That’s a wrap!

Imagine 2022 was a smash hit — and we’ll be back to do it again in 2023. Stay tuned.
Meanwhile, you can re-watch all the talks and demos here.

View agenda


with businesses

Hear from embedded ML industry leaders, visionaries, and researchers, and participate in live discussions.


from workshops

Gain firsthand experience from technical workshops to build the next generation of devices that can hear, feel, and see.


with developers

Be at the center of the data-driven revolution and connect with like-minded developers and engineers.


Hear from industry leaders and pioneers on the future of embedded machine learning

Zach Shelby

CEO and Co-Founder
Edge Impulse

Jan Jongboom

CTO and Co-Founder
Edge Impulse

Simon Segars

Edge Impulse Board of Directors
Former CEO of Arm

Mark Benson

Head of
Samsung SmartThings

Stephanie O'Donnell

Founder and
Community Manager

Katelijn Vleugels

HealthTech Entrepreneur
Klue, Medtronic

Sandeep Bandil

VP IoT Edge Devices & Solutions

Hubertus Breier

Head of Technology

Seann Gardiner

VP, Sales & Business Development
Weights & Biases

Ben Gibbs

Ready Robotics

Eric Pan

Seeed Studio

Chris Anderson


Kate Kallot

Co-Founder and CIO

Fran Baker

Social Impact & Innovation Lead

Sam Kelly

Project Lead: Sentinel AI
Conservation X Labs

Tim van Dam

Smart Parks

Jim Bennett

Regional Cloud Advocate

Paul Ruiz

Developer Relations Engineer —Machine Learning

Tom Quigley

Managing Director, Superorganism

Alessandro Grande

Director of Product
Edge Impulse
Master of Ceremonies

Dan Kozin

Sr. Product Manager Machine Learning Software and Developer Experience (DX), Silicon Labs

Scott Castle

Director, Innovation & Emerging Technologies,

3 days of embedded ML

Keynotes, panels, and presentations

Talks and interviews with industry leaders and pioneers

2022-09-23 08:30 AM
CEO Keynote

Zach Shelby, CEO and Co-Founder, Edge Impulse

Industry Welcome

Simon Segars, Board Member

Application of Edge ML in the Supply Chain Logistics Industry

Sandeep Bandil, VP, IoT Edge Devices & Solutions, Brambles

Machine Learning on the Edge: An Industrial Perspective

Hubertus Breier, Head of Technology, Balluff

Conservation/AI Ethics Panel

Stephanie O'Donnell, Founder and Community Manager, Wildlabs
Tim van Dam, Founder, Smart Parks
Sam Kelly, Project Lead, Sentinel AI, Conservation X Labs
Kate Kallot, Co-Founder and CIO, Mara
Fran Baker, Social Impact and Innovation Lead, Arm
Tom Quigley, Managing Director, Superorganism

Digital Health and Edge ML

Katelijn Vleugels, HealthTech Entrepreneur, Klue, Medtronic

Lightning Talks and Demos
Lightning Talks
Enabling Deep Learning on the Edge with Neural Native Processors

Mallik P. Moturi, Chief Business Officer, Syntiant

Deep learning is the most effective method of artificial intelligence for interpreting patterns and classifying them for the real world. However, due to the computational complexity, it is usually relegated to the realm of energy hungry GPUs and CPUs, making it difficult to realize on edge devices. Syntiant’s Core 2 Neural Decision Processors (NDP) are optimally designed for deploying deep learning models on the edge, where power and area are often constrained.

In this talk, we will briefly touch on some of the challenges of the edge and how Syntiant’s NDP architecture can best be utilized to address these challenges.

Lightning Talks
Now Ready for AI Solutions That Enable Social Implementation, Renesas RZ Family

Mitsuo Baba, Senior Director, Renesas

Recently, AI implementation in embedded computing is accelerating rapidly in all markets. In the ever-evolving AI technology, there are three key requirements for deploying AI functions "flexibility," "power efficiency," and "real-time operation." In this session, Renesas will explain the importance of these requirements and introduce solutions by the ready-to-use RZ family.

Lightning Talks
Computer Vision Techniques for Reducing the Data Collection Pain

Omar Oreifej, Director, Computer Vision and Machine Learning, Synaptics

In this talk, we will share our experience in developing computer vision models for low power AI at the edge. We will illustrate some techniques which greatly reduced the effort in producing representative annotated training data.

