As artificial intelligence models continue to evolve at ever-increasing speed, the demand for training data and the ability to test capabilities grows alongside them. But in a world with equally ...

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

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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 ...

AI is always hungry. To clarify, the smartness in Artificial Intelligence (AI) is a factor of how much data we allow our AI ‘engines’ to ingest and how well the datasets that comprise that data ...

With the rise of generative AI, synthetic images and text have become common knowledge -- but are you familiar with synthetic data? As the name implies, the term refers to data that is artificially ...

Where real data is unethical, unavailable, or doesn’t exist, synthetic data sets can provide the needed quantity and variety. Devops teams aim to increase deployment frequency, reduce the number of ...

AI and ML algorithms rely heavily on vast data for training and development. However, the availability of high-quality, diverse, and secure data can be a significant challenge. In fact, upon not being ...

Synthesis AI, a startup developing a platform that generates synthetic data to train AI systems, today announced that it raised $17 million in a Series A funding round led by 468 Capital with ...