Podcasts about Knowledge management

In 2016 Fulyana and Kim talked through 2 podcasts about knowledge management and knowledge transfer in organisations – its importance, how it could be managed, how it could be systematically stored. Now in 2026 knowledge management is a very different topic requiring a fundamental change to how we use, access and store both internal information and the wealth of external information now so readily available through AI and LLMs. Here are 10 areas to think about now…… Knowledge Management and AIDownload

Pour ce septième épisode de la saison 4 de Morning Data Chat, Aurélien Barthe, Chief Data & AI Officer de la MGEN, partage la manière dont l'organisation structure son knowledge management pour soutenir durablement ses usages data et IA.Il explique comment la gouvernance des données non structurées ; fiches de connaissance, documents réglementaires, contenus métiers, repose sur un réseau humain de référents, de rédacteurs et d'experts terrain, organisé selon une logique de gouvernance fédérée.Aurélien revient sur l'importance de la qualité, de la fraîcheur et de la structuration des contenus pour alimenter efficacement les cas d'usage d'IA générative, tout en conservant l'humain dans la boucle grâce à des rôles clés comme les Product Owners IA et les knowledge managers.Hébergé par Ausha. Visitez ausha.co/politique-de-confidentialite pour plus d'informations.

In this episode of Software People Stories, Jordan Richards, a Digital Transformation and Knowledge Management technologist, and Founder of Tacitous (www.tacitous.com) a Knowledge Management blueprint and platform designed to help organisations capture, retain, and share critical knowledge at scale shares his extensive experience with technology and knowledge management. From his early days with the ZX 80 computer to his consulting work with oil companies, Jordan emphasizes the importance of solving real-world problems through technology. He advocates for a 'people first, process second, technology third' approach, and shares insights on how to ensure successful adoption of IT solutions by understanding user stories and daily workflows. Jordan discusses the critical importance of managing both knowledge and collaboration within organizations, especially with regard to retirees, and touches on the implications of AI and digital twins in modern business environments. He also shares personal practices that help him stay grounded and continuously updated with the latest trends in technology. 00:00 Introduction and Welcome00:45 Guest's Origin Story in Technology01:43 Solving Problems with Technology02:15 User-Centric Approach to IT Solutions05:02 Challenges in IT Deployment05:41 Building Effective IT Strategies06:40 Understanding Organizational Knowledge Flows11:14 Importance of Personas in IT Solutions18:56 Knowledge Management and AI27:56 Engaging Retirees: Challenges and Solutions29:38 Building a National Repository of Expertise32:04 Encouraging Knowledge Sharing and Consumption34:41 The Role of AI in Knowledge Management39:21 The Importance of Human Oversight in Technology43:07 Staying Updated and Lifelong Learning49:00 Personal Principles for Staying GroundedThe timestamps are approximate and do not include the time for the intro. Add about 90 seconds to locate the sectionJordan Richards is a Digital Transformation and Knowledge Management technologist, and Founder of Tacitous (www.tacitous.com) a Knowledge Management blueprint and platform designed to help organisations capture, retain, and share critical knowledge at scale. With 20+ years of international experience across high-risk and complex environments (including Oil & Gas and large-scale operations), Jordan specialises in institutional memory, lessons learned, communities of practice, and AI-enabled knowledge retention. He works with government entities, NGOs, and industry leaders to build practical, technology-enabled KM ecosystems that strengthen workforce continuity and organisational resilience.Website: www.tacitous.comLinkedIn: https://www.linkedin.com/in/jordanrichards/Email: collaboration@tacitous.com

Ever feel like your notes, files, and ideas are scattered everywhere? You're not alone. In this episode, Bradley tackles one of the most common challenges for business owners: personal knowledge management. From books and podcasts to conference notes and client materials, learn where to put everything so you can actually find it when you need it. Bradley shares his proven three-system approach that will help you optimize for retrieval, not just organization.Register Now! Lead Yourself First: February 24th - an Above The Business WorkshopFREE workshop for business owners who planned well but are running on fumes.You set the goals in January. You aligned the team. You built the plan.But six weeks in, you're exhausted.Here's the truth: Your business won't grow beyond you until you lead yourself first.Join Bradley for a FREE 2-hour workshop on February 24th at 10 AM CST.You'll build your Personal Operating System, Decision Framework, Energy Protection Plan, Role Clarity Matrix, and 90-Day Accountability Structure.Space is limited. https://blueprintos.com/assetsThanks to our sponsors...Coach P found great success as an insurance agent and agency owner. He leads a large, stable team of professionals who are at the top of their game year after year. Now he shares the systems, processes, delegation, and specialization he developed along the way. Gain access to weekly training calls and mentoring at www.coachpconsulting.com. Be sure to mention the Above The Business Podcast when you get in touch.Autopilot Recruiting helps small business owners solve their staffing challenges by taking the stress out of hiring. Their dedicated recruiters work on your behalf every single business day - optimizing your applicant tracking system, posting job listings, and sourcing candidates through social media and local communities. With their continuous, hands-off recruiting approach, you can save time, reduce hiring costs, and receive pre-screened candidates, all without paying any hiring fees or commissions. More money & more freedom: that's what Autopilot Recruiting help business owners achieve. Visit https://www.autopilotrecruiting.com/ and don't forget to mention you heard about us on the Above The Business podcast.Direct Clicks is built is by business owners, for business owners. They specialize in custom marketing solutions that deliver real results. From paid search campaigns to SEO and social media management, they provide the comprehensive digital marketing your business needs to grow. Here's an exclusive offer for Above The Business listeners: Visit directclicksinc.com/abovethebusiness for a FREE marketing campaign audit. They'll assess your website, social media, SEO, content, and paid advertising, then provide actionable recommendations. Plus, when you choose to partner with them, they'll waive all setup fees.About Above The Business:Above The Business is hosted by Bradley Hamner, founder of BlueprintOS, and focuses on helping small business owners transition from Rainmaker to Architect. Each week, Bradley shares frameworks, interviews successful entrepreneurs, and provides actionable insights for building businesses that run without you. Whether you're doing $300K or $3M in revenue, this show will help you get above your business and design the systems you need to scale.

In this episode of the Crazy Wisdom Podcast, host Stewart Alsop sits down with Larry Swanson, a knowledge architect, community builder, and host of the Knowledge Graph Insights podcast. They explore the relationship between knowledge graphs and ontologies, why these technologies matter in the age of AI, and how symbolic AI complements the current wave of large language models. The conversation traces the history of neuro-symbolic AI from its origins at Dartmouth in 1956 through the semantic web vision of Tim Berners-Lee, examining why knowledge architecture remains underappreciated despite being deployed at major enterprises like Netflix, Amazon, and LinkedIn. Swanson explains how RDF (Resource Description Framework) enables both machines and humans to work with structured knowledge in ways that relational databases can't, while Alsop shares his journey from knowledge management director to understanding the practical necessity of ontologies for business operations. They discuss the philosophical roots of the field, the separation between knowledge management practitioners and knowledge engineers, and why startups often overlook these approaches until scale demands them. You can find Larry's podcast at KGI.fm or search for Knowledge Graph Insights on Spotify and YouTube.Timestamps00:00 Introduction to Knowledge Graphs and Ontologies01:09 The Importance of Ontologies in AI04:14 Philosophy's Role in Knowledge Management10:20 Debating the Relevance of RDF15:41 The Distinction Between Knowledge Management and Knowledge Engineering21:07 The Human Element in AI and Knowledge Architecture25:07 Startups vs. Enterprises: The Knowledge Gap29:57 Deterministic vs. Probabilistic AI32:18 The Marketing of AI: A Historical Perspective33:57 The Role of Knowledge Architecture in AI39:00 Understanding RDF and Its Importance44:47 The Intersection of AI and Human Intelligence50:50 Future Visions: AI, Ontologies, and Human BehaviorKey Insights1. Knowledge Graphs Combine Structure and Instances Through Ontological Design. A knowledge graph is built using an ontology that describes a specific domain you want to understand or work with. It includes both an ontological description of the terrain—defining what things exist and how they relate to one another—and instances of those things mapped to real-world data. This combination of abstract structure and concrete examples is what makes knowledge graphs powerful for discovery, question-answering, and enabling agentic AI systems. Not everyone agrees on the precise definition, but this understanding represents the practical approach most knowledge architects use when building these systems.2. Ontology Engineering Has Deep Philosophical Roots That Inform Modern Practice. The field draws heavily from classical philosophy, particularly ontology (the nature of what you know), epistemology (how you know what you know), and logic. These thousands-year-old philosophical frameworks provide the rigorous foundation for modern knowledge representation. Living in Heidelberg surrounded by philosophers, Swanson has discovered how much of knowledge graph work connects upstream to these philosophical roots. This philosophical grounding becomes especially important during times when institutional structures are collapsing, as we need to create new epistemological frameworks for civilization—knowledge management and ontology become critical tools for restructuring how we understand and organize information.3. The Semantic Web Vision Aimed to Transform the Internet Into a Distributed Database. Twenty-five years ago, Tim Berners-Lee, Jim Hendler, and Ora Lassila published a landmark article in Scientific American proposing the semantic web. While Berners-Lee had already connected documents across the web through HTML and HTTP, the semantic web aimed to connect all the data—essentially turning the internet into a giant database. This vision led to the development of RDF (Resource Description Framework), which emerged from DARPA research and provides the technical foundation for building knowledge graphs and ontologies. The origin story involved solving simple but important problems, like disambiguating whether "Cook" referred to a verb, noun, or a person's name at an academic conference.4. Symbolic AI and Neural Networks Represent Complementary Approaches Like Fast and Slow Thinking. Drawing on Kahneman's "thinking fast and slow" framework, LLMs represent the "fast brain"—learning monsters that can process enormous amounts of information and recognize patterns through natural language interfaces. Symbolic AI and knowledge graphs represent the "slow brain"—capturing actual knowledge and facts that can counter hallucinations and provide deterministic, explainable reasoning. This complementarity is driving the re-emergence of neuro-symbolic AI, which combines both approaches. The fundamental distinction is that symbolic AI systems are deterministic and can be fully explained, while LLMs are probabilistic and stochastic, making them unsuitable for applications requiring absolute reliability, such as industrial robotics or pharmaceutical research.5. Knowledge Architecture Remains Underappreciated Despite Powering Major Enterprises. While machine learning engineers currently receive most of the attention and budget, knowledge graphs actually power systems at Netflix (the economic graph), Amazon (the product graph), LinkedIn, Meta, and most major enterprises. The technology has been described as "the most astoundingly successful failure in the history of technology"—the semantic web vision seemed to fail, yet more than half of web pages now contain RDF-formatted semantic markup through schema.org, and every major enterprise uses knowledge graph technology in the background. Knowledge architects remain underappreciated partly because the work is cognitively difficult, requires talking to people (which engineers often avoid), and most advanced practitioners have PhDs in computer science, logic, or philosophy.6. RDF's Simple Subject-Predicate-Object Structure Enables Meaning and Data Linking. Unlike relational databases that store data in tables with rows and columns, RDF uses the simplest linguistic structure: subject-predicate-object (like "Larry knows Stuart"). Each element has a unique URI identifier, which permits precise meaning and enables linked data across systems. This graph structure makes it much easier to connect data after the fact compared to navigating tabular structures in relational databases. On top of RDF sits an entire stack of technologies including schema languages, query languages, ontological languages, and constraints languages—everything needed to turn data into actionable knowledge. The goal is inferring or articulating knowledge from RDF-structured data.7. The Future Requires Decoupled Modular Architectures Combining Multiple AI Approaches. The vision for the future involves separation of concerns through microservices-like architectures where different systems handle what they do best. LLMs excel at discovering possibilities and generating lists, while knowledge graphs excel at articulating human-vetted, deterministic versions of that information that systems can reliably use. Every one of Swanson's 300 podcast interviews over ten years ultimately concludes that regardless of technology, success comes down to human beings, their behavior, and the cultural changes needed to implement systems. The assumption that we can simply eliminate people from processes misses that huma...

