ST Artificial Intelligence Solution Webinar

Join us for our 1-hour Artificial Intelligence solutions on STM32 webinar


Tuesday, January 21st 2020 

► 10:00 am CET |  2.30 pm IST (EMEA and Asia Pacific)
► 12:00 pm EST (Americas)

 

Register now

Implementing Neural Networks on STM32 microcontrollers to develop AI applications.

In this 1-hour session, we will introduce Artificial Intelligence for Edge computing and show you how ST's offer can help you run Neural Networks on microcontrollers and microprocessors.

Thanks to concrete application examples, you will know more about running Artificial Neural Networks and you will learn how to use the STM32Cube.AI tool to convert Neural Networks into optimized code for STM32 MCUs.

Use the power of Deep Learning and hop on board: discover how ST’s AI solutions, ecosystem and network of expert partners can support AI application development and help you reduce time-to-market.

Agenda

There will be a live Q&A session at the end of the webinar where ST’s experienced engineers will be available to answer your questions.

Registration information

This webinar will be broadcast twice, at convenient times for international audiences. Please review the times listed below and register for the most appropriate option for your time zone.

  • For EMEA and Asia Pacific: January 21st, 2019 at 10:00 am CET l 2:30 pm IST
  • For Americas: January 21st, 2019 at 12:00 pm EST

There is no charge to participate in this event, but it is necessary to register through my.st.com.

Register now


Speakers

Raphael Apfeldorfer is responsible for Artificial Intelligence Marketing at ST. Focusing on innovation in digital transformations, he has 20 years’ experience in telecom and IoT industry, from broadband to LPWAN connectivity, security and low-power applications.

Matthieu Durnerin is the head of Artificial Itelligence Applications, Algorithms and Tools team in the Microcontroller and Digital IC's group after leading several activities on cellular telecommunications, audio, sensor hub and machine learning. He has a background in telecommunications and a PhD in Signal Processing

 

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