We've seen this repeated over and over: AI models are only as good as the data they’re trained on. The secret sauce is training your model on your proprietary data while ensuring that your data ...

AI initiatives don’t stall because models aren’t good enough, but because data architecture lags the requirements of agentic systems.

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.

If we want to avoid making AI agents a huge new attack surface, we’ve got to treat agent memory the way we treat databases: ...