Podcasts about Knowledge management

"ELECTION WEDNESDAYS BROUGHT TO YOU BY THE IEC". As the country prepares to hold the local government elections on the 4th of November this year. The national voter registration weekend will take place on 20 and 21 June. We continue with our Call-to-Action theme, with more focus on who registers to vote? What to bring, why we vote and why you need to update your details What you need to register to vote. Bongiwe Zwane spoke to the IEC General Manager of Civic and Democracy Education, Research & Knowledge Management, Moagisi Lethlaku

Royce Sin spent a decade at HSBC automating things nobody asked him to automate. He didn't ask for permission. He just did it, showed people the results, and let the time savings speak for itself. That instinct, to question why things are done a certain way and then actually do something about it, is what eventually led him into the AI space.In this episode, Peter and Dave sit down with Royce Sin to talk about what it actually takes for AI to stick inside an organization. Spoiler: it's not about the tools.We get into the tension between flexibility and reliability, why most people are being set up to fail with AI, and what it means to think like a manager when you're not one. Royce also shares his MIND framework, a practical way to think about AI adoption that he developed through hands-on work across enterprise and startup environments.There's also a good conversation about the trades, no-UI as an ideal, and why the most dangerous move in transformation is knocking down fences you don't fully understand.This week's takeaways:Think of AI as a new type of employee. Set it up for success the same way you'd set up your staff. Design roles and processes to match what it's actually good at.Not every rule is a hard rule. Before treating a constraint as a blocker, understand what's behind it. Some fences are load-bearing. Some aren't. Know the difference before you act.Don't just bring in AI. Know what outcome you're after. If you can't tell whether it's working, you don't have a tool problem, you have a clarity problem.Have a thought on any of this? Reach us at feedback@definitelymaybeagile.com

