I know I have referenced this before, but it looks like Graphcore could be a competitor in the automotive ADAS industry, with their IPU, which also seems to be capable of autonomous recognition.
“... To test out its IPU prototype, the team fed it a standard data-training model of millions of labeled images of common objects (fruits, animals, cars). An engineer then queried the IPU with a photo of his own cat, Zeus, and within an hour the computer not only identified it correctly but correctly described Zeus’ coat. “The IPU was able to recognize it as a tabby,” Knowles says. Since that first test, the IPU has sped up and can now recognize more than 10,000 images per second.”
How many images can Akida recognise per second and what advantages would an Akida ASIC have over such an IPU?
Tobias Jahn, principal investor at BMW’s venture capital arm, envisions Graphcore chips in the automaker’s data centers and perhaps its cars. “BMW has an interest in Graphcore becoming a large-scale, worldwide silicon supplier,” Jahn says. The immediacy with which autonomous vehicles must execute so many critical tasks makes them a key market for something like an IPU, given the lag time that so often accompanies work in the cloud. Arm Holdings co-founder Hauser, now a partner at Amadeus Capital, estimates that each driverless car may need two IPUs.”
”..Graphcore has a good position, but it’s still a very small competitor compared to Nvidia’s market presence. So although their IPUs may be better than Nvidia’s GPUs for these workloads, the risk they face is customers choosing ‘good enough’ over ‘brilliant.’ ”
Could BRN’s Akida ASIC when produced by Socionext, face a similar situation?
Could it also compete with the processing power of something like Graphcore’s IPU?
https://www.bloomberg.com/news/articles/2019-06-05/graphcore-s-ai-chips-could-kickstart-the-next-wave-of-computing
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