CoreWeave positions open development loop as differentiator in AI cloud market
The infrastructure provider is moving beyond GPU access to offer integrated training, inference and evaluation capabilities, arguing that AI cloud success depends on openness across models, frameworks and platforms.
Competing in the AI cloud space increasingly hinges on more than raw compute power. Infrastructure vendors are racing to bundle hardware with software tools, partnerships and domain expertise to stand out in a crowded field.
CoreWeave Inc. is pursuing this strategy through CoreWeave Forge, a development platform announced recently that ties together model training, inference and evaluation. The company sees this integration as a way to capture insights from production systems and feed them back into model improvement, according to Jean English, CoreWeave's chief marketing officer.
We believe that the loop should be connected. It should be open to different models, different frameworks, different clouds.
Jean English, CoreWeave chief marketing officer
English made these remarks during an appearance at the Fully Connected event, where she spoke with theCUBE Research's Dave Vellante and John Furrier. The discussion covered how CoreWeave is combining GPU capacity with an open development loop, partner integrations and customer support.
Building a full-stack AI cloud from first principles
Rather than repurposing infrastructure built for earlier web applications, CoreWeave designed its platform specifically around AI workloads from the start. Customers migrating from competing cloud providers frequently report shortcomings in speed, performance, capacity or available tooling, English noted.
In this market, I think the AI era calls for building from first principles. That's why we are purpose-built. It was really built from the ground up … and I think that's why, when clients are with other clouds, they're not able to move as fast and able to get the performance they need.
Jean English
Hardware remains a critical component of this approach. CoreWeave was the first to deploy and validate Nvidia Corp.'s Vera Rubin platform, and the company recently received SemiAnalysis' Platinum ClusterMAX rating for the third consecutive time. Yet the real competitive advantage lies in the layers above the silicon, where partners contribute tooling, infrastructure and API connections to support diverse models.
It's so much beyond the GPU. It's about a full-stack AI cloud. That means that the tooling that we need, there's got to be other partners that we work with.
Jean English
CoreWeave's full-stack approach encompasses both training and inference workloads. The platform integrates compute, networking, storage, software and operational capabilities to handle AI systems in production environments. Customers typically start with a single use case before expanding.
https://www.youtube.com/embed/6mnvKbYL71Y?feature=oembed
A lot of customers right now are looking at inference. The model makers are definitely training big frontier models. The enterprises are working on the best use case to show results and impact, and it's not just, 'AI is driving a transformation.' It is, 'What is the use case?' that's relevant for my team.
Jean English