In this episode of the Crazy Wisdom Podcast, host Stewart Alsop interviews Joshua Pearce, the John Thompson Chair in Innovation at the Department of Electrical and Computer Engineering and Ivey Business School at Western University, about the revolution in open source hardware for scientific research. They discuss how three-dimensional printing, Arduino controllers, and open source designs are dramatically reducing research costs—often by 85-95%—while democratizing access to lab equipment worldwide. Pearce shares stories from his 2013 book "Open Source Lab" and explains how the movement has exploded since then, covering everything from filter wheel changers and ball mills to metal three-dimensional printers and battery research equipment. The conversation explores recycle bots that turn plastic waste into filament, the role of AI in accelerating hardware development, and how open source licensing creates a global knowledge management system where improvements are shared across the scientific community. For those interested in learning more, Pearce recommends checking out the journal HardwareX, repositories like Thingiverse and My Mini Factory, and appropedia.org for open source scientific tools and appropriate technology designs.Timestamps00:00 Welcome and introduction to Joshua Pearce, discussing his work on open source lab equipment and the evolution since publishing his book in 201305:00 Early development of open source hardware including the breakthrough filter wheel changer project built by a high school student that saved thousands of dollars10:00 Discussion of how Arduino and RepRap three-d printers enabled the democratization of scientific tools, making complex equipment accessible to anyone15:00 Economic impact showing average tool savings of 85 percent, with Arduino and three-d printing combinations reaching mid-90s percent cost reduction20:00 Case study of PhD student Mariam building complete battery research tool chain from scratch using open source designs and three-d printed components25:00 Recycle bots enabling transformation of waste plastic into three-d printer filament for pennies, revolutionizing material costs and sustainability30:00 Collaboration between universities and open source companies creating fluid handlers and acquisition systems, accelerating research capabilities globally35:00 Large language models assisting code translation and research planning, though hallucinations require careful verification and domain expertise40:00 Importance of fundamental knowledge when using AI tools, comparing vibe coding acceleration with necessity for understanding underlying principles45:00 Testing standards and calibration methods for open source equipment, balancing precision requirements against cost-effectiveness for specific applications50:00 Metal and ceramic three-d printing developments including MIG welding techniques and sintering processes for creating functional parts55:00 Knowledge management through open source licenses, repositories like Thingiverse and Apropedia enabling global collaboration and continuous improvementKey Insights1. Open source hardware has evolved dramatically since Joshua Pearce wrote his book in 2012-2013, to the point where he can no longer keep up with all the developments in the field. What started as a collection where every single example could fit in one book has exploded into an entire ecosystem with dedicated journals and thousands of researchers contributing. The vision was that scientific papers would eventually include hyperlinks to equipment designs that anyone could download and replicate, and that future is largely here today. There are now so many open source hardware articles being published that no single person can read them all, which represents a massive success for the movement.2. The fundamental breakthrough enabling open source scientific hardware came from combining several key technologies, particularly the RepRap three-d printer project and Arduino microcontrollers. Pearce's introduction to the field came when he needed a sixty-five dollar plastic part for a solar laptop project and discovered Adrian's open-sourced rapid prototyper that could make its own parts. This led to building equipment like a filter wheel changer for testing solar panels with a high school student in about a week, replacing a device that would have cost two thousand five hundred dollars with five months lead time. The democratization of tools like three-d printing and Arduino, combined with extensive code libraries and shared designs, means that even high school students can now create sophisticated scientific equipment.3. Open source scientific hardware delivers massive economic benefits, with the average tool saving scientists around eighty-five percent compared to commercial equipment, and savings reaching the mid-nineties when using Arduino and three-d printing. The economics are so compelling that the tax paid on a normal scientific tool can cover the cost of an open source alternative. A thousand dollar three-d printer can manufacture scientific tools worth more than a thousand dollars in a single Saturday. This dramatic cost reduction makes sophisticated research accessible to laboratories around the world regardless of their funding levels, fundamentally democratizing scientific capability.4. The knowledge management approach enabled by open source licenses creates a powerful collaborative improvement cycle where thousands of people worldwide contribute to evolving designs. When researchers publish equipment designs with strong reciprocal licenses, anyone can use, modify, or even sell the designs, but improvements must be shared back with the community. This creates a dispersed international engineering effort where equipment continuously improves through contributions from researchers across different institutions and countries. The RepRap three-d printer exemplifies this process, starting as barely functional prototypes but evolving through community contributions to surpass commercial alternatives in speed, resolution, and material capabilities.5. The integration of large language models and AI tools has significantly accelerated open source hardware development, though with important caveats about their limitations. LLMs excel at translating code between languages, suggesting experimental approaches, and helping researchers navigate unfamiliar fields by quickly synthesizing information from scientific literature. However, they suffer from hallucination problems and cannot be trusted for writing scientific articles or conducting complete literature reviews without verification. The key to effective use is having enough foundational knowledge to ask the right questions and verify outputs, using AI as a powerful acceleration tool rather than a replacement for expertise.6. Material science capabilities in open source hardware have expanded far beyond plastic three-d printing to include metals, ceramics, semiconductors, and composites through innovative adaptations of basic equipment. Pearce's lab has developed methods for metal three-d printing using modified MIG welding for as little as twelve hundred dollars, created slot-die coating systems for seventeen nanometer semiconductor layers using converted three-d printers, and developed techniques for ceramic printing through various material mixing approaches. The recycle bot technology enables converting waste plastic into high-quality filament for twenty-five cents instead of twenty-five dollars per roll, dramatically reducing material costs while enabling circular manufacturing practices.7. The infrastructure for sharing and discovering open source hardware designs has matured into a robust ecosystem spanning academic journals, commercial repositories, and specialized communities. Hardware X and the Journal of Open Hardware publish peer-reviewed designs alongside traditional scientific journals increasingly incorporating open hardware sections. Repositories like Thingiverse recently returned to hardcore open source principles after ownership changes and contains millions of designs, while Appropedia serves as a wiki for appropriate technology with thousands of open source designs. The GOSH community hosts annual conferences bringing together university researchers, companies, and independent hardware hackers, while field-specific communities have formed around technologies like the OpenFlexure microscope, creating networks where knowledge accumulates and never gets lost.

