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takyon [soylentnews.org] writes:

Here's a machine learning chip startup [nextplatform.com]:

Chip startups come and go. Generally, we cover them because of novel architectures or potential for specific applications. But in some cases, like today, it is for those reasons and because of the people behind an effort to bring a new architecture into a crowded, and ultimately limited, landscape.

With $100 million in "patience money" from a few individual investors who believe in the future of sparse matrix-based computing on low-power and reprogrammable devices, Austin-based Knupath [knupath.com], has spent a decade in stealth mode designing and fabricating a custom digital signal processor (DSP) chip to target deep learning training, machine learning-based analytics workloads, and naturally, signal processing. The company, led by famed NASA administrator Dan Goldin [wikipedia.org], has already fulfilled a $20 million contract for its first generation DSP-based system and has an interesting roadmap ahead, which will include the integration of FPGAs, among other devices.

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