CoreWeave to Acquire Weights & Biases, Expanding AI Developer Platform

Mar 5, 2025
CoreWeave has announced its agreement to acquire Weights & Biases, aiming to create an end-to-end platform for AI labs and enterprises, according to a press release.
CoreWeave to Acquire Weights & Biases, Expanding AI Developer Platform

CoreWeave has announced it will acquire Weights & Biases, a leading AI developer platform, announced in a press release. This acquisition aims to enhance CoreWeave's cloud platform by providing an end-to-end experience for AI labs and enterprises, facilitating faster market entry for new innovations.

The integration of CoreWeave's infrastructure and managed cloud services with Weights & Biases' platform will offer a comprehensive application development workflow. This combination is expected to accelerate AI roadmaps and improve the development, tuning, and deployment of AI applications. CoreWeave plans to maintain the existing functionality of Weights & Biases while introducing new innovations to the platform.

Founded in 2017, Weights & Biases has become a prominent player in the MLOps and LLMOps space, with its platform used by over 1 million AI engineers. The acquisition is subject to customary closing conditions and regulatory approvals, with an expected completion in the first half of 2025.

We hope you enjoyed this article

Consider subscribing to one of our newsletters like AI Funding Brief, Silicon Brief or Daily AI Brief.

Also, consider following us on social media:

AI Funding News AI Chips & Datacenters AI Brief AI Brief (X)
Free newsletter

Silicon Brief

Weekly coverage of AI hardware developments including chips, GPUs, cloud platforms, and data center technology.

AI Token Webinar

Whitepaper

Tensordyne Napier: What If One Rack Could Do the Work of Nine?

Tensordyne

This Tensordyne whitepaper presents Napier, an inference-focused AI processor and rack-scale system based on the company’s TDN Math logarithmic number system. It examines infrastructure requirements for large mixture-of-experts and agentic models, compares major inference architecture approaches, and details the TDN AIP processor, TDN72 pod, TDN Link fabric, and Napier Ultra configuration. The paper reports simulation-based performance, cost, and accuracy-validation results, including Tensordyne’s projected comparison of one Napier rack with a nine-rack Nvidia Rubin plus Groq deployment; the chip is reported as taped out and in fabrication.

Read more

You may also like

Free, six days a week

Daily AI Brief: the AI news that matters, in your inbox.