In this episode of the Crazy Wisdom Podcast, host Stewart Alsop explores the complex world of context and knowledge graphs with guest Youssef Tharwat, the founder of NoodlBox who is building dot get for context. Their conversation spans from the philosophical nature of context and its crucial role in AI development, to the technical challenges of creating deterministic tools for software development. Tharwat explains how his product creates portable, versionable knowledge graphs from code repositories, leveraging the semantic relationships already present in programming languages to provide agents with better contextual understanding. They discuss the limitations of large context windows, the advantages of Rust for AI-assisted development, the recent Claude/Bun acquisition, and the broader geopolitical implications of the AI race between big tech companies and open-source alternatives. The conversation also touches on the sustainability of current AI business models and the potential for more efficient, locally-run solutions to challenge the dominance of compute-heavy approaches.For more information about NoodlBox and to join the beta, visit NoodlBox.io.Timestamps00:00 Stewart introduces Youssef Tharwat, founder of NoodlBox, building context management tools for programming05:00 Context as relevant information for reasoning; importance when hitting coding barriers10:00 Knowledge graphs enable semantic traversal through meaning vs keywords/files15:00 Deterministic vs probabilistic systems; why critical applications need 100% reliability20:00 CLI tool makes knowledge graphs portable, versionable artifacts with code repos25:00 Compiler front-ends, syntax trees, and Rust's superior feedback for AI-assisted coding30:00 Claude's Bun acquisition signals potential shift toward runtime compilation and graph-based context35:00 Open source vs proprietary models; user frustration with rate limits and subscription tactics40:00 Singularity path vs distributed sovereignty of developers building alternative architectures45:00 Global economics and why brute force compute isn't sustainable worldwide50:00 Corporate inefficiencies vs independent engineering; changing workplace dynamics55:00 February open beta for NoodlBox.io; vision for new development tool standardsKey Insights1. Context is semantic information that enables proper reasoning, and traditional LLM approaches miss the mark. Youssef defines context as the information you need to reason correctly about something. He argues that larger context windows don't scale because quality degrades with more input, similar to human cognitive limitations. This insight challenges the Silicon Valley approach of throwing more compute at the problem and suggests that semantic separation of information is more optimal than brute force methods.2. Code naturally contains semantic boundaries that can be modeled into knowledge graphs without LLM intervention. Unlike other domains where knowledge graphs require complex labeling, code already has inherent relationships like function calls, imports, and dependencies. Youssef leverages these existing semantic structures to automatically build knowledge graphs, making his approach deterministic rather than probabilistic. This provides the reliability that software development has historically required.3. Knowledge graphs can be made portable, versionable, and shareable as artifacts alongside code repositories. Youssef's vision treats context as a first-class citizen in version control, similar to how Git manages code. Each commit gets a knowledge graph snapshot, allowing developers to see conceptual changes over time and share semantic understanding with collaborators. This transforms context from an ephemeral concept into a concrete, manageable asset.4. The dependency problem in modern development can be solved through pre-indexed knowledge graphs of popular packages. Rather than agents struggling with outdated API documentation, Youssef pre-indexes popular npm packages into knowledge graphs that automatically integrate with developers' projects. This federated approach ensures agents understand exact APIs and current versions, eliminating common frustrations with deprecated methods and unclear documentation.5. Rust provides superior feedback loops for AI-assisted programming due to its explicit compiler constraints. Youssef rebuilt his tool multiple times in different languages, ultimately settling on Rust because its picky compiler provides constant feedback to LLMs about subtle issues. This creates a natural quality control mechanism that helps AI generate more reliable code, making Rust an ideal candidate for AI-assisted development workflows.6. The current AI landscape faces a fundamental tension between expensive centralized models and the need for global accessibility. The conversation reveals growing frustration with rate limiting and subscription costs from major providers like Claude and Google. Youssef believes something must fundamentally change because $200-300 monthly plans only serve a fraction of the world's developers, creating pressure for more efficient architectures and open alternatives.7. Deterministic tooling built on semantic understanding may provide a competitive advantage against probabilistic AI monopolies. While big tech companies pursue brute force scaling with massive data centers, Youssef's approach suggests that clever architecture using existing semantic structures could level the playing field. This represents a broader philosophical divide between the "singularity" path of infinite compute and the "disagreeably autistic engineer" path of elegant solutions that work locally and affordably.

In dieser Folge tauchen Daniel Dippold, EWOR, und Mike Mahlkow tief in ihre persönlichen Produktivitäts-Setups ein. Sie sprechen offen und konkret über die Tools, die ihnen wirklich Zeit sparen und ihren Arbeitsalltag effizienter machen – von E-Mail und Kalender über File Management und Meeting-Transkription bis hin zu Hardware-Tipps. Dabei geht es nicht um Tool-Overload, sondern um die Frage: Wie findet man die richtige Balance und was bringt wirklich Return on Time? Was du aus der Folge mitnimmst: Konkret & ehrlich: Welche Tools Daniel und Mike täglich wirklich nutzen und warum – von Superhuman für E-Mail, Raycast für Mac, cal.com/WimCall für Scheduling, Optiverse für Meeting-Transkription bis zu ClickUp und Google für Projekt- und Wissensmanagement. Prozess statt Hype: Wie man Tools auswählt und woran man erkennt, ob sich das Onboarding und der Wechsel wirklich lohnt. Hardware matters: Warum ein guter Laptop, stabile Kopfhörer, Mikro & Internet genauso produktiv machen wie die beste Software. Ergonomie & Gesundheit: Wie ein Laptopständer und externe Tastatur Nackenproblemen vorbeugen. Tool-Philosophie: Produktivität ist kein Tool-Overload! Es geht um wenige, aber wirkungsvolle Tools – und darum, regelmäßig zu prüfen, was wirklich Zeit spart. Bonus: Ausblick auf AI-Workflows und warum ein bewusster Umgang mit neuen Tools und Automatisierungen immer wichtiger wird. ALLES ZU UNICORN BAKERY: https://stan.store/fabiantausch   Daniel Dippold  LinkedIn: https://www.linkedin.com/in/danieldippold  Website: https://www.ewor.com/  Mike Mahlkow LinkedIn: https://www.linkedin.com/in/mikemahlkow/  Website: https://fastgen.com/  Join our Founder Tactics Newsletter: 2x die Woche bekommst du die Taktiken der besten Gründer der Welt direkt ins Postfach: https://www.tactics.unicornbakery.de/  Kapitel: (00:00:00) Produktivität: Tools und Prinzipien (00:01:30) Superhuman & E-Mail-Produktivität (00:04:42) Snippets, Scheduling und Follow-ups in Superhuman (00:07:15) Inbox Zero & Unified Inbox (00:09:09) Raycast & File-Management auf dem Desktop (00:12:15) Naming, AI-Features und Quick Links in Raycast (00:16:42) Kalender-Tools: cal.com, WimCall & Scheduling-Infrastruktur (00:22:48) Meeting-Transkriptionstools & Automatisierungen (00:26:21) Hardware: Kopfhörer, Mikrofone, Laptops & Setup (00:37:16) Die drei wichtigsten Tools für junge Companies (00:38:27) Project Management: ClickUp, Google Docs & Knowledge Management (00:42:47) Internet & Tastatur als unterschätzte Produktivitätsfaktoren (00:46:07) Ergonomie: Laptopständer & Nackenprobleme (00:47:46) Zeittracking & ROI von Tools (00:49:05) Fazit: Weniger ist mehr & Ausblick auf AI-Tools

In this episode of the Crazy Wisdom podcast, host Stewart Alsop welcomes Roni Burd, a data and AI executive with extensive experience at Amazon and Microsoft, for a deep dive into the evolving landscape of data management and artificial intelligence in enterprise environments. Their conversation explores the longstanding challenges organizations face with knowledge management and data architecture, from the traditional bronze-silver-gold data processing pipeline to how AI agents are revolutionizing how people interact with organizational data without needing SQL or Python expertise. Burd shares insights on the economics of AI implementation at scale, the debate between one-size-fits-all models versus specialized fine-tuned solutions, and the technical constraints that prevent companies like Apple from upgrading services like Siri to modern LLM capabilities, while discussing the future of inference optimization and the hundreds-of-millions-of-dollars cost barrier that makes architectural experimentation in AI uniquely expensive compared to other industries.Timestamps00:00 Introduction to Data and AI Challenges03:08 The Evolution of Data Management05:54 Understanding Data Quality and Metadata08:57 The Role of AI in Data Cleaning11:50 Knowledge Management in Large Organizations14:55 The Future of AI and LLMs17:59 Economics of AI Implementation29:14 The Importance of LLMs for Major Tech Companies32:00 Open Source: Opportunities and Challenges35:19 The Future of AI Inference and Hardware43:24 Optimizing Inference: The Next Frontier49:23 The Commercial Viability of AI ModelsKey Insights1. Data Architecture Evolution: The industry has evolved through bronze-silver-gold data layers, where bronze is raw data, silver is cleaned/processed data, and gold is business-ready datasets. However, this creates bottlenecks as stakeholders lose access to original data during the cleaning process, making metadata and data cataloging increasingly critical for organizations.2. AI Democratizing Data Access: LLMs are breaking down technical barriers by allowing business users to query data in plain English without needing SQL, Python, or dashboarding skills. This represents a fundamental shift from requiring intermediaries to direct stakeholder access, though the full implications remain speculative.3. Economics Drive AI Architecture Decisions: Token costs and latency requirements are major factors determining AI implementation. Companies like Meta likely need their own models because paying per-token for billions of social media interactions would be economically unfeasible, driving the need for self-hosted solutions.4. One Model Won't Rule Them All: Despite initial hopes for universal models, the reality points toward specialized models for different use cases. This is driven by economics (smaller models for simple tasks), performance requirements (millisecond response times), and industry-specific needs (medical, military terminology).5. Inference is the Commercial Battleground: The majority of commercial AI value lies in inference rather than training. Current GPUs, while specialized for graphics and matrix operations, may still be too general for optimal inference performance, creating opportunities for even more specialized hardware.6. Open Source vs Open Weights Distinction: True open source in AI means access to architecture for debugging and modification, while "open weights" enables fine-tuning and customization. This distinction is crucial for enterprise adoption, as open weights provide the flexibility companies need without starting from scratch.7. Architecture Innovation Faces Expensive Testing Loops: Unlike database optimization where query plans can be easily modified, testing new AI architectures requires expensive retraining cycles costing hundreds of millions of dollars. This creates a potential innovation bottleneck, similar to aerospace industries where testing new designs is prohibitively expensive.

