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
Dec 11, 2023 • 36min
Patterns and Middleware for LLM Applications with Kyle Roche - #659
Join Kyle Roche, the founder and CEO of Griptape and former GM at AWS, as he dives deep into middleware for generative AI. He unveils innovative patterns for LLM applications, including off-prompt data retrieval and flexible pipeline management. Roche discusses how Griptape enhances data connectivity while addressing privacy and management concerns. Tune in to learn about driving efficiencies in various industries and the impact of responsible AI solutions!
Dec 4, 2023 • 42min
AI Access and Inclusivity as a Technical Challenge with Prem Natarajan - #658
In this discussion, Prem Natarajan, Chief Scientist and Head of Enterprise AI at Capital One, tackles AI access and inclusivity as critical challenges in banking. He highlights the importance of diversity in data sets to combat biases and improve fraud detection. Prem shares insights on the use of foundation models and federated learning, emphasizing data quality and privacy preservation. He also stresses the need for collaboration between academia and industry to enhance AI impact, ultimately advocating for mission-inspired research that benefits customers and the broader community.
31 snips
Nov 28, 2023 • 43min
Building LLM-Based Applications with Azure OpenAI with Jay Emery - #657
In a captivating discussion, Jay Emery, Director of Technical Sales & Architecture at Microsoft Azure, shares insights on crafting applications using large language models. He tackles challenges organizations face, such as data privacy and performance optimization. Jay reveals innovative techniques like prompt tuning and retrieval-augmented generation to enhance LLM outputs. He also discusses unique business use cases and effective methods to manage costs while improving functionality. This conversation is packed with practical strategies for anyone interested in the AI landscape.
15 snips
Nov 20, 2023 • 41min
Visual Generative AI Ecosystem Challenges with Richard Zhang - #656
In this discussion, Richard Zhang, a Senior Research Scientist at Adobe Research specializing in visual generative AI, tackles significant challenges in the AI ecosystem. He dives into the creation of effective perceptual metrics for AI, emphasizing the role of LPIPS in aligning human and machine evaluations. Zhang also addresses the pressing need for detection tools to combat fake visuals and the complexities of data attribution in generative art. His insights emphasize the delicate balance between creator autonomy and consumer trust in this rapidly evolving field.
Nov 13, 2023 • 39min
Deploying Edge and Embedded AI Systems with Heather Gorr - #655
Heather Gorr, Principal MATLAB Product Marketing Manager at MathWorks, dives into the fascinating world of deploying AI models for embedded systems. She emphasizes crucial factors like data preparation, device constraints, and latency requirements for successful implementation. Heather shares insights on MLOps techniques to enhance deployment speed, while tailoring AI solutions for industries such as automotive and oil & gas. Anecdotes of real-world AI applications illustrate the importance of rigorous validation processes and interdisciplinary collaboration in ensuring safety and reliability.
40 snips
Nov 6, 2023 • 48min
AI Sentience, Agency and Catastrophic Risk with Yoshua Bengio - #654
Yoshua Bengio, a leading AI safety researcher from Université de Montréal, joins the conversation to discuss the dire risks posed by advanced AI technologies. He highlights the potential for AI to manipulate, spread disinformation, and concentrate power, raising alarm over its impact on democracy. The discussion dives into the complexities of AI safety, agency, and the troubling distinction between mimicking emotion and true sentience. Bengio advocates for robust safety measures, regulatory frameworks, and an urgent need to align AI developments with human values.
20 snips
Oct 30, 2023 • 44min
Delivering AI Systems in Highly Regulated Environments with Miriam Friedel - #653
Miriam Friedel, Senior Director of ML Engineering at Capital One, shares her insights on deploying AI tools in regulated environments. She discusses creating a culture of collaboration and the importance of standardized tooling. Miriam highlights strategies like using open-source tools for compliance and speed, and dives into the challenges of maintaining consistency across large organizations. Her thoughts on building a 'unicorn' team and making smart build vs. buy decisions for MLOps offer a fresh perspective on the future of enterprise AI.
78 snips
Oct 23, 2023 • 40min
Mental Models for Advanced ChatGPT Prompting with Riley Goodside - #652
Riley Goodside, a staff prompt engineer at Scale AI, shares insights on mastering prompt engineering for large language models. He dives into the limitations and capabilities of LLMs, emphasizing the intricacies of autoregressive inference. Goodside discusses the effectiveness of zero-shot vs. k-shot prompting and the crucial role of Reinforcement Learning from Human Feedback. He highlights how effective prompting acts as a scaffolding structure to achieve desired AI responses, blending technical skill with strategic thinking.
42 snips
Oct 16, 2023 • 1h 19min
Multilingual LLMs and the Values Divide in AI with Sara Hooker - #651
Sara Hooker, Director at Cohere and head of Cohere For AI, dives into the fascinating world of multilingual language models and responsible AI. She discusses challenges in data quality, the Mixture of Experts technique, and the need for better collaboration between researchers and hardware architects. Sara highlights the emotional connection language models create in society, as well as safety concerns regarding universal AI models. The conversation emphasizes the importance of open science, inclusivity, and responsible practices in AI development for a harmonious future.
18 snips
Oct 9, 2023 • 39min
Scaling Multi-Modal Generative AI with Luke Zettlemoyer - #650
In this discussion, Luke Zettlemoyer, a University of Washington professor and Meta research manager, dives into the fascinating realm of multimodal generative AI. He highlights the transformative impact of integrating text and images, illustrating advancements like DALL-E 3. Zettlemoyer explains the significance of open science for AI development and the complexities of data in enhancing model performance. Topics also include the role of self-alignment in training and the future of multimodal AI amidst rising technology costs and the need for better assessment methods.
