New for 2021, tinyML Summit is developing a series of breakout sessions. Breakouts are focused on bringing focused topics directly to the audience that needs them. They will be practical and interactive discussions to foster better understanding of design and application issues, best practices, tools, and funding opportunities to accelerate the deployment of ultra-low power machine learning solutions. The audience will have the chance to hear from industry leaders in their specific fields and ask questions of them.
Sessions will include:
tinyML Applications
This session will focus on the many diverse market segments where ultra-low power machine learning designs are being deployed such as smart devices to wildlife monitoring. Real world cases will be described where machine learning meets the rugged demands of ultra-low power, performance and code efficiency. Industry leaders and innovators will describe how ultra-low power machine learning solved specific problems and review techniques you could use in your designs today.
tinyML Tools
This session will describe a selection of tools available to get you started in hardware and software development utilizing ultra-low power machine learning. Industry leaders will discuss technology trends, best design practices and what tools are more suited to specific tasks.
tinyML Grants
The explosion of ultra-low power machine learning at the edge designs across multiple worldwide applications has opened up opportunities for academia and commercial organizations to seek grant opportunities in many fields. In this session we will hear from a leading US Government agency on what grant opportunity trends they see in the coming months and years and how to apply. We will also hear from a grant recipient on how they navigated the grant application process and some of the do’s and don’ts in taking advantage of grants for your ultra-low power machine learning research and projects.
tinyML Summit Partner Sessions
The Partner Sessions will be an opportunity to hear from commercial companies in the tiny machine learning ecosystem on market and technology trends they are addressing to enable the exponential growth of tiny machine learning solutions. These will not be detailed company product or marketing talks but more interesting discussions on what these companies see happening given their particular vantage points. Expect to hear how problems and gaps are being solved and what still needs to be done and why.