Lightning Talks
Hardware Accelerated ML on Alif Semiconductor's Ensemble Devices Takes Edge Processing From Watts to Milliwatts

Henrik Flodell, Marketing Director, Alif

Alif Semiconductor recently introduced the Ensemble family of microcontrollers and fusion processors. These devices are the first general-purpose controllers in the market to feature Arm’s Cortex-M55 MCU core as well as the Ethos-U55 microNPU, which is designed specifically for accelerating machine learning operations on deeply embedded devices. In this session, we will introduce the Ensemble family, and showcase the uplift it brings to voice and vision use cases in particular, in terms of raw performance and power savings.

Lightning Talks
Sony’s Spresense Edge Computing with Low-Power Consumption

Armaghan Ebrahimi, Partner Solutions Engineer, Sony

Introducing a high-performance microcontroller board with hi-res audio, camera, integrated GPS, and edge AI support.

Lightning Talks
Silicon Labs introduces it MG24 with an integrated ML accelerator

Isaac Sanchez, Sr. Partner Program Manager, Silicon Labs

Silicon Labs is a leading pureplay IoT semiconductor manufacturer with the widest range of wireless protocols available on TinyML devices. They recently introduced EFR32MG24 which includes an integrated AI/ML accelerator that not only enables more complex applications but also optimizes TinyML devices to operate more efficiently. This is a huge benefit to IoT devices at the very edge looking to implement ML on top of their application and wireless stacks.

Lightning Talks
Essential AI

Rob Telson, Vice President, Ecosystem and Partnerships, BrainChip

Join BrainChip as they discuss the convergence of AI with the proliferation of sensors — bringing scalable and effective AI to the sensor and beyond.

Lightning Talks
Optra Edge: Build, Deploy and Scale AI at the Edge

Scott Castle, Director, Innovation & Emerging Technologies Lexmark

For enterprises, building a good model is the start of operationalizing. Stakeholders across an organization, from IT to finance to field service, will ask challenging questions about the security, return on investment, and ongoing support. Not only for the model, but for the accompanying hardware, firmware, application management, and device management, especially for geographically distributed instances. Lexmark's Optra platform is a commercialized offering solving these problems. When combined with Edge Impulse the realization of AI's potential to enhance Operations effectiveness is closer than ever.

Edge Impulse Innovation, Demos, and Features

Jan Jongboom, CTO and Co-Founder, Edge Impulse

Building a System of Record for Edge ML

Seann Gardiner, VP, Business Development, Weights & Biases

Karan Nisar, Machine Learning Engineer, Weights & Biases

Modern Aviation

Chris Anderson, CTO, Kittyhawk


Registrations for workshops will be reviewed and confirmed

Sept 29 - 9:00 AM (PT)
8:30am — Building Neuromorphic Models with BrainChip’s Akida

Nikunj Kotecha and Chris Anastasi

Learn how to leverage BrainChip MetaTF to convert traditional CNNs to spiking neural networks (SNNs) with ease and apply to real world use cases.

  • Ability level: Beginner to advanced ML engineers

  • Prerequisites: Python, TensorFlow, and ML knowledge a plus

  • Hardware: Software simulation provided

All times are in PT (Pacific) Timezone
8:30am — Edge AI Connectivity Made Simple with Blues Wireless

TJ VanToll and Paige Niedringhaus

If you’ve ever tried to run your ML applications outside of comfortable Wi-Fi range, you know how difficult IoT connectivity still is in 2022. The Blues Wireless Notecard solves this problem elegantly, by offering subscription-free cellular connectivity, on a secure system-on-module with a simple JSON API. The Notecard is the perfect companion to your ML applications, letting you focus on polishing your models, while allowing the Notecard to handle your connectivity needs.

In this workshop you’ll see how it all works. You’ll start by going through a hands-on tutorial to learn about the Notecard, and then see a real-world example of how to do ML inferencing on the edge while sending your results to a cloud dashboard. Plus, we might have an exciting new feature to demo for you live.

All times are in PT (Pacific) Timezone
10:15am — Running AI Models on the Nvidia Jetson CPU and GPU, with balena and Edge Impulse

Marc Pous and Alan Boris

In this workshop, balena's Marc Pous, Developer Advocate, and Alan Boris, Hardware Hacker in Residence, will showcase machine learning fleet management using the Nvidia Jetson Nano on the balenaCloud device management platform. The Jetson Nano will run AI models on both the CPU and the GPU, and we'll also show how to re-train and update the model across the fleet of devices. If you have a Jetson Nano, bring it to the virtual workshop to participate in the live-build of the fleet.

