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

The discussion centers on the emotional impact of systemic racism, ignited by the deaths of George Floyd and others. It underscores the pressing socio-economic issues faced by communities of color. Emphasis is placed on the importance of empathy and the significance of being active participants in advocacy. The conversation also addresses the need for change in America’s racial and class landscape, calling attention to the ongoing fight for justice and equality.

Andreas Tolias, a Professor of Neuroscience at Baylor College of Medicine, dives into the intriguing relationship between brain function and AI. He discusses how traditional AI has limitations that neuroscience can help overcome. The conversation highlights innovative data collection methods, like fMRI and high-density recordings. Tolias emphasizes the significance of understanding behavior outside neural structures and how using biological insights can enhance machine learning models. He also proposes new benchmarks to refine AI capabilities, aiming for systems that better mimic human cognition.

Joseph Gonzalez, Assistant Professor at UC Berkeley, joins to discuss his innovative approach to model efficiency. He delves into his research on training large models followed by compressing them, questioning the balance between model size and computational resource use. The talk includes insights on rapid architecture iteration and how larger models can still be efficient. He also shares strategies like weight pruning and dynamic querying that enhance performance without excessive resource investment, making advanced AI more accessible.

Alpha Lee, a Winton Advanced Fellow at Cambridge and co-founder of PostEra, delves into the fascinating intersection of physics, chemistry, and machine learning. He discusses how his startup innovates drug discovery through advanced algorithms and Bayesian approaches to manage uncertainty. The conversation highlights the parallels between physical systems and deep learning, and how transformers are revolutionizing chemical predictions. Lee also touches on recent efforts in developing effective COVID-19 therapies, underscoring the importance of collaboration in science.

In this engaging discussion, Emily M. Bender, a Professor of Linguistics at the University of Washington, explores the intersection of linguistics and NLP. She challenges the current boundaries of NLP research and emphasizes the importance of linguistic insights in improving language models. The conversation dives into the limitations of models like BERT in grasping true meaning and highlights the ethical implications of language in technology. Bender also advocates for interdisciplinary collaboration to enhance understanding and inclusivity in NLP.

Nataniel Ruiz, a PhD student at Boston University specializing in image and video computing, dives into the intricate world of deepfakes. He discusses the importance of adversarial attacks in combating manipulative technology while navigating the ethical implications of image translation networks. The conversation addresses the complexities of protecting digital images and explores potential applications of blockchain in image security. Ruiz highlights the delicate balance needed in executing effective attacks and developing defenses, all while reflecting on the challenges of research amid uncertainty.

Sherri Rose, an Associate Professor at Harvard Medical School, delves into pressing data quality issues in healthcare during the COVID-19 pandemic. She emphasizes the critical need for reliable datasets and rigor in research methodologies. The discussion highlights the rise of algorithmic fairness, particularly its importance for marginalized communities, and critiques current standards in causal inference. Sherri also explores the nuances of risk adjustment in healthcare funding, urging a thoughtful engagement with research to better inform healthcare policies.

Lukas Biewald, Founder and CEO of Weights & Biases, dives into the world of machine learning artifact management. He shares insights about their new tool, Artifacts, designed to track datasets, models, and pipelines seamlessly. The conversation also highlights the challenges of data provenance and reproducibility, alongside the evolution from simplistic methods to more advanced solutions. Biewald emphasizes the importance of user-friendly approaches and the need for organizations to understand their data processes for successful integration and project outcomes.

In this engaging discussion, Richard Socher, Chief Scientist and Executive VP at Salesforce, unveils his groundbreaking work in AI, including the CTRL language model and ProGen, an AI protein generator. He shares insights on how language models are reshaping protein engineering and the ethical implications of AI-generated content. The conversation also dives into Salesforce's innovative AI applications in CRM, exploring how they enhance customer relationships and tackle real-world challenges. Socher emphasizes the importance of balancing research with practical needs in a large tech company.

Manuela Veloso, Head of AI Research at J.P. Morgan Chase and a renowned professor at Carnegie Mellon University, shares her insights on leveraging AI to combat financial crime and enhance client experiences. She discusses the ambitious research goals set by her team and reflects on her journey from robotics to AI in finance. The conversation also touches on her role in founding RoboCup, emphasizing the transformative power of AI in various industries and the importance of collaboration in solving complex financial challenges.