In this episode of the Crazy Wisdom podcast, host Stewart Alsop sits down with Kelvin Lwin for their second conversation exploring the fascinating intersection of AI and Buddhist cosmology. Lwin brings his unique perspective as both a technologist with deep Silicon Valley experience and a serious meditation practitioner who's spent decades studying Buddhist philosophy. Together, they examine how AI development fits into ancient spiritual prophecies, discuss the dangerous allure of LLMs as potentially "asura weapons" that can mislead users, and explore verification methods for enlightenment claims in our modern digital age. The conversation ranges from technical discussions about the need for better AI compilers and world models to profound questions about humanity's role in what Lwin sees as an inevitable technological crucible that will determine our collective spiritual evolution. For more information about Kelvin's work on attention training and AI, visit his website at alin.ai. You can also join Kelvin for live meditation sessions twice daily on Clubhouse at clubhouse.com/house/neowise.Timestamps00:00 Exploring AI and Spirituality05:56 The Quest for Enlightenment Verification11:58 AI's Impact on Spirituality and Reality17:51 The 500-Year Prophecy of Buddhism23:36 The Future of AI and Business Innovation32:15 Exploring Language and Communication34:54 Programming Languages and Human Interaction36:23 AI and the Crucible of Change39:20 World Models and Physical AI41:27 The Role of Ontologies in AI44:25 The Asura and Deva: A Battle for Supremacy48:15 The Future of Humanity and AI51:08 Persuasion and the Power of LLMs55:29 Navigating the New Age of TechnologyKey Insights1. The Rarity of Polymath AI-Spirituality Perspectives: Kelvin argues that very few people are approaching AI through spiritual frameworks because it requires being a polymath with deep knowledge across multiple domains. Most people specialize in one field, and combining AI expertise with Buddhist cosmology requires significant time, resources, and academic background that few possess.2. Traditional Enlightenment Verification vs. Modern Claims: There are established methods for verifying enlightenment claims in Buddhist traditions, including adherence to the five precepts and overcoming hell rebirth through karmic resolution. Many modern Western practitioners claiming enlightenment fail these traditional tests, often changing the criteria when they can't meet the original requirements.3. The 500-Year Buddhist Prophecy and Current Timing: We are approximately 60 years into a prophesied 500-year period where enlightenment becomes possible again. This "startup phase of Buddhism revival" coincides with technological developments like the internet and AI, which are seen as integral to this spiritual renaissance rather than obstacles to it.4. LLMs as UI Solution, Not Reasoning Engine: While LLMs have solved the user interface problem of capturing human intent, they fundamentally cannot reason or make decisions due to their token-based architecture. The technology works well enough to create illusion of capability, leading people down an asymptotic path away from true solutions.5. The Need for New Programming Paradigms: Current AI development caters too much to human cognitive limitations through familiar programming structures. True advancement requires moving beyond human-readable code toward agent-generated languages that prioritize efficiency over human comprehension, similar to how compilers already translate high-level code.6. AI as Asura Weapon in Spiritual Warfare: From Buddhist cosmological perspective, AI represents an asura (demon-realm) tool that appears helpful but is fundamentally wasteful and disruptive to human consciousness. Humanity exists as the battleground between divine and demonic forces, with AI serving as a weapon that both sides employ in this cosmic conflict.7. 2029 as Critical Convergence Point: Multiple technological and spiritual trends point toward 2029 as when various systems will reach breaking points, forcing humanity to either transcend current limitations or be consumed by them. This timing aligns with both technological development curves and spiritual prophecies about transformation periods.

Dans cette interview accordée à CEO Radio, Ferréol Mayoly, Président de TAKOMA, partage la vision stratégique de l'entreprise autour du knowledge management. TAKOMA accompagne les organisations dans la captation, la structuration et la transmission de leurs savoirs clés. Face aux enjeux de transformation, de renouvellement des compétences et d'IA, la connaissance devient un actif stratégique. Grâce à ses expertises en documentation, formation, communication et conseil, TAKOMA sécurise le capital immatériel des entreprises. Une approche qui conjugue performance, innovation et durabilité.Hébergé par Ausha. Visitez ausha.co/politique-de-confidentialite pour plus d'informations.

Arvind Jain couldn't find his own company's data at Rubrik. So in 2019 before ChatGPT, before the AI boom, he built Glean, the first enterprise generative AI company. Now they're doubling past $100M ARR with 1,100 employees and watching tech giants copy their playbook. But Jain admits his biggest mistake: being too conservative. "We should have gone much bigger, much faster," he says, crediting his Indian upbringing for the cautious approach. Still, Glean remains years ahead as competitors scramble to build "AI that knows your company's data." His contrarian take on AI? It won't shrink workforces, it'll just raise the bar for everyone. The real edge isn't the technology; it's execution. And despite the relentless pace keeping him up at night, Jain's never been more optimistic about building a multi-billion dollar business.You can follow Swathi Moorthy on her social media: X and Linkedin Check out other interesting episodes like: How Will a Volatile ₹ Impact You in 2026?, How Quick Commerce is Triggering a Health Crisis for Gen Z, India’s Labour Law Reboot, Viral to Valuation: Building Women’s Cricket as a Brand and much more. Catch the latest episode of ‘The Morning Brief’ on The Economic Times Online, Spotify, Apple Podcasts, JioSaavn, Amazon Music and Youtube.See omnystudio.com/listener for privacy information.

As 2026 approaches, workplace regulations are shaking up the scene – and Maureen Lavery from Littler's Knowledge Management team joins Claire Deason and Nicole LeFave to help employers stay ahead of the curve. The trio dives into new legislation and regulatory trends set to impact organizations in the coming year. From Connecticut's paid sick leave expansion (spoiler: almost everyone's invited), Colorado's first-in-the-nation NICU leave, and Minnesota's meal and rest break overhaul, the team tackles compliance changes with the energy of people who've had one too many krumkake. Plus, a round of predictions for what's next in anti-TRAP laws, AI in hiring, menopause accommodations, and immigration protections – helping employers prepare for what could be ahead. https://www.littler.com/news-analysis/podcast/littler-lounge-ahead-bill-curve-2026-legislative-look-ahead

As we close out 2025, Peter and Dave are making predictions about what's coming in 2026, especially around AI, organizational change, and how teams actually work.They cover five key predictions:AI moves from tools to organizational capability: Organizations that invest in literacy, governance, and data foundations will pull ahead of those just sprinkling AI on top and hoping for the best.Critical thinking beats prompt engineering: The real competitive advantage won't be writing clever prompts. It'll be knowing when to pause, think through the problem, and decide if you even need the AI in the first place.Product delivery becomes non-negotiable: After 20 years of pushing Agile principles, AI might finally force organizations to actually adopt them (even if they're reluctant to call it "Agile").Businesses return to fundamentals: Just like the dot-com bubble, we're heading toward a moment where the market will care more about revenue, customers, and sustainability than hype.Reskilling becomes a structural investment: Organizations will need to figure out what roles actually look like in an AI-enabled world and invest in growing their people, not just replacing them.At the end, Peter and Dave pick which prediction is hardest to measure (spoiler: it's critical thinking) and commit to revisiting these in March to see how wrong they were.If you've been wondering where all this AI stuff is actually heading, this episode cuts through the noise with grounded, practical predictions you can actually use.Related episodes:AI and Knowledge Management with Derek Crager: https://www.buzzsprout.com/1643821/episodes/17360635Product vs. Process Innovation: https://www.buzzsprout.com/1643821/episodes/7953100There Are No Safe Bets in Business Anymore: https://www.buzzsprout.com/1643821/episodes/17433034Reach out: feedback@definitelymaybeagile.com

In this episode, we explore how TRANSFORM has helped promote a ‘culture of social protection' across Africa, shaping how civil servants approach their roles and how institutions adapt to address lifecycle challenges using TRANSFORM's building-block methodology. The conversations highlight the initiative's leadership effects and its influence at national and sub-national levels, while also examining how it has supported the integration of social protection into the priorities of the African regional bodies and governments. This is the second of the three-part TRANSFORM Podcast Series, which will present the initiative's achievements 10 years since its inception through conversations with guests from the continent. In case you missed the first episode of the TRANSFORM series, you can access it here: Ep. 1 | Social Protection Capacity Building in Africa: 10 Years of TRANSFORM Hosted by Abidemi Coker, a passionate TRANSFORM Master Trainer. Meet our guests for episode 2: Thebuho Kavubya, District Social Welfare Officer, Ministry of Community Development and Social Services of Zambia. Ivan Oscar Langa, Social Protection and Policy Specialist and a TRANSFORM Master Trainer from Mozambique. For our testimonial segment, we welcome Felix Mwenge, TRANSFORM Coordinator and the Technical Officer for TRANSFORM and Knowledge Management at the ILO Country Office for Zambia, Malawi, and Mozambique. To learn more and explore how TRANSFORM can be tailored to your own context and how you can get involved with the initiative, go to https://transformsp.org and contact transform_socialprotection@ilo.org.

What happens when AEC marketing owns the data story and becomes a true strategic partner to the firm?Katie Cash sits down with Katie Robinson, Chief Marketing Officer at LS3P, to unpack how a traditional proposal shop evolved into a firmwide, agency-style marketing and knowledge management team. Katie shares how LS3P aligned marketing with business strategy, centralized project data through a data manager program, and used tools like Power BI and AI to unlock insights that support both pursuit strategy and firm leadership. She also explains why open access to project data, clear security rules, and cross-functional collaboration are non-negotiables for sustainable growth.From Expert Hours that support thought leadership to an AI steering committee that protects IP and improves efficiency, Katie shares a practical roadmap that any AEC firm can start small and scale. Marketers will come away with clear strategies for strengthening relationships across the firm, earning a seat at the strategic table, and elevating marketing from a support function to a true driver of growth.Topics discussed in this episode:AEC marketingLS3PCRMPower BIAI in AECStrategic planningConnect with Katie Robinson, Chief Marketing Officer / Vice President / Principal at LS3P:https://www.ls3p.com/portfolio/katie-robinson/ https://www.linkedin.com/in/katie-schroer-robinson/ Connect with Katie:  https://smartegies.com/ Rate, Review, & Follow on Apple Podcasts:We hope you're finding value in our AEC Marketing For Principals.  Your feedback is important to us and we'd love to hear from you. Here's how you can help.  Scroll to the bottom, rate our podcast with five stars, and select “Write a Review.”  Let us know what you found most helpful from this episode!  And if you haven't done so already, give the podcast a follow, and you'll be notified when new episodes come out.

In this episode, Jeffrey discusses the need for Knowledge ManagementEach week, Jeffrey will be sharing his knowledge on Service Delivery (Mondays) and Service Management (Thursdays). Jeffrey is the founder of Service Management Leadership, an IT consulting firm specializing in Service Management, Asset Management, CIO Advisory, and Business Continuity services.  The firm's website is www.servicemanagement.us.  Jeffrey has been in the industry for 30 years and brings a practical perspective to the discussions. He is an accomplished author with seven acclaimed books in the subject area and a popular YouTube channel with approximately 1,500 videos on various topics.  Also, please follow the Service Management Leadership LinkedIn page.

Wissen ist die wahre Währung moderner Unternehmen, doch kaum jemand zeigt Führungskräften, wie man damit richtig umgeht. In dieser Folge erfahren Sie, warum Wissensmanagement weit über Fachwissen hinausgeht und wie Top-Manager die Informationsflut souverän meistern. (02:18) Definition von Wissensmanagement (03:26) Effektiver Umgang mit Informationen für Top-Führungskräfte (06:25) Was wir von der Natur über Wissensmanagement lernen können (12:05) Fazit und weiterführende Ressourcen - Wie lautet die Definition von Wissensmanagement? - Wie gehen Sie richtig mit Informationen um? - Was können Sie für Ihr Wissensmanagement im Unternehmen von der Natur lernen? Aus dieser Folge werden Sie mitnehmen, wie gutes Wissensmanagement aussieht und was Führungskräfte rund um das Knowledge Management beachten müssen. ___ **Links zur Folge:** Webseite: https://www.galileo-institut.de/wissen-richtig-managen/ Link zur NL-Anmeldung: https://www.galileo-institut.de/newsletter/ ___ Sie sind neu an der Unternehmensspitze oder kämpfen bereits mit scheinbar unlösbaren Herausforderungen? Vielleicht klemmt es gerade in der Transformation? Vielleicht läuft sogar alles gut und Sie sind dennoch unzufrieden? In meinem kostenfreien Onlinecoaching zeige ich Ihnen Lösungen für diese Herausforderungen.

