The TWIML AI Podcast (formerly This Week in Machine Learning & Artificial Intelligence)
Sam Charrington
Machine learning and artificial intelligence are dramatically changing the way businesses operate and people live. The TWIML AI Podcast brings the top minds and ideas from the world of ML and AI to a broad and influential community of ML/AI researchers, data scientists, engineers and tech-savvy business and IT leaders. Hosted by Sam Charrington, a sought after industry analyst, speaker, commentator and thought leader. Technologies covered include machine learning, artificial intelligence, deep learning, natural language processing, neural networks, analytics, computer science, data science and more.
Episodes
Mentioned books
Mar 18, 2021 • 49min
Accelerating Innovation with AI at Scale with David Carmona - #465
David Carmona, General Manager of Artificial Intelligence & Innovation at Microsoft, dives into AI at scale and the evolution of natural language processing. He shares insights on the shift toward massive models and how attention mechanisms are revolutionizing understanding. Discussing the importance of ethical AI, he also explores the journey from fine-tuning to zero-shot learning, enhancing model adaptability. Their integration into Microsoft products enriches capabilities like semantic search and document summarization, highlighting AI's transformative role in technology.
7 snips
Mar 15, 2021 • 33min
Complexity and Intelligence with Melanie Mitchell - #464
In this engaging discussion, Melanie Mitchell, a Davis Professor at the Santa Fe Institute and author, dives into the complexities of intelligence and AI. She highlights the challenges of getting AI to make analogies, drawing parallels with social learning observed in humans. The conversation explores alternative learning paradigms and their implications for machine intelligence. Mitchell also addresses the limitations of current AI systems, emphasizing the need for responsible application and a focus on interdisciplinary research to advance the field.
Mar 11, 2021 • 42min
Robust Visual Reasoning with Adriana Kovashka - #463
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.
Mar 8, 2021 • 58min
Architectural and Organizational Patterns in Machine Learning with Nishan Subedi - #462
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.
Mar 4, 2021 • 37min
Common Sense Reasoning in NLP with Vered Shwartz - #461
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.
Mar 1, 2021 • 36min
How to Be Human in the Age of AI with Ayanna Howard - #460
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.
Mar 1, 2021 • 37min
How to Be Human in the Age of AI with Ayanna Howard - #460
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.
Feb 25, 2021 • 57min
Evolution and Intelligence with Penousal Machado - #459
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.
Feb 22, 2021 • 44min
Innovating Neural Machine Translation with Arul Menezes - #458
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.
27 snips
Feb 18, 2021 • 44min
Building the Product Knowledge Graph at Amazon with Luna Dong - #457
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.
