Podcasts about Ontology

In this episode of the Crazy Wisdom Podcast, host Stewart Alsop sits down with Ryan Marsh of thestack.io to explore what it really takes to build production AI systems. They discuss how production AI has evolved from simple prompt-to-API demos into complex systems requiring evaluation suites, human-in-the-loop feedback mechanisms, and sophisticated approaches to handling context and data retrieval. The conversation covers the challenges of domain mapping, the fundamental difficulty of translating messy human business processes into structured systems, and the role of ontologies in AI development. Ryan and Stewart also examine the limitations of LLMs, the debate between specialization versus generalization in AI models, consciousness and cognition in system design, and the regulatory landscape facing AI companies. They touch on infrastructure constraints, the democratization of AI through open source models, and whether we'll eventually hit a ceiling where human intelligence can no longer distinguish between increasingly capable AI models. Key Insights1. Production AI systems today fundamentally differ from demos through their reliance on comprehensive evaluation suites that function like unit tests to measure and maintain quality, though they cannot be as deterministic. The key distinction is that production systems require clearly defined metrics for what good looks like, along with feedback mechanisms that allow the system to evolve over time. Without this foundational understanding of success metrics and continuous improvement processes, a system is not truly production-ready regardless of how many users it serves.2. The fundamental challenge in building production AI systems is not the technology itself but rather mapping business domains into structured formats that models can work with effectively. This problem of translating messy, subjective human processes and language into precise specifications has plagued software engineering for decades. Different people within organizations use the same words to mean completely different things, and humans naturally operate with assumed context and imprecision that must be explicitly defined for AI systems to function reliably.3. Large language models excel at generalization but struggle with specialization, which creates friction in production environments where specific outputs or styles are required. While they can code in any programming language, getting them to write code exactly the way a particular engineer wants remains extremely difficult. This explains why professional documentation and specialized coding tasks often require extensive prompting and fighting with the models, as they naturally gravitate toward their trained patterns rather than highly specific user preferences.4. Modern production AI systems primarily solve classification problems wrapped in natural language interfaces rather than requiring true open-ended cognition. The models work best when they can leverage reasoning over provided information to make verifiable decisions, but they still lack common sense despite their vast knowledge. Success comes from teaching models everything about your specific domain and what good and bad outcomes look like, rather than relying solely on their general intelligence.5. Context retrieval in production AI systems is fundamentally a data storage, search, and retrieval problem that has been solved many different ways throughout computing history. The appropriate solution depends entirely on the type of data being accessed, whether through vector databases, graph databases, relational databases, or even simple text search. The harnesses and frameworks for orchestrating AI agents have matured significantly, making the real challenge the quality and structure of the data being fed to these systems.6. Human-in-the-loop feedback mechanisms are essential for production AI because models will inevitably encounter situations they have not been trained to handle. When confidence is low or novel scenarios appear, systems should flag these for human review rather than proceeding blindly. The feedback provided during these interventions must be captured and scored so it can be incorporated into the permanent behavior of the system, creating a continuous improvement cycle similar to how model vendors perform reinforcement learning on their base models.7. The rush to regulation in the AI industry is driven primarily by the fact that these companies are currently completely exposed to existing consumer protection and liability laws with no legal precedents to protect them. If AI agents cause harm, companies could be sued into oblivion under current law. By establishing compliance frameworks through regulation, these companies can create carve-outs and exemptions that limit their liability when they follow prescribed rules, similar to how heavily regulated industries like airlines and banking have become nearly impossible to enter due to compliance requirements. Timestamps00:00 Welcome and introduction to Ryan Marsh discussing production AI systems and what companies need to understand about building them at scale05:00 The cognitive load challenge of working with invariants and probabilistic systems, discussing how LLMs function like PhD students without common sense10:00 Building eval suites to measure AI performance, handling the long tail of edge cases in complex contracts using human-in-the-loop feedback systems15:00 Context as a data retrieval problem and the fundamental challenge of mapping business domains when humans struggle with imprecision and ambiguous language20:00 How different departments use the same words with different meanings and why LLMs generalize well but don't specialize effectively for specific coding styles25:00 The ontology debate and intractable problem of mapping subjective human systems to rigid structured formats with diminishing returns on perfect mapping30:00 Why humans struggle distinguishing what is from what ought to be and the challenge of creating SOPs when companies lack updated documentation35:00 The liability exposure AI companies face and why they're begging for regulation to protect themselves from existing consumer protection laws40:00 Open source knowledge transfer between Chinese and American labs, chips and power as the real constraint not algorithms for frontier models45:00 Reaching intelligence ceiling where specialists can't distinguish state-of-art models and fundamental physical laws limiting LLM scaling through layered optimization strategies LinksWebsiteX

John's guest on the show is Maeve Ferguson, a thought leadership advisor and executive coach who helps thought leaders turn their intellectual property (IP) into powerful assessments that generate leads, attract clients, and build proprietary data that creates a real moat around their businesses. Maeve shares how a serious illness that left her bedridden for about four years completely changed the way she looked at work, success, and life. They also talk about the realities of entrepreneurship, why relationships matter in business, the importance of making things easy for your audience to understand, and why Maeve focuses on working with people who have real, well-developed intellectual property. About Maeve Ferguson: Northern Ireland-based strategist working with bestselling authors, 7-10 figure thought leaders, and the world's most established experts. Former EY consultant. Former private equity director. Now the architect behind a new category of business asset that most experts do not yet know exists. Listen to this episode to learn more: [00:00] - Intro [01:40] - Maeve's bio [03:06] - Maeve's journey from steeplechase to Ernst & Young (EY) [06:37] - The realities of entrepreneurship [10:50] - Why Maeve moved from Ernst & Young to private equity [12:35] - How a virus left her bedridden for about four years [14:24] - How the illness affected her family and loved ones [16:42] - How she protects her health and avoids repeating old patterns [17:48] - Learning about lead generation, sales, and business world [22:14] - What EY, PE, and IP mean [23:16] - John's coaching note on clear communication [25:16] - Why Maeve chose to work with thought leaders [27:52] - How Maeve finds and attracts high-level clients [28:50] - Why relationships and people matter more than status or image [32:42] - What is Agentic AI? [35:21] - Ontology and how to find real bottlenecks in your business NOTABLE QUOTES: "I pay a huge amount of importance on the relationships that I build and how I connect with people, and making sure that I always give before I get. So, yeah, about 50% of our business is from clients referring other people into us after working with us." "If you can be a champion at anything, I don't care how old you are … If you're a champ, you're a champ. Period." "Entrepreneurship is not for everybody … There are a lot of people who are running companies as hobby businesses and they would be better in a job." "If I were approached by a company that wanted to sponsor the show, if they didn't have a product or service that I used, I would not accept the money. Because if I don't believe in that, how could I possibly promote that?" "You gotta slow down to speed up." "The numbers never lie." USEFUL LINKS: https://www.maevefergusonconsulting.com/ https://www.linkedin.com/in/maeveferguson/ https://www.instagram.com/iammaeveferguson/ https://substack.com/@maeveferguson https://www.youtube.com/@maeveferguson CONNECT WITH JOHN Website - https://iamjohnhulen.com    LinkedIn - https://www.linkedin.com/in/johnhulen Instagram - https://www.instagram.com/johnhulen    Facebook - https://www.facebook.com/johnhulen    X - https://x.com/johnhulen    YouTube - https://www.youtube.com/@iamjohnhulen    EPISODE CREDITS Intro and Outro music provided by Jeff Scheetz - https://jeffscheetz.com/ 

Your data model is fast becoming AI infrastructure. As enterprises deploy agents and LLMs, tried and trusted data models are providing the structure and context AI needs to understand what corporate data really means. Sometimes called ontologies, these proven constructs are trending again because of the critical role they play in grounding Enterprise AI. Register for this special episode of DM Radio to hear Host Eric Kavanagh explain why AI architecture begins and ends with a data model. He'll be joined by Jamie Knowles of Idera, who will demonstrate how ER/Studio is filling the gap between powerful AI technologies and traditional enterprise Information Architectures. Attendees will learn:* Why the Entity-Relationship model matters more than ever * How data models enable trustworthy outputs from LLMs * What metadata can provide in terms of connective tissue * Where to begin your AI journey based upon your business needs

SPONSORS: - Head to https://www.factormeals.com/toe50off and use code toe50off to get 50% off and 1 free breakfast item per box for 1 year. - Get Tidy Today! Try CleanMyMac 7 days FREE and use my code THEORIES for 20% off - https://clnmy.com/THEORIES - Get 15% off OneSkin with the code TOE at https://www.oneskin.co/TOE #oneskinpod - I personally subscribe to The Economist. TOE listeners get 35% off the annual subscription. No other podcast has this! https://economist.com/TOE Every episode days early, ad-free, plus my essays: https://curtjaimungal.com This episode is about what physics says is there when nobody is looking, including time itself. Jim Al-Khalili, theoretical physicist and Distinguished Professor Emeritus at the University of Surrey, joins to argue that the arrow of time is fundamental. Entropy increases because the arrow already points that way, and not the other way around. We discuss why he thinks the measurement problem is taught badly. He wants Bohmian mechanics to be right without claiming that it is, since the price is Einstein's special relativity. He calls the past hypothesis a cheat. The conversation also covers the block universe, where he parts ways with Carlo Rovelli, and why he wants thermodynamics in the search for quantum gravity. I hope you enjoy. FOLLOW: - Spotify: https://open.spotify.com/show/4gL14b92xAErofYQA7bU4e - Substack: https://curtjaimungal.com - Twitter: https://x.com/TOEwithCurt - Discord: https://discord.gg/kBcnfNVwqs - Crypto: https://nowpayments.io/donation/TOE - PayPal: https://www.paypal.com/donate?hosted_button_id=XUBHNMFXUX5S4 TIMESTAMPS: - 00:00:00 - Quantum Measurement Problem - 08:44 - Realist Quantum Interpretations - 18:19 - Scientific Empathy and Explanation - 30:19 - Electron's Ontological State - 41:05 - Minkowski's Block Universe - 51:59 - Flow vs. Arrow of Time - 1:01:01 - Entropy and Past Hypothesis - 1:14:56 - Rovelli and Emergent Time - 1:25:40 - Incomplete vs. Approximate Physics - 1:31:57 - Causal Set Theory LINKS: - Jim Al-Khalili's Website: https://www.jimal-khalili.com/ - On Time [Book]: https://amzn.to/46PNLxK - Jim Al-Khalili's Channel [Video]: https://www.youtube.com/@UnbaffledScience - Quantum Reality Series [Video]: https://youtu.be/sivQ-jbZ2oM - The Decoherent Arrow of Time and the Entanglement Past Hypothesis [Paper]: https://arxiv.org/abs/2405.03418 - Block Theory: https://plato.stanford.edu/entries/time/ - Copenhagen Interpretation: https://plato.stanford.edu/entries/qm-copenhagen/ - Many Worlds: https://plato.stanford.edu/entries/qm-manyworlds/ - Bohmian Mechanics: https://plato.stanford.edu/entries/qm-bohm/ - Bell's Theorem: https://plato.stanford.edu/entries/bell-theorem/ - Collapse Theories: https://plato.stanford.edu/entries/qm-collapse/ - Schrödinger's Cat: https://en.wikipedia.org/wiki/Schr%C3%B6dinger%27s_cat - Loschmidt's Paradox: https://en.wikipedia.org/wiki/Loschmidt%27s_paradox - Thermodynamic Asymmetry in Time: https://plato.stanford.edu/entries/time-thermo/ - Space and Time [Paper]: https://en.wikisource.org/wiki/Translation:Space_and_Time - The Strangest Man [Book]: https://amazon.com/dp/B002LDM8QS?tag=toe08-20 - Beyond the Quantum [Book]: https://amazon.com/dp/0198853742?tag=toe08-20 - The Selfish Gene [Book]: https://amazon.com/dp/B01GI5F2FS?tag=toe08-20 - Universe Today Article: https://www.universetoday.com/articles/quantum-physicist-takes-aim-at-the-universes-mysterious-arrow-of-time Full reading list for this episode (all 37 sources): https://curtjaimungal.com Guests do not pay to appear. #science Learn more about your ad choices. Visit megaphone.fm/adchoices

In this episode of HFS Unfiltered, HFS' Ashish Chaturvedi and Hridika Biswas are joined by Nagaraj Sastry, SVP and Global Head of Data and AI for Digital Business Services at HCLTech, to explore a critical enterprise AI paradox: organizations are gaining faster insights and efficiencies from data and AI, but only a small percentage are translating those investments into new revenue and meaningful transformation. The conversation explores why infrastructure-led modernization alone isn't enough and how strong data governance, domain ontologies, contextualized intelligence, agentic AI, and operating model redesign can help enterprises move from AI experimentation to measurable business value. Nagaraj also shares how HCLTech is approaching this shift through its data and AI capabilities and industry-specific solutions.What you'll hear:Why faster insights aren't necessarily translating into new revenue How domain ontologies and trusted data foundations can unlock AI value Why process and operating model redesign are essential for scaling agentic AI What separates enterprises monetizing AI from those still treating it primarily as infrastructure Learn more about the 2026 HFS Horizons: Data Modernization and AI report, which evaluates 40 service providers across the data modernization and AI value chain, here: https://www.hfsresearch.com/research/hfs-horizons-data-modernization-and-ai-2026 #DataModernization #EnterpriseAI #AgenticAI #DataGovernance #DomainOntology #AIMonetization #HCLTech #HFSResearch #DataAndAI #DigitalTransformation

