ACM ByteCast

In this episode of ACM ByteCast, Bruke Kifle hosts Partha Talukdar, Senior Staff Research Scientist at Google Research India, where he leads a group focused on natural language processing (NLP), and an Associate Professor at the Indian Institute of Science (IISc) Bangalore. Partha was previously a postdoctoral fellow at Carnegie Mellon University’s Machine Learning Department and received his PhD in computer information science from the University of Pennsylvania. He is broadly interested in natural language processing, machine learning, and making language technologies more inclusive. Partha is a co-author of a book on graphs-based learning and the recipient of several awards, including the ACM India Early Career Researcher Award for combining deep scholarship of NLP, graphical knowledge representation, and machine learning to solve long-standing problems. He is also the founder of Kenome, an enterprise knowledge graph company with the mission to help enterprises make sense of big dark data. Partha shares how exposure to language processing drew him to languages with limited resources and NLP. He and Bruke discuss the role of language in machine learning and whether current AI systems are merely memorizing and reproducing data or are actually capable of understanding. He also talks about his recent focus on inclusive and equitable language technology development through multilingual-multimodal Large Language Modeling, including Project Bindi. They discuss current limitations in machine learning in a world with more than 7,000 languages, as well as data scarcity and how knowledge graphs can mitigate this issue. Partha also shares his insights on balancing his time and priorities between industry and academia, recent breakthroughs that were impactful, and what he sees as key future achievements for language inclusion.

Special guest Rosalind Picard, inventor and engineer, joins host Scott Hanselman to discuss affective computing, human emotions, ethical AI interactions, monitoring blood sugar levels with wearable tech, navigating AI and emotions, and the significance of facial expressions in communication and learning.

Edward Y. Chang, a prominent figure in computer science, discusses his journey from studying operations research to leading AI advancements at Google. He shares insights on developing generative AI technologies, exploring the potential of AI in healthcare and investment banking, and the importance of human collaboration in AI-driven systems.

Jacki O'Neill, Director of Microsoft Africa Research in Nairobi, discusses her journey blending research, engineering, and design to address local/global challenges in AI, HCI, and technology for emerging markets. She emphasizes ethnography for effective tech design, user-centered design for global impact, and the importance of interdisciplinary collaboration. O'Neill explores the socio-tector model in African small businesses and advocates for technology for social impact, guiding young professionals towards impactful careers.

2022 ACM Fellow Ranveer Chandra discusses his journey from India to leading Microsoft's Agri-Food initiatives. He talks about using AI to empower farmers, bridging connectivity gaps with TV white spaces, and the transformative potential of AI in agriculture and food production.

Yael Tauman Kalai, a cryptography expert, discusses her career journey, work on blockchain privacy with ring signatures, concerns around quantum computing, and exciting emerging areas in cryptography. She touches on the balance between academia and industry, verification methods, and the intersection of AI and cryptography.

Noriko Arai, a professor in the Information and Society Research Division of the National Institute of Informatics in Tokyo, Japan, discusses being a creative in academia, the impact of AI, mentors and colleagues who inspired her, essential skills and ethics in AI research, and the challenges faced by female researchers in IT and the gender gap in Japan.

Eugenio Zuccarelli, Data Science Manager at CVS Health, discusses his early passions in engineering and technology, his work on MIT Media Lab's Project US, challenges and concerns across different industries such as data sharing and privacy, and the importance of trust in data sharing in healthcare. He also explores the risks and challenges of using synthetic data in research and the need for adapting skills and attitude in corporate settings. The chapter concludes by emphasizing the significance of students acquiring real-life application knowledge alongside technical expertise and the potential of AI and machine learning in healthcare.

Regina Barzilay, School of Engineering Distinguished Professor of AI & Health at MIT, discusses her journey to develop an AI-based system for early detection of breast cancer. She explores challenges in clinical AI and the promise of ChatGPT in healthcare. She also addresses the need to mitigate inequity in medicine while advancing clinical AI.

Host Bruke Kifle interviews Kush Varshney, a distinguished research scientist at IBM Research. They discuss responsible AI, operationalizing RAI principles, risks of generative AI, and coordinating AI safety. Kush also shares insights from his book 'Trustworthy Machine Learning' and his work with IBM's Science for Social Good initiative.