AI thrives on data but feeding it the right data is harder than it seems. As enterprises scale their AI initiatives, they face the challenge of managing diverse data pipelines, ensuring proximity to ...

[Cal Bryant] hacked together a home automation system years ago, which more recently utilizes Piper TTS (text-to-speech) voices for various undisclosed purposes. Not satisfied with the ...

AIs built on Large Language Models have wowed by producing particularly fluent text. However, their ability to do this is limited in many languages. As the data and resources used to train a model in ...

Once upon a time, machine learning was an arcane field, the preserve of a precious few researchers holed up in grand academic institutions. Progress was slow, and hard won. Today, however, just about ...

As artificial intelligence developers run out of data to train their models, they are turning to “synthetic data” — data made by the A.I. itself. By Cade Metz and Stuart A. Thompson Cade Metz reports ...

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.

Maybe they should have called it DeepFake, or DeepState, or better still Deep Selloff. Or maybe the other obvious deep thing that the indigenous AI vendors in the United States are standing up to ...