Leveraging silicon photonics for scalable and sustainable AI hardware
The emergence of AI has profoundly transformed numerous industries. Driven by deep learning technology and Big Data, AI requires significant processing power for training its models. While the existing AI infrastructure relies on graphical processing units (GPUs), the substantial processing demands and energy expenses associated with its operation remain key challenges. Adopting a more efficient and sustainable AI infrastructure paves the way for advancing AI development in the future.
Reinventing enterprise computing for the modern era, VMware CEO Raghu Raghuram Tuesday announced the availability of the VMware vSphere 8 enterprise workload platform running on NVIDIA DPUs, or data processing units, an initiative formerly known as Project Monterey. Placing the announcement in context, Raghuram and NVIDIA founder and CEO Jensen…
NVIDIA DGX Cloud — which delivers tools that can turn nearly any company into an AI company — is now broadly available, with thousands of NVIDIA GPUs online on Oracle Cloud Infrastructure, as well as NVIDIA infrastructure located in the U.S. and U.K. Unveiled at NVIDIA’s GTC conference in March,…
Artificial intelligence is reshaping our world – accelerating discovery, optimising systems, and unlocking new possibilities across every sector. But with its vast potential comes a shared responsibility. AI can be a powerful ally for transforming businesses and reducing cost. It can help organizations minimize carbon emissions, industries manage energy use,…