http://simonwillison.net/2024-01-16T18:49:03+00:00Simon Willison2024-01-16T18:49:03+00:002024-01-16T18:49:03+00:00https://simonwillison.net/2024/Jan/16/daniel-situnayake/#atom-tag

<blockquote cite="https://news.ycombinator.com/item?id=39016433"><p>You likely have a TinyML system in your pocket right now: every cellphone has a low power DSP chip running a deep learning model for keyword spotting, so you can say "Hey Google" or "Hey Siri" and have it wake up on-demand without draining your battery. It’s an increasingly pervasive technology. [...]</p> <p>It’s astonishing what is possible today: real time computer vision on microcontrollers, on-device speech transcription, denoising and upscaling of digital signals. Generative AI is happening, too, assuming you can find a way to squeeze your models down to size. We are an unsexy field compared to our hype-fueled neighbors, but the entire world is already filling up with this stuff and it’s only the very beginning. Edge AI is being rapidly deployed in a ton of fields: medical sensing, wearables, manufacturing, supply chain, health and safety, wildlife conservation, sports, energy, built environment—we see new applications every day.</p></blockquote> <p class="cite">&mdash; <a href="https://news.ycombinator.com/item?id=39016433">Daniel Situnayake</a></p> <p>Tags: <a href="https://simonwillison.net/tags/machine-learning">machine-learning</a>, <a href="https://simonwillison.net/tags/ai">ai</a>, <a href="https://simonwillison.net/tags/tinyml">tinyml</a>, <a href="https://simonwillison.net/tags/ai-energy-usage">ai-energy-usage</a></p>

2024-01-16T18:46:02+00:002024-01-16T18:46:02+00:00https://simonwillison.net/2024/Jan/16/daniel-situnayake-explains-tinyml-in-a-hacker-news-comment/#atom-tag

<p><strong><a href="https://news.ycombinator.com/item?id=39016433">Daniel Situnayake explains TinyML in a Hacker News comment</a></strong></p> Daniel worked on TensorFlow Lite at Google and co-wrote the TinyML O’Reilly book. He just posted a multi-paragraph comment on Hacker News explaining the term and describing some of the recent innovations in that space.</p> <p>“TinyML means running machine learning on low power embedded devices, like microcontrollers, with constrained compute and memory.” <p>Tags: <a href="https://simonwillison.net/tags/machine-learning">machine-learning</a>, <a href="https://simonwillison.net/tags/ai">ai</a>, <a href="https://simonwillison.net/tags/tinyml">tinyml</a></p>