Was passiert, wenn kritisches Wissen nur in den Köpfen einzelner Mitarbeitender existiert? In dieser Episode des Leadership Podcasts spricht Niels Brabandt über das Problem mit Druidenwissen: unverzichtbares Erfahrungswissen, das nicht dokumentiert ist, nicht geteilt wird und Organisationen dadurch abhängig, langsam und verletzlich macht. Druidenwissen entsteht häufig aus Engagement, Kompetenz und Loyalität. Doch wenn dieses Wissen nicht systematisch gesichert wird, entsteht ein erhebliches Geschäftsrisiko. Besonders betroffen sind Unternehmen mit historisch gewachsenen Prozessen, inhabergeführte Mittelständler, technische Schlüsselrollen, vertriebsnahe Kundenbeziehungen und Organisationen ohne klare Vertretungs- und Nachfolgeplanung. Niels Brabandt erläutert, warum Druidenwissen selten nur ein Dokumentationsproblem ist. Im Kern geht es um Vertrauen, Vorhersagbarkeit von Führung, psychologische Sicherheit und Wertschätzung. Mitarbeitende teilen kritisches Wissen nur dann offen, wenn sie nicht befürchten müssen, durch ihr eigenes Wissen austauschbarer zu werden. In dieser Episode erfahren Sie: ·         Was Druidenwissen in Organisationen bedeutet ·         Warum kritisches Wissen oft bei einzelnen Personen hängen bleibt ·         Welche Risiken für Geschäftsmodelle, IT, Vertrieb und Nachfolgeplanung entstehen ·         Weshalb Dokumentation ohne Vertrauen scheitert ·         Warum vorhersagbares Führungsverhalten entscheidend ist ·         Wie Unternehmen Wissen sichern, ohne Mitarbeitende zu entwerten ·         Welche Schritte Führungskräfte sofort einleiten sollten Diese Folge richtet sich an Geschäftsführerinnen und Geschäftsführer, Vorstände, Führungskräfte, HR-Verantwortliche, Organisationsentwicklerinnen und Organisationsentwickler sowie alle Entscheidungstragenden, die Wissensmanagement, Knowledge Management, Sustainable Leadership und Unternehmensresilienz strategisch verbessern möchten. Niels Brabandt steht für Sustainable Leadership, Führungskräfteentwicklung, Organisationsentwicklung, Professional Training, Speaking, Coaching, Consulting, Mentoring sowie Projekt- und Interim Management. Weitere Informationen: www.NB-Networks.biz Host: Niels Brabandt / NB@NB-Networks.com Kontakt zu Niels Brabandt: https://www.linkedin.com/in/nielsbrabandt/ Niels Brabandts Leadership Letter: https://expert.nb-networks.com/ Niels Brabandts Webseite: https://www.nb-networks.biz/ 

Safee-Naaz Siddiqi, Professional Support Lawyer in the Knowledge Management practice at Cliffe Dekker Hofmeyr, speaks to Lester Kiewit about the growing legal and compliance risks linked to artificial intelligence tools in the workplace. As more businesses use AI platforms to draft, summarise and analyse sensitive information, questions are being raised about whether confidential or legally privileged material could unintentionally be exposed to third parties, potentially weakening legal protections and creating serious consequences for companies without clear AI policies in place. Good Morning Cape Town with Lester Kiewit is a podcast of the CapeTalk breakfast show. This programme is your authentic Cape Town wake-up call. Good Morning Cape Town with Lester Kiewit is informative, enlightening and accessible. The team’s ability to spot & share relevant and unusual stories make the programme inclusive and thought-provoking. Don’t miss the popular World View feature at 7:45am daily. Listen out for #LesterInYourLounge which is an outside broadcast – from the home of a listener in a different part of Cape Town - on the first Wednesday of every month. This show introduces you to interesting Capetonians as well as their favourite communities, habits, local personalities and neighbourhood news. Thank you for listening to a podcast from Good Morning Cape Town with Lester Kiewit. Listen live on Primedia+ weekdays between 06:00 and 09:00 (SA Time) to Good Morning CapeTalk with Lester Kiewit broadcast on CapeTalk https://buff.ly/NnFM3Nk For more from the show go to https://buff.ly/xGkqLbT or find all the catch-up podcasts here https://buff.ly/f9Eeb7i 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/@CapeTalkSee omnystudio.com/listener for privacy information.

Today, the podcast is focused on the practical and personal impact of AI in daily workflows and business operations. One theme that emerged was the creation of a custom AI-powered journaling and knowledge management system, Navigator, used for personal insights, team collaboration, and onboarding. The discussion explored how AI provides a “second brain,” enhances memory, and enables more intentional business strategies. Several points were raised, including privacy concerns, the evolution of AI in work life, and its transformative effect on team communication and productivity. The episode highlighted both the opportunities and challenges posed by integrating AI deeply into business processes.

Conference season is back, and so are the real conversations. In this episode, Peter Maddison and Dave Sharrock catch up after a busy stretch of travel and dig into something Dave has been road-testing at conferences: why most people given access to AI tools freeze up, and what actually helps them move past that.Dave ran a workshop at the Global Scrum Gathering in Vancouver for non-technical roles - product managers, Scrum Masters, agile coaches - people who've been told "use AI" but have no clear picture of where to start. What he found is that the problem isn't motivation or technical ability. It's the lack of scaffolding. Give people the right structure and the right room to experiment, and things shift pretty quickly.The conversation then moves into multi-agent systems - how Dave's team built a group of agents that continuously refresh the workshop itself based on current thinking. Peter adds his own take on testing these systems with personas and automated quality evaluation. It gets a bit technical, but in the best way.This is a good episode if you're thinking about how to help your organization actually use AI, not just adopt it on paper.Key Takeaways:Context beats generic. Prompts work when they're specific to your role and your actual problems. A product manager needs product management context, not a one-size-fits-all example.Think in teams, not steps. Multi-agent systems work best when you treat them like a team reviewing an artifact, each agent checking for something different, rather than a linear build process.Don't assume everyone gets it. The gap between people who use AI daily and people who tried it once and gave up is wider than most of us realize. Getting both groups in the same room is where the real learning happens, for everyone.Have a question or something to add? Reach out at feedback@definitelymaybeagile.com or find us at definitelymaybeagile.com. And if you're finding the show useful, subscribing and leaving a review goes a long way.

