DataFramed

• #305 RAG 2.0 and The New Era of RAG Agents with Douwe Kiela, CEO at Contextual AI, Adjunct Professor at Stanford University, Inventor of RAG

  Retrieval Augmented Generation (RAG) continues to be a foundational approach in AI despite claims of its demise. While some marketing narratives suggest RAG is being replaced by fine-tuning or long context windows, these technologies are actually complementary rather than competitive. But how do you build a truly effective RAG system that delivers accurate results in high-stakes environments? What separates a basic RAG implementation from an enterprise-grade solution that can handle complex queries across disparate data sources? And with the rise of AI agents, how will RAG evolve to support more dynamic reasoning capabilities?Douwe Kiela is the CEO and co-founder of Contextual AI, a company at the forefront of next-generation language model development. He also serves as an Adjunct Professor in Symbolic Systems at Stanford University, where he contributes to advancing the theoretical and practical understanding of AI systems.Before founding Contextual AI, Douwe was the Head of Research at Hugging Face, where he led groundbreaking efforts in natural language processing and machine learning. Prior to that, he was a Research Scientist and Research Lead at Meta’s FAIR (Fundamental AI Research) team, where he played a pivotal role in developing Retrieval-Augmented Generation (RAG)—a paradigm-shifting innovation in AI that combines retrieval systems with generative models for more grounded and contextually aware responses.In the episode, Richie and Douwe explore the misconceptions around the death of Retrieval Augmented Generation (RAG), the evolution to RAG 2.0, its applications in high-stakes industries, the importance of metadata and entitlements in data governance, the potential of agentic systems in enterprise settings, and much more.Links Mentioned in the Show:Contextual AIConnect with DouweCourse: Retrieval Augmented Generation (RAG) with LangChainRelated Episode: High Performance Generative AI Applications with Ram Sriharsha, CTO at PineconeRegister for RADAR AI - June 26New to DataCamp?Learn on the go using the DataCamp mobile appEmpower your business with world-class data and AI skills with DataCamp for business

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• #304 Accelerating Data Science with Nick Becker, Technical Product Manager at NVIDIA & Dan Hannah, Associate Director at SES AI

  GPU acceleration is transforming how data scientists tackle computationally intensive problems in the AI and materials science fields. When dealing with billions of potential molecular combinations or massive datasets requiring dimensionality reduction, traditional CPU approaches often become prohibitively slow and expensive. How can data professionals determine when GPU acceleration will provide meaningful benefits to their workflows? Understanding the right applications for this technology can mean the difference between waiting hours versus minutes for critical results.Nick Becker is a Group Product Manager at NVIDIA, focused on building RAPIDS and the broader accelerated data science ecosystem. Nick has a professional background in technology and government. Prior to NVIDIA, he worked at Enigma Technologies, a data science startup. Before Enigma, he conducted economics research and forecasting at the Federal Reserve Board of Governors, the central bank of the United States.Dan Hannah is an Associate Director at SES AI Corporation. At SES, Dan leads a research program focused on discovering new battery materials using machine learning, chemical informatics, and physics-driven simulations. Prior to joining SES, Dan spent several years as a data scientist in the cybersecurity industry. Dan holds a Ph.D. in Physical Chemistry from Northwestern University and did a postdoctoral fellowship at Berkeley National Lab, where his focus was the discovery of novel inorganic materials for energy applications.In the episode, Richie, Nick, and Dan explore the quest for new battery technologies, the role of data science and machine learning in material discovery, the integration of NVIDIA's GPU technology, the balance between computational simulations and lab work, and much more.Links Mentioned in the Show:NVIDIA RAPIDSSES AI CorporationConnect with Dan and NickCareer Track: Machine Learning Scientist in PythonRelated Episode: Data Science Trends from 2 Kaggle Grandmasters with Jean-Francois Puget, Distinguished Engineer at NVIDIA & Chris Deotte, Senior Data Scientist at NVIDIARewatch sessions from RADAR: Skills EditionNew to DataCamp?Learn on the go using the DataCamp mobile appEmpower your business with world-class data and AI skills with DataCamp for business

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• #303 Increasing Your Organization's AI Maturity with Iwo Szapar & Eryn Peters, Founders at AI Maturity Index

