CoreWeave Pitches Open AI Cloud Stack Beyond GPU Access
The infrastructure provider is positioning itself in the full-stack AI cloud market by connecting training, inference and evaluation through a new development platform, arguing that success requires more than hardware alone.
Competing in the full-stack AI cloud space means offering far more than raw GPU capacity. Infrastructure vendors are now racing to bundle hardware with software tools, ecosystem partnerships and domain expertise to stand out from rivals.
CoreWeave Inc. is making this case with CoreWeave Forge, a newly launched development platform designed to link model training, inference and evaluation into a single workflow. The company wants teams to use production insights to refine their models and agents, 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 shared these thoughts during an appearance at the Fully Connected event, where she spoke with theCUBE Research's Dave Vellante and John Furrier in an exclusive broadcast on theCUBE, SiliconANGLE Media's livestreaming platform. The conversation centered on how CoreWeave combines GPU resources with an open development workflow, partner integrations and structured customer support.
Building a full-stack AI cloud from first principles
Rather than repurposing infrastructure built for earlier web applications, CoreWeave engineered its platform from the ground up specifically for AI workloads. 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 capabilities remain a critical component of the equation. CoreWeave was the first to deploy and test Nvidia Corp.'s Vera Rubin platform, and the company has earned SemiAnalysis' Platinum ClusterMAX rating for three consecutive periods. However, English contends that the real competitive advantage lies in the software layer above the silicon, where partner companies contribute tools, infrastructure and API integrations across a diverse set of 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 extends well beyond model training into production inference. The integrated platform combines compute, networking, storage, software and operational capabilities to handle AI workloads at scale. Customers have the flexibility to start with a single use case and expand from there, English explained.
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
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