  • Prerequisites: Knowledge of Docker is a plus

  • Hardware: Nvidia Jetson, NanoCameraSD, CardLaptop adapter for SD card (if no internal port)

All times are in PT (Pacific) Timezone
10:15am — Running Sensor Models on Syntiant's TinyML Board

Atul Gupta

Learn how to run sensor models on Syntiant's TinyML Board.

  • Prerequisites: Successful completion of go/stop keyword tutorial on the TinyML Board

  • Hardware: TinyML Board required

All times are in PT (Pacific) Timezone
12:00pm — Combining ModusToolbox and Edge Impulse to create and Deploy Acoustic Event Classifications on PSoC 6

Danny Watson and Nick Sharp

The Infineon PSoC 6 is a highly capable Dual Core device that has been launched into the Edge Impulse Ecosystem. In this session we will provide an acoustic classification use case and go through the firmware compilation through ModusToolbox, on-device data collection, segmentation, labeling, training and deployment to do inferencing. By the end of the session you will have a model running on the PSoC 6 and prizes given to the most innovative and reliable deployments.

Ability Level: None

Hardware/Software: In advance of the workshop, please purchase and download:
PSoC 6 Wi-Fi BT Prototyping Kit
• Install ModusToolbox

All times are in PT (Pacific) Timezone
12:00pm — Train and Deploy your Own AI Model into a Vision AI Sensor

Lakshantha Dissanayake

Artificial Intelligence camera (AI camera) is an enhanced camera powered by a built-in edge machine learning algorithm, smartly processing with computational photography to perform enhanced object detection in real-time. It has been widely used in smartphones for face recognition, edge devices for wildlife detection, and other edge intelligence applications. Featuring the Vision AI camera, Seeed Studio released the latest sensor prototype kit that includes the Grove - Vision AI module as the highlight to bring edge computing to IoT sensors. The module is a compact AI camera that supports simple ML model training and implementation thanks to the support from Edge Impulse. In this workshop, Seeed Studio will provide step-by-step guidance on how to train your own AI model for your specific application with Edge Impulse, and then deploy it easily to the Grove - Vision AI module to create you own Vison AI sensor.

Ability Level: Any skill level

SenseCAP K1100 - The Sensor Prototype Kit (Note: This kit is discounted and has free global shipping until September 30)

All times are in PT (Pacific) Timezone
Tech Talks
1:30pm — Hardware Accelerated ML on Alif Semiconductor's Ensemble Devices Takes Edge Processing From Watts to Milliwatts

Henrik Flodell

Alif Semiconductor recently introduced the Ensemble family of Microcontrollers and Fusion processors. These devices are the first general purpose controllers in the market to feature Arm’s Cortex-M55 MCU core, as well as the Ethos-U55 microNPU, which is design specifically for accelerating machine learning operations on deeply embedded devices.

In this session we will introduce the Ensemble family, and showcase the uplift it brings to Voice and Vision use cases in particular, in terms of raw performance and power savings.

All times are in PT (Pacific) Timezone
Tech Talks
2:30pm — The Fully Self-Contained Embedded ML Prototyping Solution

Robin M Saltnes

The Nordic Thingy:53 is the first fully self-contained prototyping solution for embedded ML with complete wireless Edge Impulse integration through Bluetooth Low Energy. It takes the simplicity of getting started with embedded machine learning to a whole new level.

In this tech talk, Robin from Nordic Semiconductor will walk you through how easy it is to set up the Thingy:53 to communicate with the Edge Impulse cloud and use it both for uploading new training data and deploying ML models in the field. He will also give a closer look at the core components of the Thingy:53, including all of its built-in sensor hardware, and the key feature of the nRF5340 dual-core wireless SoC that enables both the ML capabilities and wireless connectivity.

All times are in PT (Pacific) Timezone
Tech Talks
3:00pm — Smart Sensors for Smarter Spaces

Chetan Joshi

ML at Edge is and will be increasingly prevalent in ambient intelligence. In this talk, the attendees will hear from Panasonic about the fundamental shifts undergoing in the smart building industry. Using the example of Panasonic Grid-Eye infra-red matrix sensor, we will underline how simple, low-cost sensors can be improved using ML techniques, giving rise to deep insights into utilization of space.

