tinyML Talks on January 13, 2022 by Liang Shen, Brian Plancher and Greg Gage

We held our next tinyML Talks webcast. Liang Shen from Qualcomm presented Evolutionary Needs of TinyML, Brian Plancher from Harvard University presented tinyMLedu: widening access to tinyML education and resources and Greg Gage from Backyard Brains presented tinyML4STEM: using tinyML for Neuroscience in K12 on January 13, 2022.

January 13 forum new

During the past decade, Deep Learning based AI technology not only becomes the predominant solutions for existing or new problems, also almost instantly deployed to various smart devices. In this talk, we start with a brief review on how power-efficient AI engine helped this new AI wave and effectively enabled billions of battery-powered devices; then, we touch the new trend: always-on or long-continuous-run AI use cases, which require optimal minimum power solution. We discuss some details of ultra-low-power AI solution and how it offers the improved quality for targeted use cases. With continuous evolution of new intelligent algorithms, this talk concludes with on-going challenges and some potential directions.

Liang Shen
Liang Shen joined Qualcomm from AMD/ATI as part of acquisition in 2009 and has been leading the development of multimedia software components for Snapdragon products. He and his team have been focusing on AI Processors and System since 2016. Liang got his B.Sc. on Biomedical Engineering and M.Sc./Ph.D. on Image Processing and Pattern Recognition with over 20 publications in journals and conferences. He worked on real-time signal & data processing algorithms and systems for radar, sonar, and satellites. He then led the development and successful commercialization of new-generation communication systems with TTS and ASR. In ATI/AMD, Liang was responsible for next-gen ASIC software and handheld software. While interested and enjoyed with all the projects/products he involved/developed, the most unimaginable one is cycling back to work on AI, his fantasy area – allowing him pursuing dream to make IoT becoming Wisdom-of-Things (WoT).
TinyML can be used to enrich courses across the STEM curriculum, ranging from machine learning to embedded systems, with exciting, hands-on projects. tinyMLedu is working to help widen access to such applied machine learning experiences by building an international coalition of researchers and practitioners. Through collaborations across academia and industry, we are working to develop and share high quality, open-access educational materials globally and provide global access to the requisite hardware and software resources. You can learn more about our efforts at tinyMLedu.org.

TinyML can be used to enrich courses across the STEM curriculum, ranging from machine learning to embedded systems, with exciting, hands-on projects. tinyMLedu is working to help widen access to such applied machine learning experiences by building an international coalition of researchers and practitioners. Through collaborations across academia and industry, we are working to develop and share high quality, open-access educational materials globally and provide global access to the requisite hardware and software resources. You can learn more about our efforts at tinyMLedu.org.

Brian Plancher
Brian is a Ph.D. Candidate studying Robotics at Harvard University working with Vijay Janapa Reddi and Scott Kuindersma and co-chairs tinyMLedu. His research is focused on developing and implementing open-source algorithms for dynamic motion planning and control of robots by exploiting both the mathematical structure of algorithms and the design of computational platforms. As such, his research is at the intersection of Robotics and Computer Architecture / Embedded Systems, Numerical Optimization, and Machine Learning. He also wants to improve the accessibility of STEM education. He enjoys teaching and designing new interdisciplinary, project-based, open-access courses that lower the barrier to entry of cutting edge topics like tinyML. He also enjoys spending his free time with my wife, daughter, and puppy, and ski racing in the winters.

Combining tinyML and Neuroscience enables exciting, hands-on STEM education experiences for the K12 audience. In this talk we will describe our successful effort piloting this exciting collaboration through Backyard Brains this past summer.

Greg Gage
Greg Gage is a neuroscientist, engineer, the CEO of Backyard Brains, and helps lead the tinyML4STEM effort. Greg develops tools, curriculum and experiments that allow the general public participate, hands-on, in neural discovery. He is senior fellow at TED and has given many TED talks (9 online), received the director’s innovation award as an investigator at the National Institute of Health (NIH), and was recognized in a White House ceremony for being Obama’s Champion of Change for his commitment to citizen science. In his free time, he enjoys changing diapers of his 2 young daughters.

=========================

Watch on YouTube:
Liang Shen
Brian Plancher
Greg Gage

Download presentation slides:
Liang Shen
Brian Plancher
Greg Gage

Feel free to ask your questions on this thread and keep the conversation going!

Thanks for this information! Really interesting!

A software development team should include specialists and generalists, based on their skills and experience. It should be clear which roles are important for the company https://mlsdev.com. If a project requires multiple specialists, you might want to consider adding a team that includes a plethora of generalists. If you have a lot of specialized knowledge, it is best to have people who can switch between roles and skills. That way, you can ensure that your team members are all working towards the same goal.