In this special episode of LawTech Talks, produced in partnership with iManage, we explore how teams – both in-house and in private practice – can leverage their internal knowledge assets to prepare them for the next generation of legal services and AI and digital transformation. Host Jerome Doraisamy speaks with iManage's global product director for knowledge and AI, Alex Smith, and Asia-Pacific legal industry expert Madeleine Porter about why knowledge management is such an urgent priority for legal teams, how cognisant lawyers are of this urgency, lessons learnt from this past year, whether certain practices and processes remain fit for purpose in the current climate, and whether it's becoming harder for legal teams to avoid drowning in knowledge. Smith and Porter also delve into the questions that legal teams need to ask of themselves in better mastering their knowledge management, creating a more holistic operational culture, approaches that will not work moving forward, practical steps that need to be taken, leveraging business data, the role of AI and automation, ethical considerations, and the opportunities to be gleaned from taking such action. To learn more about iManage, click here.

Operators with 30 years of pattern recognition leave for competitors. Engineers carrying legacy system intelligence depart. Everyone understands the risk. Few solve the execution: Systematically extracting tacit intelligence that experts can't articulate because it operates below the conscious threshold.Dr. Refiloe Mabaso and Wisdom Ndashe architected what many struggle to build - knowledge-capture systems that function independently of voluntary participation. At ATNS, harvesting is mandated by policy and embedded in workflows. Their "Legends and Beneficiaries" program identifies critical expertise five years before departure, mapping tacit intelligence to next-generation operators through structured protocols. The execution breakthrough: embedding capture into SOPs makes retention automatic. Travel with Purpose demonstrates strategic reach - converting unaccounted expenditures into documented intelligence acquisition with measurable ROI. Cost centers become intelligence operations.Paradigm Shifts:

In this episode of Crazy Wisdom, host Stewart Alsop talks with Kevin Smith, co-founder of Snipd, about how AI is reshaping the way we listen, learn, and interact with podcasts. They explore Snipd's vision of transforming podcasts into living knowledge systems, the evolution of machine learning from finance to large language models, and the broader connection between AI, robotics, and energy as the foundation for the next technological era. Kevin also touches on ideas like the bitter lesson, reinforcement learning, and the growing energy demands of AI. Listeners can try Snipd's premium version free for a month using this promo link.Check out this GPT we trained on the conversationTimestamps00:00 – Stewart Alsop welcomes Kevin Smith, co-founder of Snipd, to discuss AI, podcasting, and curiosity-driven learning.05:00 – Kevin explains Snipd's snipping feature, chatting with episodes, and future plans for voice interaction with podcasts.10:00 – They discuss vector search, embeddings, and context windows, comparing full-episode context to chunked transcripts.15:00 – Kevin shares his background in mathematics and economics, his shift from finance to machine learning, and early startup work in AI.20:00 – They explore early quant models versus modern machine learning, statistical modeling, and data limitations in finance.25:00 – Conversation turns to transformer models, pretraining, and the bitter lesson—how compute-based methods outperform human-crafted systems. 30:00 – Stewart connects this to RLHF, Scale AI, and data scarcity; Kevin reflects on reinforcement learning's future. 35:00 – They pivot to Snipd's podcast ecosystem, hidden gems like Founders Podcast, and how stories shape entrepreneurial insight. 40:00 – ETH Zurich, robotics, and startup culture come up, linking academia to real-world innovation. 45:00 – They close on AI, robotics, and energy as the pillars of the future, debating nuclear and solar power's role in sustaining progress.Key InsightsPodcasts as dynamic knowledge systems: Kevin Smith presents Snipd as an AI-powered tool that transforms podcasts into interactive learning environments. By allowing listeners to “snip” and summarize meaningful moments, Snipd turns passive listening into active knowledge management—bridging curiosity, memory, and technology in a way that reframes podcasts as living knowledge capsules rather than static media.AI transforming how we engage with information: The discussion highlights how AI enables entirely new modes of interaction—chatting directly with podcast episodes, asking follow-up questions, and contextualizing information across an author's full body of work. This evolution points toward a future where knowledge consumption becomes conversational and personalized rather than linear and one-size-fits-all.Vectorization and context windows matter: Kevin explains that Snipd currently avoids heavy use of vector databases, opting instead to feed entire episodes into large models. This choice enhances coherence and comprehension, reflecting how advances in context windows have reshaped how AI understands complex audio content.Machine learning's roots in finance shaped early AI thinking: Kevin's journey from quantitative finance to AI reveals how statistical modeling laid the groundwork for modern learning systems. While finance once relied on rigid, theory-based models, the machine learning paradigm replaced those priors with flexible, data-driven discovery—an essential philosophical shift in how intelligence is approached.The Bitter Lesson and the rise of compute: Together they unpack Richard Sutton's “bitter lesson”—the idea that methods leveraging computation and data inevitably surpass those built from human intuition. This insight serves as a compass for understanding why transformers, pretraining, and scaling have driven recent AI breakthroughs.Reinforcement learning and data scarcity define AI's next phase: Stewart links RLHF and the work of companies like Scale AI and Surge AI to the broader question of data limits. Kevin agrees that the next wave of AI will depend on reinforcement learning and simulated environments that generate new, high-quality data beyond what humans can label.The future hinges on AI, robotics, and energy: Kevin closes with a framework for the next decade: AI provides intelligence, robotics applies it to the physical world, and energy sustains it all. He warns that society must shift from fearing energy use to innovating in production—especially through nuclear and solar power—to meet the demands of an increasingly intelligent, interconnected world.

In this episode of Crazy Wisdom, host Stewart Alsop talks with Jessica Talisman, founder of Contextually and creator of the Ontology Pipeline, about the deep connections between knowledge management, library science, and the emerging world of AI systems. Together they explore how controlled vocabularies, ontologies, and metadata shape meaning for both humans and machines, why librarianship has lessons for modern tech, and how cultural context influences what we call “knowledge.” Jessica also discusses the rise of AI librarians, the problem of “AI slop,” and the need for collaborative, human-centered knowledge ecosystems. You can learn more about her work at Ontology Pipeline and find her writing and talks on LinkedIn.Check out this GPT we trained on the conversationTimestamps00:00 Stewart Alsop welcomes Jessica Talisman to discuss Contextually, ontologies, and how controlled vocabularies ground scalable systems.05:00 They compare philosophy's ontology with information science, linking meaning, categorization, and sense-making for humans and machines.10:00 Jessica explains why SQL and Postgres can't capture knowledge complexity and how neuro-symbolic systems add context and interoperability.15:00 The talk turns to library science's split from big data in the 1990s, metadata schemas, and the FAIR principles of findability and reuse.20:00 They discuss neutrality, bias in corporate vocabularies, and why “touching grass” matters for reconciling internal and external meanings.25:00 Conversation shifts to interpretability, cultural context, and how Western categorical thinking differs from China's contextual knowledge.30:00 Jessica introduces process knowledge, documentation habits, and the danger of outsourcing how-to understanding.35:00 They explore knowledge as habit, the tension between break-things culture and library design thinking, and early AI experiments.40:00 Libraries' strategic use of AI, metadata precision, and the emerging role of AI librarians take focus.45:00 Stewart connects data labeling, Surge AI, and the economics of good data with Jessica's call for better knowledge architectures.50:00 They unpack content lifecycle, provenance, and user context as the backbone of knowledge ecosystems.55:00 The talk closes on automation limits, human-in-the-loop design, and Jessica's vision for collaborative consulting through Contextually.Key InsightsOntology is about meaning, not just data structure. Jessica Talisman reframes ontology from a philosophical abstraction into a practical tool for knowledge management—defining how things relate and what they mean within systems. She explains that without clear categories and shared definitions, organizations can't scale or communicate effectively, either with people or with machines.Controlled vocabularies are the foundation of AI literacy. Jessica emphasizes that building a controlled vocabulary is the simplest and most powerful way to disambiguate meaning for AI. Machines, like people, need context to interpret language, and consistent terminology prevents the “hallucinations” that occur when systems lack semantic grounding.Library science predicted today's knowledge crisis. Stewart and Jessica trace how, in the 1990s, tech went down the path of “big data” while librarians quietly built systems of metadata, ontologies, and standards like schema.org. Today's AI challenges—interoperability, reliability, and information overload—mirror problems library science has been solving for decades.Knowledge is culturally shaped. Drawing from Patrick Lambe's work, Jessica notes that Western knowledge systems are category-driven, while Chinese systems emphasize context. This cultural distinction explains why global AI models often miss nuance or moral voice when trained on limited datasets.Process knowledge is disappearing. The West has outsourced its “how-to” knowledge—what Jessica calls process knowledge—to other countries. Without documentation habits, we risk losing the embodied know-how that underpins manufacturing, engineering, and even creative work.Automation cannot replace critical thinking. Jessica warns against treating AI as “room service.” Automation can support, but not substitute, human judgment. Her own experience with a contract error generated by an AI tool underscores the importance of review, reflection, and accountability in human–machine collaboration.Collaborative consulting builds knowledge resilience. Through her consultancy, Contextually, Jessica advocates for “teaching through doing”—helping teams build their own ontologies and vocabularies rather than outsourcing them. Sustainable knowledge systems, she argues, depend on shared understanding, not just good technology.

Information management delivers data. Knowledge management unleashes organizational intelligence - transforming how multi-stakeholder ecosystems coordinate, decide, and optimize performance across dynamic and complex networks. D. Jasen Graham, Director of Enterprise Risk and Knowledge Management for VA's $400M+ Financial Management Business Transformation program, achieved 50% improvement in risk mitigation efficiency and 40% reduction in decision cycle time. Paradigm Shifts:

In this episode, Shiv is in conversation with Naresh Choudhary, Senior Vice President, Quality & Productivity, Infosys Ltd.Naresh shares his career journey starting from humble beginnings in Mumbai, studying engineering at VJTI, working at Arvind Mills, and eventually contributing to Infosys for 25 years. The discussion covers his transition from manufacturing to IT, the influence of mentors, various roles at Infosys, and the importance of reframing roles. Naresh also emphasizes the value of great work, networking, mentorship, and maintaining a work-life balance. He talks about driving innovation and change management effectively within a large organization through transparent communication, planning, and continuous feedback. Finally, Naresh offers personal practices like journaling, exercising, and separating work from family time to stay grounded and calm.00:00 Welcome and Introduction00:23 Early Career and Education02:00 Transition to Infosys03:43 Roles and Responsibilities at Infosys07:16 Mentorship and Career Growth10:28 Defining Great Work15:32 Overcoming Self-Doubt and Imposter Syndrome19:28 The Importance of Mentors24:23 Networking and Time Management29:19 Clearing the Mind for Focus29:51 Work-Life Balance and Breaks30:59 Organizational Change and Trust33:51 Planning and Transparency in Change34:51 Process Over Tools36:04 Sponsorship and Milestone Reviews37:46 Encouraging Knowledge Sharing43:58 Innovation and Idea Management47:33 Staying Grounded Amidst Responsibilities53:00 Personal Practices for Balance56:48 Conclusion and Final ThoughtsBio:In his stint at Infosys over 2 decades, Naresh has worked in different roles in Software Delivery, Consulting, Quality Assurance, Open Source, Enterprise Platforms, Products, Tools & Technology that have provided him opportunities to work on key transformation programs.Naresh has experience in Software Development, Quality System Design, Process definition, Implementation and Consulting, Product & Platform Engineering, Software Reuse, Knowledge Management, Training, Audits and Assessments. He possesses a sound understanding of various quality models, methodologies and frameworks like CMMI, ISO, Six Sigma, MBNQA, AI, Automation,  Agile, DevSecOps & SRE.Naresh participates on several product councils and advisory boards with Infosys' global technology partners and is currently leading the effort on reimagining the tooling, engineering excellence, digital platforms, Lean and automation landscape for the enterpriseHe is a self confessed Foodie, History enthusiast, Amateur Chef, Motivational Speakerhttps://www.linkedin.com/in/nareshchoudhary/

