Machine learning at the edge: TinyML is getting big. Featuring Qualcomm Senior Director Evgeni Gousev, Neuton CTO Blair Newman and Google Staff Research Engineer Pete Warden artwork
Orchestrate all the Things podcast: Connecting the Dots with George Anadiotis

Machine learning at the edge: TinyML is getting big. Featuring Qualcomm Senior Director Evgeni Gousev, Neuton CTO Blair Newman and Google Staff Research Engineer Pete Warden

  • S2E21
  • 1:05:33
  • June 7th 2021

Being able to deploy machine learning applications at the edge is the key to unlocking a multi-billion dollar market. TinyML is the art and science of producing machine learning models frugal enough to work at the edge, and it's seeing rapid growth.

Edge computing is booming. Although the definition of what constitutes edge computing is a bit fuzzy, the idea is simple. It's about taking compute out of the data center, and bringing it as close to where the action is as possible.

Whether it's stand-alone IoT sensors, devices of all kinds, drones, or autonomous vehicles, there's one thing in common. Increasingly, data generated on the edge are used to feed applications powered by machine learning models.

There's just one problem: machine learning models were never designed to be deployed on the edge. Not until now, at least. Enter TinyML.

Tiny machine learning (TinyML) is broadly defined as a fast growing field of machine learning technologies and applications including hardware, algorithms and software capable of performing on-device sensor data analytics at extremely low power, typically in the mW range and below, and hence enabling a variety of always-on use-cases and targeting battery operated devices.

Article published on ZDNet

Orchestrate all the Things podcast: Connecting the Dots with George Anadiotis

I've got tech, data, and media, and i'm not afraid to use them.

My name is George Anadiotis, and i am a writer, a planner and a doer. I am an Onalytica Top 100 Influencer in Big Data and Cloud, a Knowledge Graph expert, and a P2P Foundation and ZDNet contributor, among other things.

Linked Data Orchestration is my brand. This podcast is where i share my work, as well as conversations with people who bring interesting news and views to the table.

Some might call this futurism; let's just say it's connecting the dots.

Coming from a technology background, i've had the chance to learn to play many instruments on the way to becoming a one man band and an orchestrator.

Before starting a career as an analyst and journalist, i served Fortune 500, startups and NGOs as a consultant, built and managed projects, products and teams of all sizes and shapes, and got involved in award-winning research. I still try to do that stuff as much as possible.