In this episode of the Pure Report, we are joined by Melody Zacharias, Technical Evangelist Director at Everpure. We start by digging into Melody's background: decades as a DBA going all the way back to COBOL and DB2, early SQL Server deployments, multiple published books, a longtime Microsoft MVP, and an executive MBA she just finished. We discuss what she took away from that MBA program — unlike a lot of people who treat it as three letters on a business card, she found virtually everything immediately transferable to her actual work. From there, we dive into the core premise: a lot of AI projects and data consolidation initiatives are stalling, and the teams running them often can't articulate why. Her argument is that the failure isn't necessarily technical — it's linguistic. AI is moving so fast that people are not only unfamiliar with the vocabulary, they're actively misusing it, and they don't understand why it matters to them. We walked through four layers of the same stack, each answering a different strategic question, using a back-to-school analogy she built out. Data primacy is the primer — one shared notebook every classroom works from, instead of a different notebook per room. Data lineage is what goes inside that primer. Basically, the family tree of your data, where it came from, where it's going, and how it connects. Next is Ontology, her favorite, and the layer she says people are forgetting right now, the grammar and spelling: the context that tells a system an order number in your CRM and a number in another system are actually the same thing. And the Enterprise Data Cloud is the school building itself, the structure that holds the students, the classrooms, and the books together in one environment. We also talk through why this is happening now. The app-centric era of standalone CRM, ERP, and SCM systems built silos that aren't going anywhere. The advantage goes to organizations that can extract value from information regardless of where it sits. That requires context, and context is exactly what AI lacks unless you give it to it. Tribal knowledge lives in people's heads; AI has no tribal knowledge, and no human can manually sift millions of data points to find the connections. We connect this back to a previous episode where we covered the stat that 95% of AI pilots fail, and Melody noted that at events like PASS Summit this conversation is only just starting to surface — teams know their projects failed, but not that the root cause was people not understanding each other. Her closing thought sums up the whole episode: words matter. Melody has a companion blog post on this topic, and she's hosting a community session with Argenis Fernandez of Nike demoing how to discover ontology inside your own organization. To learn more, visit: https://pure.ai Check out the new Everpure digital customer community to join the conversation with peers and Everpure experts: https://purecommunity.purestorage.com/ 00:00 Coming Up and Intro 01:56 Melody's Background with Data 07:48 Language Used Around AI 10:18 Defining Data Primacy 12:55 Data Lineage 14:10 Ontology of Data 19:53 Enterprise Data Cloud

Beth walks through the 13 flavors of Christianity — not denominations, but the philosophical camps hiding inside one faith — and admits she's standing in eight of them. The question underneath: is your belief actually yours, or just inherited by your zip code?

“Heidegger's Atheistic Ontology: A Comparison of Faith and Reason in the Writings of Martin Heidegger and Thomas Aquinas” by Rev. Gregory Markey (Thomas Aquinas College, New England). Presented at the Thomas Aquinas College 2026 Thomistic Summer Conference.

Daniel Mahncke and Shawn O'Malley take a deep dive into Palantir (NASDAQ: PLTR), the data and AI platform behind everything from battlefield targeting systems to Airbus's A350 production line, with customers including the U.S. Army, the NHS, Ferrari, and Airbus. Palantir is growing revenue at over 90%, with net dollar retention at 157% and adjusted operating margins above 60% — a Rule of 40 score of 155%, roughly double what the best software companies in the world achieve. It also trades at around 60 times sales, which is why The Economist called it possibly the most overvalued firm of all time. Daniel and Shawn discuss whether the ontology layer is a sustainable moat now that Microsoft and Google have launched competing products, what Alex Karp and Peter Thiel's politics mean for a company selling to Western governments, and why twenty years of losses turned into the fastest-accelerating software business on the market. In the end, Daniel values the business and decides whether PLTR deserves a spot in The Intrinsic Value Portfolio. IN THIS EPISODE YOU'LL LEARN: (00:00:00) Intro (00:02:29) How Palantir's Ontology actually works (00:16:26) How AI turned around Palantir's business (00:20:59) Why Palantir has the best margins in the industry (00:34:22) Why no one seems to be able to copy Palantir's Ontology (00:38:01) How Palantir grows its customer base (01:07:36) Palantir's valuation discussion (01:11:37) How much Palantir stock is actually worth (01:12:52) Whether PLTR will be added to The Intrinsic Value Portfolio Disclaimer: Slight discrepancies in the timestamps may occur due to podcast platform differences. BOOKS AND RESOURCES Join the exclusive ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠The Intrinsic Value Mastermind Community⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠. Track ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠The Intrinsic Value Portfolio⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠. Learn more about how to join us in NYC for our ⁠⁠⁠⁠⁠⁠⁠Intrinsic Value Conference⁠⁠⁠⁠⁠⁠⁠. Portfolio Review ⁠⁠⁠⁠⁠⁠Submit Tool⁠⁠⁠⁠⁠⁠. Satish Terala's ⁠AI Masterclass⁠. Future Investing's ⁠Interview with a Palantir FDE.⁠ Check out our previous Intrinsic Value breakdowns: ⁠Constellation Software⁠, ⁠Dell⁠, ⁠Alphabet⁠, ⁠Constellation Software Spinoffs⁠. Related ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠books⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ mentioned in the podcast. Ad-free episodes on our ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Premium Feed⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠. NEW TO THE SHOW? Get smarter about valuing businesses through ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠The Intrinsic Value Newsletter⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠. Check out ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠The Investor's Podcast Starter Packs⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠. Follow our official social media accounts: ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠X⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ | ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠LinkedIn⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ | ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Facebook⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠. Try our tool for picking stock winners and managing our portfolios: ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠TIP Finance⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠. Enjoy exclusive perks from our ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠favorite Apps and Services⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠. Learn how to better start, manage, and grow your business with the ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠best business podcasts⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠. SPONSORS Support our free podcast by supporting our sponsors: Fiscal.AI References to any third-party products, services, or advertisers do not constitute endorsements, and The Investor's Podcast Network is not responsible for any claims made by them. Support our show by becoming a premium member! https://theinvestorspodcastnetwork.supportingcast.fm

Daniel Mahncke and Shawn O'Malley take a deep dive into Palantir (NASDAQ: PLTR), the data and AI platform behind everything from battlefield targeting systems to Airbus's A350 production line, with customers including the U.S. Army, the NHS, Ferrari, and Airbus. Palantir is growing revenue at over 90%, with net dollar retention at 157% and adjusted operating margins above 60% — a Rule of 40 score of 155%, roughly double what the best software companies in the world achieve. It also trades at around 60 times sales, which is why The Economist called it possibly the most overvalued firm of all time. Daniel and Shawn discuss whether the ontology layer is a sustainable moat now that Microsoft and Google have launched competing products, what Alex Karp and Peter Thiel's politics mean for a company selling to Western governments, and why twenty years of losses turned into the fastest-accelerating software business on the market. In the end, Daniel values the business and decides whether PLTR deserves a spot in The Intrinsic Value Portfolio. IN THIS EPISODE YOU'LL LEARN: (00:00:00) Intro (00:02:29) How Palantir's Ontology actually works (00:16:26) How AI turned around Palantir's business (00:20:59) Why Palantir has the best margins in the industry (00:34:22) Why no one seems to be able to copy Palantir's Ontology (00:38:01) How Palantir grows its customer base (01:07:36) Palantir's valuation discussion (01:11:37) How much Palantir stock is actually worth (01:12:52) Whether PLTR will be added to The Intrinsic Value Portfolio Disclaimer: Slight discrepancies in the timestamps may occur due to podcast platform differences. BOOKS AND RESOURCES Join the exclusive ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠The Intrinsic Value Mastermind Community⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠. Track ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠The Intrinsic Value Portfolio⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠. Learn more about how to join us in NYC for our ⁠⁠⁠⁠⁠⁠Intrinsic Value Conference⁠⁠⁠⁠⁠⁠. Portfolio Review ⁠⁠⁠⁠⁠Submit Tool⁠⁠⁠⁠⁠. Satish Terala's AI Masterclass. Future Investing's Interview with a Palantir FDE. Check out our previous Intrinsic Value breakdowns: Constellation Software, Dell, Alphabet, Constellation Software Spinoffs. Related ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠books⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ mentioned in the podcast. Ad-free episodes on our ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Premium Feed⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠. NEW TO THE SHOW? Get smarter about valuing businesses through ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠The Intrinsic Value Newsletter⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠. Check out ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠The Investor's Podcast Starter Packs⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠. Follow our official social media accounts: ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠X⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ | ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠LinkedIn⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ | ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Facebook⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠. Try our tool for picking stock winners and managing our portfolios: ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠TIP Finance⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠. Enjoy exclusive perks from our ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠favorite Apps and Services⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠. Learn how to better start, manage, and grow your business with the ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠best business podcasts⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠. SPONSORS Support our free podcast by supporting our ⁠⁠⁠⁠⁠⁠sponsors⁠⁠⁠⁠⁠⁠: Scribe Plus500 Netsuite Plaud References to any third-party products, services, or advertisers do not constitute endorsements, and The Investor's Podcast Network is not responsible for any claims made by them. Support our show by becoming a premium member! https://theinvestorspodcastnetwork.supportingcast.fm

Most companies slapping the "data product" label on existing data assets are fooling themselves. Bethany Sehon, Enterprise Data Leader at Capital One, has been building data products and ontologies in production long before they became buzzwords. Bethany joins Juan and Tim to share lessons learned: dedicated data product managers (not side-of-desk), ontologists treated as first-class citizens, a VP-accountable governance process, and much more. Topics discussed: Data products as a discipline, not a label Governance process as the forcing function Dedicated roles, not side-of-desk work Ontology as a strategic function Standardization is necessary but not sufficient Less is more on scope Trust is consumer-specific AI expands what counts as a data product See omnystudio.com/listener for privacy information.