In this episode of Crazy Wisdom, host Stewart Alsop talks with Rob Meyerson, co-founder and CEO of Interlune and former president of Blue Origin, about building the next phase of the space economy—from mining Helium-3 on the Moon to powering quantum computing and future fusion reactors on Earth. They explore the science behind lunar regolith, cryogenic separation, robotic excavation, and how private industry is rekindling the optimism of Apollo. Rob also shares lessons from scaling Blue Origin and explains why knowledge management and intuition matter when engineering at the edge of possibility. Follow Rob and Interlune on LinkedIn, X (Twitter), and Instagram.Check out this GPT we trained on the conversationTimestamps00:00 Stewart Alsop welcomes Rob Meyerson, who introduces Interlune's mission to extract Helium-3 from the Moon and explains its origins in the Apollo samples.05:00 Meyerson describes how lunar regolith traps solar wind gases, the role of ilmenite, and how spectrometry helps identify promising Helium-3 sites.10:00 Discussion shifts to Helium-3's commercial potential, the Department of Energy's isotope program, and its link to tritium decay and nuclear stockpiles.15:00 Meyerson connects Helium-3 to quantum computing, explaining cryogenic dilution refrigeration and the importance of ultra-cold temperatures.20:00 They explore cryogenic engineering, partnerships with Vermeer for lunar excavation, and developing solar wind–implanted regolith simulants.25:00 Rob reflects on his 15 years at Blue Origin, scaling from 10 to 1,500 people, and the importance of documentation and knowledge retention.30:00 The talk turns to lunar water, propellant production, and how solar and nuclear power could support a permanent in-space economy.35:00 Meyerson outlines robotic harvesting, lunar night hibernation, and AI applications for navigation, autonomy, and resource mapping.40:00 The conversation broadens to intuition in engineering, testing in lunar gravity, and lessons from Apollo's lost momentum and industrial base.50:00 Rob closes with optimism for private industry's role in rebuilding lunar infrastructure and how Interlune fits into humanity's return to the Moon.Key InsightsHelium-3 as a Lunar Resource: Rob Meyerson explains that Helium-3, a rare isotope on Earth but abundant on the Moon due to billions of years of solar wind implantation, could power future fusion energy and enable cleaner, more efficient energy sources. Interlune's mission is to commercialize this resource, beginning with robotic prospecting and extraction missions.The Science of Lunar Regolith: The Moon's regolith—the dusty surface soil—acts as a natural collector of solar wind gases like hydrogen, helium, and helium-3. Meyerson describes how Interlune identifies promising mining locations using data from NASA's Lunar Reconnaissance Orbiter and the presence of ilmenite, a titanium-rich mineral that traps more Helium-3 than other regions.Cryogenics and Quantum Computing: Helium-3 is essential for dilution refrigerators that cool quantum computers to millikelvin temperatures, colder than any place in the universe. Meyerson highlights a new commercial contract with Bluefors, a Finnish cryogenics leader, to supply Helium-3 starting in 2028—proving the economic case for lunar resource extraction.Fusion Energy and Strategic Supply: While today's fusion reactors rely on tritium and deuterium, Helium-3 could be the next-generation fuel—safer and more efficient. With tritium decay from aging nuclear stockpiles as the only current terrestrial source, Interlune's lunar supply could fill a critical gap for future clean-energy systems.Building Lunar Infrastructure: Interlune's long-term vision extends beyond Helium-3 to producing rocket propellant, metals, and industrial materials on the Moon. By developing cryogenic separation and excavation systems, they aim to enable a self-sustaining “in-space economy” where resources mined in space fuel space-based operations.AI and Autonomy in Space Mining: Artificial intelligence and advanced sensing will guide robotic harvesters on the Moon's harsh terrain. AI will also analyze imagery and soil data to map Helium-3 concentrations and manage knowledge across missions, turning data into operational insight.Lessons in Leadership and Scale: Drawing from his 15 years leading Blue Origin, Meyerson stresses the importance of documentation, mentorship, and maintaining technical continuity as teams grow. He contrasts Apollo's lost potential with today's resurgence of private space ventures, expressing deep optimism for U.S. innovation and the rebirth of lunar industry.

John Maytham speaks to Retha Beerman, Director and Head of the Knowledge Management practice at CDH, about how these AI legal tools are being integrated responsibly, and what this means for clients across the continent. Afternoon Drive with John Maytham is the late afternoon show on CapeTalk. Presenter John Maytham is an actor and author-turned-talk radio veteran and seasoned journalist. His show serves a round-up of local and international news coupled with the latest in business, sport, traffic and weather. The host’s eclectic interests mean the program often surprises the audience with intriguing book reviews and inspiring interviews profiling artists. A daily highlight is Rapid Fire, just after 5:30pm. CapeTalk fans call in, to stump the presenter with their general knowledge questions. Another firm favourite is the humorous Thursday crossing with award-winning journalist Rebecca Davis, called “Plan B”. Thank you for listening to a podcast from Afternoon Drive with John Maytham Listen live on Primedia+ weekdays from 15:00 and 18:00 (SA Time) to Afternoon Drive with John Maytham broadcast on CapeTalk https://buff.ly/NnFM3Nk For more from the show go to https://buff.ly/BSFy4Cn or find all the catch-up podcasts here https://buff.ly/n8nWt4x Subscribe to the CapeTalk Daily and Weekly Newsletters https://buff.ly/sbvVZD5 Follow us on social media: CapeTalk on Facebook: https://www.facebook.com/CapeTalk CapeTalk on TikTok: https://www.tiktok.com/@capetalk CapeTalk on Instagram: https://www.instagram.com/ CapeTalk on X: https://x.com/CapeTalk CapeTalk on YouTube: https://www.youtube.com/@CapeTalk567 See omnystudio.com/listener for privacy information.

Enterprise Knowledge's Lulit Tesfaye, VP of Knowledge & Data Services, speaks with Daan Hannessen, Global Head of Knowledge Management at Shell. He has over 20 years experience in Knowledge Management for large knowledge-intensive organizations in Europe, Australia, and the USA, ranging from continuous improvement programs, KM transformations, lessons learned solutions, digital workplaces, AI driven expert bots, enterprise search, and much more. In their conversation, Lulit and Daan discuss the importance of senior leadership support in ensuring the success of KM initiatives, emphasizing "speaking their language" as key to implementing KM and the semantic layer at a global scale. They also touch on how to measure the success of AI, when AI-generated content can be considered valuable insights, and why to invest in a semantic layer in the first place, as well as Daan's talk at the upcoming Semantic Layer Symposium.To learn more about the Semantic Layer Symposium, check it out here: ⁠⁠https://semanticlayersymposium.com/⁠⁠ *25% off discount code: knowledgecastTo learn more about Enterprise Knowledge, visit us at: ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠enterprise-knowledge.com⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠.EK's Knowledge Base: ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠https://enterprise-knowledge.com/knowledge-base/⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Contact Us: ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠https://enterprise-knowledge.com/contact-us/⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠LinkedIn: ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠https://www.linkedin.com/company/enterprise-knowledge-llc/⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Twitter/X: ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠https://twitter.com/ekconsulting⁠⁠⁠

In this episode of IDEA Collider, we are joined by Alex Telford, a biotech founder, writer, and thinker based in the San Francisco Bay Area. As the co-founder of Convoke Bio, Alex discusses his journey from studying biochemistry at UCL to founding a company that develops software tools for streamlining biopharmaceutical workflows.The conversation dives into the impact of AI and language models on the biotech industry, addressing inefficiencies in drug development, and exploring the potential of synthetic biology and personalized medicine. The discussion also touches on the future of drug discovery, China's role in biotech, and the challenges of understanding neuroscience and consciousness. Don't miss this insightful discussion on the future of biopharma innovation! 00:00 Welcome to Idea Collider00:04 Introducing Alex Telford01:59 Alex's Journey from UCL to Convoke Bio05:29 The Mission and Work of Convoke Bio07:57 Challenges in Pharma Decision Making14:05 The Role of AI in Pharma18:26 Knowledge Management and AI27:58 Staying Updated in the Fast-Moving AI Field30:25 AI's Impact on Industry Economics31:38 AI in Clinical Trials and Drug Development35:56 China's Role in Drug Discovery39:24 Neuroscience and AI: Blurring the Lines46:05 Future Predictions in Pharma51:20 Addressing Cognitive Bias in Pharma53:13 Concluding Thoughts and Future Directions Keep up with Alex Telford;LinkedIn: https://www.linkedin.com/in/alexander-telford/Website: atelfo.github.ioX: https://twitter.com/atelfoSubstack: atelfo.substack.com Follow Mike Rea On;Website: https://www.ideapharma.com/X: https://x.com/ideapharmaLinkedIn: https://www.linkedin.com/in/bigidea/ Listen to more fantastic podcast episodes: https://podcast.ideapharma.com/

Salum Abdul-Rahman: The SECI Model of Knowledge Management Applied to Team Retrospectives Read the full Show Notes and search through the world's largest audio library on Agile and Scrum directly on the Scrum Master Toolbox Podcast website: http://bit.ly/SMTP_ShowNotes. Salum explains how the key role for Scrum Masters is to help teams develop themselves to the point where they can learn and grow without constant guidance. Success means building team resilience and operational capability while knowing when to step back. He emphasizes the importance of recalibration workshops to maintain shared understanding and the balance between supporting teams and challenging them to become self-sufficient. When teams reach this level of maturity, Scrum Masters can focus their efforts elsewhere, knowing the team has developed the capability to continue evolving independently. Featured Retrospective Format for the Week: The 5-Stage Retro Format From the book "Agile Retrospectives," this format captures the complete learning process and aligns beautifully with knowledge management principles. Salum connects the three central phases of this format to the SECI model of knowledge management, particularly referencing Nonaka and Takeuchi's work in "The Knowledge Creating Company." This retrospective structure helps teams create new knowledge and behavioral change by following a systematic approach that transforms individual insights into collective team learning and action. In this segment, we also refer to the seminal article by Takeuchi and Nonaka: “The New New Product Development Game”, which originated the work on Scrum as a framework.  Self-reflection Question: How do you recognize when your team has developed enough self-sufficiency that your role as facilitator can evolve or step back? [The Scrum Master Toolbox Podcast Recommends]

Enterprise Knowledge's Lulit Tesfaye, VP of Knowledge & Data Services, speaks with Dawn Brushammar, currently an independent KM consultant, advisor, and frequent contributor at industry events. She has spent her 25+ year career connecting people to relevant knowledge and information. Her experience across industries and geographies includes leading an internal Knowledge Management team at McKinsey and Company, building databases for the Oprah Winfrey Show, running research services for a division of American Express, and managing academic librarianship at several universities and an environmental and sustainability research institute. In their conversation, Lulit and Dawn discuss the similarities between their early career paths and KM journeys, the evolving role of the modern librarian, and how KM and semantics support AI technologies. They also define what a "knowledge-first organization" should look like, and touch on Dawn's upcoming talk at the Semantic Layer Symposium on the rising importance of library science to the Semantic Layer.To learn more about the Semantic Layer Symposium, check it out here: ⁠https://semanticlayersymposium.com/⁠ *25% off discount code: knowledgecastTo learn more about Enterprise Knowledge, visit us at: ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠enterprise-knowledge.com⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠.EK's Knowledge Base: ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠https://enterprise-knowledge.com/knowledge-base/⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Contact Us: ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠https://enterprise-knowledge.com/contact-us/⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠LinkedIn: ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠https://www.linkedin.com/company/enterprise-knowledge-llc/⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Twitter/X: ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠https://twitter.com/ekconsulting⁠⁠⁠

Hosted by David Cowen | Presented by Steno Live from the floor at ILTACON 2025, in this rich, retrospective conversation, Phil Bryce, longtime legal Knowledge Management leader and strategist - traces the evolution of legal tech from the dawn of email to today's GenAI disruption. But this episode is about more than just tech. Phil shares hard-earned lessons on connection, courage, and how relationships made 20 years ago still shape his career today. If you're navigating what's next or building your place in this industry, Phil's story is a masterclass in going far together. Key Topics Covered: What GenAI means now and how it echoes the early days of legal tech How Knowledge Management, strategy, and innovation emerged from organized chaos The power of connection: how one lunch sparked a 20-year peer network Why today's best opportunities aren't in job descriptions, you create them “Follow the joy”: Phil's framework for building a career worth having How courage and curiosity created the career he didn't know he was building The future of legal tech leadership and why thinking like a managing partner matters This Episode is presented by Steno: Smarter transcripts. Faster delivery. Built for modern legal teams.

