- This event has passed.
AI for Everyone: Challenges & Opportunities for AI Software & Hardware at Scale
June 23, 2022 @ 3:00 pm - 4:00 pm PDT
Artificial Intelligence and deep learning are reaching human-level or better accuracies in the fields of vision, NLP, and others. Applied machine learning is helping push the envelope in drug discovery, fraud detection, and other areas by deriving valuable insights from massive troves of data in many fields. Join the Fire-side chat with Huma Abidi, Senior Director, and Meena Arunachalam, Director & Principal Engineer—both part of the AI and Analytics Group at Intel Corp—and hear about the myriad challenges and opportunities in AI hardware, software, and ecosystem for Scaling AI Everywhere for Everyone.
Huma Abidi is a Senior Director of AI Software Products at Intel, leading a globally diverse team of engineers and technologists responsible for delivering world-class Deep Learning and Machine Learning products that enable customers to create artificial intelligence (AI) solutions. Huma joined Intel as a software engineer and has since worked in a variety of engineering, validation, and management roles in the areas of compilers, binary translation, AI and deep learning. She is the founder of the Women in Machine Learning group at Intel. She is a two-time recipient of Intel’s highest honor—the Intel Achievement Award. She is an industry champion and advocate of Diversity, Equity & Inclusion in AI and is passionate about women’s education, supporting several organizations around the world for this cause. She was recently named as an honoree for the 2021 TRIBUTE TO WOMEN award by Silicon Valley YWCA and recognized as WOMEN OF INFLUENCE 2021 by Silicon Valley Business Journal.
Meena Arunachalam Ph.D., Director and Principal Engineer in AI and Analytics Group at Intel Corp. She works on software performance optimizations of end-to-end pipelines for vision, video, recommendation, ML, NLP, and many other AI use cases with Intel Xeon CPUs and accelerators. She heads a team that focuses on End-to-End AI performance, HW/SW Co-design, and workload performance modeling. She served as Chapter Director and Mentoring Chair at Women in Big Data and is a core member of Women at Intel and Women in Machine learning at Intel.