In this episode of the Crazy Wisdom Podcast, host Stewart Alsop sits down with Joshua Bate, founder of Bonfires.ai and DeciWorld, for a wide-ranging conversation covering knowledge management, graph technology, ontologies, decentralized science, and the future of how humans organize and share information. They break down the differences between personal and enterprise knowledge management, explore why flat ontological graphs may be the key to making diverse knowledge bases interoperable, and get into why traditional RAG systems break down at scale and how graph RAG offers a more principled solution. The conversation expands into the philosophy of categorization, the slow death of basic "gentleman science" under institutional pressures, and how decentralized protocols might restore a kind of mycelial knowledge network connecting small groups of researchers, enthusiasts, and communities — much like the original spirit of the encyclopedia before it was co-opted by institutions. You can learn more about Joshua's work at bonfires.ai and deci.world or follow him on X at @Bonfiresai and @DeSciWorld.Timestamps00:00 - Stewart introduces Joshua Bate, founder of Bonfires.ai, discussing personal versus enterprise knowledge management and their fundamental differences at scale.05:00 - Joshua explains ontologies as classifiers for knowledge structures, describing their two-year search for a perfect ontology and ultimately building a flat, ontology-less graph protocol.10:00 - Stewart connects categorization to shamanic practice and intercategorical theory, noting how major companies like Netflix and Yahoo built graph-based ontologies while the discipline remains underappreciated philosophically.15:00 - Joshua traces Bonfires origins through decentralized science, explaining how NFT community excitement inspired redirecting capital toward funding unconventional researchers locked out of institutional systems.20:00 - Joshua describes building federated knowledge networks through hackathons and conferences, comparing the vision to what Wikipedia could have been with decentralized incentive structures.25:00 - Discussion shifts toward inevitable collapse of rigid scientific institutions, debating patchwork age theory, nation-state fragmentation, and rhizomatic versus arboreal knowledge structures.30:00 - Joshua articulates the mycelial network vision, enabling direct cross-cultural information access where individuals control their own narrative lens, warning against collective we thinking and authoritarianism.Key Insights1. Knowledge management exists on a spectrum from personal to enterprise, but the founder of Bonfires argues this split is artificial. He believes knowledge itself does not respect those boundaries, and that small groups, researchers, hobbyists, and large institutions all possess knowledge that can and should interoperate with each other.2. After two and a half years of searching for the perfect ontology to structure their knowledge graph, the team concluded that no perfect ontology exists. Their solution was to build the flattest possible graph structure with only events, entities, and edges, creating a base layer others can build specialized ontologies on top of.3. Graph-based knowledge systems are more efficient than traditional databases for AI traversal because once a graph is computed, it is relatively free to query. Graph RAG combines the discovery power of vector search with the structured precision of graph traversal, solving many hallucination problems associated with standard retrieval augmented generation.4. Basic scientific research, the soil from which applied discoveries grow, is deteriorating because institutional funding structures only reward commercially viable outcomes. The founder built his platform partly to redirect community-driven capital toward researchers who are doing important work without institutional support.5. The institutionalization of science has historically blocked the open exchange of ideas that drove the original scientific revolution. The human spirit for open inquiry has not changed, but people cannot pursue it without financial support, and building decentralized infrastructure could restore that possibility.6. A federated knowledge network would allow individuals to access information from any contributor and filter it through their own preferred lens, rather than receiving information pre-filtered by centralized platforms. This represents a form of information symmetry similar to how mycelial networks distribute nutrients across a forest.7. The concern is not whether current scientific and governmental institutions will change but in what direction the rebuilding goes. Those capitalizing on the transition carry the same incentives as the previous era, which risks reproducing the same problems inside new structures.