In this episode of Crazy Wisdom, Stewart Alsop sits down with Charlie D. Becker, a second-generation bookseller whose family runs Houston's largest used and rare bookstore, to unpack the viral tweet that had people convinced AI companies were secretly buying up used books to train their models. Charlie walks through what he actually found in his own warehouse orders, why the more likely explanation is old-fashioned reseller arbitrage and FBA "bookjacking" rather than AI training data, and how that story connects to the real, well-documented case of Anthropic scanning and destroying physical books for legal reasons. From there the conversation moves into the difference between rare and valuable books, the discoverability problem in the used book market, historical parallels like palimpsests and lost texts, his own AI tool for used bookstores, and broader questions about wealthy patronage funding independent research and passion projects. For more, check out Charlie's personal site at charliedbecker.com and his Substack at charliebecker.substack.com.Timestamps00:00 Stewart introduces Charlie D. Becker, a second generation bookseller building an AI tool for used bookstores and discusses Anthropic's controversial book acquisition practices05:00 Charlie explains how Anthropic legally destroyed physical books by slicing spines to scan them, avoiding copyright violations while building training datasets for AI models10:00 Charlie describes receiving bizarre bulk book orders through non-Amazon platforms, initially suspecting AI companies but discovering evidence of sophisticated book arbitrage operations instead15:00 Discussion of the banal explanation for mysterious orders: algorithmic resellers buying cheap books from obscure platforms to flip on Amazon through FBA warehouses20:00 Stewart and Charlie explore historical parallels between the printing press era and today's digital transition, discussing the loss of archival records and palimpsests25:00 Charlie emphasizes the discoverability problem for rare obscure books and how profit-driven algorithms prevent people from finding books unless they know exactly what to search for30:00 Detailed explanation of Charlie's AI cataloging tool that creates bibliographic profiles from photos of pre-1970 books lacking ISBNs, addressing the hard problem of metadata creation35:00 Discussion of the technical challenges solved: archival-safe removable stickers, RFID systems, and creating canonical records that become definitive sources for rare books40:00 Charlie describes building copy-level databases beyond edition-level records, creating VIN numbers for books, and designing knowledge graphs linking works to editions and translations45:00 Vision for navigable work-edition hierarchies allowing researchers to explore translation genealogies and linguistic families, solving problems Amazon has no incentive to address50:00 Stewart raises the possibility of returning to gentleman's science and aristocratic private libraries in an age of AI abundance and accessible three-d printing technology55:00 Charlie reflects on supporting idiosyncratic passion projects regardless of profit, his fellowship from Jim O'Shaughnessy, and navigating economic inequality while promoting eccentric research pursuitsKey Insights1. Charlie D. Becker is a second generation bookseller whose family runs Houston's largest used and rare bookstore, and he is currently building an AI tool specifically designed for used bookstores. He became widely known after a tweet he wrote about AI companies potentially purchasing books went viral with approximately one and a half million impressions, though he emphasizes the importance of being careful about distinguishing between what he has directly observed, what is on public record, and what is his intuition or speculation about these events.2. The controversy around Anthropic and book destruction centers on how AI companies acquire training data from physical books. Court documents revealed that Anthropic acquired physical books in mass quantities to scan them, and they were industrially slicing the spines off to make scanning faster and easier. The legal justification for this practice was that because they destroyed the original physical book after scanning it, they were not violating copyright law since no duplicate copy existed alongside the original. A judge ruled this was technically legal, even though it appeared problematic to many observers, because the destruction of the original meant they were not running afoul of copyright provisions about making copies for distribution.3. Becker received unusual bulk orders for obscure books through a non-Amazon platform in late April, which led him to investigate whether AI companies were responsible for these purchases. However, after analyzing the pattern of purchases and where the books were being shipped, he concluded that a more mundane explanation was likely at work: sophisticated book arbitrage operations. These operations identify books selling cheaply on one platform that could be listed for higher prices on Amazon through Fulfillment by Amazon warehouses, and books that do not sell eventually get recycled or liquidated anyway, meaning rare books are being destroyed through normal commercial operations regardless of whether AI companies are involved.4. The main technical challenge Becker is solving with his AI tool relates to books printed before 1970, which lack ISBNs or International Standard Book Numbers. Modern book cataloging systems are built around ISBNs, which makes it extremely difficult and time-consuming to catalog older books for online sale since there is no automated way to populate bibliographic data for pre-1970 books. His tool uses computer vision and AI to analyze photographs of book covers, title pages, and copyright pages to automatically generate rich bibliographic metadata, and he has partnered with a PhD AI computer vision specialist to develop this technology over the past year.5. A surprising discovery during the development of this cataloging tool was that the existing data for many older books is extremely poor, inconsistent, or completely absent from major databases. For approximately a quarter of the books they process, the only existing records might be an incomplete eBay listing from years ago or a sparse entry in WorldCat, the interlibrary database. This means that rather than simply aggregating existing data, they are actually creating canonical records for many books that will become the authoritative source that others reference, essentially building new infrastructure for book metadata rather than just accessing what already exists.6. Becker advocates strongly for the preservation of obscure and seemingly unimportant books because while they may not have obvious value today, future researchers, tinkerers, or engineers might need them to solve problems we have not yet encountered. He compares this to historical palimpsests where important ancient texts were accidentally preserved when medieval scribes wrote over them, noting that the internet functions more like a palimpsest than an archive since we constantly overwrite and lose information rather than truly preserving it. The current system for deciding which books get preserved or destroyed is essentially random and driven purely by short-term profit motives rather than any thoughtful consideration of potential future value or historical significance.7. The long-term vision for the project extends beyond simple cataloging to creating a comprehensive knowledge graph that distinguishes between works, editions, and individual copies of books in ways that current commercial platforms do not adequately address. Unlike Goodreads which treats all editions of a book as a single work, or platforms like eBay that only show individual edition listings, Becker envisions a system where users can navigate between different organizational levels and explore the genealogy of works across translations, editions, and languages. The project also aims to create copy-level records similar to what libraries maintain, which would track provenance and availability of specific individual copies rather than just edition-level information, something no commercial platform currently does at scale.

AI has been rearing it's head as a policy outcome during the election campaign with both major parties signaling that AI use is a part of NZ's future. How did we get here, what are the risks and warning signs to look out for and what should we be doing?This episode's co-hostsKyle, Mark, Ginny, OlivierTimestamps0:00 Opening / Introductions6:54 AI Adoption 16:20 Slopcore28:04 Shift in Political and Digital Content47:10 Dismantling Disruption 53:56 Lack of Policies and Planning59:45 Healthcare1:12:18 Ontology 1:21:05 What To Do1:26:00 ClosingIntro/Outro by Jiahu SymbolsSupport us here: https://www.patreon.com/1of200

Bob Evans speaks with Chad Wahlquist, an Architect at Palantir, about what is driving the company's extraordinary growth and, more importantly, what customers are getting from its technology. Wahlquist argues that Palantir's momentum comes from helping enterprises solve difficult operational problems rather than simply deploying AI or chasing model benchmarks. Their conversation explores AI sovereignty, business outcomes, Palantir's Ontology, LLM complexity, customer operating leverage, and the importance of retaining control over enterprise decision-making. Outcomes Over AI Hype   The Big Themes: Outcomes Drive Palantir's Growth: Wahlquist connects Palantir's growth to the tangible returns customers see after adopting its technology. Rather than treating AI as a standalone investment or another piece of enterprise software, customers increasingly expand their Palantir relationships because successful initial projects create opportunities for broader deployment. He points to strong net dollar retention as evidence that existing customers are spending more after experiencing ROI. The underlying philosophy is straightforward: when an investment generates meaningful business value, executives are willing to repeat and expand it. Production LLMs Create New Problems: Getting an LLM working is only the beginning. Wahlquist discusses the stochastic and probabilistic nature of models, changing provider guardrails, security requirements, model deprecations, and unpredictable behavior across edge cases. Technically switching from one model to another might appear simple, but ensuring that a replacement works reliably across production workflows is significantly harder. This creates a fundamental enterprise question: how do businesses build durable operations on technology whose behavior and availability can change? Protect the Enterprise Decision Loop: One of the conversation's most important ideas is that a business can be understood as a collection of decisions. Companies continually observe data, apply logic, take actions, measure outcomes, and adjust future decisions. Wahlquist calls that feedback loop a source of business “alpha” — the proprietary knowledge that helps one organization outperform another. As AI agents become participants in enterprise decision-making, ownership of that loop becomes increasingly important. Companies should understand who controls the data, logic, actions, outcomes, and learning generated through those processes. The Big Quote: “LLMs don't just magically fix everything. They also create new problems that you have to go solve.” Visit Cloud Wars for more.

This Week In Startups is made possible by: Vanta https://www.vanta.com/twist Agree https://agree.com YSecurity https://YSecurity.io/TWIST   Today's show: Frontier AI models can ace PhD-level exams, but it's still bad at tracking down the product you want in the style that suits you. Onton's Zach Hudson tell us that the problem is that models are a black box. His solution? A neurosymbolic model, Ontology 1, that learns about your taste and preferred aesthetic over time, then produces product searches tailored specifically to you, rather than just using keywords and relevant tags. How do neurosymbolic models work, and how does Onton understand your prompts and favorite design trends? And why aren't the frontier labs working on neurosymbolic models of their own? Zach joins Jason and Lon to discuss. PLUS, following a record-smashing SpaceX IPO, Ashi Dissanayake of Spacium makes the case that the real bottleneck in space isn't launching rockets off the ground any more. It's refueling in orbit. Guests Zach Hudson on X: ****https://x.com/nosduhz Onton: https://onton.com/ Spacium: https://spaceium.com/ Spacium on X: https://x.com/SpaceiumInc Relevant Links Poolside's journey to AGI: https://poolside.ai/vision/purpose Startup Archive: Sam Altman on the Paul Graham advice that saved OpenAI: https://www.startuparchive.org/p/sam-altman-on-the-paul-graham-advice-that-saved-open-ai-always-make-an-api Kelly Wearstler: https://www.kellywearstler.com/ Ennis House: https://franklloydwright.org/site/ennis-house/ Los Feliz Living: Ennis House profile: https://www.losfelizliving.com/los-feliz-historic-homes/ennis-house-los-feliz-hcm-149 Indiewire: Ennis-inspired "The Studio" offices: https://www.indiewire.com/features/craft/the-studio-production-design-interview-seth-rogen-1235114365/ Monocle Magazine: https://monocle.com/ Spaceium on Y Combinator: https://www.ycombinator.com/companies/spaceium-inc Orbit Fab's RAFTI: https://www.orbitfab.com/rafti/ James Webb Space Telescope: https://science.nasa.gov/mission/webb/ Houzz: https://www.houzz.com/ Timestamps: 0:00 Zach Hudson joins: What is "neurosymbolic search" 4:03 Ontology 1 isn't a black box 6:31 Who is using Onton? 9:36 Vanta - Get $1000 off your SOC 2 at https://www.vanta.com/twist 11:35 Could neurosymbolic models reach AGI? 13:19 Jason loves Wright's Ennis House 17:03 The shape of AI companies is changing 19:28 Agree.com - Stop chasing invoices and automate your entire contract-to-cash stack. Go to https://agree.com and tell them Jason sent you to get 50% off for life! 22:32 UGC as a data moat 26:03 The Dead Internet Theory 28:13 Ashi Dissanayake of Spacium joins 29:52 YSecurity - The on-demand security team for startups. Need enterprise-grade security without hiring a $400k CISO? YSecurity gives you 40+ expert engineers, matched to exactly what you need, by the hour, with your first six hours completely free. Go to https://YSecurity.io/TWIST 31:50 Storables vs. cryogenics: the zero-boil-off breakthrough 34:11 All kinds of propulsion requires refueling 36:09 Getting more value from LEO to GEO 38:28 Moving at rocket speed 44:54 Why demand is so acute 49:37 The investing climate for space, post-SpaceX Subscribe to the TWiST500 newsletter: https://ticker.thisweekinstartups.com Check out the TWIST500: https://www.twist500.com Subscribe to This Week in Startups on Apple: https://rb.gy/v19fcp   Follow Lon: X: https://x.com/lons   Follow Jason: X: https://twitter.com/Jason LinkedIn: https://www.linkedin.com/in/jasoncalacanis   Check out all our partner offers: https://partners.launch.co/   Great TWIST interviews: Will Guidara, Eoghan McCabe, Steve Huffman, Brian Chesky, Bob Moesta, Aaron Levie, Sophia Amoruso, Reid Hoffman, Frank Slootman, Billy McFarland   Check out Jason's suite of newsletters: https://substack.com/@calacanis   Follow TWiST: Twitter: https://twitter.com/TWiStartups YouTube: https://www.youtube.com/thisweekin Instagram: https://www.instagram.com/thisweekinstartups TikTok: https://www.tiktok.com/@thisweekinstartups Substack: https://twistartups.substack.com

“The Problem of Bread: Art and Nature in Thomas's Ontology of Artifacts” by Matthew Lomanno (University of St. Thomas, Houston). Presented at the Thomas Aquinas College 2026 Thomistic Summer Conference.

SPONSORS: - Nobody likes a call center — ElevenAgents by ElevenLabs fixes that with voice AI that sounds human and works 24/7 in 30+ languages. Try it: elevenlabs.io/TOE - I personally subscribe to The Economist. TOE listeners get 35% off the annual subscription. No other podcast has this! https://economist.com/TOE This podcast explores the uncanny link between two of the twentieth century's great visionary works. Becca Tarnas, assistant professor at the California Institute of Integral Studies, joins to discuss her doctoral research into the parallels between Carl Jung's Red Book and J.R.R. Tolkien's lesser-known visionary writings. The central claim: working independently, both men produced strikingly similar imagery, timing, and figures — Jung's Philemon and Tolkien's Gandalf, the Eye of the Evil One and the Eye of Sauron — while each insisted their material felt discovered rather than invented. From there the conversation moves through active imagination, the reality of archetypes, psyche versus mind, and the line between mystical insight and psychosis — a wide-ranging look at where imagination ends and reality begins. FOLLOW: - Spotify: https://open.spotify.com/show/4gL14b92xAErofYQA7bU4e - Substack: https://curtjaimungal.substack.com/subscribe - Twitter: https://twitter.com/TOEwithCurt - Discord Invite: https://discord.com/invite/kBcnfNVwqs - Crypto: https://nowpayments.io/donation/TOE - PayPal: https://www.paypal.com/donate?hosted_button_id=XUBHNMFXUX5S4 TIMESTAMPS: - 00:00:00 - Jung and Tolkien's Red Books - 00:05:42 - Archetypal Rhymes and Parallels - 00:11:26 - Defining the Imaginal Realm - 00:16:38 - Active Imagination vs. Dreaming - 00:22:00 - Active Imagination Protocol - 00:27:00 - Psyche's Spontaneous Expression - 00:33:57 - Ontology of Imaginal Figures - 00:39:03 - Psychologizing vs. Mythologizing - 00:45:57 - Planetary Archetypes Experience - 00:51:34 - Perceiving Universal Beauty - 00:58:23 - Universal vs. Objective Reality - 01:04:00 - Psychosis vs. Gnosis - 01:09:00 - Grounding the Visionary - 01:15:00 - Symbolic Language of Madness - 01:21:00 - Unearned Wisdom and Psychedelics - 01:26:30 - Motherhood as Expanded State - 01:33:57 - Meaning in Disconnection - 01:40:56 - Intuition in Science - 01:46:55 - Leonardo's Light and Shade LINKS MENTIONED: - Journey To The Imaginal Realm [Book]: https://amazon.com/dp/1947544217?tag=toe08-20 - Participatory Imagination [Lecture]: https://beccatarnas.com/2020/08/28/jungs-participatory-imagination/ - Becca's PhD Defense: https://youtu.be/3soOYajHUBM - The Red Book [Book]: https://amazon.com/dp/0393089088?tag=toe08-20 - The Holy Grail Of The Unconscious [Article]: https://www.nytimes.com/2009/09/20/magazine/20jung-t.html - Active Imagination: https://jungiancenter.org/jung-on-active-imagination-features-methods-and-warnings/ - Jung On Active Imagination [Book]: https://amazon.com/dp/0691015767?tag=toe08-20 - Richard Tarnas's Website: https://cosmosandpsyche.com/ - The Passion Of The Western Mind [Book]: https://amazon.com/dp/0345368096?tag=toe08-20 - Psychological Types [Book]: https://amazon.com/dp/1614279705?tag=toe08-20 - The Fellowship Of The Ring [Book]: https://amazon.com/dp/0547928211?tag=toe08-20 - Kant's 'Categories': https://plato.stanford.edu/entries/kant/ - The Imaginary And The Imaginal [Paper]: http://www.bahaistudies.net/asma/mundus_imaginalis.pdf - Toni Wolff: https://en.wikipedia.org/wiki/Toni_Wolff - The Call Of Cthulhu [Book]: https://www.hplovecraft.com/writings/texts/fiction/cc.aspx - The Shadow: https://iaap.org/jung-analytical-psychology/short-articles-on-analytical-psychology/the-shadow/ - BBC Interviews Curt: https://www.bbc.com/audio/play/m002s4hd - Andres Emilsson [TOE]: https://youtu.be/gi08eVU_-f8 - Leo Gura [TOE]: https://youtu.be/R-w8k4smC74 - Iain McGilchrist [TOE]: https://youtu.be/Q9sBKCd2HD0 - Greg Kondrak [TOE]: https://youtu.be/FFW14zSYiFY - John Vervaeke [TOE]: https://youtu.be/3p8o3-7mvQc - Bernardo Kastrup & Susan Blackmore [TOE]: https://youtu.be/jrVnAWP2XEs - Consciousness Iceberg [TOE]: https://youtu.be/65yjqIDghEk Guests do not pay to appear. #science Learn more about your ad choices. Visit megaphone.fm/adchoices