  AI maturity isn't achieved through technology alone—it requires organizational alignment, cultural readiness, and strategic implementation. Companies across industries are working to move beyond experimental AI use toward systematic integration that delivers measurable business value. How do you assess where your organization stands on the AI maturity spectrum? What frameworks can help prioritize your efforts?Eryn Peters, Co-founder & co-creator at AI Maturity Index, is a future of work evangelist. She is the co-creator of a tool for assessing AI maturity, and regularly advises companies on how to assess and improve their AI maturity. Eryn is also the Editor of the Weekly Workforce newsletter and the Principal at the Startup Consortium consultancy. Previously, she was the Global Director of the Association for the Future of Work, and VP of Marketing at Andela.Iwo Szapar is a serial entrepreneur with a passion for creating impactful solutions that enable people to work smarter, not harder. He is the co-founder of several innovative initiatives, including Remote-how, Remote-First Institute, AI-Mentor, and the Saudi AI Leadership Forum. Throughout his career, Iwo has helped transform how over 3,000 companies—including Microsoft, Walmart, and ING Bank—approach the future of work.In the episode, Richie, Eryn, and Iwo explore AI maturity in organizations, the balance between top-down and bottom-up AI adoption, the relationship between data and AI maturity, the importance of change management, practical steps for AI implementation, and much more.Links Mentioned in the Show:AI Maturity IndexEryn’s WebsiteIwo’s Book: Remote Work Is The WayConnect with Eryn and IwoState of Data & AI Literacy Report 2025Eryn’s previous webinar: Assessing Your Organization's AI MaturityRelated Episode: Scaling Responsible AI Literacy with Uthman Ali, Global Head of Responsible AI at BPRewatch sessions from RADAR: Skills EditionNew to DataCamp?Learn on the go using the DataCamp mobile appEmpower your business with world-class data and AI skills with DataCamp for business

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• #302 Making AI Applications like Greased Lightning with William Falcon, CEO at Lightning AI

  AI tooling continues to expand with specialized solutions for every step of the development process. For data scientists and engineers, this creates a paradox: more options but potentially more complexity and integration challenges. How do you determine which tools actually improve productivity versus adding unnecessary overhead? Should you prioritize flexibility with individual best-of-breed components or streamline with integrated platforms? What's the most effective way to bridge the gap between experimentation and production-ready AI applications?William Falcon is an AI researcher and the CEO of Lightning AI. He is the creator of PyTorch Lightning, a lightweight framework designed for training models of any size. As the founder of Lightning AI, he leads the development of Lightning AI Studios and the AI Hub. Falcon also shares his expertise in AI research and machine learning engineering through educational content on YouTube and X (formerly Twitter). He is passionate about leveraging AI for social impact.In the episode, Richie and William explore the NY AI hub, the journey from AI idea to production, diverse perspectives in AI development, how Lightning AI simplifies AI workflows, the significance of open-source models, and much more.Links Mentioned in the Show:Lightning AIPyTorch LightningConnect with WilliamCourse: Introduction to Deep Learning in PyTorch CourseRelated Episode: Building Multi-Modal AI Applications with Russ d'Sa, CEO & Co-founder of LiveKitRewatch sessions from RADAR: Skills EditionNew to DataCamp?Learn on the go using the DataCamp mobile appEmpower your business with world-class data and AI skills with DataCamp for business

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• #301 What the Like Button Tells You About Your Customers with Bob Goodson, Inventor of the Like Button

  The like button has transformed how we interact online, becoming a cornerstone of digital engagement with over 7 billion clicks daily. What started as a simple user interface solution has evolved into a powerful data collection tool that companies use to understand customer preferences, predict trends, and build sophisticated recommendation systems. The data behind these interactions forms what experts call the 'like graph' - a valuable network of connections that might be one of your company's most underutilized assets.Bob Goodson is President and Founder of Quid, a Silicon Valley–based company whose AI models are used by a third of the Fortune 50. Before starting Quid, he was the first employee at Yelp, where he played a role in the genesis of the like button and observed firsthand the rise of the social media industry. After Quid received an award in 2016 from the World Economic Forum for “Contributions to the Future of the Internet,” Bob served a two-year term on WEF’s Global Future Council for Artificial Intelligence & Robotics. While at Oxford University doing graduate research in language theory, Bob co-founded Oxford Entrepreneurs to connect scientists with business-minded students. Bob is co-author of a new book, Like: The Button That Changed the World, focussed on the origins of the ubiquitous Like Button in social media.In the episode, Richie and Bob explore the origins of the like button, its impact on user interaction and business, the evolution of social media features, the significance of relational data, and the future of social networks in the age of AI, and much more.Links Mentioned in the Show:Bob’s book—Like: The Button That Changed the WorldConnect with BobCourse: Analyzing Social Media Data in PythonRelated Episode: How I Nearly Got Fired For Running An A/B Test with Vanessa Larco, Former Partner at New Enterprise AssociatesRewatch sessions from RADAR: Skills EditionNew to DataCamp?Learn on the go using the DataCamp mobile appEmpower your business with world-class data and AI skills with DataCamp for business

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