Summary In this episode, Andy welcomes back Steve Kahle, entrepreneur, executive, and fractional CIO, author of Leadership Recall: Harness Insights. Accelerate Innovation. LEAD WITH AUTHORITY. Steve first joined the podcast in episode 184 to discuss email overload. This time, the conversation turns to a challenge every leader faces: the forgetting curve. Research suggests we forget up to 83% of what we learn within a week, and Steve argues this is not just a learning problem, it's a leadership problem. Steve shares his CCR framework (Capture, Catalog, and Recall), along with practical tools such as the Anki flashcard app and the Email Me voice-note app, to build what he calls a learning operating system. The discussion covers how to design a recall fitness practice in as little as three minutes a day and how removing friction at every step keeps the system sustainable. If you're looking for a practical system to stop letting great insights slip away and start leading with more authority, this episode is for you! Sound Bites "I think God put in my heart to be a relentless optimizer. I like to see things work and work well." "When you really zoom out in life, those who are really successful have figured out what are the frameworks, what are the methodologies that work, and they simply apply those." "Our subconscious mind can handle about 11 million bits of data per second, but about 40 bits conscious mind." "I went all in. Christ totally transformed my heart, and I'm realizing that scripture memory is a superpower." "Time swiftly washes away the obvious." "Learning really is a privilege, and we need to be able to find time that works with our daily rhythms." "Three minutes a day is really all you need to be able to see tremendous traction on being able to recall things that matter" "Instead of 'I'm bad at remembering names,' you could, do a reframe like, 'Hey, I'm getting better at remembering people's names.'" Chapters 00:00 Introduction 01:48 Start of Interview 02:06 Early Experiences and the Instinct to Remember 04:08 Is Memory a Natural Gift or a Trainable Skill? 05:19 Forgetting as a Feature, Not Just a Bug 07:10 The Leadership Cost of Forgetting 09:10 Shifting the Bottleneck from Input to Retention 12:02 The Five-Hour Rule and Three Learning Archetypes 14:19 The CCR Framework in Practice: Capture, Catalog, and Recall 19:50 Removing Friction from Your Learning System 23:23 Inside Anki: Cloze Deletions and Building Cards 26:10 Organizing Your Recall Decks 27:30 Real-World Results: When Readers Apply the System 28:56 Building Recall Habits in Your Kids 32:50 How to Get the Book 34:01 End of Interview 34:17 Andy Comments After the Interview 37:46 Outtakes Learn More You can learn more about Steve and his work at leadershiprecall.com. For more learning on this topic, check out: Episode 184 with Steve Kahle. It's our previous conversation about keeping your head above water when drowning in email and commitments. Definitely recommend checking it out. Episode 411 with Laura Mae Martin. She's the head of productivity at Google and shares ideas that I still use to this day. Episode 376 with Nick Sonnenberg. It's a book about helping you and your team stop drowning in all the information and commitments at work. Chat with PMeLa You can chat directly with PMeLa—the podcast's AI persona—to get episode recommendations and answers to your project management and leadership questions. Visit PeopleAndProjectsPodcast.com/PMeLa to chat with her. Pass the PMP Exam If you or someone you know is thinking about getting PMP certified, we've put together a helpful guide called The 5 Best Resources to Help You Pass the PMP Exam on Your First Try. We've helped thousands of people earn their certification, and we'd love to help you too. It's totally free, and it's a great way to get a head start. Just go to 5BestResources.PeopleAndProjectsPodcast.com to grab your copy. I'd love to help you get your PMP this year! Join Us for LEAD52 I know you want to be a more confident leader–that's why you listen to this podcast. LEAD52 is a global community of people like you who are committed to transforming their ability to lead and deliver. It's 52 weeks of leadership learning, delivered right to your inbox, taking less than 5 minutes a week. And it's all for free. Learn more and sign up at GetLEAD52.com. Thanks! Thank you for joining me for this episode of The People and Projects Podcast! Talent Triangle: Power Skills Topics: Leadership, Memory, Learning, Productivity, Knowledge Management, Recall, Spaced Repetition, Personal Development, Continuous Learning, Networking, Project Management The following music was used for this episode: Music: Imagefilm 034 by Sascha Ende License (CC BY 4.0): https://filmmusic.io/standard-license Music: Tuesday by Sascha Ende License (CC BY 4.0): https://filmmusic.io/standard-license

