The TWIML AI Podcast (formerly This Week in Machine Learning & Artificial Intelligence)

Adriana Kovashka, an Assistant Professor at the University of Pittsburgh, dives into her research on visual commonsense and robust visual reasoning. She discusses the interplay between media studies and machine learning, using examples like public service announcements to highlight the complexity of interpretation. Adriana elaborates on the pitfalls in visual question answering datasets and the innovations in weakly supervised object detection. She also shares insights into practical AI applications, emphasizing the need for common sense in assistive technologies.

Nishan Subedi, VP of Algorithms at Overstock.com, shares his journey from physics to leading machine learning initiatives. He delves into how Overstock utilizes ML for search and marketing, highlighting the importance of architectural patterns in ML systems. Nishan discusses the innovative concept of 'squads' in organizational structures and how flexibility and collaboration enhance team effectiveness. He also examines the challenges of moving ML from the lab to production and the future of integrated architectural patterns in the industry.

Vered Shwartz, a Postdoctoral Researcher at the Allen Institute for AI and the University of Washington, dives deep into common sense reasoning in natural language processing. She shares insights on training neural networks, the challenges of integrating common sense knowledge, and the innovative 'self-talk' model that enhances contextual understanding. Vered also discusses biases in language models stemming from training data and explores multimodal reasoning, aiming to improve AI's grasp on human-like logic and communication.

Ayanna Howard, the Dean of the College of Engineering at The Ohio State University, is a prominent robotics researcher focusing on human-robot interaction. In this conversation, she dives into her book, exploring the social dynamics between people and AI, including biases that arise from both data and model design. She highlights the ethical responsibilities of AI builders and discusses her transition to OSU, emphasizing future projects that address AI's societal impacts, trust issues during emergencies, and the need for a mindful approach to technology.

Join Ayanna Howard, Dean of the College of Engineering at The Ohio State University and founder of Zyrobotics, as she dives into her book on the intricate dynamics between humans and robots. She discusses how AI carries societal biases, particularly regarding gender, emphasizing the responsibility of developers in mitigating these issues. The conversation explores the complexities of emotion recognition in AI and highlights the ethical implications of technology in society. Howard also reflects on her new role and the future of applied AI, advocating for equitable advancements.

Penousal Machado, an Associate Professor at the University of Coimbra, combines his expertise in evolutionary computation with a passion for images and graphics. He discusses the link between creativity and humanity, challenging the anthropocentric view of AI. The conversation also delves into the evolution of mating habits across species and how these insights can inform machine learning. By exploring the connections between art, nature, and technology, Machado highlights the transformative potential of AI in both creative fields and scientific understanding.

Arul Menezes, a Distinguished Engineer at Microsoft with 30 years of experience, discusses the evolution of machine translation technology. He highlights key breakthroughs from seq2seq to transformer models and the use of multilingual transfer learning. Arul also delves into domain-specific improvements, optimization techniques like document-level translation, and the challenges in voice translation technology. His insights into integrating speech recognition and enhancing translation accuracy for diverse languages showcase the future of this field.

In this engaging discussion, Luna Dong, Sr. Principal Scientist at Amazon, shares her expertise in product knowledge graphs and their role in enhancing search and recommendation systems. She explores the integration of machine learning and discusses the challenges of data curation. Luna delves into the unique dynamics of media versus retail knowledge graphs and the necessity of human intervention for data quality. The conversation also highlights practical applications of knowledge graphs and the importance of standardization across the industry.

In this discussion, Sarah M. Brown, an Assistant Professor at the University of Rhode Island, dives into the crucial need for a systems-level approach to fairness in AI. She introduces Wiggum, a groundbreaking tool for detecting bias that fosters collaboration between technical experts and social scientists. The conversation also touches on how aggregated data can mislead perceptions of fairness, emphasizing the significance of granular analysis. Brown explores the complexities of defining fairness and the importance of innovative educational frameworks in addressing ethical algorithmic challenges.

Join Andrew Trister, Deputy Director for Digital Health Innovation at the Bill & Melinda Gates Foundation, as he shares insights from his impressive background, including his work on Apple's ResearchKit. He discusses innovative AI applications aimed at enhancing community-based healthcare, particularly in underserved areas. The conversation highlights tackling COVID-19 and improving malaria testing accuracy using Bayesian models. Andrew also addresses challenges in scaling digital health technologies and the importance of community engagement in driving successful health solutions.