Send us a textWhat if your doctor knew everything about you—not just your medical history, but your genetics, lifestyle, environment, and social circumstances? Abbas Zavar, a physician and digital health leader with over 20 years of experience, believes this comprehensive approach is the key to fixing Canada's broken healthcare system.Our conversation dives deep into the crisis facing Canadian healthcare: overcrowded emergency rooms, months-long wait times, physician shortages, and a system that waits for people to get sick instead of preventing illness. Dr. Zavar challenges this reactive model, proposing a revolutionary shift toward personalized, proactive medicine powered by artificial intelligence and knowledge management.The vision is compelling: imagine AI systems that can gather comprehensive health data across five domains—medical records, genetic information, lifestyle factors, environmental exposures, and social determinants—then transform this information into actionable knowledge for physicians. These systems wouldn't replace doctors but would augment their capabilities, handling administrative burdens that currently consume up to 20 extra hours per week while providing critical insights at the point of care.We explore real-world applications already emerging, like systems that can analyze a patient's genetic profile to determine which medications will be most effective for their unique biology. We also discuss the barriers to implementation, from data silos and interoperability challenges to the slow pace of policy development in the face of rapidly advancing technology.Throughout our discussion,Abbas Zavar emphasizes that the goal isn't to remove humanity from healthcare but to enhance it—freeing physicians from administrative tasks so they can focus on providing compassionate care. As he puts it, "AI won't replace physicians, but physicians who use AI will replace those who don't."Join us for this fascinating glimpse into the future of healthcare, where medicine isn't based on statistics but tailored specifically to you as an individual. Subscribe now to hear more conversations about how technology and innovation are reshaping our world.The music for this episode, Out There, is performed by our current artist in residence,#TracyJones from his album #LuckyTimeYou can find out more about Tracy by visiting the Blog Post for his episode Knowledge Management Institute of CanadaFrom those who know to those who need to knowWorkplace Innovation Network for CanadaEvery Graduate is Innovation-Enabled; Every Employee can Contribute to InnovationDisclaimer: This post contains affiliate links. If you make a purchase, I may receive a commission at no extra cost to you.Support the showreview us on Podchaser Show website - https://fwiw.buzzsprout.comFollow us on:Show Blog Face Book Instagram: Support usEmail us: fwiw.thepodcast@gmail.com

Discover how AI is revolutionizing Personal Knowledge Management (PKM). Join Thanh and Brooks as they discuss their evolving PKM systems, exploring new AI-first tools, the future of Evernote, and the impressive AI capabilities within Obsidian. Learn when to embrace new AI tools and when to stick with proven systems for maximum productivity. Sign up for […]

In this episode of the Real Estate Pros podcast, host Kristen Knapp interviews Ryan Pease, founder of SOP Mojo, about the importance of streamlining business operations through effective documentation and systems. Ryan shares his insights on the gaps he identified in the market, the difference between systems and automation, and the critical role of documentation in achieving efficiency and consistency in business processes. He discusses his journey in starting SOP Mojo, the significance of maintaining systems, and the tools available for knowledge management. Ryan also outlines his future plans for expanding his business and offers valuable resources for listeners. Professional Real Estate Investors - How we can help you: Investor Fuel Mastermind:  Learn more about the Investor Fuel Mastermind, including 100% deal financing, massive discounts from vendors and sponsors you're already using, our world class community of over 150 members, and SO much more here: http://www.investorfuel.com/apply   Investor Machine Marketing Partnership:  Are you looking for consistent, high quality lead generation? Investor Machine is America's #1 lead generation service professional investors. Investor Machine provides true ‘white glove' support to help you build the perfect marketing plan, then we'll execute it for you…talking and working together on an ongoing basis to help you hit YOUR goals! Learn more here: http://www.investormachine.com   Coaching with Mike Hambright:  Interested in 1 on 1 coaching with Mike Hambright? Mike coaches entrepreneurs looking to level up, build coaching or service based businesses (Mike runs multiple 7 and 8 figure a year businesses), building a coaching program and more. Learn more here: https://investorfuel.com/coachingwithmike   Attend a Vacation/Mastermind Retreat with Mike Hambright: Interested in joining a “mini-mastermind” with Mike and his private clients on an upcoming “Retreat”, either at locations like Cabo San Lucas, Napa, Park City ski trip, Yellowstone, or even at Mike's East Texas “Big H Ranch”? Learn more here: http://www.investorfuel.com/retreat   Property Insurance: Join the largest and most investor friendly property insurance provider in 2 minutes. Free to join, and insure all your flips and rentals within minutes! There is NO easier insurance provider on the planet (turn insurance on or off in 1 minute without talking to anyone!), and there's no 15-30% agent mark up through this platform!  Register here: https://myinvestorinsurance.com/   New Real Estate Investors - How we can work together: Investor Fuel Club (Coaching and Deal Partner Community): Looking to kickstart your real estate investing career? Join our one of a kind Coaching Community, Investor Fuel Club, where you'll get trained by some of the best real estate investors in America, and partner with them on deals! You don't need $ for deals…we'll partner with you and hold your hand along the way! Learn More here: http://www.investorfuel.com/club   —--------------------

In this episode of KP Unpacked, the #1 podcast in AEC, Jeff Echols sits down with Chris Parsons, founder and CEO of Knowledge Architecture, to explore why knowledge management (KM) is no longer just an IT function—it's a strategic currency for AEC firms.Chris shares his 15-year journey building Synthesis, a knowledge platform purpose-built for AEC, and how today's KM 3.0 (powered by AI) is reshaping how firms capture, share, and scale what they know. From navigating firm growth to managing M&A, this conversation covers what it really takes to design a smarter business.

Interview with Steven Johnson Amazon buys Bee AI wearable that listens to everything you say Lovable becomes a unicorn with $200M Series A just 8 months after launch | TechCrunch (21) Jeff Wang on X: "To put it mildly, the past week at Windsurf has been crazy. There have been a lot of different rumors and reports, so I want to share a transparent account of how it actually went down. Before I start, I just want to say that Varun and Douglas were great founders and this" / X Thinking Machines Lab Raises $2 Billion at $10 Billion Valuation The Epic Battle for AI Talent—With Exploding Offers, Secret Deals and Tears OpenAI partners with Oracle to built out 4.5 gigawatts in data center capacity SoftBank and OpenAI's $500 Billion AI Project Struggles to Get Off Ground (21) Alexander Wei on X: "1/N I'm excited to share that our latest @OpenAI experimental reasoning LLM has achieved a longstanding grand challenge in AI: gold medal-level performance on the world's most prestigious math competition—the International Math Olympiad (IMO)." / X It's rude to show AI output to people | Alex Martsinovich Trump's AI Action Plan Is a Crusade Against 'Bias'—and Regulation Elon Musk's xAI tried to teach Grok how to be human — by recording its own workers' faces A new study just upended AI safety 'I destroyed months of your work in seconds' says AI coding tool after deleting a dev's entire database during a code freeze: 'I panicked instead of thinking' Tesla results Total Party Kill Twin Peaks as it is meant to be seen Attack of the clever crows Hosts: Leo Laporte, Jeff Jarvis, and Paris Martineau Guest: Steven Johnson Download or subscribe to Intelligent Machines at https://twit.tv/shows/intelligent-machines. Join Club TWiT for Ad-Free Podcasts! Support what you love and get ad-free shows, a members-only Discord, and behind-the-scenes access. Join today: https://twit.tv/clubtwit Sponsors: smarty.com/twit agntcy.org

Interview with Steven Johnson Amazon buys Bee AI wearable that listens to everything you say Lovable becomes a unicorn with $200M Series A just 8 months after launch | TechCrunch (21) Jeff Wang on X: "To put it mildly, the past week at Windsurf has been crazy. There have been a lot of different rumors and reports, so I want to share a transparent account of how it actually went down. Before I start, I just want to say that Varun and Douglas were great founders and this" / X Thinking Machines Lab Raises $2 Billion at $10 Billion Valuation The Epic Battle for AI Talent—With Exploding Offers, Secret Deals and Tears OpenAI partners with Oracle to built out 4.5 gigawatts in data center capacity SoftBank and OpenAI's $500 Billion AI Project Struggles to Get Off Ground (21) Alexander Wei on X: "1/N I'm excited to share that our latest @OpenAI experimental reasoning LLM has achieved a longstanding grand challenge in AI: gold medal-level performance on the world's most prestigious math competition—the International Math Olympiad (IMO)." / X It's rude to show AI output to people | Alex Martsinovich Trump's AI Action Plan Is a Crusade Against 'Bias'—and Regulation Elon Musk's xAI tried to teach Grok how to be human — by recording its own workers' faces A new study just upended AI safety 'I destroyed months of your work in seconds' says AI coding tool after deleting a dev's entire database during a code freeze: 'I panicked instead of thinking' Tesla results Total Party Kill Twin Peaks as it is meant to be seen Attack of the clever crows Hosts: Leo Laporte, Jeff Jarvis, and Paris Martineau Guest: Steven Johnson Download or subscribe to Intelligent Machines at https://twit.tv/shows/intelligent-machines. Join Club TWiT for Ad-Free Podcasts! Support what you love and get ad-free shows, a members-only Discord, and behind-the-scenes access. Join today: https://twit.tv/clubtwit Sponsors: smarty.com/twit agntcy.org

Interview with Steven Johnson Amazon buys Bee AI wearable that listens to everything you say Lovable becomes a unicorn with $200M Series A just 8 months after launch | TechCrunch (21) Jeff Wang on X: "To put it mildly, the past week at Windsurf has been crazy. There have been a lot of different rumors and reports, so I want to share a transparent account of how it actually went down. Before I start, I just want to say that Varun and Douglas were great founders and this" / X Thinking Machines Lab Raises $2 Billion at $10 Billion Valuation The Epic Battle for AI Talent—With Exploding Offers, Secret Deals and Tears OpenAI partners with Oracle to built out 4.5 gigawatts in data center capacity SoftBank and OpenAI's $500 Billion AI Project Struggles to Get Off Ground (21) Alexander Wei on X: "1/N I'm excited to share that our latest @OpenAI experimental reasoning LLM has achieved a longstanding grand challenge in AI: gold medal-level performance on the world's most prestigious math competition—the International Math Olympiad (IMO)." / X It's rude to show AI output to people | Alex Martsinovich Trump's AI Action Plan Is a Crusade Against 'Bias'—and Regulation Elon Musk's xAI tried to teach Grok how to be human — by recording its own workers' faces A new study just upended AI safety 'I destroyed months of your work in seconds' says AI coding tool after deleting a dev's entire database during a code freeze: 'I panicked instead of thinking' Tesla results Total Party Kill Twin Peaks as it is meant to be seen Attack of the clever crows Hosts: Leo Laporte, Jeff Jarvis, and Paris Martineau Guest: Steven Johnson Download or subscribe to Intelligent Machines at https://twit.tv/shows/intelligent-machines. Join Club TWiT for Ad-Free Podcasts! Support what you love and get ad-free shows, a members-only Discord, and behind-the-scenes access. Join today: https://twit.tv/clubtwit Sponsors: smarty.com/twit agntcy.org