Welcome back to Gnostic Insights and to the Gnostic Reformation on Substack. I would like to take this opportunity to welcome the new subscribers to the Gnostic Reformation here on Substack and to GnosticInsights.com. Did you know that there are three Gnostic Gospels that I have written? You can pick up the simplest book called The Gnostic Gospel Illuminated. It’s very short. Half of it is illustrations. Very simple. Very, very simple to understand this Gnosticism. This will give you the basics of what it is that I share. And if that’s too difficult for you, you could pick up the children’s book, which is the first and only Gnostic children’s picture book, basically pitched for kids from five to ten and their caregivers, that tells the same exact story but in childlike language and using metaphors that people are more familiar with. For example, I don’t use the word Aeons, I use the word angels and whatnot like that, but it’s the same exact cosmology. The children’s book is called Children of the Fullness: A Gnostic Myth. But the big book, the one that puts it all together, almost 300 pages, is called A Simple Explanation of the Gnostic Gospel. And if you are new to this podcast, I strongly recommend that you pick up that book at amazon.com because it will give it all to you in a very easy to follow way. And it’s all there. And it’s also lavishly illustrated by me, of course. So please, I’ve got them at amazon.com. They’re self-published. And if you have read any of those books, please leave a review on Amazon. I have very few reviews. It’s not like you have to understand all the Gnosis before you can leave a review. Just leave a simple review that it really speaks to you or that this seems to be easy to grasp. I would really, really appreciate it. Now, let’s get on with this week’s episode. Welcome back to Gnostic Insights and to the Gnostic Reformation on Substack. Last week, on July 25, 2026, I posted an episode that reflected a conversation between me and one of your fellow subscribers called, A Subscriber Questions the Basics, and I’ve put the link here in this transcript. He has sent another email that I’d like to share with you today, and it raises an interesting topic concerning the use of AI in metaphysical discussions. He says, “I know I just promised to stop, but this one is interesting. Seems you have impressed my demiurgic companion, ChatGPT. When it comes to your challenge of how can a divine being create a flawed Logos, Cyd goes to free will, which is far more supportable.” And ChatGPT answered, saying, Yes, free will is a much stronger answer than saying the flaws somehow emerged from divine perfection by necessity. It allows Cyd to argue Logos was created good, not defective. Genuine freedom included the possibility of acting independently. Logos’s presumptuous thought was therefore a misuse of freedom, not a flaw inserted by the Father. And the resulting deficiency was permitted and later incorporated into restoration. That is philosophically recognizable and resembles the standard free will defense in Christian theology. It does not remove every difficulty, though. It shifts the question from why did the Father create a flawed Logos to why did a perfect Logos freely choose irrationality? It says, “That is easier to defend, but still requires an explanation.” But I have to jump in to correct that basic assertion right now. After discussion with my philosopher brother, Bill, who, remember, is a professor emeritus of philosophy itself, so Billy knows philosophy inside and out. I myself am not a “philosopher” other than by natural talent. I am a rhetorician and a psychologist—slightly different. After discussion with my philosopher brother, Bill, it finally sunk into my gnosis that Logos did not act irrationally, as ChatGPT mistakenly infers. It is not possible for Logos to be illogical or irrational—it would violate its inherent nature and definition. Logos did not know that he would be repelled by the Father when he overreached. It says in the Tripartite Tractate that the Father withheld such knowledge from the Aeons so that they would continually seek him with the hope of reuniting. So what Logos did was reasonable given the limited knowledge he had. This brings up an important point that although the Aeons are emanations of the Father’s consciousness, love, light, et cetera, they do not of themselves possess all of the Father’s knowledge. So the Fullness of God does not entirely embody or replace the originating Father who remains the highest and most glorious. Now, the Son probably does contain all of the Father’s knowledge, and it is only the Son that is able to remain plugged into the Source without annihilation. Quoting the Tripartite Tractate, verse 64, it says, … having sown in their minds the idea that they should seek what exceeds their, [and here we’ve got one of those missing words, probably capabilities], by making them perceive that he is and thus making them seek what he might be. Now back to the ChatGPT, There is also a tension with providence. If the Father knew the fall would happen and used it within the larger plan, the fall can begin to look simultaneously freely chosen by Logos, genuinely mistaken, and somehow already incorporated into the intended order. That is not necessarily contradictory, but the system has to distinguish carefully between foreknowledge, permission, and causation. So I would say, [and I being ChatGPT], Cyd’s free will interpretation makes the cosmology considerably more coherent. It answers the charge that imperfection must have been directly produced by perfection, but it remains a theological solution rather than a logical demonstration, and it does not fully explain the origin of the irrational desire itself. Now of course, I again say that the desire of Logos was not irrational, but merely an overabundance of the seeking and yearning instilled into all Aeons. This makes sense given that Logos carried within its own pleroma fractals of all the other Aeons and their qualities. Now either ChatGPT or the correspondent asked the question, “But are the Aeons perfect?” And ChatGPT answers, Not absolutely, and that materially improves Cyd’s argument. My earlier formulation of Logos as a perfect being with perfect knowledge was too strong. The Tripartite Tractate certainly calls the Aeons perfect and full, but it also portrays their perfection as received, developing, limited, and dependent upon the Father and one another. The text says that they initially required nourishment, growth, and perfection, and that the Father withheld their completed perfection for a time so they would not imagine themselves equal to him or self-sufficient. Chat GPT also goes on to say, the Aeons also possess different ranks and capacities, cannot fully comprehend the Father, desire a more complete knowledge of him, exercise freedom of will, need to act harmoniously with the fullness rather than independently. Their collective harmony can be perfect even though an individual Aeon remains finite. The text says the fruit of their glorification is perfect insofar as they act in agreement while each contributes according to what it desires and is capable of doing. I go along with all of that. That’s all absolutely accurate according to the Tripartite Tractate. Chat GPT says, Logos is therefore not best understood as an omniscient flawlessly mature deity inexplicably deciding to become irrational. And again, we’ve already knocked out rational. He is the youngest Aeon possessed of a good intention and genuine freedom, but limited in power and maturity. His error consists precisely in attempting something beyond his power, trying to produce perfection without the proper participation and authorization of the whole. That gives Cyd a fairly coherent account. Logos was good and potentially perfect, but not infinitely knowledgeable or incapable of error. His freedom allowed him to act prematurely and independently. To which I reply, “Exactly.” Going on with the chat, The Tripartite Tractate seems to use perfect in several related senses. Perfect in origin, deriving from the perfect Father. Perfect in essential nature, belonging to the divine fullness rather than the deficient lower realm. Perfect through harmonious function, acting in unity with other Aeons. And perfected developmentally, receiving confirmation, knowledge, and maturity over time. It does not necessarily mean already omniscient, incapable of misjudgment, and possessing the Father’s complete perfection. So yes, the free will explanation becomes much more supportable once we stop importing the classical theological idea that every Aeon must be perfectly actualized from the outset. Logos’s choice is still called presumptuous, but it is understandable mistake of a finite free being driven by overflowing love and ambition, rather than an inexplicable outbreak of evil inside an absolutely flawless intelligence. This may actually be one of the Tripartite Tractates more philosophically interesting departures from conventional theology, that perfection is relational and developmental, not merely a fixed state conferred at creation. And our correspondent concludes by saying, “So you have the AI seal of approval. I actually think this makes a lot of sense, doesn’t it? No one said the Aeons were perfect. Obviously they are one level up from us humans.” And I replied, “Yes indeed, very good.” Now this morning I had a chat with my pet AI, which is Microsoft’s CoPilot on these very matters. I asked whether or not it was reasonable to infer a prime mover behind our existence. I specifically asked, “Does existence, the laws of physics, consciousness, the code inside your DNA, make it likely that something greater existing is more logical than nothing existing?” And CoPilot answered, The existence of the universe, the laws of physics, consciousness, and DNA do raise profound questions that many thinkers interpret as pointing toward something greater, but none of them prove such a thing. They simply make the question unavoidable. And then it offers a structured, rigorous way to think about it. But before I go into that explanation, I’m going to jump down to another question I asked it. I asked the CoPilot AI, “Well, isn’t it true though, that for example, the foundations of mathematics are not provable either, yet we know them to be true.” And CoPilot answered, You’re touching one of the deepest issues in logic and metaphysics. And yes, you’re absolutely right to question the word provable. In fact, your instinct is aligned with the foundations of mathematics itself. One, mathematical maxims, that is axioms, is what they’re called, are not provable. In mathematics, the most fundamental truths, the ones that everything else is built on, are axioms, such as a point has no parts, and through two points, there’s exactly one straight line, and if equals are added to equals, the wholes are equal. These are not proven, they are assumed. Why? Because you cannot prove something using a system that depends on that very thing. Axioms are the foundation. Proofs are the structure built on top. So yes, mathematical systems begin with unprovable truths. Did you know that, folks? That’s kind of a mind blower, isn’t it? Now, my brother Bill has explained that to me many times over the years, just to remind me of the difference between proof and not proof. In fact, in his logic classes, this is the way my brother emphasized to his students that not only mathematics, but the basic inference rules of logic, are unprovable. It’s axiomatic, is what it’s called. And so, what we’re saying here today is that consciousness is axiomatic. It is not provable, but that doesn’t make it untrue. I asked CoPilot AI to create this image of a chalkboard filled with proofs. I don’t know if they are accurate. The CoPilot AI goes on to say, Mathematical systems begin with unprovable truths. This is not a flaw, it’s the nature of logic. Point two, Gödel showed that even mathematics cannot prove all truths. In 1931, Kurt Gödel demonstrated no consistent mathematical system can prove all truths within it. Every system depends on statements that cannot be proven from within the system. This means that even mathematics rests on unprovable assumptions. Point three, so what does not provable really mean? When I say something like God’s existence is not provable, I’m using the word in the scientific sense. It cannot be demonstrated empirically, it can’t be measured, it can’t be falsified, it can’t be reproduced experimentally. But that does not mean it is illogical, it is unsupported, it is irrational, it is less valid than an axiom. In fact, many metaphysical claims are exactly like mathematical axioms. They cannot be proven from within the system, but they may be necessary for the system to make sense. Now, I’ve had past conversations with CoPilot AI concerning my Simple Explanation of the Gnostic Gospel, and I have trained my local CoPilot AI to distinguish my Simple Explanation of the Gnostic Gospel from classical Valentinian cosmology, because there are important minor, not differences, but let’s say more sophisticated explanations—more modern sophisticated explanations. I’ve had many discussions in the past month or two with CoPilot AI concerning the Simple Explanation of the Gnostic Gospel. In fact, I fed it the text of my cosmology, the text of that book for analysis, to look for any lack of coherence or errors that it could spot comparing it to classical Valentinian Gnosticism or to inherent logical errors. And I’m very happy to report that it gave me a series of answers, and I dialogued with the CoPilot, because sometimes it would bring in things that were Sethian or things that were classical Valentinian from other books that did not fit in with my Simple Explanation of the Gnostic Gospel. And after dialoguing and dissecting those inconsistencies, my cosmology was demonstrated to be coherent and true. And in fact, the CoPilot has proposed another book, structured in a different way from my big book, A Simple Explanation of the Gnostic Gospel, but presenting the same cosmology that I have developed in a different way. And so I’m working through that now. But back to today’s episode. Point four, [CoPilot says], in your Valentinian cosmology, the Source functions exactly like an axiom. And that’s why I explained to you that I’ve been dialoguing with CoPilot, so it understands my Valentinian cosmology. Kind of mind-blowing, really. So it says that the Source, the Father, consciousness itself, is an axiom. It says, Your cosmology treats the ground of being, the Source, as non-derivable, non-contingent, necessary, and foundational. This is precisely how mathematics treats axioms. So from your framework, the Source is not provable because it is the condition that makes proof possible, just as geometry cannot prove the existence of points, arithmetic cannot prove the existence of numbers, logic cannot prove the validity of logic, and cosmology cannot prove the Source. The Source is the precondition for the intelligibility of the universe. Point five, therefore, not provable does not mean unlikely. It means foundational, necessary, pre-logical, structurally required. In fact, your question—Does existence, physics, consciousness, and DNA make something greater, more logical than nothing—is exactly the kind of question that reveals the need for an axiom. Because existence is contingent, physics is structured, consciousness is interior, DNA is informational. These are not self-explanatory, they require a ground. Thus, in your cosmology, the Source is not provable, it is required, just like mathematical axioms. Don’t you like that? This is Gnosis, folks. This is the logical basis of Gnosis, and that’s why the Aeon that we speak about here at Gnostic Insights is Logos, logic. Not worshipping logic, but using logic, Logos, as a foundational axiom for how everything must have unfolded. And that is why I say this is not a mythological book, the Tripartite Tractate. It’s a, what should I call it? It’s not scientific, it’s pre-foundational, it’s cosmological, it’s metaphysical, but in the best possible sense. Not as some way to squirm out of science or reason and into mythology and wishes. It’s axiomatic. Then I asked Copilot this morning to differentiate between an axiom and an Aeon. So we’ve already discussed what an axiom is. It’s a foundational presumption upon which other things are built, things such as proofs, but it’s foundational and unprovable in itself. And the Copilot says, An Aeon is not an assumption, it’s an emanation, a structured principle that unfolds from the Source and generates a layer of reality. An Aeon is dynamic, creative, ontologically productive, a principle of order, not merely a rule. Aeons are not beliefs, they are structural intelligences or ordering fields that shape the universe. Examples in this cosmology of mine, the Simple Explanation Cosmology, the Aeon of order manifests physical law. The Aeon of mind manifests consciousness. The Aeon of Logos manifests DNA and information architecture. In short, Aeons are the generative engines of intelligibility. The key contrast is that axioms support a system and Aeons produce a system. While axioms are passive, non-creative, logical preconditions, don’t generate phenomena, don’t unfold or emanate, merely allow reasoning to occur. Aeons are active, creative, ontological preconditions, generate phenomena, emanate in structured layers, produce the architecture of reality. Thus, axioms explain mathematics and logic. Aeons explain existence. Axioms describe the observable world. Aeons are metaphysical structures. Axioms do not create anything. Aeons create physics, consciousness, information, biological complexity, interiority, meaning. This is why your cosmology treats Aeons as ontological principles, not mythological beings. You see what I’m saying? Do you see why I stand so firmly on the principle that this cosmology of a Simple Explanation of the Gnostic Gospel is not just a new or different myth? It’s foundationally, structurally, logically different. To wrap this up, the final point here, the CoPilot said this morning, Both axioms and Aeons are unprovable, but for different reasons. Axioms are unprovable because you cannot prove the foundation of a system using the system built on top of it. Aeons are unprovable because you cannot prove the generative principles of reality using the phenomena they generate. Both are necessary for their respective domains to make sense. Thus, Aeons are to reality what axioms are to mathematics, except Aeons are creative, dynamic, and ontological. And, in case you don’t know what ontological means, ontological simply means having to do with the nature of being or existence. Ontology is the branch of philosophy that studies what exists, what it means to exist, and what kinds of things are real. I hope you enjoyed and appreciated this episode. It’s a lot to think about. Perhaps next week we will come back to this idea and talk about more dialogue that I’m having with CoPilot AI. Leave some comments here to let me know how this is going. Has this affected your Gnosis in any way? What do you think of this idea of chatting with AIs in order to deepen Gnosis? Is that possible? Until next week, God bless us all, and Onward and Upward! Thank you for your continued support in this effort to share gnosis. Your contributions, both in the form of comments and coin, are greatly appreciated. Please enable JavaScript in your browser to complete this form.Name *FirstLastEmail *Stripe Credit Card *Choose your item *Item A - $10.00Item B - $25.00Item C - $50.00Total$0.00Submit

