tinyML Summit and Research Symposium 2023

tinyML Summit and Research Symposium
Date: 27-29 March
Where: Hyatt Regency San Francisco Airport
1333 Bayshore Highway, Burlingame, CA 94010

Go to the tinyML Foundation website and register here.

NEWS! On March 27, from 1:30 to 5:30pm, access to the exhibition hall will be free for all. Register here

The latest schedule is here

Sensors, microcontrollers and actuators with integrated resource-constrained processing along with connectivity functions, are massively scaling across a wide variety of application areas: industrial, fitness, medical and healthcare, transportation, consumer and personal devices, urban management, automotive and robotics.

Today, the widespread diffusion of sensors is generating an unprecedented amount of information that – when sent to the cloud as raw data – are responsible for massive workloads and the explosion of energy consumption required to execute centralized intelligent processing. For a more sustainable future, the scalable solution is to distribute and deploy tiny machine learning into the sensor, MCU/MPU and actuation chips.

tinyML is a fast-growing machine learning community composed of experts on technologies and applications including tools, hardware, algorithms and software capable of performing on-device sensor data analytics at extremely low power, enabling a variety of always-on use cases and targeting battery-operated devices.

To address the above-mentioned applications, the tinyML community started in 2018 and to date includes several hundreds of companies and universities across the world. Synergically within this well-established community we are developing machine learning algorithms, architectures, techniques, tools, and system approaches enabling on-device analytics for a variety of sensors (vision, audio, motion, environment, chemical, and more) at a power range below the microwatt level required for always-on and battery-operated devices.

Since 2019, STMicroelectronics is an active contributor to the tinyML community and continues to provide outstanding support as a Strategic Partner and Gold Sponsor.

This year ST will enthusiastically participate in the Summit with presentations, customer stories, a poster and an On Device Learning technical paper presentation at the Symposium. We’ll have a booth in the exhibition area, with demos and ST colleagues eager to start a conversation and share their experiences with you.

Join us and contribute to the development of tiny Machine Learning!


Conference agenda – ST sessions at the Symposium and SUMMIT – 27-29 March

date Time (PST) Title Speakers
27 March Tba SYMPOSIUM
Paper Presentation: TinyRCE: Forward Learning under Tiny Constraints
Danilo Pau,
ST Presenter
27-29 March   SUMMIT - Poster Session
Enabling on-device learning on STM32 microcontrollers
Beatrice Rossi,
ST Presenter
28 March 10:05 SUMMIT - Main Agenda
Personal Computing devices use-case and applications enabled by Smart Sensors
Nick Thamma,
HP Presenter Mahesh Chowdhary,
ST Presenter
29 March 11:15 SUMMIT – Main Agenda
End to End MLOp system for pre-clinical medical research
Marco Garzola,
Tecniplast Presenter
29 March 4:00 SUMMIT - Main Agenda
Accelerating Binary and Mixed-Precision NNs Inference on STMicroelectronics Embedded NPU with Digital In-Memory-Computing
    Danilo Pau,
ST Presenter,
Fabrizio Indirli,
ST author

ST demos:

AI in the edge: a new sensor with an Intelligent Sensor Processing Unit inside, capable of unsupervised on-device learning and recognizing physical activities.

  STM32Cube.AI Developer Cloud, a free-of-charge online platform and services allowing the creation, optimization, benchmarking, and generation of AI for any STM32 microcontroller.