Best Nlu Podcasts (2025)

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1101: NLU Personal Golf Rewind 2025 1:54:00

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11d ago1:54:00

1:54:00

Soly, TC, Randy, DJ and Neil comb through the data of Team NLU’s golf in 2025 via the USGA GHIN app to see who made the biggest moves in the last twelve months, how we fared in the “Will They Go Lower in 2025” game from last year’s pod and guess if we’ll better our low round from this year in 2026. We also vow to stop (or start) something in 2026, …

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Why Your AI Is Failing: The NLU Paradigm Shift CTOs Must Understand 31:51

13d ago31:51

31:51

Is your AI initiative falling short despite the hype? The root cause often lies not in the AI technology itself but in how your architecture handles the Natural Language Understanding (NLU) layer. In this episode, we explore why treating AI as a bolt-on feature leads to failure and what leadership must do to embrace the fundamental paradigm shift r…

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Why Your AI Is Failing: The NLU Paradigm Shift CTOs Can’t Ignore 38:32

17d ago38:32

38:32

Are your AI initiatives stalling in production? This episode uncovers the critical architectural shift brought by the Natural Language Understanding (NLU) layer and why treating AI as just another feature is setting CTOs up for failure. Learn how rethinking your entire stack—from closed-world deterministic workflows to open-world AI-driven orchestr…

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1104: 2025 Birdies and Bogeys + Mike McCartin from National Links Trust 1:53:29

3d ago1:53:29

1:53:29

DJ, Tron and Soly have our final Sunday night pod of 2025 with a two part episode this evening. We start with a Birdies and Bogeys segment highlighting the biggest newsmakers and moments in 2025. Part two focuses on the news this week from the National Links Trust and the political involvement that could harm access to affordable golf in DC. Soly a…

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1103: The World of Simulator Golf with Carl Markestad 1:03:57

6d ago1:03:57

1:03:57

Carl Markestad - owner of Carl's Place in Milton, Wisconsin - has turned what started out as a business focused on outdoor projector screen setups into one of the largest indoor golf simulator companies in the country. As winter sets in across the country, DJ and Carl discuss the evolution of the indoor golf simulator, technological updates that ha…

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1102: LPGA Season Wrap-Up 2025 1:25:08

8d ago1:25:08

1:25:08

Randy, Cody and Jordan put a bow on the 2025 LPGA season with a quick review of last week’s Grant Thornton (Way to go LC!!!) and the biggest storylines from the past twelve months in the women’s game including Craig Kessler’s arrival as the new LPGA Tour Commissioner, Nelly’s winless campaign in the year of parity on tour, emerging Japanese players…

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Model Context Protocol: The Universal AI Integration Standard Explained 20:10

10d ago20:10

20:10

Discover how the Model Context Protocol (MCP) is revolutionizing AI systems integration by simplifying complex multi-tool interactions into a scalable, open standard. In this episode, we unpack MCP’s architecture, adoption by industry leaders, and its impact on engineering workflows. In this episode: - What MCP is and why it matters for AI/ML engin…

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Model Context Protocol (MCP): The Future of Scalable AI Integration 18:27

11d ago18:27

18:27

Discover how the Model Context Protocol (MCP) is revolutionizing AI system integration by simplifying complex connections between AI models and external tools. This episode breaks down the technical and strategic impact of MCP, its rapid adoption by industry giants, and what it means for your AI strategy. In this episode: - Understand the M×N integ…

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RAG Evaluation with ragas: Reference-Free Metrics & Monitoring 26:47

11d ago26:47

26:47

Unlock the secrets to evaluating Retrieval-Augmented Generation (RAG) pipelines effectively and efficiently with ragas, the open-source framework that’s transforming AI quality assurance. In this episode, we explore how to implement reference-free evaluation, integrate continuous monitoring into your AI workflows, and optimize for production scale …

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RAG & Reference-Free Evaluation: Scaling LLM Quality Without Ground Truth 23:39

13d ago23:39

23:39

In this episode of Memriq Inference Digest - Leadership Edition, we explore how Retrieval-Augmented Generation (RAG) systems maintain quality and trust at scale through advanced evaluation methods. Join Morgan, Casey, and special guest Keith Bourne as they unpack the game-changing RAGAS framework and the emerging practice of reference-free evaluati…

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Agent Engineering Unpacked: New Discipline or Just Hype? 30:02

12d ago30:02

30:02

Is agent engineering the next big AI discipline or a repackaged buzzword? In this episode, we cut through the hype to explore what agent engineering really means for business leaders navigating AI adoption. From market growth and real-world impact to the critical role of AI memory and the evolving tool landscape, we provide a clear-eyed view to hel…

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Agent Engineering Unpacked: New Discipline or Just Hype? 29:49

