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CoreWeave targets GPU utilization in continuous AI post-training

Credited to SiliconANGLE · siliconangle.com · 23h ago

Photograph · SiliconANGLE

GPU utilization during post-training depends partly on how efficiently infrastructure moves data and loads updated models. As enterprises continually refine AI agents, reducing delays between training rounds can help keep that process moving.

The need for continual improvement is pushing CoreWeave Inc. to build a full-stack AI cloud for the agent lifecycle. You.com Inc. provides web search tools for those agents, according to Saurabh Sharma (pictured, right), chief product officer of You.com.

“What we’re seeing is that the ceiling is no longer model intelligence,” Sharma said. “The models are getting more intelligent, but it’s their ability to use the tools that dictates the agent’s success.”

Sharma and Corey Sanders (left), senior vice president of product at CoreWeave, spoke with theCUBE Research’s Dave Vellante and John Furrier at the Fully Connected event, during an exclusive broadcast on theCUBE, SiliconANGLE Media’s livestreaming studio. They discussed tool skills, graphics processing unit utilization and continuous model improvement. (* Disclosure below.)

Post-training puts GPU utilization at the heart of the AI loop

CoreWeave has announced CoreWeave Forge, which connects model deployment, evaluation and improvement. Its reinforcement learning Rollouts capability, currently in preview, supports repeated cycles of generating training responses and updating models, Sanders explained.

“For the weight synchronization, this is an area that we’ve done a bunch of work to be able to bring the weights in sort of a hot start versus starting cold every time,” Sanders said. “Instead of the weight always coming from object storage, we now get weights from other peers nearby.”

Data movement also matters when the goal is keeping GPU utilization high between training rounds. CoreWeave AI Object Storage now supports cross-region writes, letting post-training jobs write results back for others to use, according to Sanders.

“There actually is core infrastructure like our object storage, which we’ve built around trying to get data into the GPU as fast and as easy as possible,” Sanders said. “You write like it’s a local machine. We treat it like it’s a global system.”

You.com, which runs its own web index, has joined CoreWeave’s partner network to give agents a search layer. Working with Nvidia, the companies used RL Rollouts to post-train Nemotron 3.5 Lightning in eight hours with You.com’s web search tools.

“What our customers are seeing is that … they are able to run their workloads with higher accuracy and lower total cost of ownership,” Sharma said. “If you can do this in eight hours, this is no longer something that only the frontier labs can do.”

Here’s the complete video interview, part of SiliconANGLE’s and theCUBE’s coverage of the Fully Connected event:

(* Disclosure: TheCUBE is a paid media partner for the Fully Connected event. Neither CoreWeave, the sponsor of theCUBE’s event coverage, nor other sponsors have editorial control over content on theCUBE or SiliconANGLE.)

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Applied Materials, Intel Partner on Next-Generation Chip Manufacturing Technology

Credited to TheElec · thelec.net · Just now

Applied Materials is partnering with Intel to develop next-generation semiconductor manufacturing technologies.

Applied Materials stated on October 6 that Intel has joined the Applied EPIC Center as a founding partner. The two companies will jointly research and develop process technologies and equipment across the front-end-of-line (FEOL), back-end-of-line (BEOL), and packaging stages of semiconductor manufacturing.

The collaboration is aimed at supporting higher interconnect density, improved power delivery, and enhanced thermal performance for high-performance computing (HPC) platforms. HPC platforms refer to integrated computing systems designed to support workloads suited to agentic artificial intelligence (AI).

The EPIC Center is a joint research and development facility for equipment and process innovation and commercialization being established in Silicon Valley. It aims to shorten the time required to commercialize semiconductor technologies, from the research stage to mass production.

Specifically, the companies will collaborate on new materials for next-generation logic processes, device architectures, and advanced interconnect processes, as well as Foveros-based 3D-stacking packaging processes. Applied Materials will provide Intel with a dedicated secure space inside the EPIC Center. Intel will connect infrastructure at its research and development campus in Hillsboro, Oregon, with the EPIC Center.

Gary Dickerson, chairman and chief executive officer (CEO) of Applied Materials, said, “Applied Materials and Intel have worked closely together for decades, pushing the boundaries of materials engineering to advance semiconductor technology.” He added, “With our teams working together at the EPIC Center, we will accelerate innovations in devices, interconnects, and packaging that will shape the future of AI computing.”

Lip-Bu Tan, Intel CEO, said, “Intel is working closely with partners across the ecosystem to drive innovation in performance, power efficiency, and packaging as demand for AI computing grows.” He added, “We look forward to expanding our collaboration at the Applied EPIC Center and accelerating the path from research in the US to high-volume manufacturing.”

The EPIC Center has more than 10 participating companies and organizations, including Samsung Electronics, SK hynix, Micron Technology, TSMC, and Broadcom. The facility is in the final stages of preparations for operations. Its opening ceremony is scheduled for October 12. A total investment of 7 trillion won will be made in stages.