Mythic can do an 8-bit multiply and add in a single transistor

2020-10-17: AI Analog Compute

Mythic is the first and only company that have been able to implement a deep learning model like ResNet 50 in a non-digital architecture: > 50 layers, 1000 fps, 3W total, 9->2ms latency, 8 TOPS/W in 40nm silicon. 10x cost advantage over digital chips.

2023-04-11: Commercialization takes a long time

Mythic’s analog chip uses less power by storing neural weights not in SRAM but in flash memory, which doesn’t consume power to retain its state. And the flash memory is embedded in a processing chip, a configuration Mythic calls “compute-in-memory.” Instead of consuming a lot of power moving millions of bytes back and forth between memory and a CPU (as a digital computer does), some processing is done locally. Mythic’s success on that front has been variable: The company ran out of cash and raised $13 million in new funding and appointed a new CEO.
I asked him whether the state of analog computing today could be compared to that of quantum computing 25 years ago. Could it follow a similar path of development, from fringe consideration to common (and well-funded) acceptance?

It would take a fraction of the time. “We have our experimental results. It has proven itself. If there is a group that wants to make it user-friendly, within 1 year we could have it.” And at this point he is willing to provide analog computer boards to interested researchers, who can use them with Achour’s compiler.

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