13d ago29:49

29:49

Is agent engineering the next big AI discipline or a repackaged buzzword? In this episode, we cut through the hype to explore what agent engineering really means for business leaders navigating AI adoption. From market growth and real-world impact to the critical role of AI memory and the evolving tool landscape, we provide a clear-eyed view to hel…

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Procedural Memory for RAG (Chapter 18) 18:48

14d ago18:48

18:48

Unlock how procedural memory transforms Retrieval-Augmented Generation (RAG) systems from static responders into autonomous, self-improving AI agents. Join hosts Morgan and Casey with special guest Keith Bourne as they unpack the concepts behind LangMem and explore why this innovation is a game-changer for business leaders. In this episode: - Under…

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Agentic Memory: Stateful RAG and AI Agents (Chapter 16) 19:27

18d ago19:27

19:27

Unlock the future of AI agents with agentic memory — a transformative approach that extends Retrieval-Augmented Generation (RAG) by incorporating persistent, evolving memories. In this episode, we explore how stateful intelligence turns stateless LLMs into adaptive, personalized agents capable of learning over time. In this episode: - Understand th…

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Procedural Memory for RAG: Deep Dive with LangMem (Chapter 18) 18:09

18d ago18:09

18:09

Unlock the power of procedural memory to transform your Retrieval-Augmented Generation (RAG) agents into autonomous learners. In this episode, we explore how LangMem leverages hierarchical learning scopes to enable AI agents that continuously adapt and improve from their interactions — cutting down manual tuning and boosting real-world performance.…

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RAG-Based Agentic Memory: Code Perspective (Chapter 17) 16:47

18d ago16:47

16:47

Unlock how Retrieval-Augmented Generation (RAG) enables AI agents to remember, learn, and personalize over time. In this episode, we explore Chapter 17 of Keith Bourne’s "Unlocking Data with Generative AI and RAG," focusing on implementing agentic memory with the CoALA framework. From episodic and semantic memory distinctions to real-world engineer…

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Advanced RAG with Complete Memory Integration (Chapter 19) 17:15

17d ago17:15

17:15

Unlock the next level of Retrieval-Augmented Generation with full memory integration in AI agents. In the previous 3 episodes, we secretly built up what amounts to a 4-part series on agentic memory. This is the final piece of that 4-part series that pulls it ALL together. In this episode, we explore how combining episodic, semantic, and procedural …

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Ontology-Based Knowledge Engineering for Graphs (Chapter 13) 17:57

18d ago17:57

17:57

Unlock how ontology-driven knowledge engineering transforms AI from guesswork into a trusted decision partner. In this episode, we explore why ontologies matter now, their strategic advantages for compliance and risk management, and how tools like Protégé and OWL enable explainable, multi-step AI reasoning. In this episode: - Understand the differe…

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Advanced RAG & Memory Integration (Chapter 19) 18:22

14d ago18:22

18:22

Unlock how AI is evolving beyond static models into adaptive experts with integrated memories. In the previous 3 episodes, we secretly built up what amounts to a 4-part series on agentic memory. This is the final piece of that 4-part series that pulls it ALL together. In this episode, we unpack Chapter 19 of Keith Bourne's 'Unlocking Data with Gene…

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RAG-Based Agentic Memory in AI (Chapter 17) 18:51

14d ago18:51

18:51

Unlock how RAG-based agentic memory is transforming AI from forgetful chatbots into intelligent assistants that remember and adapt. In this episode, we break down the core concepts from Chapter 17 of Keith Bourne’s “Unlocking Data with Generative AI and RAG,” exploring why memory-enabled AI is a game changer for customer experience and operational …

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Semantic Caches: Faster, Cheaper AI Inference (Chapter 15) 18:43

14d ago18:43

18:43

Semantic caches are revolutionizing AI-powered applications by drastically reducing query latency and inference costs while improving response consistency. In this episode, we unpack Chapter 15 of Keith Bourne’s 'Unlocking Data with Generative AI and RAG' to explore how semantic caching works, why it’s critical now, and what it means for business l…

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Graph-Based RAG: Smarter, Explainable AI Reasoning (Chapter 14) 19:06

18d ago19:06

19:06

Unlock the power of Graph-Based Retrieval-Augmented Generation (RAG) with insights from Chapter 14 of Keith Bourne's 'Unlocking Data with Generative AI and RAG.' This episode explores how combining knowledge graphs with generative AI transforms accuracy, explainability, and multi-step reasoning—critical for leaders in regulated industries. In this …

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Agentic RAG & LangGraph: Next-Gen AI Orchestration (Chapter 12) 21:15

18d ago21:15

21:15

Unlock the next evolution of Retrieval-Augmented Generation in this episode of Memriq Inference Digest – Engineering Edition. We explore how combining AI agents with LangGraph's graph-based orchestration transforms brittle linear RAG pipelines into dynamic, multi-step reasoning systems that self-correct and scale. In this episode: - Understand the …

