The discovery that led Nir Shavit to start a company came about the way most discoveries do: by accident. The MIT professor was working on a project to reconstruct a map of a mouse’s brain and needed some help from deep learning. Not knowing how to program graphics cards, or GPUs, the most common hardware choice for deep-learning models, he opted instead for a central processing unit, or CPU, the most generic computer chip found in any average laptop.
“Lo and behold,” Shavit recalls, “I realized that a CPU can do what a GPU does—if programmed in the right way.”
This insight is now the basis for his startup, Neural Magic, which launched its first suite of products today. The idea is to allow any company to deploy a deep-learning model without the need for specialized hardware. It would not only lower the costs of deep learning but also make AI more widely accessible.
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