Kaoutar
El Maghraoui
Principal Research Staff Member at IBM Research
"Powering the Future of Sustainable AI through Specialized AI hardware Accelerators "
"Powering the Future of Sustainable AI through Specialized AI hardware Accelerators "
08 - 4:50 PM EDT/New York (See in local time)
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04//2024 4:50 PM
04//2024 05:30 PM
America/New_York
#WTGC2024
"Powering the Future of Sustainable AI through Specialized AI hardware Accelerators "
#WTGC2024
"Powering the Future of Sustainable AI through Specialized AI hardware Accelerators "
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https://www.womentech.net/vfairs
"Powering the Future of Sustainable AI through Specialized AI hardware Accelerators "
"Powering the Future of Sustainable AI through Specialized AI hardware Accelerators "
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Session: Powering the Future of Sustainable AI through Specialized AI hardware Accelerators
AI and especially deep learning have achieved incredible performances in numerous fields including Computer Vision, Speech Recognition, Natural Language Processing etc. However, with this huge success, comes the increased size and complexity of AI models which both translate into high computational and increased carbon footprint. To address these challenges, there is Cambrian explosion of innovative AI hardware-accelerator architectures optimized for deep learning and machine learning across cloud and edge platforms. Purpose-built hardware will shift the traditional balances between cloud and edge, structured and unstructured data, and training and inference. This talk uncovers the evolving landscape of specialized AI hardware accelerators. It also highlights IBM Research suite of techniques towards the design & build of optimized deep learning hardware as part of IBM’s AI hardware Center initiative. We are making further strides in AI hardware-software co-design using approximate computing principals and Analog non-Von-Neumann approaches to unlock exponential gains of AI computations making AI faster, more efficient, and sustainable.Key Takeaways
- The ever increasing complexity, computational cost and carbon footpring of AI models demand innvoations across the stack to build sustabled and efficient AI technologies.
- The need for AI hardware-accelerator architectures optimized for deep learning and machine learning across cloud and edge platforms
Bio
Dr. Kaoutar El Maghraoui is a principal research staff member at the IBM T.J Watson Research Center where she is focusing on innovations at the intersection of systems and artificial intelligence (AI). She leads the research agenda of the AI testbed of the IBM Research AI Hardware Center, a global research hub focusing on enabling next-generation accelerators and systems for AI workloads. She co-led IBM’s Global Technology Outlook in 2017 where she contributed to creating IBM’s vision for the future of IT across global labs and business units focusing on IBM’s AI leadership. Kaoutar has co-authored several patents, conference, and journal publications in the areas of systems research, distributed systems, high performance computing, and AI. Kaoutar holds a PhD. degree from Rensselaer Polytechnic Institute, USA. She received several awards including the Robert McNaughton Award for best thesis in computer science, Best of IBM award in 2021, IBM’s Eminence and Excellence award for leadership in increasing Women’s presence in science and technology, several IBM outstanding technical accomplishments, and 2021 IEEE TCSVC Women in Service Computing award. Kaoutar is global vice-chair of the Arab Women in Computing organization and avid supporter and active member in many women in science and technology initiatives.