Law firms sell experience — but for decades, harnessing and operationalizing that experience has been a largely manual, chaotic process. In this episode, recorded live at the Legal Marketing Association annual conference in New Orleans, host Bob Ambrogi sits down with Jason Noble, president and chief of product strategy at Ikaun, to talk about how his company is changing that. Ikaun is a managed service and technology platform that helps law firms streamline the proposal and RFP response process — from capturing and organizing matter experience data to using AI to assemble and draft competitive pitches. Jason explains how the platform works, how the arrival of generative AI transformed what was previously possible, and why Ikaun positions itself as a managed service rather than a self-serve SaaS tool. Jason and Bob also get into the bigger picture of how law firms are responding to AI-driven changes in the competitive landscape, whether the billable hour can survive in an AI-augmented world, and whether the RFP process itself will look the same in the years ahead — or whether we're moving toward a future where agents are submitting and responding to proposals with minimal human involvement.   Thank You To Our Sponsors This episode of LawNext is generously made possible by our sponsors. We appreciate their support and hope you will check them out.   Paradigm, home to the practice management platforms PracticePanther, Bill4Time, MerusCase and LollyLaw; the e-payments platform Headnote; and the legal accounting software TrustBooks. Briefpoint, eliminating routine discovery response and request drafting tasks so you can focus on drafting what matters (or just make it home for dinner).   Chapters   (00:00) Introduction to ICON and Legal Tech Innovations (02:30) Jason Noble's Journey and Background (05:20) The Evolution of ICON and Its Focus (07:09) Experience Management in Legal Firms (10:30) Gathering Experience Data in Litigation (11:48) How ICON's Platform Works (14:05) The Impact of AI on Proposal Processes (18:07) Current Landscape of RFP Responses (20:31) Differentiating ICON from Competitors (22:45) Knowledge Management vs. Experience Management (24:01) Tailoring Solutions for Law Firms (25:49) Qualities of Successful Law Firms (27:24) Law Firms' Response to AI Integration (29:54) Pricing Strategies in RFP Responses (31:21) Competitive Landscape and AI's Influence (33:27) The Future of Billable Hours (35:50) The Future of RFPs and AI's Role (39:33) Client Satisfaction and Future Directions   If you enjoy listening to LawNext, please leave us a review wherever you listen to podcasts.  

Enterprise Knowledge CEO Zach Wahl speaks with Aman Bhatnagar, Director of Global Knowledge Management at JLL. With over 18 years of leadership in KM, strategic planning, and content strategy, Aman leverages data analytics to optimize processes and implement innovative solutions for enhanced knowledge sharing and organizational performance.In this conversation, Zach and Aman discuss selling KM to leadership, the importance of adapting the narrative of KM to different audiences, and the distinction between "knowledge" and "information." They also chat about how JLL is applying AI within the organization, and how critical the underlying data is to supporting successful solutions in the long-term.---Comment below to tell us how your organization is applying AI, or to ask any questions you have for our Knowledge Cast hosts! They may be answered in a future episode.---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 episode of Disruption/Interruption, host KJ sits down with Ome Ogbru, PharmD, CEO and founder of AINGENS, to tackle a decades-old problem hiding in plain sight: life sciences runs on groundbreaking science, but is buried in broken processes. After 20+ years as a clinician, professor, and pharmaceutical executive, Ome reached a breaking point, and instead of finding a new job, he built a new company. He shares how generative AI, used responsibly and strategically, can finally give researchers their time back, cut through misinformation, and help the right information reach the right people faster. Four Key Takeaways: The scientific content workflow is fundamentally broken [4:15] -- Research teams are so resource-strapped that PhDs spend their time managing IT systems instead of doing science. Procuring a software solution could take one to two years and often didn't even solve the right problem. Generative AI isn't the magic wand, it's how you use it [20:01] -- When Ome first tested ChatGPT on biotech content and got poor results, he had a revelation: the tool wasn't the problem. The problem was not knowing how to use it. Pairing AI with deep domain expertise and proper workflows is where the real power lies. The human expert must remain in the driver's seat [32:30] -- AINGENS' platform (MACG) is built so the professional is in control. The AI handles the time-consuming, mundane tasks like literature search, drafting, and formatting, while the expert applies regulatory knowledge, judgment, and guardrails. Misinformation in life sciences is a public health problem [35:49] -- Misinformation travels faster than accurate data. Ome's vision is for generative AI to help industry proactively get accurate, personalized scientific information to the people who need it, patients, clinicians, and researchers alike, before the noise wins. Quote of the Show (35:41):"Misinformation flies faster than correct information." -- Ome Ogbru Join our Anti-PR newsletter where we’re keeping a watchful and clever eye on PR trends, PR fails, and interesting news in tech so you don't have to. You're welcome. Want PR that actually matters? Get 30 minutes of expert advice in a fast-paced, zero-nonsense session from Karla Jo Helms, a veteran Crisis PR and Anti-PR Strategist who knows how to tell your story in the best possible light and get the exposure you need to disrupt your industry. Click here to book your call: https://info.jotopr.com/free-anti-pr-eval Ways to connect with Ome Ogbru:LinkedIn: https://www.linkedin.com/in/ome-ogbru-pharmd/Company Website: http://www.aingens.com How to get more Disruption/Interruption: Amazon Music - https://music.amazon.com/podcasts/eccda84d-4d5b-4c52-ba54-7fd8af3cbe87/disruption-interruption Apple Podcast - https://podcasts.apple.com/us/podcast/disruption-interruption/id1581985755 Spotify - https://open.spotify.com/show/6yGSwcSp8J354awJkCmJlDSee omnystudio.com/listener for privacy information.