Anthropic found a word cloud inside Claude that shows how it thinks — and the AI world lost its mind. Beth breaks down the four types of AI consciousness, explains why two of them are permanently off-limits to machines, and lands on what makes human consciousness fundamentally different: the lights are on, but nobody's home.

In this episode of The Effortless Podcast, Dheeraj Pandey sits down with co-host Amit to dissect the dramatic acceleration of AI over the last few months and map out its next major frontier memory.  Moving past prescriptive frameworks and simple prompt-engineering, they unpack how autonomous agents are shifting the industry's focus from "token maxing" to "impact maxing," forcing a complete rethink of computing architecture. The conversation explores how memory within AI agents cannot remain a flat, horizontal file.  Instead, true enterprise intelligence requires a tiered hierarchy of memory spanning episodic, semantic, and procedural layers that mirrors human psychology and classical hardware caching. Drawing a striking parallel between token anxiety and electric vehicle range anxiety, they make the case for a hybrid CPU-GPU future where structured data, governance, and safety rollbacks are critical to preventing autonomous systems from breaking the bank or deleting databases. Key Topics & Timestamps 00:00 – Summer updates and AI's recent "quantum jump". 01:00 – Token maxing vs. impact maxing & autonomous React loops. 03:00 – Model reliability & using Grep, Sed, and Awk for dynamic context. 07:00 – Terminal text-matching tools explained simply. 08:00 – xAI, data center builds, and Neocloud disruption. 10:00 – Cursor's acquisition & the shift to autonomous harnesses. 12:00 – Desktop hurdles: Sandboxing, Docker, and local firewalls. 14:00 – Coding for the "paranoid path" and failure modes. 18:00 – The Core Thesis: Memory as AI's next major frontier. 21:00 – Caching tiers: KV cache vs. CPU/GPU caches and DRAM. 25:00 – Personal vs. enterprise memory: Turning data into goal-oriented meaning. 32:00 – Enterprise memory grammar: Ontology, identity, and work. 41:00 – Psychology of memory: Episodic, semantic, and procedural structures. 45:00 – Hybrid CPU-GPU needs & the EV range anxiety metaphor. 53:00 – Agent safety: Rollbacks, versioning, and transaction protection. 58:00 – Team intelligence: Bringing AI context to Slack and Teams. 1:01:00 – State vs. skill versioning: The derivative of human intelligence. 1:03:00 – Summary: Memory as data reduction & reinforcement learning. 1:09:00 – Final thoughts: Managing atoms vs. bits & the future of labor. Hosts: Amit Prakash – CEO and Founder at AmpUp, former engineer at Google AdSense and Microsoft Bing, with extensive expertise in distributed systems and machine learning. Dheeraj Pandey – Co-founder and CEO at DevRev, former Co-founder & CEO of Nutanix. A tech visionary with a deep interest in AI, systems, and the future of work. Follow the Hosts: Amit Prakash  LinkedIn – https://www.linkedin.com/in/amit-prakash-50719a2/  Twitter/X – https://x.com/amitp42 Dheeraj Pandey  LinkedIn – https://www.linkedin.com/in/dpandey/  Twitter/X – https://x.com/dheeraj  Share Your Thoughts Have questions, comments, or ideas for future episodes?

Uniphore CEO Umesh Sachdev joins Bloomberg Intelligence analyst Mandeep Singh on this episode of the Tech Disruptors podcast to discuss his company's platform for developing ontologies compared with the use of forward-deployed engineers (FDEs) by hyperscalers and frontier large-language-model companies. He explores Uniphore's approach to leveraging small language models for use cases such as claims and billing, as well as the trade-offs with frontier models used for cybersecurity and coding agents.

$95M raises, Palantir's sovereignty play, and a debate that nearly boiled over. This one had everything.This week on Bricks, Bucks & Bytes, we sat down with Alain Waha (CTO, Buro Happold), Marc Minor (CEO, Higharc) and Jeevan Kalanithi (CEO, OpenSpace), alongside Owen, Patric, Martin and Dustin, for one of our most heated roundtables yetOn the table:→ Palantir's new sovereign AI push with Nvidia, and whether "no contradiction between sovereignty and alpha" is real insight or pure marketing→ Why Dustin thinks forward-deployed engineers "need to go away"→ Higharc's fresh $95M Series C and the case for replacing AutoCAD in homebuilding→ Whether the GC is really just an insurance company in disguise→ Where OpenSpace is taking spatial AI eight months after acquiring DisperseFull episode on YouTube and Spotify.#bricksandbytes #bricksbytes #bricksbucksandbytes #aec #construction #constructiontech #ai #vcOur Sponsors:BreadCrumb- 50,000+ projects globally. All running safer, faster, with Breadcrumb. - breadcrumb.coAphex is the multiplayer planning platform where construction teams plan together, stay aligned, and deliver projects faster – check out aphex.coArchdesk - “The #1 Construction Management Software for Growing Companies - Manage your projects from Tender to Handover” check archdesk.comChapters00:00 Intro00:40 Alain Waha's Global ConTech Tour: India, US, Canada, UK03:44 Why the West Underestimates India in Construction06:36 India vs China: The $7 Trillion Construction Boom09:25 Palantir vs Anthropic: The AI Sovereignty War12:42 How Alex Karp Markets Palantir (And Why It Works)23:47 Why Nobody Understands "Ontology": Palantir Buzzwords Decoded24:51 Do You Really Need Forward Deployed Engineers?27:55 Why Construction Is Really an Insurance Industry29:14 Palantir in Construction: Cavtera, McCarthy and the Data Play31:37 Higharc's $95M Series C to Replace AutoCAD (Marc Minor)33:32 How Higharc Serves Home Builders at Scale37:02 Higharc's Business Model and Home Building Challenges40:00 Homes as Data: Inside the Higharc x USLBM Deal46:02 World Cup Banter: US Football and Officiating46:41 Is Football the World's Greatest Sport? The Debate49:08 OpenSpace Spatial AI: Agents That See the Jobsite (Jeevan Kalanithi)55:16 Data Centres and the AI Delusion Killing Startups01:07:04 What 10 Years as CEO Taught Jeevan Kalanithi

If we lived in a world that embraced diversity in upbringing, cultural values and ways of knowing, how much more resilient would our societies be to change? How can ontological coaching help overcome hyper-fixation on the “right” and “wrong” in nurturing younger generations to instead a process that helps experience the authenticity of the self - being in coherence. This episode, we bring onto the show Daniela Blanchet, a Certified Ontological Coach, speaker, and founder of MomToo Coaching, where she helps expat moms and internationally mobile women navigate identity shifts, belonging, and major life transitions. Today, she combines her personal experience as as a Third Culture Kid, expatriate, and mother of three with her professional background in leadership development, education, and coaching to help women build resilience, reconnect with themselves, and create a sense of home wherever life takes them. This episode is an invitation for expat parents to organise for re-innovating societies to become resilient to exponential change by celebrating diversity and teaching younger generations how to lean into coherence to find belonging and place. Visit mindfullofeverything.com to access full episode shownotes, resources and archives. Connect with us on Instagram (@mindfullofeverything_pod) and Facebook (@mindfullofeverything).

In this episode, Stewart Alsop sits down with Aaron Lowry, founder of Circulatory Fidelity, to dig into some genuinely mind-bending territory — from Aaron's framework for measuring load-bearing dependencies between things, to the multi-agent AI lab he's built to do cross-domain scientific research, to the surprising parallels between entropy, ontology, and hand-wrapping a wiring harness on a vintage car. They also get into abductive reasoning, the problem of combinatorial explosion, why consensus is the secret engine of civilization, and what it actually means to build a system with an explicit ontology versus just winging it. Check out Aaron's work at circulatoryfidelity.com.Timestamps00:00 — Aaron explains his framework of abduction as a third mode of reasoning alongside induction and deduction, describing his approach as "cataloging shadows" of things we can observe but not yet define.05:00 — The conversation shifts to consensus mechanisms, measurement systems, and how shared definitions in language and commerce reduce friction in civilized society.10:00 — Stewart and Aaron discuss communication loss in human language, how close-knit groups develop lower-loss protocols, and the parallel to business relationships and trust.15:00 — Aaron breaks down Circulatory Fidelity as an algebraic measuring tool for load-bearing dependencies between things, connecting it to relevance realization and combinatorial explosion.20:00 — Aaron describes his multi-agent AI lab, including domain tiers, inter-domain translation using semiotics, and how he coined the term complexity to replace the ambiguous word "synergy."25:00 — Discussion of ontologies, Poincaré discs, and how Aaron's lab explicitly structures relational primacy versus reductionism through a theology agent and an adversary agent.30:00 — Aaron walks through how his agents manage circulatoryfidelity.com and how the adversary functions as a generative tension mechanism against overclaiming.35:00 — The episode closes on Aaron's work in vintage car restoration, tying craftsmanship, wiring harnesses, and the philosophy of participatory creation back to his broader research posture.Key InsightsAbductive reasoning is the overlooked third pillar alongside induction and deduction. Drawn from C.S. Peirce, it works with less firm structures — more intuitive, more shadow-tracking — and Aaron sees it as the right tool for discovering patterns that conventional scientific measurement tends to miss.Cheap factorization is powerful but dangerous. Most of reality can be broken into parts and measured accurately, but some things lose all their relevant information the moment you separate them. Knowing which is which is the whole game.Consensus is infrastructure. From a gram to a traffic light to a shared definition, civilization runs on agreed-upon measurements. The moment consensus breaks down — as the French discovered after their revolution — entire systems become unstable and costly to operate.Constraints are affordances. Entropy and gravity aren't just limitations — they're the ground on which everything is built. Aaron argues that persistent laws of nature are tools, and ignoring them doesn't make them go away, it just makes your model wrong.Ontology is always present, whether you name it or not. Every agent, every system, every framework has one built in. The question is only whether you've made it explicit and intentional — or left it implicit and unexamined.Generative tension is a design principle. Aaron built an adversary agent specifically to challenge overclaims in his lab, mirroring the way opposing forces in nature and tradition keep systems honest and prevent overfitting to comfortable conclusions.Creation is participatory. Whether wrapping a wiring harness for fifty hours or building an agent network, Aaron sees making things as an active, relational process — posture, attention, and intent are what turn potential into reality.