Interview with Steven Johnson Amazon buys Bee AI wearable that listens to everything you say Lovable becomes a unicorn with $200M Series A just 8 months after launch | TechCrunch (21) Jeff Wang on X: "To put it mildly, the past week at Windsurf has been crazy. There have been a lot of different rumors and reports, so I want to share a transparent account of how it actually went down. Before I start, I just want to say that Varun and Douglas were great founders and this" / X Thinking Machines Lab Raises $2 Billion at $10 Billion Valuation The Epic Battle for AI Talent—With Exploding Offers, Secret Deals and Tears OpenAI partners with Oracle to built out 4.5 gigawatts in data center capacity SoftBank and OpenAI's $500 Billion AI Project Struggles to Get Off Ground (21) Alexander Wei on X: "1/N I'm excited to share that our latest @OpenAI experimental reasoning LLM has achieved a longstanding grand challenge in AI: gold medal-level performance on the world's most prestigious math competition—the International Math Olympiad (IMO)." / X It's rude to show AI output to people | Alex Martsinovich Trump's AI Action Plan Is a Crusade Against 'Bias'—and Regulation Elon Musk's xAI tried to teach Grok how to be human — by recording its own workers' faces A new study just upended AI safety 'I destroyed months of your work in seconds' says AI coding tool after deleting a dev's entire database during a code freeze: 'I panicked instead of thinking' Tesla results Total Party Kill Twin Peaks as it is meant to be seen Attack of the clever crows Hosts: Leo Laporte, Jeff Jarvis, and Paris Martineau Guest: Steven Johnson Download or subscribe to Intelligent Machines at https://twit.tv/shows/intelligent-machines. Join Club TWiT for Ad-Free Podcasts! Support what you love and get ad-free shows, a members-only Discord, and behind-the-scenes access. Join today: https://twit.tv/clubtwit Sponsors: smarty.com/twit agntcy.org

Interview with Steven Johnson Amazon buys Bee AI wearable that listens to everything you say Lovable becomes a unicorn with $200M Series A just 8 months after launch | TechCrunch (21) Jeff Wang on X: "To put it mildly, the past week at Windsurf has been crazy. There have been a lot of different rumors and reports, so I want to share a transparent account of how it actually went down. Before I start, I just want to say that Varun and Douglas were great founders and this" / X Thinking Machines Lab Raises $2 Billion at $10 Billion Valuation The Epic Battle for AI Talent—With Exploding Offers, Secret Deals and Tears OpenAI partners with Oracle to built out 4.5 gigawatts in data center capacity SoftBank and OpenAI's $500 Billion AI Project Struggles to Get Off Ground (21) Alexander Wei on X: "1/N I'm excited to share that our latest @OpenAI experimental reasoning LLM has achieved a longstanding grand challenge in AI: gold medal-level performance on the world's most prestigious math competition—the International Math Olympiad (IMO)." / X It's rude to show AI output to people | Alex Martsinovich Trump's AI Action Plan Is a Crusade Against 'Bias'—and Regulation Elon Musk's xAI tried to teach Grok how to be human — by recording its own workers' faces A new study just upended AI safety 'I destroyed months of your work in seconds' says AI coding tool after deleting a dev's entire database during a code freeze: 'I panicked instead of thinking' Tesla results Total Party Kill Twin Peaks as it is meant to be seen Attack of the clever crows Hosts: Leo Laporte, Jeff Jarvis, and Paris Martineau Guest: Steven Johnson Download or subscribe to Intelligent Machines at https://twit.tv/shows/intelligent-machines. Join Club TWiT for Ad-Free Podcasts! Support what you love and get ad-free shows, a members-only Discord, and behind-the-scenes access. Join today: https://twit.tv/clubtwit Sponsors: smarty.com/twit agntcy.org

In this episode of Confessions of a B2B Entrepreneur, host Tom Hunt sits down with Alex Heublein, President of Innovation Business at Netsurit, to explore how businesses can effectively implement AI solutions that accelerate productivity and drive growth. Alex shares practical insights on optimising internal processes and enhancing customer research, demonstrating how AI can be a "bicycle for the mind" for your team. Discover how to leverage internal and external data to boost efficiency and make customers happier, all while maintaining data security and privacy.

SummaryIn this conversation, Maurie and Jim Beasley explore the multifaceted world of artificial intelligence, sharing personal anecdotes and practical applications of AI in education and beyond. They discuss the importance of understanding AI basics, the diverse ways individuals can utilize AI tools, and the significance of personalizing AI experiences. The conversation also explores the role of AI in workflow automation, content creation, and ethical considerations in education, highlighting the importance of teachers staying informed and engaged with AI advancements.TakeawaysAI can be used for personal tasks to enhance daily life.Starting with personal applications makes AI more relatable.Multimodal AI can recognize and process images and text.Different users have unique ways of utilizing AI tools.Planning and prototyping are essential in AI tool usage.Workflow automation can streamline tasks and improve efficiency.Visuals created with AI can enhance educational materials.AI literacy is crucial for educators to keep up with advancements.Documentation should be made AI-friendly for better accessibility.Teaching remains a human-centered profession despite AI advancements.Sound bites"How do I use this thing?""Start with something personal.""Teaching is still human work."Chapters00:00 Introduction to AI and Personal Experiences01:51 Understanding AI Basics and Personal Applications04:41 Exploring Multimodal AI and Personal Use Cases06:14 Diverse AI Utilization: Educator vs. Engineer Perspectives10:16 Planning and Prototyping with AI Tools14:19 Workflow Automation and Organizational Tools16:18 Visuals and Content Creation for Educators19:39 AI in Training and Professional Development22:17 Research and Ethical Considerations in AI25:09 Documentation and Knowledge Management with AI

Enterprise Knowledge CEO Zach Wahl speaks with Jeff Vargas, former Director of Knowledge Management at Paramount. In this conversation, Zach and Jeff discuss being KM evangelists and the trick to selling KM programs to executives. They get into "invisible KM," talking about how everyone is doing KM but may not realize it, and how to find and boost those pockets of success. Jeff also shares the "lightbulb" moment that catapulted him from technical writing, to learning and development, and, ultimately, to knowledge management.To learn more about Enterprise Knowledge, visit us at: ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠enterprise-knowledge.com⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠.EK's Knowledge Base: ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠https://enterprise-knowledge.com/knowledge-base/⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Contact Us: ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠https://enterprise-knowledge.com/contact-us/⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠LinkedIn: ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠https://www.linkedin.com/company/enterprise-knowledge-llc/⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Twitter/X: ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠https://twitter.com/ekconsulting⁠⁠⁠

In this bonus episode of Higher Ed Pulse recorded live at the 2025 Engage Summit, host Mallory Willsea sits down with Hannah Wilson, Knowledge Management and CRM Coordinator at Forsyth Tech Community College. This episode explores the vital role of clean data, the evolving relationship between humans and AI in student engagement, and how smart use of chatbots can revolutionize community college communications. From innovative experiments to real-world enrollment gains, Hannah shares how Forsyth Tech is leading the charge in AI implementation in higher ed. - - - -Connect With Our Host:Mallory Willsea https://www.linkedin.com/in/mallorywillsea/https://twitter.com/mallorywillseaAbout The Enrollify Podcast Network:The Higher Ed Pulse is a part of the Enrollify Podcast Network. If you like this podcast, chances are you'll like other Enrollify shows too!Enrollify is made possible by Element451 — the next-generation AI student engagement platform helping institutions create meaningful and personalized interactions with students. Learn more at element451.com.Attend the 2025 Engage Summit! The Engage Summit is the premier conference for forward-thinking leaders and practitioners dedicated to exploring the transformative power of AI in education. Explore the strategies and tools to step into the next generation of student engagement, supercharged by AI. You'll leave ready to deliver the most personalized digital engagement experience every step of the way.Register now to secure your spot in Charlotte, NC, on June 24-25, 2025! Early bird registration ends February 1st -- https://engage.element451.com/register

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In this episode of The Reformed Brotherhood, Tony Arsenal takes listeners on a deep dive into the art and purpose of effective note-taking, particularly within the context of Christian living and theological study. With Jesse absent for this episode, Tony explores practical techniques to help Christians retain, process, and apply what they read, whether it be from Scripture, theological works, or even secular writings. Highlighting his own personal process, Tony emphasizes the importance of reading with intention and grounding all study in the ultimate goal of glorifying God and enjoying Him forever. The episode details Tony's structured note-taking process, which includes reading with a clear purpose, capturing highlights, organizing thoughts systematically, and reviewing and reusing notes for practical outcomes. He emphasizes the importance of using tools that work for the individual, whether digital platforms like Obsidian markdown or analog methods like commonplace books. The central theme throughout is that note-taking is not just about acquiring knowledge, but about using that knowledge to reflect God's glory in everyday life. Tony also ties the practice of note-taking to theological principles, referencing the Westminster Catechism's teaching that every action should aim to glorify God. He challenges listeners to examine their own study habits and consider how they can better use what they learn to serve their families, churches, and communities. Whether through teaching Sunday school, sharing the faith with children, or preparing sermons, the episode demonstrates how intentional note-taking can enhance spiritual growth and equip believers for ministry. Key Points: The Purpose of Note-Taking: Note-taking is not an end in itself but a means to glorify God and enjoy Him forever. It helps Christians reflect on and apply what they learn in practical ways. Tony's Note-Taking Process: A step-by-step guide that includes reading with intention, highlighting key insights, organizing notes with tags, and reviewing them regularly for reuse. Tools and Techniques: Recommendations for using tools like Obsidian markdown or analog methods, emphasizing flexibility and personalization in developing a system that works. Practical Applications: The importance of using notes for teaching, sermon preparation, family devotions, and theological discussions, making knowledge actionable and impactful. Theological Foundations: Connecting note-taking to the broader Christian life, including meditating on Scripture and theological works as a means of sanctification. Questions for Reflection: How does your current note-taking process help you retain and apply what you read? In what ways can you ensure that your study habits glorify God and enhance your enjoyment of Him? What tools or methods could you adopt to make your note-taking more effective and organized? How can you use what you learn to serve your church, family, or community more effectively? What intentions or goals should you set before starting your next reading or study session?

I, Stewart Alsop, welcomed Alex Levin, CEO and co-founder of Regal, to this episode of the Crazy Wisdom Podcast to discuss the fascinating world of AI phone agents. Alex shared some incredible insights into how AI is already transforming customer interactions and what the future holds for company agents, machine-to-machine communication, and even the nature of knowledge itself.Check out this GPT we trained on the conversation!Timestamps00:29 Alex Levin shares that people are often more honest with AI agents than human agents, especially regarding payments.02:41 The surprising persistence of voice as a preferred channel for customer interaction, and how AI is set to revolutionize it.05:15 Discussion of the three types of AI agents: personal, work, and company agents, and how conversational AI will become the main interface with brands.07:12 Exploring the shift to machine-to-machine interactions and how AI changes what knowledge humans need versus what machines need.10:56 The looming challenge of centralization versus decentralization in AI, and how Americans often prioritize experience over privacy.14:11 Alex explains how tokenized data can offer personalized experiences without compromising specific individual privacy.25:44 Voice is predicted to become the primary way we interact with brands and technology due to its naturalness and efficiency.33:21 Why AI agents are easier to implement in contact centers due to different entropy compared to typical software.38:13 How Regal ensures AI agents stay on script and avoid "hallucinations" by proper training and guardrails.46:11 The technical challenges in replicating human conversational latency and nuances in AI voice interactions.Key InsightsAI Elicits HonestyPeople tend to be more forthright with AI agents, particularly in financially sensitive situations like discussing overdue payments. Alex speculates this is because individuals may feel less judged by an AI, leading to more truthful disclosures compared to interactions with human agents.Voice is King, AI is its HeirDespite predictions of its decline, voice remains a dominant channel for customer interactions. Alex believes that within three to five years, AI will handle as much as 90% of these voice interactions, transforming customer service with its efficiency and availability.The Rise of Company AgentsThe primary interface with most brands is expected to shift from websites and apps to conversational AI agents. This is because voice is a more natural, faster, and emotive way for humans to interact, a behavior already seen in younger generations.Machine-to-Machine FutureWe're moving towards a world where AI agents representing companies will interact directly with AI agents representing consumers. This "machine-to-machine" (M2M) paradigm will redefine commerce and the nature of how businesses and customers engage.Ontology of KnowledgeAs AI systems process vast amounts of information, creating a clear "ontology of knowledge" becomes crucial. This means structuring and categorizing information so AI can understand the context and user's underlying intent, rather than just processing raw data.Tokenized Data for PrivacyA potential solution to privacy concerns is "tokenized data." Instead of providing AI with specific personal details, users could share generalized tokens (e.g., "high-intent buyer in 30s") that allow for personalized experiences without revealing sensitive, identifiable information.AI Highlights Human InconsistenciesImplementing AI often brings to light existing inconsistencies or unacknowledged issues within a company. For instance, AI might reveal discrepancies between official scripts and how top-performing human agents actually communicate, forcing companies to address these differences.Influence as a Key Human SkillIn a future increasingly shaped by AI, Sam Altman (via Alex) suggests that the ability to "influence" others will be a paramount human skill. This uniquely human trait will be vital, whether for interacting with other people or for guiding and shaping AI systems.Contact Information*   Regal AI: regal.ai*   Email: hello@regal.ai*   LinkedIn: www.linkedin.com/in/alexlevin1/