In this insightful conversation, Unisys Chief Commercial Officer Joel Raper explores how traditional knowledge management is being transformed by AI and agentic systems. From cleaning and structuring enterprise data to enabling autonomous agents and digital twins, this discussion uncovers how organizations can unlock real value from AI by rethinking how knowledge is created, managed, and applied. https://www.linkedin.com/in/joel-raper-5020063/ https://www.linkedin.com/in/lanecooper/ #CIOLeadershipLive Follow CIO for more Business Strategies in Tech!

Enterprise Knowledge CEO Zach Wahl speaks with Ashish Kanal, a founder and independent advisor currently working at the intersection of Knowledge Management and Organizational Learning. Over 24 years across life sciences, chemicals, oil & gas, IT, and more, Ashish has led KM and L&D initiatives to create ecosystems from strategy and governance to platforms, adoption, and behavioral change.In this conversation, Zach and Ashish discuss how to capture context around decision making in an organization, the relationship between knowledge management (KM) and learning and development (L&D), and the importance of transparency, explainability, and the human-in-the-loop approach to AI when there are lives on the line. Ashish also shares success stories where he has delivered captured knowledge at the point of need, and gives advice for the next generation of KMers.---Comment below to tell us how you've delivered captured knowledge at the point of need, or to ask any questions you have for our Knowledge Cast hosts! They may be answered in a future episode.---You can connect with Ashish on all things Knowledge Management, Learning, and AI strategy at ⁠https://in.linkedin.com/in/ashishkanal⁠⁠ 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 episode of the SAATKORN Podcast, I'm talking to Gabriele Riedmann de Trinidad, Founder & CEO of Platform 3L – a company focused on combining knowledge management and learning to future-proof organizations. With a background in global tech, telecom, and innovation leadership, she has spent years building systems, scaling businesses, and solving complex transformation challenges.

Clement Manyathela hosts Moagisi Letlhaku, who is General Manager for Civic Education Research and Knowledge Management at the IEC to discuss voter sentiment amid a new report that raises concerns about attitudes of young people. The Clement Manyathela Show is broadcast on 702, a Johannesburg based talk radio station, weekdays from 09:00 to 12:00 (SA Time). Clement Manyathela starts his show each weekday on 702 at 9 am taking your calls and voice notes on his Open Line. In the second hour of his show, he unpacks, explains, and makes sense of the news of the day. Clement has several features in his third hour from 11 am that provide you with information to help and guide you through your daily life. As your morning friend, he tackles the serious as well as the light-hearted, on your behalf. Thank you for listening to a podcast from The Clement Manyathela Show. Listen live on Primedia+ weekdays from 09:00 and 12:00 (SA Time) to The Clement Manyathela Show broadcast on 702 https://buff.ly/gk3y0Kj For more from the show go to https://buff.ly/XijPLtJ or find all the catch-up podcasts here https://buff.ly/p0gWuPE Subscribe to the 702 Daily and Weekly Newsletters https://buff.ly/v5mfetc Follow us on social media: 702 on Facebook https://www.facebook.com/TalkRadio702 702 on TikTok https://www.tiktok.com/@talkradio702 702 on Instagram: https://www.instagram.com/talkradio702/ 702 on X: https://x.com/Radio702 702 on YouTube: https://www.youtube.com/@radio702 See omnystudio.com/listener for privacy information.