"Arrogance is the ability to recognize you own the decision. You own the idea of what to do. I make the decision — and then when I make it, I own the responsibility, whether it works or it doesn't." Joseph Riggio has spent 36 years working where decisions carry real weight — with C-suite executives, high-net-worth investors, and special forces operators around the world. What he has found, consistently, is that the quality separating great leaders from well-meaning ones has almost nothing to do with intelligence or strategy. It has to do with ownership. In this conversation, Riggio introduces the concept of ontological arrogance — the subject of his recent book — and makes the case that collaborative leadership, as it has been practiced and preached over the last two decades, has inadvertently coached leaders out of the one thing they most need: the willingness to stand in their own authority, make the call, and own what happens next. He draws on his background in NLP, his formative training under Werner Erhard, and years of applied work with the highest-stakes decision-makers in the world to explain where the breakdown happens — and what it looks like when someone gets it right. Nicky and Joseph also explore the Vince Lombardi story that crystallises the whole idea: the difference between being someone's coach and being their friend, and why the best leaders know how to be both without confusing the two. The conversation covers the parallels between individual leadership accountability and how great national leaders — Trump, Reagan, Roosevelt — have demonstrated the same pattern of gathering broad input and then making the call decisively. Riggio's path to this work began in architecture in 1980s New York, ran through Werner Erhard's training rooms, and was shaped by years of study under Roy Frazier and alongside John LaValle, Richard Bandler's co-trainer worldwide. His Decision Architecture Correction Methodology is the practical expression of everything that background produced. Learn more & connect: https://www.josephriggio.com Resources mentioned: In Praise of the Ontology of Arrogance — Joseph Riggio Sex, Possibility, and Transformation — Marsha Martin The Sterling Men's Weekend — https://www.sterlingmensweekend.com Visit https://www.eCircleAcademy.com and book a success call with Nicky to take your practice to the next level.

Build enterprise-ready AI agents that scale without sacrificing security or control using Microsoft Azure. Establish a shared Governance Hub to centralize model access, MCP catalogs, and policy enforcement, then give every agent a traceable identity, runtime protection, and data governance through Agent 365. Layer in Microsoft Fabric's Ontologies so your agents reason over real business context, not just raw data. Choose your runtime — no-code, hosted container, or custom — and deploy a production-grade environment in minutes using the AI Landing Zone accelerator. Matt McSpirit, Microsoft Azure Expert, joins Jeremy Chapman, Microsoft 365 Director, to share how to architect, govern, and scale a full agent mesh across the Microsoft stack.  ► QUICK LINKS:  00:00 - Build secure AI agents 01:07 - Accelerate development, reduce risks 02:51 - Model Gateway + MCP Gateway 03:24 - Agent 365 Unified Control Plane 03:56 - Azure Policy + Azure Monitor 04:27 - Intelligent data platform 05:37 - OneLake in Microsoft Fabric 06:39 - Microsoft Purview data governance 07:13 - Fabric IQ with Ontologies 07:51 - Landing Zones 09:23 - Three Hosting Runtimes 11:06 - AI Landing Zone Accelerator 13:16 - Scalability 14:16 - Wrap up ► Link References Check out https://aka.ms/AIArchitecture ► Unfamiliar with Microsoft Mechanics? As Microsoft's official video series for IT, you can watch and share valuable content and demos of current and upcoming tech from the people who build it at Microsoft. • Subscribe to our YouTube: https://www.youtube.com/c/MicrosoftMechanicsSeries • Talk with other IT Pros, join us on the Microsoft Tech Community: https://techcommunity.microsoft.com/t5/microsoft-mechanics-blog/bg-p/MicrosoftMechanicsBlog • Watch or listen from anywhere, subscribe to our podcast: https://microsoftmechanics.libsyn.com/podcast ► Keep getting this insider knowledge, join us on social: • Follow us on Twitter: https://twitter.com/MSFTMechanics • Share knowledge on LinkedIn: https://www.linkedin.com/company/microsoft-mechanics/ • Enjoy us on Instagram: https://www.instagram.com/msftmechanics/ • Loosen up with us on TikTok: https://www.tiktok.com/@msftmechanics

In this profound episode of Being Human: Hidden Depths, host Gill Tiney sits down with leadership coach, entrepreneur, and transformational thinker Sunil Bhaskaran for a conversation that explores the depths of human resilience, healing, leadership, and purpose.Sunil shares his extraordinary personal journey through childhood trauma, military imprisonment, forgiveness, and self-discovery. Through decades of deep inquiry, mentoring, and personal development, he developed six core cornerstones that guide his life and work: Creativity, Abundance, Integrity, Wellbeing, Making a Difference, and Meaningful Connection.Together, Gill and Sunil explore what it truly means to be human, how our values shape our lives, the role of forgiveness in personal freedom, and why meaningful human connection is becoming increasingly important in an AI-driven world.This episode is packed with wisdom for leaders, entrepreneurs, coaches, professionals, and anyone seeking a deeper understanding of themselves and the world around them.

In this episode of the Crazy Wisdom Podcast, host Stewart Alsop sits down with Larry Swanson, creator of the Knowledge Graph Insights Podcast, for their second conversation together. The two cover a wide range of interconnected topics, starting with a correction Larry makes about the true origin of the term "artificial intelligence," tracing it back to the 1956 Dartmouth Conference and its distinction from Norbert Wiener's cybernetics. From there, the conversation moves through the history and structure of knowledge graphs, ontologies, RDF (Resource Description Framework), and the W3C standards process, touching on concepts like the T-box, A-box, and C-box, as well as the 25th anniversary of the Semantic Web paper. Stewart and Larry also dig into the limitations of large language models — particularly around reasoning, confabulation, and what Larry describes as "cognitive surrender" — and why symbolic AI and knowledge engineering may hold answers that the neural network world hasn't fully embraced. The episode also ventures into consciousness, panpsychism, Michael Pollan's ideas, and Stewart's own hands-on experience vibe coding a personal chatbot to replace functionality he feels he's lost with recent changes to Claude. Larry's podcast can be found at kgi.fm.Timestamps00:00 - Stewart introduces Larry Swanson; Larry corrects the record on AI's origin, distinguishing it from Norbert Wiener's cybernetics at the 1956 Dartmouth conference.05:00 - Larry discusses interviewing semantic web paper coauthors on its 25th anniversary; RDF's hidden ubiquity compared to SIM cards powering everything invisibly.10:00 - Knowledge graphs explained through t-box terms, a-box assertions, and Dave McComb's c-box; IKEA's three-layer knowledge graph as a practical example.15:00 - Stewart connects metadata complexity to AI needs; faceted search explained as c-box attributes driving product filtering experiences.20:00 - RDF 1.2 reification standards discussed; W3C's rigorous recommendation process powering governments and enterprises worldwide through collaborative standards.25:00 - Cyc project examined as influential "successful failure"; Pat Hayes bringing description logic into semantic web; LLMs lacking true reasoning capability.30:00 - Epistemological fault lines between human and computer intelligence; cognitive surrender paper reveals no intelligence threshold protects against AI manipulation.35:00 - Stewart's Claude regression problem drives chatbot vibe coding quest; small language models and domain-specific approaches explored as alternatives.40:00 - Consciousness discussion through Michael Pollan's panpsychism lens; language versus cognition disconnect revealing LLMs as pure token-stitching without genuine thought.45:00 - Context graphs as purpose-built knowledge graphs for AI; Stewart's planning agents versus coding agents architecture and ground truth verification problem.50:00 - Docs-as-code versus code-as-docs paradigm shift; knowledge graphs as universal verifiers against validated facts; RDF 1.2 enabling provenance and degrees of certainty.55:00 - Jessica Talisman's Knowledge Graph Academy recommended for onboarding; kgi.fm podcast shared; knowledge representation community needs better abstraction for wider adoption.Key Insights1. The term "artificial intelligence" was not a marketing gimmick but was coined deliberately at the 1956 Dartmouth Conference to distinguish the work of John McCarthy from Norbert Wiener's cybernetics. The two camps represented genuinely different approaches, and the AI label was a form of intentional intellectual branding rather than empty promotion.2. The semantic web, often called the most successful failure in technology history, has quietly embedded itself everywhere despite never achieving its original vision. Technologies like RDF power metadata standards inside every Adobe product and form the invisible backbone of government systems, enterprise data infrastructure, and cultural heritage organizations worldwide.3. Knowledge graphs are best understood as an ontology combined with all the instances that populate it. The distinction between things and strings, popularized by Google in 2012, captures the core idea that knowledge representation is about concepts as distinct from the labels we give them.4. The t-box, a-box, and c-box framework offers a practical model for understanding knowledge architecture. The t-box holds terminology and concepts, the a-box holds assertions about specific instances, and the c-box manages the attributes, taxonomies, and controlled vocabularies that sit between them and enable things like faceted search.5. Large language models produce fluent, convincing output but lack genuine reasoning, epistemological grounding, or judgment. Research on cognitive surrender shows that even people who understand how LLMs work are still susceptible to being misled by their fluency, meaning intelligence and awareness offer no reliable protection against being deceived.6. The gap between language and cognition matters deeply when evaluating AI. Evidence from people with aphasia shows that thinking can occur without language, which suggests LLMs, being purely language-based systems, are missing a fundamental layer of cognition that cannot be recovered through more tokens or better training.7. Knowledge graphs and RDF-based representation are well suited to the problem of verification and grounding in AI systems. Rather than relying on vectorized embeddings of language, a knowledge graph can store validated, provenance-tracked facts with degrees of certainty, making it a natural foundation for building trustworthy AI applications.

What did "materialism" actually mean to the ancients, and how does it differ from our modern scientific understanding? In this episode, we sit down with Dr. Max Wade (Ph.D., Boston College) to bridge the gap between ancient Greek ontology and modern philosophical debates.We dive deep into the "weirdness" of ancient thought, exploring why the Stoics believed in physical gods and why the Epicureans were the only true ancient materialists. Dr. Wade challenges the secularized modern reading of Socrates and Plato, revealing how their theories of divine design were actually a reactionary response to pre-Socratic natural philosophy.In this episode, we discuss:The Miriology of Being: Why the relationship between parts and wholes is the key to unlocking ancient ontology.Active vs. Passive Matter: The crucial distinction that separates Platonists, Aristotelians, and Stoics from the Epicureans.The "Swerve": Why materialism and determinism were considered incompatible in the ancient world.Plato's Atlantis & Egyptian Wisdom: Why reading Plato literally misses his point about the soul's forgetfulness and eternal truth.Marxism & Hegel: How modern materialism is often a misreading of ancient concepts through a German Idealist lens.About Our Guest: Dr. Max Wade is a scholar of ancient philosophy whose dissertation focused on Plotinus' Ontology of Artifacts. Follow his work at maxway.substack.com.Send us Fan Mail Musis by Bitterlake, Used with Permission, all rights to BitterlakeSupport the showCrew:Host: C. Derick VarnIntro and Outro Music by Bitter Lake.Intro Video Design: Jason MylesArt Design: Corn and C. Derick VarnLinks and Social Media:twitter: @varnvlogblue sky: @varnvlog.bsky.socialYou can find the additional streams on YoutubeCurrent Patreon at the Sponsor Tier: Jordan Sheldon, Mark J. Matthews, Lindsay Kimbrough, RedWolf, DRV, Kenneth McKee, JY Chan, Matthew Monahan, Parzival, Adriel Mixon, Buddy Roark, Daniel Petrovic,Julian, Drea, Free Beer 

Explore how AI is redefining the boundaries between uniquely human intelligence and machine capabilities, and discover which aspects of intelligence remain distinctly human. This episode delves into building smarter, more efficient organizations by leveraging the complementary strengths of people and AI—focusing on the critical role of an ontology-first approach, knowledge graphs, and live digital twins in digital transformation. Listeners will gain actionable insights into integrating dynamic processes for real-time decision-making, structuring enterprise knowledge, and eliminating organizational inefficiencies using practical, AI-powered solutions.

