Data platforms make decisions all day. An SQL query keeps the rows over a threshold, matches a keyword, and joins two tables ...

When AI models fail to meet expectations, the first instinct may be to blame the algorithm. But the real culprit is often the data—specifically, how it’s labeled. Better data annotation—more accurate, ...

Databricks AI Runtime (AIR) is now Generally Available (GA), helping teams train and fine-tune models faster on serverless ...

In medical imaging and across R&D, the bottleneck is the data, not the model. A data-first case for governing, querying, and ...

In predictive modeling, future events are predicted based on statistical analysis. Read this guide to understand how predictive modeling works and how it can benefit your business. The rapid adoption ...

Self-supervised learning creates training targets from the structure of unlabeled data, allowing models to learn ...

AI is forcing a reckoning with a problem enterprises have been deferring. Organizations are sitting on vast, untapped data ...

A large language model (LLM) is a type of artificial intelligence algorithm that uses deep learning techniques and massively large data sets to understand, summarize, generate and predict new content.

AI success depends on whether enterprise data is ready, reachable, and close enough to the workloads that need it. In this eSpeaks episode, Dell Technologies’ Vrashank Jain explains why fragmented ...

Biohub, the Department of Energy, NIH, Google DeepMind, Isomorphic Labs, Meta, and other partners have committed $1.8 billion to generate open, AI-ready biological data for building predictive models ...