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tinyML Tutorials 101

tinyML Summit 2020

Enabling ultra-low Power Machine Learning at the Edge

February 12-13, 2020

San Jose, California

About the tinyMLTM Summit

Following the success of the inaugural tinyML Summit 2019, the tinyML committee invites low power machine learning experts from the industry, academia, start-ups and government labs from all over the Globe to join the tinyML Summit 2020 to share the “latest & greatest” in the field and to collectively drive the whole ecosystem forward.

Tiny machine learning is broadly defined as a fast growing field of machine learning technologies and applications including hardware (dedicated integrated circuits), algorithms and software capable of performing on-device sensor (vision, audio, IMU, biomedical, etc.) 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. The inaugural tinyML Summit in March 2019 showed very strong interest from the community with active participation of senior experts from 90 companies. It revealed that: (i) tiny machine learning capable hardware is becoming “good enough” for many commercial applications and new architectures (e.g. in-memory compute) are on the horizon; (ii) significant progress on algorithms, networks and models down to 100kB and below; and (iii) initial low power applications in the vision and audio space. There is growing momentum demonstrated by technical progress and ecosystem development.

tinyML Summit 2020 will continue the tradition of high quality invited talks, poster and demo presentations, open and stimulating discussions, and significant networking opportunities. It will cover the whole stack of technologies (Systems-Hardware-Algorithms-Software-Applications) at the deep technical levels, a unique feature of the tinyML Summits. While the majority of the participants and speakers will come from industry, leading edge academic research will be represented as well as an important ingredient of the evolving tiny machine learning ecosystem. In 2020, special attention will be given to recent progress on algorithm development and tiny machine learning use-cases and applications. The program will be organized in four technical sessions: Hardware, Systems, Algorithms & Software, and Applications. There will be approximately twenty invited presentations selected by the Technical Program Committee and dedicated poster sessions and demos by tiny machine learning companies and sponsors. Overview and hands-on tutorials on hardware and software developments will be available the day before the main technical program starts. Registration will open in October 2019.


February 11 (Tuesday) Location: Qualcomm, 3195 Kifer Road, Building B, Santa Clara, CA


  • 7:30 am – 8:30 am

  • 8:30 am – 10:00 am

    NVIDIA Deep Learning Accelerator (NVDLA)

    Led by: Yilin Zhang, Senior Hardware Architect, NVIDIA

  • 10:00 am – 10:30 am

  • 10:30 am – 12:00 pm

    Algorithmic and SW Techniques for designing and implementing energy efficient CNNs

    Led by: Jinwon Lee, Senior Staff Engineer at Qualcomm AI Research

  • 12:00 pm – 1:00 pm

  • 1:00 pm – 2:30 pm

    tinyML SW frameworks for tinyML: TF-lite

    Led by: Pete Warden, Technical lead of the TensorFlow mobile and embedded team, Google

    This workshop will show you how to run a magic wand and other machine learning examples in the TensorFlow Lite for Microcontrollers framework.

  • 3:00 pm – 4:30 pm

    Enabling Intelligent edge devices with ultra low-power ARM MCUs and TensorFlow Lite

    Led by: Wei Xiao, Principal Evangelist, Arm AI Ecosystems

    Advances in processing power and machine learning algorithms enable us to run machine learning models on tiny far edge devices. Arm’s latest improvements in SIMD and DSP extensions as well as our collaboration with Google TensorFlow Lite team is pushing machine smarts to our tiniest micro-controllers used in intelligent wireless sensors.

    In this hands-on workshop, attendees will build a machine learning application with TensorFlow Lite Micro on Arm Cortex-M devices, then optimize our solution to unleash the unparalleled power of Arm microcontrollers.

  • Register for Tutorials here

February 11 (Tuesday) evening Location: To be announced

  • 6 pm - 9 pm

    VIP Reception For Summit Speakers, Panelists, Tutorial Instructors, Sponsors and Committee Members

February 12 (Wednesday) Location: Samsung, 3655 N First St, San Jose, CA

February 13 (Thursday) Location: Samsung, 3655 N First St, San Jose, CA


General Chairs:

Technical Program Committee:


Initial Speakers

(others to be announced):

Tutorial Leaders




2020 tinyML Summit Sponsors


tinyML Executive and Founders

Platinum Sponsors

Gold Sponsors

Silver Sponsors

Supporting Sponsors

Poster Abstract Guidelines

Submission for 2020 tinyML Summit Poster abstracts are closed.

Please contact Bette Cooper if you have any questions.


Due to high demand, event sponsors will have priority for demo tables to highlight their products and technology. A waiting list will be available for any remaining tables for those companies wishing to do a demo but are unable to become sponsors.

Venue & Accommodations


3655 N 1st St, San Jose, CA 95134



There have been no room block arrangements made at any hotel. The types and prices of properties vary greatly depending on what are you choose to stay. This link will provide you with many choices. On the left of the listings you may filter to put in your minimum/maximum price range, cancellation policies, etc. Search by zip code 95113.

Samsung rates may be available at the hotels below, but you must call them to ask what the rate is.

Walking distance to Samsung:

On the VTA (Valley Transportation Authority) light rail system:


tinyML book written by Pete Warden and Daniel Situnayake of Google

Neural networks are getting smaller. Much smaller. The OK Google team, for example, has run machine learning models that are just 14 kilobytes in size—small enough to work on the digital signal processor in an Android phone. With this practical book, you’ll learn about TensorFlow Lite for Microcontrollers, a miniscule machine learning library that allows you to run machine learning algorithms on tiny hardware.

read full description

Stanford University Seminar

Evgeni Gousev of Qualcomm and Pete Warden of Google participated in a panel at Stanford University seminar "Current Status of tinyML and the Enormous Opportunities Ahead".

read full article

AI at the Very, Very Edge (EE Times)

When the TinyML group recently convened its inaugural meeting, members had to tackle a number of fundamental questions, starting with: What is TinyML? TinyML is a community of engineers focused on how best to implement machine learning (ML) in ultra-low power systems. The first of their monthly meetings was dedicated to defining the issue.

read full article

TinyML Sees Big Hopes for Small AI (EE Times)

SUNNYVALE, Calif. – A group of nearly 200 engineers and researchers gathered here to discuss forming a community to cultivate deep learning in ultra-low power systems, a field they call TinyML. In presentations and dialogs, they openly struggled to get a handle on a still immature branch of tech’s fastest-moving area in hopes of enabling a new class of systems.

read full article


We currently have two tinyML groups called tinyML: Enabling ultra-low power ML at the Edge: a Bay Area group and an Austin, TX group.

The meetups are designed to be an informal gathering of people interested in various aspects of tinyML technologies and a great opportunity of networking and also a good way to grow the tinyML Community.

2019 Meetups

December 2 Bay Area Meetup

November 20 Austin Meetup

October 28 Bay Area Meetup

September 26 Meetups

There were two Meetups on September 26, one in the Bay Area, the other in Austin, TX. Links to the slides, and a video link for the Bay Area meeting.

Bay Area


July 25 Meetup

Held at Qualcomm in Santa Clara and attended by over 100 people, we had two speakers – click on title for slides:

June 27 Meetup

Our first meetup was held on June 27 at Qualcomm and was a great success. Over 130 people were in attendance. Below are the presentations and a video file:

Visit our event page for photos of the event.

tinyML meetups will be held on the last Thursday of each month. Visit our Meet up page for updates.

Meetup Committee

Contact Us

Bette Cooper
tinyML Summit Organizer