TUTORIAL #1
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Danilo Pau
Technical Director, IEEE AAIA & ST Fellow, APSIPA Life Member
System Research and Applications; STMicroelectronics, Agrate Brianza, Italy
Tiny Machine Learning and Embedded engineers urge new tools to support them in being faster, more productive to unleash their creativity more than ever. To devise breakthrough applications for automotive, IoT, medical, industrial, robotics etc. an end of end workflow of interoperable unified, across tiny devices, AI tools is a game changer.
Any fragmentation of them with respect to the underlying hardware adopted is miserably limiting ML engineers creativity and capability to serve their stakeholders in the best way they need. Therefore, ST, devoted its best resources across product divisions and system research to create the Unified AI Core Technology.
It solves above challenges and acts as the enabling unifying AI technology to serve all heterogeneous products such as micro-controllers and sensors. Furthermore, this technology interfaces the most widely used
Deep Learning representation standards such as Google Keras, QKeras and Tensorflow Lite and the Open Neural Network Exchange (ONNX). It outputs optimized C code across heterogeneous instruction sets with public APIs for STM32, STM32N6, Stellar MCUs and AI MEMs sensors.
With that we help developers to be free to use the IDE they are comfortable with to finalize their application of choice with unprecedented speed.
Danilo PAU (h-index 27, i10-index 74) graduate in 1992 at Politecnico di Milano, Italy. On 1991, he joined SGS-THOMSON (now STMicroelectronics) as interns on Advanced Multimedia Architectures, and he worked on memory reduced HDMAC HW design. Then MPEG2 video memory reduction. Next, on video coding, transcoding, embedded (Khronos) 2/3D graphics, and (ISO/IEC/MPEG CDVS and CDVA with Leonardo Chiariglione) computer vision. Currently, his work focuses on the ST unified AI core technology integrated into company tools (STM32Cube.AI, STM32Cube.ai Developer Cloud, Stellar.AI, SPC5- Studio.AI, MEMs Studio). Danilo is an IEEE Fellow, 2019; AAIA Fellow on 2023; In IEEE he is a Member of the Machine Learning, Deep Learning and AI in the CE (MDA) Technical Stream Committee CESoc. He wrote the IEEE Milestone on Multiple Silicon Technologies on a chip, 1985 which was ratified by IEEE BoD in 2021 and IEEE Milestone on MPEG Multimedia Integrated Circuits, 1984-1993 which was ratified in 2022. He serves as TPC member to TinyML Symposium, Summit, and as 2022/3 IEEE Computer Society Fellow Evaluating Committee Members. With more than 100 submitted inventions, 78 and 68 respectively European and US application patents, 188 scientific publications, 113 ISO/IEC/MPEG authored documents and 90 invited talks/seminars at various Universities and Conferences, Danilo’s favorite activity remains supervising undergraduate students and PhDs.
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