For the first time ever, The Learning & Development Podcast was recorded in front of a live audience in New York! In this special episode, I sit down with Julianne Gill, Director of Learning & Development at Smile Brands, to explore what it truly takes to build an L&D function that delivers measurable impact. Julianne shares insights from her career journey, how she assessed and transformed L&D at Smile Brands, and the pivotal role of performance consulting and collaborative learning in making L&D a strategic business driver. Take your L&D to the next level Take advantage of thousands of hours of analysis. Hundreds of conversations with industry innovators and 25+ years of hands-on global L&D leadership. It's all distilled into one framework to help you level up L&D. Access the L&D Maturity Model here - https://360learning.com/maturity-model KEY TAKEAWAYS L&D leaders need to think strategically to truly help the business. Seek real customer feedback. If you don´t know what people really think you can´t improve. Focus on how people really learn. It is always evolving. The L&D department needs to learn and evolve themselves. Collaborative learning works. Always partner with subject matter experts. Where possible update what they have already created, then get them to edit it. Start by helping people to achieve their KPIs. Educate yourself about performance consulting. Focus on outcomes. Be smart with people´s time. When you have different perspectives and experiences in the room you achieve more. BEST MOMENTS “You need to show value pretty quickly.” “You are telling them their baby is ugly, and nobody likes to be told that their baby is ugly.” “When training is the absolute wrong solution, you're going to waste a lot of money.” “I can turn anything into a $ sign.” “Start with the data.” “Take the wins when you can and work your way around.” Julianne Gill Bio Julianne is an innovative Learning, Development, Talent Acquisition, & Knowledge Management leader with a track record of success in leading complex initiatives. Julianne has deep expertise in training design & strategy, performance improvement, business planning, talent acquisition, employee engagement, operational efficiencies, leadership development, and change management with a proven history of building and leading high performing teams. Through leadership and collaboration, Julianne has successfully developed and executed programs and improved operational workflows that lead to performance improvement and achievement of strategic goals. VALUABLE RESOURCES The Learning And Development Podcast - https://podcasts.apple.com/gb/podcast/the-learning-development-podcast/id1466927523 L&D Master Class Series: https://360learning.com/blog/l-and-d-masterclass-home ABOUT THE HOST David James David has been a People Development professional for more than 20 years, most notably as Director of Talent, Learning & OD for The Walt Disney Company across Europe, the Middle East & Africa. As well as being the Chief Learning Officer at 360Learning, David is a prominent writer and speaker on topics around modern and digital L&D. CONTACT METHOD Twitter:  https://twitter.com/davidinlearning LinkedIn: https://www.linkedin.com/in/davidjameslinkedin L&D Collective: https://360learning.com/the-l-and-d-collective Blog: https://360learning.com/blog L&D Master Class Series: https://360learning.com/blog/l-and-d-masterclass-home

In this episode of CISO Tradecraft, host G Mark Hardy and guest Sounil Yu delve into the dual-edged sword of implementing Microsoft 365 Copilot in enterprises. While this productivity tool has transformative potential, it introduces significant oversharing risks that can be mitigated with the right strategies. Discover how Sounil and his team at Knostic have been tackling these challenges for over a year, presenting innovative solutions to ensure both productivity and security. They discuss the importance of 'need to know' principles and knowledge segmentation, providing insight into how organizations can harness the power of Microsoft 365 Copilot safely and effectively. Tune in to learn how to avoid becoming the 'department of no' and start being the 'department of know.' Transcripts https://docs.google.com/document/d/1CT9HXdDmKojuXzWTbNYUE4Kgp_D64GyB Knostic's Website - https://www.knostic.ai/solution-brief-request  Chapters 00:00 Introduction to Microsoft Copilot Risks 00:32 Meet the Guest: Sounil Yu 02:51 Understanding Microsoft 365 Copilot 06:09 The DIKW Pyramid and Knowledge Management 08:34 Challenges of Data Permissions and Oversharing 19:01 Need to Know: A New Approach to Access Control 35:10 Measuring and Mitigating Risks with Copilot 39:46 Conclusion and Next Steps

In this episode of CISO Tradecraft, host G Mark Hardy and guest Sounil Yu delve into the dual-edged sword of implementing Microsoft 365 Copilot in enterprises. While this productivity tool has transformative potential, it introduces significant oversharing risks that can be mitigated with the right strategies. Discover how Sounil and his team at Knostic have been tackling these challenges for over a year, presenting innovative solutions to ensure both productivity and security. They discuss the importance of 'need to know' principles and knowledge segmentation, providing insight into how organizations can harness the power of Microsoft 365 Copilot safely and effectively. Tune in to learn how to avoid becoming the 'department of no' and start being the 'department of know.' Transcripts https://docs.google.com/document/d/1CT9HXdDmKojuXzWTbNYUE4Kgp_D64GyB Knostic's Website - https://www.knostic.ai/solution-brief-request Chapters 00:00 Introduction to Microsoft Copilot Risks 00:32 Meet the Guest: Sounil Yu 02:51 Understanding Microsoft 365 Copilot 06:09 The DIKW Pyramid and Knowledge Management 08:34 Challenges of Data Permissions and Oversharing 19:01 Need to Know: A New Approach to Access Control 35:10 Measuring and Mitigating Risks with Copilot 39:46 Conclusion and Next Steps

On this episode of the Crazy Wisdom Podcast, host Stewart Alsop welcomes Jessica Talisman, a senior information architect deeply immersed in the worlds of taxonomy, ontology, and knowledge management. The conversation spans the evolution of libraries, the shifting nature of public and private access to knowledge, and the role of institutions like the Internet Archive in preserving digital history. They also explore the fragility of information in the digital age, the ongoing battle over access to knowledge, and how AI is shaping—and being shaped by—structured data and knowledge graphs. To connect with Jessica Talisman, you can reach her via LinkedIn.  Check out this GPT we trained on the conversation!Timestamps00:05 – Libraries, Democracy, Public vs. Private Knowledge Jessica explains how libraries have historically shifted between public and private control, shaping access to knowledge and democracy.00:10 – Internet Archive, Cyberattacks, Digital Preservation Stewart describes visiting the Internet Archive post-cyberattack, sparking a discussion on threats to digital preservation and free information.00:15 – AI, Structured Data, Ontologies, NIH, PubMed Jessica breaks down how AI trains on structured data from sources like NIH and PubMed but often lacks alignment with authoritative knowledge.00:20 – Linked Data, Knowledge Graphs, Semantic Web, Tim Berners-Lee They explore how linked data enables machines to understand connections between knowledge, referencing the vision behind the semantic web.00:25 – Entity Management, Cataloging, Provenance, Authority Jessica explains how libraries are transitioning from cataloging books to managing entities, ensuring provenance and verifiable knowledge.00:30 – Digital Dark Ages, Knowledge Loss, Corporate Control Stewart compares today's deletion of digital content to historical knowledge loss, warning about the fragility of digital memory.00:35 – War on Truth, Book Bans, Algorithmic Bias, Censorship They discuss how knowledge suppression—from book bans to algorithmic censorship—threatens free access to information.00:40 – AI, Search Engines, Metadata, Schema.org, RDF Jessica highlights how AI and search engines depend on structured metadata but often fail to prioritize authoritative sources.00:45 – Power Over Knowledge, Open vs. Closed Systems, AI Ethics They debate the battle between corporations, governments, and open-source efforts to control how knowledge is structured and accessed.00:50 – Librarians, AI Misinformation, Knowledge Organization Jessica emphasizes that librarians and structured knowledge systems are essential in combating misinformation in AI.00:55 – Future of Digital Memory, AI, Ethics, Information Access They reflect on whether AI and linked data will expand knowledge access or accelerate digital decay and misinformation.Key InsightsThe Evolution of Libraries Reflects Power Struggles Over Knowledge: Libraries have historically oscillated between being public and private institutions, reflecting broader societal shifts in who controls access to knowledge. Jessica Talisman highlights how figures like Andrew Carnegie helped establish the modern public library system, reinforcing libraries as democratic spaces where information is accessible to all. However, she also notes that as knowledge becomes digitized, new battles emerge over who owns and controls digital information​​.The Internet Archive Faces Systematic Attacks on Knowledge: Stewart Alsop shares his firsthand experience visiting the Internet Archive just after it had suffered a major cyberattack. This incident is part of a larger trend in which libraries and knowledge repositories worldwide, including those in Canada, have been targeted. The conversation raises concerns that these attacks are not random but part of a broader, well-funded effort to undermine access to information​​.AI and Knowledge Graphs Are Deeply Intertwined: AI systems, particularly large language models (LLMs), rely on structured data sources such as knowledge graphs, ontologies, and linked data. Talisman explains how institutions like the NIH and PubMed provide openly available, structured knowledge that AI systems train on. Yet, she points out a critical gap—AI often lacks alignment with real-world, authoritative sources, which leads to inaccuracies in machine-generated knowledge​​.Libraries Are Moving From Cataloging to Entity Management: Traditional library systems were built around cataloging books and documents, but modern libraries are transitioning toward entity management, which organizes knowledge in a way that allows for more dynamic connections. Linked data and knowledge graphs enable this shift, making it easier to navigate vast repositories of information while maintaining provenance and authority​​.The War on Truth and Information Is Accelerating: The episode touches on the increasing threats to truth and reliable information, from book bans to algorithmic suppression of knowledge. Talisman underscores the crucial role librarians play in preserving access to primary sources and maintaining records of historical truth. As AI becomes more prominent in knowledge dissemination, the need for robust, verifiable sources becomes even more urgent​​.Linked Data is the Foundation of Digital Knowledge: The conversation explores how linked data protocols, such as those championed by Tim Berners-Lee, allow machines and AI to interpret and connect information across the web. Talisman explains that institutions like NIH publish their taxonomies in RDF format, making them accessible as structured, authoritative sources. However, many organizations fail to leverage this interconnected data, leading to inefficiencies in knowledge management​​.Preserving Digital Memory is a Civilization-Defining Challenge: In the digital age, the loss of information is more severe than ever. Alsop compares the current state of digital impermanence to the Dark Ages, where crucial knowledge risks disappearing due to corporate decisions, cyberattacks, and lack of preservation infrastructure. Talisman agrees, emphasizing that digital archives like the Internet Archive, WorldCat, and Wikimedia are foundational to maintaining a collective human memory​​.