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Semantic Caches: Scaling AI with Smarter Caching (Chapter 15) 20:04

18d ago20:04

20:04

emantic caches are transforming how AI systems handle costly reasoning by intelligently reusing prior agent workflows to slash latency and inference costs. In this episode, we unpack Chapter 15 of Keith Bourne’s "Unlocking Data with Generative AI and RAG," exploring the architectures, trade-offs, and practical engineering of semantic caches for pro…

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Agentic Memory: Stateful AI & RAG Extensions (Chapter 16) 17:55

14d ago17:55

17:55

Discover how agentic memory is transforming AI from forgetful assistants into adaptive, stateful partners that remember, learn, and evolve over time. In this episode, we unpack Chapter 16 of Keith Bourne’s 'Unlocking Data with Generative AI and RAG' and explore the strategic impact of extending Retrieval-Augmented Generation (RAG) with dynamic memo…

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Agent-Enhanced RAG & LangGraph: Deep Dive for Leaders (Chapter 12) 14:45

18d ago14:45

14:45

Unlock the future of AI-driven insights by combining Retrieval-Augmented Generation (RAG) with AI agents and LangGraph’s graph-based orchestration. This episode breaks down how multi-step reasoning loops and precise workflow control transform AI from a simple Q&A tool into a dynamic problem solver — a must-know for product leaders, founders, and de…

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Graph-Based RAG: Hybrid Embeddings & Explainable AI (Chapter 14) 21:44

18d ago21:44

21:44

Unlock the power of graph-based Retrieval-Augmented Generation (RAG) in this technical deep dive featuring insights from Chapter 14 of Keith Bourne's "Unlocking Data with Generative AI and RAG." Discover how combining knowledge graphs with LLMs using hybrid embeddings and explicit graph traversal can dramatically improve multi-hop reasoning accurac…

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Using LangChain to Get More from RAG (Chapter 11) 23:28

18d ago23:28

23:28

Unlock the full potential of Retrieval-Augmented Generation (RAG) with LangChain’s modular components in this episode of Memriq Inference Digest — Engineering Edition. We dive deep into Chapter 11 of Keith Bourne’s book, exploring how document loaders, semantic text splitters, and structured output parsers can transform your RAG pipelines for bette…

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Ontology-Based Knowledge Engineering for Graphs (Chapter 13) 19:07

18d ago19:07

19:07

Ontologies are the semantic backbone that enable AI systems to reason precisely over complex domain knowledge, far beyond what vector embeddings alone can achieve. In this episode, we explore ontology-based knowledge engineering for graph-backed AI, featuring insights from Keith Bourne's Chapter 13 of *Unlocking Data with Generative AI and RAG*. Le…

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Using LangChain to Get More from RAG (Chapter 11) 20:11

14d ago20:11

20:11

Unlock the true business value of Retrieval-Augmented Generation (RAG) with LangChain’s modular toolkit. In this episode, we explore how document loaders, text splitters, and output parsers transform unstructured data into actionable AI insights. Join author Keith Bourne and the Memriq team as they unpack practical strategies, trade-offs, and real-…

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1100: NLU Personal Golf Spotlight - Cody 1:02:54

14d ago1:02:54

1:02:54

Neil has returned from paternity leave to put Cody front and center for our latest installment of the Personal Golf Spotlight series. We get the latest on Cody’s game, his brief history of playing in Monday qualifiers, his favorite and least favorite golfers of all time, and his personal top ten favorite golf courses. Join us in our support of the …

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Similarity Searching with Vectors (Chapter 8) 20:34

18d ago20:34

20:34

Unlock the power of similarity search with vectors in this episode of Memriq Inference Digest – Engineering Edition. We explore how dense and sparse vector techniques combine to enable scalable, accurate semantic retrieval for AI systems, inspired by Chapter 8 of Keith Bourne’s book. Join us and special guest Keith Bourne as we unpack the engineeri…

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Evaluating RAG: Deep Dive on Metrics & Visualizations for Leaders (Chapter 9) 18:23

18d ago18:23

18:23

Unlock the power of continuous evaluation for Retrieval-Augmented Generation (RAG) systems in this episode of Memriq Inference Digest - Leadership Edition. We explore how quantitative metrics and intuitive visualizations help leaders ensure their AI delivers real business value and stays relevant post-deployment. In this episode: - Why RAG evaluati…

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Interfacing RAG with Gradio: Rapid Prototyping (Chapter 6) 19:10

19d ago19:10

19:10

Unlock the power of retrieval-augmented generation (RAG) by integrating it seamlessly with Gradio. In this episode, we explore how Gradio simplifies building interactive RAG applications, enabling AI engineers to prototype and share demos quickly without complex frontend coding. In this episode: - Discover how Gradio’s `demo.launch(share=True)` com…

