Author: Dean Takahashi / Source: VentureBeat
Nvidia loves the graphics processing unit (GPU), and all of the new kinds of computing it has enabled from self-driving cars to medical imaging devices. And venture capitalists are showing their love too, by investing in GPU computing startups.
Jeff Herbst, vice president of business development at Nvidia, said in an interview that he was encouraged at how big the ecosystem has grown for GPU computing investments. Herbst was host to a couple of hundred VCs and entrepreneurs at the GTC 2018 event in San Jose, California. The luncheon was several times bigger than last year’s event.
“They get it now,” Herbst said. “It’s great to see so many VCs here. It’s no longer a risk to see your companies build on top of the GPU platform. I think it’s a necessity. It’s real. It’s past its inflection point. The train has left the station.”
Nvidia introduced programmability to its graphics processors in 2001, inventing the GPU. Then it created the CUDA programming language in 2006, to enable programmers to run non-graphics software on the GPU, which had the advantage of having lots of parallel processors. That led to a huge wave of GPU growth, and there are now more than 820,000 CUDA programmers. CUDA has been downloaded 8 million times, and there are 350 applications.
Much of that happened because of advances in deep learning neural networks, which in the past five years have made huge strides in recognizing non-structured data such as images of flowers. Now deep learning software running on a GPU can recognize a flower in just about any photo.
Many VCs are investing in hardware rivals to Nvidia. Some are creating chips that are custom-designed for deep learning. But Herbst said he was…
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