In this episode of Disruption/Interruption, KJ sits down with Alan Paulin, co-creator of Mavis, to explore how AI is fundamentally transforming the way we write and work. Alan shares his journey from building Cash App to creating a startup that eliminates "copy-paste purgatory" between AI tools and traditional word processors. The conversation dives into why the current AI workflow is broken, how Mavis enables true human-AI collaboration, and why the education system needs to evolve for an AI-native generation. This is essential listening for anyone frustrated with bouncing between ChatGPT and Google Docs—and a glimpse into the future of iterative, intelligent document creation. Four Key Takeaways: [0:18] AI tools today force a "one-shot" workflow that doesn't match how humans actually work - Most people work iteratively, meandering through drafts, massaging thoughts, and editing as they go. Current AI interfaces require big prompts and deliver static documents that force you into copy-paste hell, abandoning you once you leave the chat interface. [18:09] The real value of AI isn't just saving time, it's increasing happiness - Professionals didn't choose their fields to spend all day writing—they chose them to solve problems. By compressing the time spent on tedious documentation, AI tools like Mavis don't just create efficiency; they give people more time to do meaningful work they actually love. [13:34] Big tech companies are too slow to innovate in the AI-writing space - Google Docs and Microsoft Word haven't fundamentally changed in decades. Their massive user bases make rapid innovation nearly impossible—they're steering the Titanic. Startups have a unique advantage to tackle niches and experiment with workflows that giants simply can't. [34:29] The future belongs to "AI-native" thinkers who use AI as an extension of themselves - Industry is actively seeking people who seamlessly integrate AI into their workflow and thinking. The education system must evolve beyond testing what calculators and AI can do—and start focusing on critical thinking, creativity, and problem-solving instead. Quote of the Show (17:52):"Most of these people didn't choose that field to spend all of their time writing. They chose it to solve problems." - Alan Paulin Join our Anti-PR newsletter where we’re keeping a watchful and clever eye on PR trends, PR fails, and interesting news in tech so you don't have to. You're welcome. Want PR that actually matters? Get 30 minutes of expert advice in a fast-paced, zero-nonsense session from Karla Jo Helms, a veteran Crisis PR and Anti-PR Strategist who knows how to tell your story in the best possible light and get the exposure you need to disrupt your industry. Click here to book your call: https://info.jotopr.com/free-anti-pr-eval Ways to connect with Alan Paulin: LinkedIn: http://www.linkedin.com/in/alanpaulinCompany Website: https://mavislabs.ai How to get more Disruption/Interruption: Amazon Music - https://music.amazon.com/podcasts/eccda84d-4d5b-4c52-ba54-7fd8af3cbe87/disruption-interruption Apple Podcast - https://podcasts.apple.com/us/podcast/disruption-interruption/id1581985755 Spotify - https://open.spotify.com/show/6yGSwcSp8J354awJkCmJlDSee omnystudio.com/listener for privacy information.

In this episode, Victor Vigliotti, Director of the Space Force Front Door, discusses how the US Space Force is transforming its knowledge management and vendor engagement processes. He shares insights into the innovative use of commercial systems like Salesforce to streamline vendor relationships, improve transparency, and enhance strategic matchmaking across government and industry.   Chapters 00:00 Introduction and Guest Background 00:39 The State of Knowledge Management in Space Force 01:17 Current Processes and Shortfalls in Knowledge Sharing 02:15 Adoption of Commercial CRM Systems like Salesforce 04:05 The Salesforce Custom Relationship Management System 05:10 Matching Capabilities to Space Force Needs 07:39 Scaling the Front Door System Internally 08:09 Internal Government Conversations and Requirements 09:34 Proactive Engagement and Vendor Relationship Building 11:18 Human and AI Roles in Matchmaking Automation 13:20 Future Automation and Data Validation with AI/ML 15:09 Engaging Defense Tech Companies and Industry Outreach 18:47 Success Stories and Industry Impact 23:35 Upcoming Developments and System Enhancements 29:50 Scaling the Front Door to NATO and Beyond 32:43 How Companies Can Engage with Space Force Front Door 36:09 Closing Remarks and Final Thoughts   USSF Front Door Website: https://sscfrontdoor.experience.crmforce.mil/SSCFrontDoor/s/   LEARN MORE: Thank you for tuning into this episode of the GovDiscovery AI Podcast with Mike Shanley. To connect with our team directly, message the host Mike Shanley on LinkedIn, or visit: https://www.govdiscoveryai.com/  

Enterprise Knowledge CEO Zach Wahl speaks with TJ Hsu, Director of R&D Knowledge Management at Amgen. With over a decade of experience in artificial intelligence and knowledge services, TJ currently leads a team dedicated to enhancing Amgen's research, development, and medical capabilities through innovative KM strategies. In this conversation, Zach and TJ discuss the impact TJ has made at Amgen so far, how moving from a collection of intelligent individuals to a collective intelligence helps organizations learn faster and get smarter over time, and different ways to get your organization applying knowledge rather than just "learning" it.They also chat about how to scale KM for the enterprise through selective persona targeting and thoughtful application of technology.---Comment below to let us know the most important lesson you've learned in your KM career, or ask any questions you have for our Knowledge Cast hosts! They may be answered in a future episode.---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 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

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.

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

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.

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 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

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.

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   —--------------------

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.

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?