AI in the Real World: From Development to Deployment
Track Overview
The explosion of data combined with the latest innovations in software have brought AI to the forefront of technology. From using complex neural networks to fight global pandemics to helping a robot solve Rubik’s cubes, developers are pushing the boundaries of what’s possible. AI technologies are enabling endless opportunities for us to solve real-world challenges. Meet with AI thought leaders, technology experts and gain hands-on experience with our tools to develop the future of AI for all.
Track Highlights
Artificial intelligence and machine learning take center stage at Arm DevSummit. If you’re a data scientist, ML software developer or a hardware engineer, expect to find what you need to develop AI-powered solutions.
Keynote Presentation from Paul Williamson, Vice President and General Manager from Arm on the Imaginative, Immersive and Intelligent Tomorrow
Hear from AI Thought Leaders
Tomorrow’s applications will be imaginative, immersive and intelligent. And they will be here sooner than you think. In fact, they are already here. Get a guided tour of the different ways to deploy and embed machine learning on mobile phones and battery-powered devices.
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Since joining Arm as one of its first employees, Simon has driven technical and business innovations to help transform the company into the leading architect of the most pervasive compute technology the world has ever seen.
Simon led the development of early ground-breaking Arm processors – the Arm7 and Arm9 – powering the world’s first digital mobile phones. He played a key role in developing industry standards, and his engineering work led to him being granted several embedded-systems patents. He became vice president of engineering in 2001, and before being named as Arm CEO in July 2013, he held several other strategy positions including global head of sales. He was personally responsible for expanding the company’s U.S. business and strengthening its leadership and relationships in California’s Silicon Valley, where he still lives with his family.
Simon helped steer the company through the 2016 acquisition by SoftBank, and, in June 2017, was elected to serve on the SoftBank board. He also sits on the boards of the Global Semiconductor Alliance (GSA), the Electronic System Design Alliance (ESD Alliance), TechWorks and is a non-executive director at Dolby Laboratories, Inc.
Simon earned his BEng in electronic engineering from the University of Sussex and an MSc in computer science from the University of Manchester. In recognition of his extraordinary lifetime accomplishments and his impact to the global tech industry, Simon was conferred an Honorary Doctor of Science from the University of Sussex.
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Paul leads the Client Line of Business within Arm. The client team defines the compute platform that shapes user experiences in smartphone, AR/VR, DTV, gaming and laptop/tablet markets.
Paul previously ran Security, IoT and wireless businesses at Arm has been involved in connected devices since the early days of Bluetooth, developing innovative products for consumer, medical and industrial markets.
Prior to joining Arm Paul led the low power wireless division of CSR, a fabless semiconductor business (now part of Qualcomm). Paul started his career in engineering consultancy, working with leading global brands to develop innovative products and services.
CloseHands-on Workshops
Simplified Deep Learning Using OpenMV Cam, Arduino, and Edge Impulse
Workshop Plus – $79
In this workshop, Kwabena Agyeman will show attendees how to quickly train a TensorFlow Lite Convolutional Neural Network (CNN) for image classification using an OpenMV Cam and Edge Impulse. Then deploy the CNN on an OpenMV Cam and have it running immediately. Finally, attendees will connect the OpenMV Cam to an Arduino to easily control devices in the real-world. This technical workshop is brought to you by OpenMV, LLC.
tinyML Development With TensorFlow Lite for Microcontrollers and CMSIS-NN
Workshop Plus – $79
Deep Neural Networks are becoming increasingly popular in endpoint devices. Developers can perform data analytics on devices with reduced latency and energy consumption. Join Google and Arm in this workshop where we will introduce how Google’s TensorFlow Lite for microcontrollers (TFLu) and its integration with CMSIS-NN maximize ML application performance. Learn how to run a person detection sample with TFLu and CMSIS-NN on an Arduino Nano device. This technical workshop is brought to you by Arm and Google.