For most enterprises, that advantage in enterprise AI lives in unstructured data: the contracts, case files, product specifications, and internal knowledge.

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.

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 ...

The shift to service as software will bring learning curve advantages, software-like marginal economics, and winner-take-most dynamics to all companies across every industry, not just tech vendors. We ...

Is it possible for an AI to be trained just on data generated by another AI? It might sound like a harebrained idea. But it’s one that’s been around for quite some time — and as new, real data is ...

Small Language Models (SLM) are trained on focused datasets, making them very efficient at tasks like analyzing customer feedback, generating product descriptions, or handling specialized industry ...

In the rapidly evolving landscape of modern manufacturing and engineering, a new technology is emerging as a crucial enabler-Data-Model Fusion (DMF). A recent review paper published in Engineering ...

AI has become the control plane of financial services, shaping fraud decisions, AML alerts, credit limits, pricing strategies and collections. Yet many banks and fintechs still view these systems as ...