All times are in PT (Pacific) Timezone
Tech Talks
3:30pm — Jump Start Your Edge AI Vision with TI

Reese Grimsley

Machine Learning Inference has thoroughly penetrated embedded applications, especially with visual and spatial data like images and radar/lidar. Texas Instruments has a growingly scalable processor portfolio for vision inference at the edge. Arm-only execution on the Sitara AM62 and accelerated execution on the Jacinto TDA4VM provides a range from 0.5 to 8 TOPS of performance in a Linux or RTOS environment. With a large collection of pre-optimized AI models, no-cost and low-cost development tools, and a hardware-agnostic software programming environment, TI helps you bring your idea to realization on an embedded device in no time. With Edge Impulse, we are further democratizing edge AI application development to bring embedded inference closer to the community by simplifying AI model development for TI processors. Please join our Tech Talk to learn how TI and Edge Impulse can accelerate your vision for machine learning at the edge.

All times are in PT (Pacific) Timezone
Tech Talks
3:45pm — Accelerating Machine Learning at the Edge with Silicon Labs recently introduced MG24

Dan Kozin

Silicon Labs recently announced our EFR32MG24, the leading wireless SoC for multi-protocol applications.  It also has an integrated AI/ML accelerator to offload machine learning operations for more optimized power applications. Edge Impulse’s Studio integrates this accelerator, enabling more complex use cases on this tiny edge device.  In this talk, we review applications enabled by the EFR32 AI/ML accelerator and also demonstrate object recognition using Edge Impulse’s FOMO block running simultaneously with wireless connectivity.

All times are in PT (Pacific) Timezone
Tech Talks
4:30pm — Extreme Edge Predictive Maintenance

Nathan Verrill and Mike Peacock

Collect multi-sensor data at scale, train once and deploy everywhere using Kafka, the Edge Impulse Ingestion API, and Custom Deployment Blocks to run EI models in Kafka Streams, in the cloud, and on devices, online and off, all from one Edge Impulse project.

All times are in PT (Pacific) Timezone
Tech Talks
5:30pm — The AWS Marketplace

Ankur Srivastava

The AWS Marketplace makes it easy for developers to discover and procure digital solutions so you can you build your next-best product.

All times are in PT (Pacific) Timezone


Discussions, panels, and project deep-dives. Developer sessions with community innovators. Awesome prizes and giveaways including the Seeed Studio Jetson Xavier reComputer, K1100 LoRaWAN kit, Wio Terminal, Arduino Portenta H7, Sony Spresense, and more.

Sept 30 - 9:00 AM (PT)
9:00am — Opening, Daily Agenda

David Tischler, Development Program Manager, Edge Impulse

All times are in PT (Pacific) Timezone
9:15am — Edge Impulse Announcements Deep Dive Session

Jan Jongboom and Arun Rajasekaran, Edge Impulse

All times are in PT (Pacific) Timezone
10:00am — Recyclable Materials Sorter with NVIDIA Jetson Nano

Constantin Craciun, Zalmotek

All times are in PT (Pacific) Timezone
10:30am — Adding AI Capabilities to Nanosaur

Raffaello Bonghi, Nvidia,
co-founder Pizza Robotics
Giovanni Di Dio Bruno, Università degli Studi di Napoli Federico II,
co-founder Pizza Robotics

All times are in PT (Pacific) Timezone
11:00am — Seeed Studio Community Discussion

Eric Pan, founder and CEO,
Seeed Studio

All times are in PT (Pacific) Timezone
11:30am — Tiny Robotics: Using MicroROS with Edge Impulse

Avi Brown, Edge Impulse Expert

All times are in PT (Pacific) Timezone
12:00pm — What’s new with Azure IoT to get you building solutions faster

Jim Bennett, Regional Cloud Advocate, Microsoft

All times are in PT (Pacific) Timezone
12:30pm — Measure Analog Gauges with Computer Vision Using a Sony Spresense

Mithun Das, Edge Impulse Expert

All times are in PT (Pacific) Timezone
1:00pm — Machine Learning in the Wild: Tales from the Real World

Angus Thomson, CEO and co-founder, Canairy AI
Walt Jacob, CTO and co-founder, Canairy AI

All times are in PT (Pacific) Timezone
1:30pm — Machine Learning on the Edge with TensorFlow Lite

Paul Ruiz, Developer Relations Engineer, Machine Learning, Google

All times are in PT (Pacific) Timezone
2:00pm — Community Fireside Chat with Hackster

David Tischler, Development Program Manager, Edge Impulse
Jessica Tangeman, CEO, Hackster
Alex Glow, Lead Hardware Nerd, Hackster
Jinger Zeng, Contest Manager, Hackster

All times are in PT (Pacific) Timezone