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SemiEngineering: Why TinyML is Such a Big Deal

By Anoop Saha

Excerpt from article: “Why TinyML is Such a Big Deal

“If you just compile everything onto the controller, even at the bare metal level, it will be more energy-efficient,” said Anoop Saha, market development manager at Siemens EDA.

“Because of Moore’s Law, every couple of years we have more powerful chips,” observed Saha. “So if you just wait it out, we’ll be able to run an algorithm on tiny devices.”

But fragmentation has its downsides. “The problem with TinyML is that the market is so fragmented that it cannot be economically viable to build a single IoT-specific chip,” Saha pointed out. According to him, that may mean composing systems out of smaller sub-system chips for things like the radio or security.

When it comes to ML, he notes, “The better choice is to build an accelerator, which will be cheaper, and the chances of success are higher and better as well.”

Read the entire article on SemiEngineering originally published on September 2nd, 2021.

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This article first appeared on the Siemens Digital Industries Software blog at https://blogs.sw.siemens.com/hlsdesign-verification/2021/09/03/tinyml-is-aimed-at-implementing-machine-learning-on-severely-resource-constrained-systems-its-both-a-concept-and-an-organization-and-it-has-acquired-significant-momentum-over-the-l/