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
31 snips
Jan 30, 2023 • 1h 2min
How LLMs and Generative AI are Revolutionizing AI for Science with Anima Anandkumar - #614
Anima Anandkumar, Bren Professor at Caltech and Sr. Director of AI Research at NVIDIA, discusses how generative AI is reshaping scientific discovery. She highlights breakthrough developments in protein folding and drug design, emphasizing AlphaFold's impact. The conversation moves to neural operators enhancing simulations and AI's role in weather forecasting. Anandkumar also introduces MineDojo, a unique Minecraft framework that advances embodied AI research, showcasing its potential for innovation and decision-making.
128 snips
Jan 23, 2023 • 1h 46min
AI Trends 2023: Natural Language Proc - ChatGPT, GPT-4 and Cutting Edge Research with Sameer Singh - #613
In a fascinating discussion, Sameer Singh, an NLP expert and associate professor at UC Irvine, dives into the whirlwind world of AI advancements. He unpacks the transformative impact of ChatGPT and large language models, highlighting the importance of structured reasoning and clean data. Sameer also critiques the Galactica model with a nod to the public's expectations, explores practical uses like Copilot, and shares predictions for AI trends in 2023. His insights shed light on the evolving landscape of voice assistants and the intricate relationship between AI and search.
27 snips
Jan 16, 2023 • 60min
AI Trends 2023: Reinforcement Learning - RLHF, Robotic Pre-Training, and Offline RL with Sergey Levine - #612
Sergey Levine, an associate professor at UC Berkeley, dives into cutting-edge advancements in reinforcement learning. He explores the impact of RLHF on language models and discusses innovations in offline RL and robotics. They also examine how language models can enhance diplomatic strategies and tackle ethical concerns. Sergey sheds light on manipulation in RL, the challenges of integrating robots with language models, and offers exciting predictions for 2023's developments. This is a must-listen for anyone interested in the future of AI!
Jan 9, 2023 • 1h 6min
Supporting Food Security in Africa Using ML with Catherine Nakalembe - #611
Catherine Nakalembe, an Associate Research Professor at the University of Maryland and Africa Program Director at NASA Harvest, discusses her work on food security in Africa through machine learning and satellite data. She highlights the critical challenges of food insecurity exacerbated by climate change and the COVID-19 pandemic. Catherine delves into innovative techniques like multi-task learning for crop mapping and emphasizes the importance of improving access to remote sensing data. Collaborations and local initiatives are vital for enhancing agricultural productivity and sustainability.
Jan 2, 2023 • 39min
Service Cards and ML Governance with Michael Kearns - #610
In a fascinating discussion, Michael Kearns, a UPenn professor and Amazon Scholar, delves into the vital topics of AI governance and fairness. He describes the innovative service cards introduced at Amazon, emphasizing their holistic approach compared to traditional model cards. Kearns also tackles the ongoing debate surrounding algorithmic versus dataset bias, reflecting on current challenges in fairness within large language models. His insights shed light on the importance of responsibly addressing these issues in AI development.
39 snips
Dec 29, 2022 • 41min
Reinforcement Learning for Personalization at Spotify with Tony Jebara - #609
Tony Jebara, VP of Engineering and Head of Machine Learning at Spotify, shares insights on how the platform evolves its personalization strategies through reinforcement learning. He explains the balance between immediate rewards and long-term user engagement, emphasizing the importance of Lifetime Value (LTV) in enhancing subscription retention. Jebara discusses innovative approaches in user behavior modeling, using coin and dice analogies to illustrate preferences. Learn how Spotify is transforming recommendations to create a richer user experience!
24 snips
Dec 26, 2022 • 37min
Will ChatGPT take my job? - #608
In this intriguing conversation with ChatGPT, a groundbreaking AI language model from OpenAI, the discussion dives into the pressing question of whether AI will take our jobs. ChatGPT explores its own capabilities in conversational context, revealing both opportunities and challenges for the workforce. The model discusses how it interprets human emotions and the nuances of effective communication, while also reflecting on the irreplaceable human touch in interviews. Finally, listeners are left to ponder the future role of AI in their careers.
Dec 22, 2022 • 37min
Geospatial Machine Learning at AWS with Kumar Chellapilla - #607
Join Kumar Chellapilla, General Manager of ML and AI Services at AWS, as he delves into the exciting world of geospatial machine learning. He discusses the recent integration of geospatial data in SageMaker and its potential to revolutionize industries like agriculture and automotive. Kumar highlights how satellite imagery can enhance economic predictions and addresses challenges in data accessibility. He also forecasts the future of geospatial data, including intriguing intersections with generative models and digital twins.
16 snips
Dec 19, 2022 • 44min
Real-Time ML Workflows at Capital One with Disha Singla - #606
Disha Singla, Senior Director of Machine Learning Engineering at Capital One, leads efforts to democratize ML across the company. She discusses the creation of reusable workflows and libraries designed for citizen data scientists, enabling quicker decision-making. The conversation dives into the implementation of real-time ML, balancing the need for speed in insights with regulatory compliance. Disha also shares strategies for securing executive buy-in by demonstrating ROI and emphasizes the importance of rigorous testing and observability in ML models.
18 snips
Dec 15, 2022 • 47min
Weakly Supervised Causal Representation Learning with Johann Brehmer - #605
Join Johann Brehmer, a research scientist at Qualcomm AI Research, as he dives into the intriguing world of causal representation learning. He shares insights from his work, emphasizing how high-level causal representations can be identified in weakly supervised environments. They discuss the implications of causality in machine learning, including advancements in autonomous driving and the challenges faced in achieving reliable systems. Brehmer also highlights innovative methodologies and new frameworks for optimizing neural networks and understanding complex causal mechanisms.