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RAG Components Unpacked (Chapter 4) 16:23

19d ago16:23

16:23

Unlock the engineering essentials behind Retrieval-Augmented Generation (RAG) in this episode of Memriq Inference Digest — Engineering Edition. We break down the core components of RAG pipelines as detailed in Chapter 4 of Keith Bourne’s book, exploring how offline indexing, real-time retrieval, and generation come together to solve the LLM knowled…

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Key RAG Components in LangChain (Chapter 10) 18:18

19d ago18:18

18:18

Unlock the inner workings of Retrieval-Augmented Generation (RAG) pipelines using LangChain in this episode of Memriq Inference Digest - Engineering Edition. We bring insights directly from Keith Bourne, author of 'Unlocking Data with Generative AI and RAG,' as we explore modular vector stores, retrievers, and LLM integrations critical for building…

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RAG Deep Dive: Building AI Systems That Actually Know Your Data (Chapter 1-3) 20:45

19d ago20:45

20:45

In this episode, we take a deep technical dive into Retrieval-Augmented Generation (RAG), drawing heavily from Keith Bourne's book Unlocking Data with Generative AI and RAG. We explore why RAG has become indispensable for enterprise AI systems, break down the core architecture, and share practical implementation guidance for engineers building prod…

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Security in RAG Systems (Chapter 5) 18:13

18d ago18:13

18:13

Unlocking the security challenges in Retrieval-Augmented Generation (RAG) systems is critical for business leaders steering AI innovation. This episode unpacks how advanced AI models can increase security risks, why layered defenses are essential, and what practical steps you can take to protect your enterprise data. In this episode: - Why smarter …

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Similarity Searching with Vectors: Deep Dive for Leaders (Chapter 8) 18:58

19d ago18:58

18:58

Discover how similarity searching with vectors is revolutionizing information retrieval beyond traditional keyword search. In this episode, we break down the business impact, technology trade-offs, and strategic considerations leaders need to harness this powerful approach. Drawing from Chapter 8 of Keith Bourne's "Unlocking Data with Generative AI…

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RAG Decoded: How Retrieval-Augmented Generation Is Transforming Enterprise AI - (Chapter 1-3) 20:34

19d ago20:34

20:34

In this episode, we break down Retrieval-Augmented Generation (RAG)—the architecture that's enabling AI systems to tap into your company's private data in real time. Drawing from the first three chapters of the second edition of Keith Bourne's Unlocking Data with Generative AI and RAG, we explore what RAG is, why it's become essential now, and how …

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Evaluating RAG: Quantitative Metrics and Visual Insights (Chapter 9) 20:13

19d ago20:13

20:13

In this episode of Memriq Inference Digest — Engineering Edition, we dive deep into rigorous evaluation strategies for Retrieval-Augmented Generation (RAG) systems. Drawing from Chapter 9 of Keith Bourne’s book, we explore how quantitative metrics and visualizations help AI engineers optimize retrieval and generation performance while managing cost…

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Interfacing with RAG and Gradio (Chapter 6) 17:11

18d ago17:11

17:11

Unlock how Gradio empowers rapid, user-friendly interfaces for Retrieval-Augmented Generation (RAG) models in this episode of Memriq Inference Digest - Leadership Edition. Join Morgan, Casey, and special guest Keith Bourne as they explore practical strategies for accelerating AI demos, gathering user feedback, and bridging complex AI technology wit…

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RAG Components (Chapter 4) 16:16

18d ago16:16

16:16

Unlock the strategic power behind Retrieval-Augmented Generation (RAG) systems in this episode of Memriq Inference Digest - Leadership Edition. We break down the core components of RAG—indexing, retrieval, and generation—and explore why these architectures are game-changers for businesses drowning in unstructured data. In this episode: - Discover w…

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Vectors & Vector Stores in RAG (Chapter 7) 19:44

19d ago19:44

19:44

Unlock the core infrastructure powering retrieval-augmented generation (RAG) systems in this technical deep dive. We explore how vector embeddings and vector stores work together to enable fast, scalable, and semantically rich retrieval for LLMs, drawing insights directly from Chapter 7 of Keith Bourne’s book. In this episode: - Understand the role…

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Vectors & Vector Stores: Deep Dive into RAG’s Secret Sauce (Chapter 7) 17:51

19d ago17:51

17:51

Unlock the game-changing role vectors and vector stores play in Retrieval-Augmented Generation (RAG) and why they’re essential for modern AI-driven businesses. In this episode, we break down how these technologies revolutionize AI search and retrieval, enabling faster, smarter, and more context-aware systems. Join us and special guest Keith Bourne,…