Spawning, a startup developing tools to enable creators to assert more control over their works online, is launching new, ostensibly more 'ethical' data sets for AI training.

Switzerland launched an open-source model called Apertus on Monday as an alternative to proprietary models like OpenAI’s ChatGPT or Anthropic’s Claude, reports SWI as spotted by Engadget. The model’s ...

One challenge of working with text data is that you need a large training data set to build robust models. You also need good, organic training data, which will be described in further detail in ...

Data scientists who are looking for high quality sets of curated data on which to train their machine learning models may want to check out CrowdFlower, which today unleashed a veritable treasure ...

A major AI training data set contains millions of examples of personal data Millions of images of passports, credit cards, birth certificates, and other documents containing personally ...

In the letter, Noyb noted that Meta only recently notified EU users on its platforms that they had until May 27 to opt their public posts out of Meta's AI training data sets.

All told, the training data set for the AFM models weighs in at about 6.3 trillion tokens. (Tokens are bite-sized pieces of data that are generally easier for generative AI models to ingest.) ...

For training AI, synthetic data uses a base data set of actual historical events or transactions and then creates a synthetic representation of that data and builds upon it.

In China, that resource is now powering an explosive new market—real-world AI training data sets—and investors are beginning to take notice.

In a step toward robots that can learn on the fly like humans do, a new approach expands training data sets for robots that work with soft objects like ropes and fabrics, or in cluttered environments.