The quality, quantity, and diversity of training data are crucial for the accuracy and generalization of AI models. Poor or insufficient data can lead to inaccurate models or overfitting, where ...

AI systems are increasingly being integrated into safety- and mission-critical applications ranging from automotive to health care and industrial IoT, stepping up the need for training data that is ...

Anthropic is making some major changes to how it handles user data. Users have until September 28 to take action.

AI may feel invisible. Just a few keystrokes and a quick reply from a chatbot. But behind the scenes, it is powered by ...

DataSum focuses on ethical guidelines, methodologies and standards to help ensure responsible, transparent and unbiased AI training data.

Meta's efforts to placate Europe over the use of personal data to train AI models hasn't worked, with privacy advocacy group noyb launching another challenge. After pausing AI training in the EE and ...