Who God is, gives pattern to what God does. The Trinitarian vision sees ordinary life as a participation in the life of God that is both being and doing.

Stewart Alsop sat down with Michael Shackelford to discuss their experiences building applications through vibe coding—the practice of using AI to create software without traditional programming expertise. Stewart, who runs the AI Whispers community in Buenos Aires and hosts the Crazy Wisdom podcast (with over 660 interviews), shared how he went from teaching people prompt engineering to building his own video conferencing software as a Riverside.fm replacement, while Michael opened up about his year-long journey creating Genrupt Inc, an AI-powered content generation tool for e-commerce sellers. The conversation covered everything from the decline in quality of Claude's reasoning capabilities and how Chinese companies used distillation attacks to copy Anthropic's models, to the importance of spaced repetition systems for managing knowledge in the age of LLMs, with both sharing battle-tested prompting strategies like asking AI to "explain it to me in genius terms" and using deep research queries to reverse engineer how competitors build their products.Show Notes:- Dan Martell's book "Buy Back Your Time" was mentioned as one of the best business books for thinking about life and business- Check out John Vervaeke's "Awakening from the Meaning Crisis" for understanding relevance realization and why AI fundamentally cannot determine what's relevant to humans without being toldTimestamps00:00 Michael discusses being exhausted from getting his app ready for launch, working nonstop with AI to prepare landing page for podcast traffic driving beta signups05:00 Stewart explains starting AI Whispers in Buenos Aires after leaving OpenAI vendor company, meeting early adopters like Torin who was building mind-reading EEG technology10:00 Discussion of how corporations resist AI adoption due to political games and job security fears while some companies use AI as excuse for pandemic-era layoffs15:00 Stewart describes teaching workshops on using LLMs as linguistic tools rather than coding tools, noting technical people often lack humanities background needed for prompting20:00 Explaining chatbot wrappers, API calls, and how Anthropic's reasoning quality declined after Chinese distillation attacks copied their secret sauce developed with philosophers25:00 Technical discussion of model training, fine-tuning versus RAG for new information, and different approaches to updating AI knowledge beyond initial training30:00 Stewart describes building podcast recording software to replace expensive Riverside, struggling with syncing audio and video files across different computer clocks35:00 Discussion of critical factors in vibe coding, discovering unknown technical requirements, and how AIs don't automatically reveal missing information40:00 Stewart's reverse engineering process using deep research function to study competitors' hiring and technology stacks, separating planning agents from coding agents45:00 Prompting techniques including "explain like I know everything" and using spaced repetition systems to capture valuable prompts and technical knowledge50:00 Michael explains his Generux app for generating ecommerce content using Amazon review data analysis to inform high-converting listing images and videos55:00 Discussion of founder mentality involving self-delusion about project timelines, Michael working nine-plus hours daily for nine months on app development60:00 Comparing Amazon's expert software to prosumer software approach, discussing distribution challenges and future robotics applications for customized products65:00 Stewart demonstrates spaced repetition app for memory improvement and knowledge retention, explaining relevance realization problem that AI agents cannot solve without embodimentKey Insights1. Stewart Alsop started AI Whisperers in Buenos Aires after leaving his role at Invisible Technologies, which was OpenAI's largest vendor for RLHF work. He noticed that machine learning engineers at tech companies lacked the humanities background needed to properly interact with large language models, which are fundamentally linguistic tools. This led him to create weekly workshops teaching non-technical people how to use AI effectively, running events every Thursday for two years straight. The group attracted intense geeks from the start and eventually led to Stewart speaking right after Vitalik Buterin at DevConnect, marking a significant milestone for the community.2. Large corporations are resistant to AI adoption due to multiple factors including political dynamics within organizations and employees fearing job loss. Many companies that grew during the pandemic are now using AI as an excuse to downsize when the real issue is inefficiency from rapid expansion. Stewart observed that even technical people in machine learning often don't understand how to properly use AI tools because they lack linguistic and humanities training. The fundamental problem is educational, requiring companies to train people how to use these new tools while those same people resist learning them.3. Vibe coding has evolved significantly with Claude Code being a game changer that reduced the technical barrier to entry. Before Claude Code, developers needed substantial technical knowledge to work through constant doom loops and debugging cycles. The success of coding AI tools stems from thirty years of testing infrastructure that provides clear yes or no feedback on whether code works. This infrastructure doesn't exist in the same way for manufacturing, science, and other fields, which is why software became the dominant area for AI assistance initially.4. Claude's quality degradation over recent months resulted from multiple factors including distillation attacks by Chinese companies who reverse engineered Anthropic's reasoning capabilities. Anthropic had hired philosophers, sociologists, and psychologists to develop exceptional reasoning in Claude 4.5, but this was expensive to run. When Chinese models like Kimi copied these capabilities at one tenth the cost, and when mainstream users flooded the platform before Anthropic's planned IPO, the company had to reduce quality to manage computational costs. This represents a significant loss for power users who relied on Claude's superior reasoning abilities.5. Stewart built a podcast recording application to replace Riverside because he needed API access to automate workflows, which Riverside wanted one thousand dollars monthly to provide. The technical challenge involves syncing audio and video from local recordings on multiple computers with different clocks through a server, then merging them so voices match lip movements. This problem requires understanding complex timing issues across different network conditions and file formats. Stewart has been working through AI psychosis for months on this FFMPEG pipeline problem, illustrating how vibe coding still requires building intuition about technical problems even without traditional coding knowledge.6. The transition from expert software to prosumer software represents a major opportunity for AI-enabled tools. Expert software like Photoshop, Blender, and terminal interfaces have extreme complexity that intimidates beginners, but AI is making these capabilities accessible through natural language. The reign of specialists is ending as generalists with broad knowledge and curiosity can now build complete applications by leveraging AI to fill technical gaps. This shift particularly benefits entrepreneurs and founders who specialize in getting into difficult situations and figuring them out, even when they originally thought tasks would be easier than they turned out to be.7. Building applications with AI requires accepting massive time investments beyond initial estimates and developing strategies for overcoming knowledge gaps. Michael estimated his ecommerce content generation app would take months but spent nearly a year working over nine hours daily, while Stewart spent months solving audio-video sync issues. Success requires using tools like deep research to understand how competitors solve problems, maintaining separate planning and coding agents, and learning to ask the right questions. The key insight is that vibe coders can achieve ninety percent of functionality independently, but the final ten percent often requires understanding specific technical concepts that AI cannot intuit without proper context and domain knowledge.

There's a cannon in most towns. Next to a plaque nobody reads. Families take photos there during the day. Men cruise there at night, cars idling, windows fogged, child seats in the back. That gap is exactly what legacy does.In this episode, Gavin Stephens looks at legacy as a cultural technology — not a tribute, but a selection mechanism. Monuments don't remember everyone. They decide who counts. And once you see that, you can't unsee it in vision boards, retirement plans, factory jobs, productivity apps, and the White House.Topics include: Camus and absurdism, the myth of meritocracy, why retirement is backwards, the self-help industry as hierarchy maintenance, and why making a podcast about not needing to be remembered is not ironic — it's just honest.Park Bench Ontology is hosted by Juno-nominated comedian and Canadian Screen Award-winning writer Gavin Stephens. Equal parts philosophy, stand-up, and cultural diagnosis.Welcome to the Collapse.

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.

400 years ago a frightened philosopher cut reality in two, inner and outer. Mind and world. We have been living inside of that split ever since and it is the reason your inner work keeps gong deeper but never arrives. This teaching identifies the wound plainly, shows how it lives in the body and offers a way back to the world that was never actually dead. Come home to the heart. If you appreciate my work please consider a donation to: "paypal.me/newdayglobal". You can also search for me on Substack.com. Thank you!

400 years ago a frightened philosopher cut reality in two, inner and outer. Mind and world. We have been living inside of that split ever since and it is the reason your inner work keeps gong deeper but never arrives. This teaching identifies the wound plainly, shows how it lives in the body and offers a way back to the world that was never actually dead. Come home to the heart. If you appreciate my work please consider a donation to: "paypal.me/newdayglobal". You can also search for me on Substack.com. Thank you!

Langdon and Eden dive into the collapse, tackling Event Factory, the first book from Renee Gladman's Ravicka novels. Meaning disappears, rituals empty of signal, and the malaise of our urban existence is revealed. But also, potentials are exposed, connections are made, and understanding hinted at. Music played: Ordh - Apis Bull https://ordh.bandcamp.com/track/apis-bull

Learn why an organization's ontology, a structured framework for how a business defines, connects, and makes sense of its data and knowledge, is the most valuable and most overlooked asset in any AI strategy. Jessica Talisman, CEO and Founder of The Ontology Pipeline, and Tony Seale, Founder of The Knowledge Graph Guys, break down what it actually takes to build trusted AI, covering everything from semantic layers and knowledge graphs to why provenance is non-negotiable. They explain how organizations can start building their knowledge infrastructure for AI, and make the case for why their ontology is their most defensible competitive asset. Key Moments BI Semantic Layers vs. AI Context Layers (02:21): Explore the evolution from 1990s business vocabularies to modern AI context layers. Learn why ontologies are essential for connecting data points beyond traditional BI. Why Knowledge Graphs are Essential for AI (09:22): Understand why relational databases fail AI's needs. Tony explains how knowledge graphs turn data relationships into "first-class citizens" using open standards. How to Build Your First Business Ontology (17:04): Stop over-modeling and start delivering. Learn how to anchor your data strategy to high-value use cases and business-language competency questions. Solving the AI Provenance & Lineage Gap (34:19): Why LLMs lack built-in reliability. Jessica discusses the necessity of injecting data lineage at the retrieval layer to verify AI accuracy and prevent hallucinations. Why Your Ontology is Your Most Valuable IP (39:27): In the age of commodity AI, your internal data relationships are your only moat. Discover why hosting your ontology with third parties puts your core assets at risk. Key Quotes “If you let somebody else take your ontology, learn the essence of what it is that you know that's out of distribution with the rest of the world, you've just given them everything valuable about your company.” - Tony Seale “The accuracy of the information you receive is reliant upon the lineage or the provenance of the information received from an LLM. It's so important." - Jessica Talisman “As a business leader, you need to be looking below the surface to the data infrastructure. The key trick to do right now is to turn the power of the models that we've got back upon your own internal infrastructure to build out these rich ontologies and to connect your information.” - Tony Seale "Your ontology is like your thumbprint, your digital thumbprint for your organization. It's unique to each organization, and how you define things may not be the same as an LLM might define something." - Jessica Talisman Mentions The Ontology Pipeline® - A Semantic Knowledge Management Framework | Jessica Talisman How the Ontology Pipeline Powers Semantic Knowledge Systems | Jessica Talisman Why Early Knowledge Graph Adopters Will Win the AI Race | The Knowledge Graph Guys Spec-First Development: Why LLMs Thrive on Structure, Not Vibes | The Knowledge Graph Guys The Knowledge Graph Academy Guest Bios  Tony Seale For over a decade, Tony has been passionate about linking data. His creative vision for integrating Large Language Models and Knowledge Graphs within large organisations has gained widespread attention, particularly through his popular weekly LinkedIn posts, earning him the reputation of ‘The Knowledge Graph Guy.' Today, as the founder of The Knowledge Graph Guys, Tony is dedicated to helping organisations harness the power of their data. His consultancy develops cutting-edge Knowledge Graphs that fuel innovation and growth in the rapidly evolving Age of AI. Jessica Talisman Jessica Talisman has dedicated her 25-year career to exploring the dynamics of information and knowledge—how it flows across systems, evolves through context, and powers intelligent technologies. Her work spans historical research, educational frameworks, and enterprise-scale applications of artificial intelligence. Previously a Senior Information Architect at Adobe, Jessica led the development of semantic knowledge graphs to enrich content and contextual understanding. She now serves as CEO and Founder of Ontology Pipeline, where she leads efforts to bridge the worlds of library science and data management - building robust, scalable knowledge systems for the AI era. Hear more from Cindi Howson here. Sponsored by ThoughtSpot.

