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AI has the potential to transform nearly every sector – from enhanced medical diagnostics, industrial automation and safety at work to increased innovation and greater productivity. However, 88% of AI proof of concepts don’t make it to production deployment. While optimism is high, skyrocketing costs and complexity to support and scale AI continues to be a challenge. But it doesn’t have to be this way.
At NeuReality, we saw early on that even if the GPU evolution is happening at breakneck speed, the efficacy of this is lost if the head node can’t keep up. The head node must be re-imagined from the ground up to deliver the orchestration and resource management to distributed GPU setups in data center environments. AI systems need to be purpose-built, not just repurposed. This was our goal with the NR1 AI-CPU: to create a purpose-built heterogeneous AI head node that can host any GPU and deliver a scalable, energy-efficient inference system with great performance at a lower cost.
Demand continues to grow for AI-ready data center infrastructure to power inference at scale, from industries including financial services and health and life sciences. Our work with Arm has played a huge role in our success with NR1 – success that we look forward to building on as we now begin to introduce our next generation NR2 chip.
