AMD to Acquire World Labs to Advance the Future of AI Compute

AMD announced that it has entered into a definitive agreement to acquire World Labs, an AI model and research lab led by AI pioneer Dr. Fei-Fei Li.The acquisition will bring a world-class team of researchers and model experts to AMD, strengthening its ability to develop AI hardware, software and systems around the needs of emerging models and applications.

As AI expands into reasoning, robotics, simulation and physical AI, the demands on compute infrastructure become more diverse. World Labs‘ expertise in developing advanced models will give AMD deeper insight into how workloads are evolving and help shape its future technology roadmaps. The acquisition advances AMD’s strategy to deliver AI infrastructure for an open ecosystem.

“Building the compute platforms for the next gen of AI requires a deep understanding of how models are evolving,” said Dr. Lisa Su, chair and CEO, AMD. “Fei-Fei and the World Labs team bring exceptional research leadership and model expertise. Together, we can use that insight to develop the hardware, software and systems that will power the next gen of AI and strengthen the open AI ecosystem.”

“Advancing the next generation of AI technology requires close collaboration across model research, systems and compute,” said Dr. Fei-Fei Li, co-founder and CEO, World Labs. “Joining AMD will give our team the resources and engineering depth to accelerate our research and help define the infrastructure needed for the next era of AI.”

Headquartered in San Francisco, World Labs develops spatial-intelligence models that generate, reconstruct and simulate interactive 3D environments from text, image and video inputs, as well as technology for robotic learning and simulation. Following the close of the transaction, the World Labs team will continue to focus on advancing AI model research, and Dr. Fei-Fei Li will join AMD as executive VP and chief scientist, reporting to Dr. Lisa Su.

The all-stock transaction is valued at approximately $8.2 billion and is expected to close by the end of 2026, subject to regulatory approvals and other customary closing conditions.

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As stated above, AMD signed a definitive agreement to buy World Labs, Dr. Fei-Fei Li's San Francisco AI lab. The deal is all-stock, valued at about $8.2B, and is expected to close by end-2026 pending regulatory approval. World Labs builds spatial-intelligence models that generate, reconstruct and simulate interactive 3D environments from text, image and video inputs, and it also works on robotic learning and simulation.

Fei-Fei Li will become AMD EVP and Chief Scientist, reporting to Lisa Su, and the team will keep doing model research. AMD's rationale is that AI is moving into reasoning, robotics, simulation and physical AI, so having model expertise in-house will help it design hardware, software and systems around future workloads. AMD frames this as part of its "open AI ecosystem" strategy.

The deal grew out of an existing partnership. World Labs says the two companies began working together last year on training and inference optimization on AMD GPUs. AMD was also already an investor: AMD Ventures invested in the Series B and again in the $1B round announced in February, alongside Autodesk, Emerson Collective, Fidelity, Nvidia and Sea.

AMD is buying a research group, not a product line. Justin Johnson and Ben Mildenhall will continue to lead the team as an AMD frontier research organization. The World Labs blog stresses open models. AMD's announcement says nothing about Marble or the World API as commercial products, so their future is an open question.

It mirrors Nvidia's approach. This is AMD's second AI acquisition in two months, after Taalas, a Toronto start-up building model-specific chips, as AMD's MI455X and 72-GPU Helios rack go up against Nvidia's Vera Rubin. Taalas brought silicon and World Labs brings models, which is the co-design loop Nvidia has used to its advantage.

On the infrastructure aspect, World models and 3D simulation consume large amounts of data. That points to future demand for storage and memory bandwidth in Helios-class systems, which is worth watching for storage vendors.