tinyML Summit and Research Symposium 2023
tinyML Summit and Research Symposium
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
|27 March||Tba||SYMPOSIUM |
Paper Presentation: TinyRCE: Forward Learning under Tiny Constraints
|Danilo Pau, |
|27-29 March||SUMMIT - Poster Session |
Enabling on-device learning on STM32 microcontrollers
|Beatrice Rossi, |
|28 March||10:05||SUMMIT - Main Agenda |
Personal Computing devices use-case and applications enabled by Smart Sensors
|Nick Thamma, |
HP Presenter Mahesh Chowdhary,
|29 March||11:15||SUMMIT – Main Agenda |
End to End MLOp system for pre-clinical medical research
|Marco Garzola, |
|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, |
|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. |