It's not just about making AI smarter, but also about making sure people can trust it and understand how it works.

One decision many enterprises have to make when implementing AI use cases revolves around connecting their data sources to the models they’re using. Different frameworks like LangChain exist to ...

A new kind of large language model, developed by researchers at the Allen Institute for AI (Ai2), makes it possible to control how training data is used even after a model has been built.

Learn how systems engineering is shifting from document-centric practices to model-based, data-driven approaches that reduce ...

Discover how financial firms are leveraging synthetic data and AI to improve forecasting, risk modeling, and decision-making in the face of complex markets.

A new crowd-trained way to develop LLMs over the internet could shake up the AI industry with a giant 100 billion-parameter model later this year. Flower AI and Vana, two startups pursuing ...

So-called “unlearning” techniques are used to make a generative AI model forget specific and undesirable info it picked up from training data, like sensitive private data or copyrighted material. But ...

AI needs human data to function effectively, but the internet is becoming flooded with AI-generated content. Artificial intelligence has revolutionized everything from customer service to content ...