MLT Workshop: Edge AI @Arm

This is a past event

60 people went

Details

We are excited to kick off our first Embedded ML workshop - a combination of presentation and ideathon.

-- YOU HAVE TO REGISTER IN THE GOOGLE FORM TO SAVE YOUR SPOT --
https://forms.gle/kho9Gt5HEk6Guryk8

Firstly, we will talk about the promise of light-weight deep neural networks for energy-efficient and low-cost IoT applications. We discuss some examples of accelerated and low-memory version of deep learning models for real-time use, predictive maintenance, time-series analysis, and demand forecast. We focus on AI methods for turning IoT data into insights and actions.

After the introductory talk about Edge AI we will build teams of 3-5 people and have 1.5 hours to come up with project ideas for embedded ML scenarios that include use case, feasibility assessment, workflow, allocation of resources (human, time, computation, ...).

-- AGENDA --
12:30 pm Doors open
1:00 pm - 1:45 pm Talk: "AI for Embedded Computing: Towards low-power Edge Inference", Hossein I. Rad
1:45 pm - 2:00 pm Edge AI Ideathon, Yoovraj Shinde
2:00 pm - 2:45 pm Team building break with snacks and drinks
2:45 pm - 4:15 pm Ideathon
4:15 pm - 5:00 pm Presentations
5:00 pm Wrap up

-- YOU HAVE TO REGISTER IN THE GOOGLE FORM TO SAVE YOUR SPOT --
https://forms.gle/kho9Gt5HEk6Guryk8

-- MLT EDGE AI TEAM --
Hossein Izadi Rad is a Ph.D. candidate of Information Science and Technology with the University of Tokyo. He has an M.E. degree in Electrical Engineering. His recent works are concerned with off-the-cloud time-series prediction and demand forecast. He has collaborated with several tech startups in Tokyo.

Yoovraj Shinde is currently working as Technologist at Rakuten Institute of Technology. Electronics Engineer by heart, but worked in software industry for about 8 years. Worked on FrontEnd, BackEnd Java systems, iOS app development. Part Time hobbies: Robot Club and Machine Learning

-- THANK YOU --
A big THANK YOU goes out to ARM for their support and providing the venue as well as snacks and drinks for this workshop. Arm is bringing AI to trillions of edge devices by adding ML capabilities to processor technology, making them smarter, more energy efficient, and more affordable. Ream more about AI at ARM https://www.arm.com/solutions/artificial-intelligence

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