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FIRST INDIAN AREA TINYML MEETUP TO BE ANNOUNCED SOON!

Based on the success of our tinyML meetup groups in the US, we are branching out to other countries.

• What is the purpose of the group?
To spread the word and educate the industry on "tinyML" (broadly defined as machine learning architectures, devices, techniques, tools and approaches capable of performing on-device analytics for a variety of sensing modalities--vision, audio, motion, environmental, human health monitoring etc.) at “mW” or below power range targeting predominately battery operated devices. The tinyML meetup group is an informal monthly gathering of researchers and practitioners working on various aspects of machine learning technologies (hardware-algorithms/networks- software-application) at the extreme low-power regime to share latest developments in this fast growing field and promote collaborations throughout the ecosystem. The format will be presentations with Q&A followed by networking.

• Who should join?
Experts in machine learning technologies at the edge, especially in the low power battery operated regime. This includes hardware architects, software engineers, systems engineers, ASIC designers, algorithms and application developers, low power sensor providers and end users. “Newbees”, i.e. people interested in joining this field and getting up to speed by listening start-of-the-art presentations and interacting with established players are very welcome to join too, both from the industry and the academia.

• What will you do at your events?
Communicate to the attendees the “latest and greatest” in tinyML by watching a presentation from a tinyML expert from the industry or the academia and interfacing with the member of the tinyML Community.

Upcoming events (2)

tinyML Talks by Chris Knorowski from SensiML

Online event

Announcing tinyML Talks on May 11th, 2021

IMPORTANT: Please register here
https://us02web.zoom.us/webinar/register/3616198089037/WN_3FhMcly_Qf6oFeWpJthHQw

Once registered, you will receive a link and dial in information to teleconference by email, that you can also add to your calendar.

8:00 AM - 9:00 AM Pacific Daylight Time (PDT)
Chris Knorowski, CTO, SensiML Corporation
"Build an Edge optimized tinyML application for the Arduino Nano 33 BLE Sense"

Building a tinyML application touches on skill sets ranging from hardware engineering, embedded programming, software engineering, machine learning, data science and domain expertise about the application you are building. The steps required to build the application can be broken into four parts:
• Collecting and annotating data
• Applying signal preprocessing
• Training a classification algorithm
• Creating firmware optimized for the resource budget of an edge device
This talk will walk you through all the steps, and by the end of it we will have created an edge optimized TinyML application for the Arduino Nano 33 BLE Sense that is capable of recognizing different boxing punches in real-time using the Gyroscope and Accelerometer sensor data from the onboard IMU sensor.

Chris Knorowski is the co-founder and CTO at SensiML where he builds tools to make it easier for developers an engineer’s create smart sensor algorithms capable of running at the extreme edge. Prior to SensiML he worked as software engineer and data scientist at Intel and Dupont Pioneer. He holds a Ph.D in computational physics from Iowa State and a B.S. in Physics from Virginia Tech.

We encourage you to register earlier since on-line broadcast capacity may be limited.

Note: tinyML Talks slides and videos will be available on the tinyML website and tinyML YouTube Channel afterwards, for those who missed the live session. Please take a moment and subscribe to the YouTube channel today: https://www.youtube.com/tinyML

tinyML Talks by Altaf Khan and Martin Kellermann

Online event

Announcing tinyML Talks on May 12th, 2021

IMPORTANT: Please register here
https://us02web.zoom.us/webinar/register/8216197334191/WN_Hi0bqpikRzK3Sd5et7qlkQ

Once registered, you will receive a link and dial in information to teleconference by email, that you can also add to your calendar.

9:30 AM - 10:30 AM Pacific Daylight Time (PDT)
Altaf Khan, CEO of Infxl LLC, Colleyville, TX
Martin Kellermann, Marketing Manager at Microchip Technology GmbH, Munich
"TinyML FPGA implementation for condition monitoring"

We have reduced the size of the deep neural net inference engine by minimizing the intra-network connectivity, eliminating the need for floating-point data, and replacing the multiply-accumulate operation with just accumulation. The resultant small-footprint, low-latency deep nets are suitable for embedded applications in general. They are especially suited for processing data from IoT sensors (inertial, vibration, temperature, flow, electrical, biochemical, etc.) in battery-powered endpoint applications in wearables, robots, and automotive, particularly for predictive maintenance, real-time condition monitoring, and process automation use cases. The trained deep nets are delivered in the form of compact and simple C code that is suitable for MCU, DSP, and FPGA implementations. We present FPGA size and performance results on an IoT condition monitoring use case.

Altaf Khan is the CEO of Infxl LLC, Colleyville, TX. He started his career as an accelerometer system engineer in Silicon Valley, but simplifying neural nets has been his passion over the last three decades. He has developed fast deep nets for real-time applications, low-cost deep nets for battery-operated IoT endpoints, and small-footprint deep nets for FPGA. He has developed intelligent solutions for a major US airline and a well-known auto parts supplier. He has been the CTO of a brokerage company, CEO of two startups, consultant for software process improvement, and an industrial controls engineer. Altaf received his BSEE from Wilkes College, MSEE for the University of Pennsylvania, and PhD from the University of Warwick.

Martin Kellermann is a Marketing Manager at Microchip Technology GmbH, Munich. Earlier he was a Staff Field Application Engineer at Xilinx. He is a seasoned FPGA and SoC professional with a track record of successful customer and project engagements in the industrial, automotive, and data-center domains. He possesses a strong background in high-speed serial data transmission, signal integrity, and hardware debugging which helped numerous customers finish their designs successfully. He has also taught courses covering industrial applications and hardware concepts. Martin is a graduate of the Landshut University of Applied Sciences.

We encourage you to register earlier since on-line broadcast capacity may be limited.

Note: tinyML Talks slides and videos will be available on the tinyML website and tinyML YouTube Channel afterwards, for those who missed the live session. Please take a moment and subscribe to the YouTube channel today: https://www.youtube.com/tinyML

Past events (46)

Photos (55)