Machine Learning in Microcontrollers
In this introductory session, we will explore the rise of AI/ML and how it impacts embedded software development. We’ll explore the types of problems that AI/ML can help developers solve, use cases, and where the technology is going. Attendees will walk away with a general overview and understand when and where to apply AI/ML in their own systems along with some of the tools to help them along the way.
Using AI/ML on the microcontroller is not the only place these technologies can help developers. AI/ML tools like ChatGPT can be used to write embedded software, too. In this session, attendees will learn how to use ChatGPT to help them develop HALs, interfaces, libraries, and even debug their code.
Selecting the right tools to train and deploy a model to an embedded system can be confusing. In this session, attendees will learn about the different tools that are available for microcontrollers to collect data, train a model, and deploy the inference to their embedded target.
In this session, attendees will learn how to use the STM32 ecosystem and tools to acquire data and train a model. We’ll dive into the details of the STM32 AI tools and how they help developers create ML inferences without being experts in machine learning.
In this session, we’ll talk about tips and tricks for deploying machine learning models to embedded targets. We’ll explore a few examples and provide the attendees with the knowledge they need to start developing and deploying their own models.
Jacob Beningo is an embedded software consultant who currently works with clients in more than a dozen countries to dramatically transform their businesses by improving product quality, cost and time to market. He has published more than 300 articles on embedded software development techniques, has published several books, is a sought-after speaker and technical trainer and holds three degrees which include a Masters of Engineering from the University of Michigan.