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. .