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 ...

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.

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, ...

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 ...

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, ...

Global tech executives are racing to deploy autonomous agents over the next two years, but in doing so they face a balancing act: How do you leverage data in a way that maximizes trust and confidence ...

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 ...