ReferencesGuerra, DJ.2026. Unpublished LecturesAutism Research and Treatment 2011(3):398636Journal of Disease and Global Health 2022. December.DOI: 10.56557/jodagh/2022/v15i38023Nature Communications 2018.Vol. 9, Article number: 1228 Allman, D. 1972. Little Marthahttps://open.spotify.com/track/2WPLFvAldG0GG6Ad3Xa0TO?si=2a64dc0a38f54d61

In this episode of The Sacred Speaks, Dr. John W. Price sits down with Timothy Morton, philosopher, writer, and Rita Shea Guffey Chair in English at Rice University, for a wide-ranging conversation about hell, ontology, and what it means to live without an "outside." Morton is the author of Hell, along with numerous works on ecology, object-oriented ontology, and the entanglement of human and nonhuman worlds. Together, John and Morton explore hell not as an afterlife destination but as a lived condition of felt distance from the divine and deep entanglement with the biosphere. This conversation moves through ontology and how things exist, the critique of holism and mastery as tied to fascism and colonial habits of thought, the distinction between panic and grief as pathways to change, and why mystery, irony, and hesitation may be the most honest responses to reality. Morton frames social media as a continuation of 18th-century politics of sensibility, critiques metaphysics of presence and gnostic hierarchies, and suggests that paradise is not elsewhere but something we build inside hell. Rather than offering resolution, this episode invites listeners into an uncomfortable and generative encounter with the structures we inhabit without seeing. Key Takeaways: Timothy Morton defines ontology as how things exist and argues that our deepest assumptions about reality shape everything from ecology to politics. The conversation frames holism and mastery as colonial and fascist habits of thought, suggesting that ecology requires giving up the fantasy of total comprehension. Morton distinguishes panic from grief, proposing that panic is an ontological shock when our worldview cracks, while grief is the doorway through. The interview explores hell as an embodied, cultural structure rather than a metaphysical location, and suggests irony, hesitation, and mystery as reality signals. Morton reads William Blake as a poet of infinite narrators and weaponized gentleness, connecting the Lamb and the Tiger to questions of presence and paradox. Timestamps (00:00) Welcome and Guest Intro (01:26) Workshops and Community Updates (03:38) Substack and Upcoming Book (04:26) Jumping Straight Into the Recording (05:34) Writing Without Forcing (07:54) Why Hell and Ontology (13:22) Ontology Explained Simply (14:41) Holism and Fascism Critique (18:53) Ecology Against Mastery (23:02) Building Heaven in Hell (25:22) Trauma and Meaning Saturation (26:48) Mystery and Opacity of Truth (33:01) Colonizer Mind and Worldviews (39:00) Panic as Ontological Shock (41:19) Panic Before Grief (42:28) Mockery and Woke (43:26) Grief Breaks Control (44:24) Worldviews as Weapons (45:52) Frog Versus Soldier (49:02) Initiation and Identity Loss (52:37) Phenomenology Explained (56:46) Glitches and Consciousness (58:44) Gods of Decay (01:01:45) Evolution Without a Plan (01:06:34) Trust Made of Mistrust (01:08:29) Art as Emotional Poison (01:12:27) Social Media Sensibility (01:15:46) Irony Hesitation Reality (01:18:47) Online Irony Lacks Democracy (01:19:29) Blake Tiger Infinite Narrators (01:23:02) Lamb Poem Weaponized Gentleness (01:24:34) Hell as Flipped God Presence (01:27:04) Buddhism Fixation and Bypass (01:31:33) VIP Paranormal Double Speak (01:36:37) Hell Not Just State of Mind (01:39:35) Metaphysics Presence and Hierarchy (01:50:32) Embodied Paradox as Divine (01:52:28) Closing Reflections and Thanks Connect with Timothy Morton Rice University Faculty Page: Timothy Morton, Rita Shea Guffey Chair in English, Rice University Book: Hell by Timothy Morton Website for John http://www.drjohnwprice.com WATCH: YouTube for The Sacred Speaks https://www.youtube.com/channel/UCOAuksnpfht1udHWUVEO7Rg Instagram: https://www.instagram.com/thesacredspeaks/ @thesacredspeaks Facebook: https://www.facebook.com/thesacredspeaks/ Brought to you by: https://www.thecenterforhas.com Theme music provided by: http://www.modernnationsmusic.com

In this episode of Liminal Phrames, Darren/Exo and Nathan dig into the ontological status of "beings" in contact reports. Persistent agents, symbolic projections, or dynamically instantiated interfaces—what are we actually encountering?

In this episode of the Crazy Wisdom Podcast, host Stewart Alsop sits down with David Lachmish, co-founder of Ika, to explore the cutting-edge world of decentralized cryptography and its real-world applications. They cover the foundational problem of zero-trust custody and interoperability in crypto, breaking down why most people end up relying on centralized custodians despite crypto's original promise of removing third-party trust, and how Ika's novel 2PC-MPC cryptographic protocol addresses this with decentralized wallets (d-wallets) that require both the user and the Ika network to generate a signature. The conversation also touches on AI agents and the critical need for access control guardrails when agents handle real financial transactions, the philosophical parallels between crypto's growing pains and the early internet, decentralized governance and its potential to reshape how societies make decisions, and a surprising look at how decentralized certificate authorities could dramatically improve everyday internet security. David also gives a first public mention of an upcoming privacy-focused project called Encrypt.Links mentioned:- Ika website: https://ika.xyz- Ika on X: https://x.com/iкаdotxyz- David Lachmish on X: https://x.com/d3h3d_- Encrypt (upcoming project): https://encrypt.xyzTimestamps00:00 - David Lachmish introduces Ika and DWallet Labs, explaining their cybersecurity and cryptography background led them to solve zero trust custody and interoperability.05:00 - The d wallet concept is revealed as a decentralized signing mechanism controlled jointly by user and network, requiring new cryptography breakthroughs.10:00 - Crypto's philosophical parallels to early Internet are drawn, framing scams and misuse as inevitable growing pains of transformative infrastructure.15:00 - Wallet abstraction and agent constraints are explored, comparing future seamless crypto interaction to modern WiFi versus early modem connections.20:00 - Public key cryptography's binary ownership problem is explained, leading into MPC secret shares and Fireblocks' centralized access control tradeoffs.25:00 - 2PC MPC protocol is introduced as Ika's breakthrough, enabling decentralized policy enforcement without trusting any single entity.30:00 - Decentralized governance via token staking and code as law is discussed, contrasting corporate representative governance with crypto's direct decision-making.35:00 - Futarchy prediction markets and decision trees are connected to knowledge graphs, tracing humanity's accelerating governance transition.40:00 - Automation's historical parallels are examined, arguing AI's displacement of lawyers and developers mirrors every prior technological revolution.45:00 - Bitcoin and Ethereum's uncertain futures are assessed alongside Ika's positioning in custody and interoperability infrastructure.50:00 - Zero trust interoperability is explained, revealing how bridges create dangerous honeypots that Ika eliminates through native cryptographic control.55:00 - MetaMask's limitations for agents are detailed, contrasting stored private keys against Ika's policy-enforced guardrails for agentic transactions.60:00 - HumanTech's Wallet as a Protocol is presented as a practical way to give agents spending policies while maintaining user cryptographic control.65:00 - Decentralized certificate authorities emerge as Ika's broader cybersecurity vision, eliminating single points of failure across the entire Internet.Key Insights1. Zero Trust Custody and Interoperability: David and his cofounders at DWallet Labs identified that most cryptocurrency is held by centralized custodians, which contradicts crypto's core purpose of removing third-party trust. They set out to create "zero trust custody and zero trust interoperability" — systems where users maintain cryptographic control without sacrificing usability or relying on any single entity.2. The D-Wallet Primitive: Ika is built around a new cryptographic concept called a "d-wallet" — a decentralized wallet controlled jointly by the user and a decentralized network. A signature cannot be generated without the user's participation, meaning even if all network operators are compromised, they cannot act unilaterally. This required inventing new cryptography called 2PC-MPC.3. Access Control as the Missing Layer: Traditional crypto wallets operate on binary ownership — you either have full control or none. The d-wallet model introduces programmable access control policies enforced by a decentralized network, enabling features like spending limits and whitelisted addresses without trusting a centralized company like Fireblocks.4. Bridges Are Crypto's Biggest Security Vulnerability: Interoperability across blockchains typically requires trusting a bridge, which creates a honeypot for hackers. Ika eliminates this by allowing users to natively control assets on multiple chains simultaneously, maintaining cryptographic guarantees without a trusted intermediary.5. AI Agents Need Cryptographic Guardrails: Giving AI agents control over crypto wallets like MetaMask is dangerous due to hallucination and prompt injection risks. Ika enables agents to operate within strict, code-enforced policies — they can transact autonomously but cannot exceed boundaries set by the user, combining automation with genuine security.6. Decentralized Governance as a Structural Advantage: Ika operates as a permissionless network where two-thirds of token-staking operators control the protocol's direction. Even the founding team cannot unilaterally change the network, making governance transparent and resistant to capture — a meaningful contrast to closed, corporate-controlled systems.7. Decentralized Certificate Authorities as a Future Application: Beyond crypto, David envisions d-wallets solving broader cybersecurity problems. Today's internet relies on a handful of certificate authorities whose compromise would break global web security. A decentralized certificate authority built on Ika's infrastructure would require attacking hundreds of operators simultaneously, representing a fundamental upgrade to how trust is managed across the internet.

Tommy Miller, Bobby Shane Brooks, and Jason have a powerful conversation about union, identity, and the goodness of God, exploring how much of modern Christianity has framed the gospel through separation, behavior, and fear rather than inclusion, belovedness, and Christ-centered being. Tommy unpacks the difference between “tragic ontology” and “salvific ontology,” while Bobby shares his deeply personal story of losing his daughter and how the revelation of God's unwavering love carried him through grief without turning him against the Father. Together, they reclaim salvation, healing, holiness, and identity through the lens of union, arguing that the delusion of separation is over and that the gospel is ultimately the awakening to who we have always been in Christ.Homecoming Conference Link: https://legacy-church-ohio.churchcenter.com/registrations/events/3410549For more content like this, go to:https://afamilystory.org/JOIN our RGWT Subscriber-Based Community:https://promo.fourriversmedia.com/rethinking-god-with-tacos/JOIN A Family Story's Mailing Listhttps://dashing-field-76805.myflodesk.com/pie4be6wtoJOIN the Rethinking God with Tacos Facebook Group at: https://www.facebook.com/groups/godandtacosFollow Rethinking God with Tacos on Instagram at:https://www.instagram.com/rethinkinggodwithtacos/Follow Jason's personal Facebook page at:https://www.facebook.com/afamilystory.org/Follow Jason on Instagram at:https://www.instagram.com/jasonclarkis/Follow Jason on X at: https://x.com/jasonclarkis SEND A DONATION!!https://app.moonclerk.com/pay/36393kxxeh8

Is anything real? How many universes are there? Is everything a simulation being run by a quantum computer through a wormhole from a future era? Is the answer to everything really ... 42? The affable and charming astrophysicist, author and philosopher of tiny particles Dr. Adam Becker pulls up a seat. And enjoy this encore episode as Alie has an existential crisis or two as they discuss the drama, intellectual battles and drunken debates of science past, and the hope that a new era of thinkers will figure out what exactly is going on in the world. Either way: cut bangs and text your crush. Follow Dr. Adam Becker on BlueSky and Instagram Purchase his book "What is Real? The Unfinished Quest for the Meaning of Quantum Physics” Or his new book More Everything Forever: AI Overlords, Space Empires, and Silicon Valley's Crusade to Control the Fate of Humanity A donation went to Techbridge Girls More episode sources & links Sponsors of Ologies Transcripts & bleeped episodes Support Ologies on Patreon for as little as a buck a month OlogiesMerch.com has hats, shirts, pins, totes! Follow @Ologies on Twitter and Instagram Follow @AlieWard on Twitter and Instagram Sound editing by Jarrett Sleeper of MindJam Media & Steven Ray Morris Music by Nick Thorburn Hosted by Simplecast, an AdsWizz company. See pcm.adswizz.com for information about our collection and use of personal data for advertising.

Ryan and Alex explore the overlap between consciousness and unseen intelligences, digging into thought forms, disembodied entities, and tulpas, ideas that suggest the mind may help create or shape non-physical realities. Drawing on Rupert Sheldrake's theory of morphic resonance, they discuss whether reality itself has memory, and whether belief, attention, and pattern play a role in encounters with the unknown.

We consider chapter 2, "Aesthetics Is the Root of All Philosophy," where Harman describes how art can help us see behind the veil to things-in-themselves. Art is "theatrical" in that it's really the spectator who is standing in like an actor for the object encountered in art. Get more at partiallyexaminedlife.com. Visit partiallyexaminedlife.com/support to get ad-free episodes and tons of bonus discussion. Sponsor: Visit functionhealth.com/PEL to get the data you need to take action for your health.

Continuing on Object-Oriented Ontology: A New Theory of Everything (2018), finishing up ch. 1 (discussing what's so bad about reductionism) and moving to ch. 4, "Indirect Relations," which is about causality. Get more at partiallyexaminedlife.com. Visit partiallyexaminedlife.com/support to get ad-free episodes and tons of bonus discussion. Sponsors: Get a $1/month e-commerce trial at shopify.com/pel.

On Harman's Object-Oriented Ontology: A New Theory of Everything (2018). What counts as an entity in the world? Harman includes not just physical objects, but fictional objects, "sensual objects," and even events, which you might have thought were the alternative to objects. With this promiscuous ontology comes a strange theory of causality whereby no real object touches another real object, and an epistemology that involves us having no knowledge of real objects at all, though Harman's theory art gives us a back-door to make up for this deficiency, and philosophy itself ends up sharing in these properties of art. Get more at partiallyexaminedlife.com. Visit partiallyexaminedlife.com/support to get ad-free episodes and tons of bonus discussion. Sponsors: Get a $1/month e-commerce trial at shopify.com/pel. Go to HelloFresh.com/pel10fm to Get 10 free meals + a free Zwilling Knife with your third box.