Data is the foundation of modern business strategy and the fuel for AI applications. It drives decision-making, optimizes operations, and creates personalized customer experiences, enabling businesses ...

Just as with LLMs, success in other frontiers of AI will require access to large volumes of high-quality data. That will ...

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 ...

Enterprises racing to deploy generative AI often focus on models. In practice, outcomes depend on how well organizations ...

“Knowledge is power,” and today’s businesses have access to more knowledge, in the form of digital data, to power their growth than ever before. Establishing a data-first corporate culture is key to ...

The rapid rise of generative artificial intelligence like OpenAI’s GPT-4 has brought remarkable advancements, but it also presents significant risks. One of the most pressing issues is model collapse, ...

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.

Yusuf Roohani, PhD, machine learning group lead at the Arc Institute, is among a team of researchers training artificial intelligence (AI) models with transcriptome data to predict how cell gene ...

Many drugs still fail after promising preclinical results, raising difficult questions about how disease is modelled in the ...