Forbes contributors publish independent expert analyses and insights. Writes about the future of finance and technology, follow for more. We live in a world where machines can understand speech, ...

A new framework restructures enterprise workflows into LLM-friendly knowledge representations to improve customer support automation. By introducing intent-based reasoning formats and synthetic ...

In September 2022, Deutsche Bank’s Corporate Venture Capital group made an investment in Synthesized, a UK-based synthetic data company. At the time, the companies said that through synthetic, ...

The integration of bioinformatics, machine learning and multi-omics has transformed soil science, providing powerful tools to ...