Crazy Wisdom

Episode #547: Dead Forests and Living Networks: Why the Future of Knowledge Looks Like Fungi, Not Filing Cabinets

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 [https://bonfires.ai] and deci.world [https://desci.world/] or follow him on X at @Bonfiresai [https://x.com/bonfiresai] and @DeSciWorld [https://x.com/DeSciWorld]. Timestamps 00:00 - 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 Insights 1. 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.

Episode #546: Beyond Postgres and Node.js: What Happens When Your Database Runs Your Code

In this episode of the Crazy Wisdom Podcast, host Stewart Alsop sits down with Tyler Cloutier, founder of Clockwork Labs and creator of SpaceTimeDB. They explore how SpaceTimeDB functions as more than just a database—it's essentially a distributed operating system that merges server logic with data storage, enabling real-time applications and time-travel capabilities. The conversation ranges from the technical architecture of databases and operating systems to the philosophy of distributed systems, touching on everything from Unix and Linux to how SpaceTimeDB could revolutionize AI-generated software deployment. Tyler explains how their system reduces the complexity of building real-time applications, makes deployment simpler for both humans and AI agents, and why games like their MMORPG BitCraft Online drove them to create this new infrastructure. They also discuss the future of the internet, the role of bots in gaming, and how SpaceTimeDB fits into the broader landscape of cloud computing alongside tools like Cloudflare, Vercel, and Docker. For more information, visit spacetimedb.com [https://spacetimedb.com/] or check out Clockwork Labs on GitHub [https://github.com/clockworklabs] and Twitter [https://x.com/clockwork_labs]. Timestamps 00:00 Stewart introduces Tyler Cloutier, founder of Clockwork Labs, discussing the origin of SpaceTimeDB's name inspired by Einstein's theory and its time travel capabilities that store all operations indefinitely 05:00 Tyler explains SpaceTimeDB as more of an operating system than a database, using tables instead of file systems while running code in a sandboxed environment with full atomic properties 10:00 Discussion of how SpaceTimeDB replaces both Node.js and Postgres by merging web server and database functionality, eliminating separate deployment concerns 15:00 Tyler explains JavaScript execution through Chrome's V8 engine and JIT compiling, leading to Node.js creation for server-side JavaScript development 20:00 Explanation of stateless web servers versus stateful game servers, and why games require in-memory state management for real-time performance 25:00 Tyler introduces reducers and real-time subscriptions, questioning why more applications aren't real-time when state changes should update immediately 30:00 Discussion of Facebook as essentially a text-based MMO, comparing social media architecture to game server requirements and the need for unified systems 35:00 Tyler explains ACID properties in databases: atomic, consistent, isolated, and durable, using game item trading examples 40:00 Comparing SpaceTimeDB to smart contract systems without cryptocurrency or global consensus, positioning it as a smart database with centralized trust 45:00 Tyler reveals SpaceTimeDB uses 43% fewer tokens than Postgres for AI-generated applications, making it valuable for vibe coding platforms 50:00 Conversation shifts to bots in games and proof-of-human concepts, with Tyler proposing biometric systems and discussing potential in-person gaming applications 55:00 Closing discussion about tracking AI-driven traffic through UTM parameters and finding SpaceTimeDB at spacetimedb.com Key Insights 1. SpaceTimeDB is fundamentally a database that runs application code directly inside it, combining what traditionally required separate systems like Postgres and Node.js. Users compile their application logic into WebAssembly or JavaScript and upload it to run within the database itself. This architecture provides high performance because the entire server backend operates inside the database environment. The system also features time travel capabilities, storing every operation and change to data persistently and indefinitely, allowing users to set application state back to any earlier point in time. This makes SpaceTimeDB more accurately described as an operating system rather than just a database, where the abstraction is that everything is a table rather than a file. 2. The inspiration for SpaceTimeDB came from building BitCraft Online, an MMORPG where all players exist in a single persistent world and rebuild civilization together. Traditional MMO backends required complex custom solutions to handle real-time state, with game servers storing state in memory and periodically writing to databases. This complexity existed because games cannot afford the latency of constantly delegating to distant databases like traditional web applications can. SpaceTimeDB solved this by making the database fast enough to handle real-time requirements directly, eliminating the need for separate game servers. This same performance advantage that benefits games also applies to web applications, which is why SpaceTimeDB evolved from a game-specific tool to a general-purpose platform. 3. SpaceTimeDB functions as a distributed operating system where each database acts like a process in an actor model system, similar to Erlang or Scala Akka. Databases can send messages to other databases and be spawned across a cluster for horizontal scaling. This represents an overlay operating system running on top of Linux rather than competing with it, providing a distributed abstraction across many machines while Linux handles device drivers and hardware support. The vision is for the cloud to function as a single enormous computer running one operating system, where developers simply publish their programs without managing separate services, deployment, routing, networking, or persistence infrastructure. 4. The real-time capabilities of SpaceTimeDB address a fundamental limitation in how most web applications work today. Traditional web servers are stateless, delegating all state to databases and accepting network round-trip latency for each request, which is why users often must refresh pages to see updates. SpaceTimeDB allows queries to be subscribed to, maintaining open connections that stream changes whenever query results update. This makes applications like Discord, Facebook, or banking systems naturally real-time without requiring page refreshes. The historical accident that more things are not real-time represents a problem SpaceTimeDB solves by unifying the web world with the game world's real-time requirements. 5. SpaceTimeDB implements ACID properties—Atomic, Consistent, Isolated, and Durable—ensuring database operations are reliable and safe. Atomic means operations either fully happen or not at all, preventing issues like item duplication in games when trading between players. Consistent means declared invariants like unique usernames are always enforced. Isolated means concurrent operations do not interfere with each other. Durable means changes persist even if computers restart, with varying levels from in-memory on one machine to disk storage across multiple geographic locations. These properties are managed through reducers, functions inspired by React Redux that fold changes into application state incrementally. 6. For AI and large language models, SpaceTimeDB offers significant advantages in building and deploying applications. Testing showed that creating applications with SpaceTimeDB uses 43% fewer tokens compared to Postgres implementations, costs less, has fewer bugs, and is easier to extend. This matters because the primary cost for vibe coding platforms is tokens. As more software gets written in the next twelve months than ever before, there is insufficient focus on infrastructure required to run all this AI-generated software. SpaceTimeDB positions itself as ideal for LLMs to target because of its simplified deployment model where developers just publish code and the system handles everything behind the scenes. 7. SpaceTimeDB can be understood as a smart contract system without cryptocurrency or global decentralized consensus. Like blockchain smart contracts, it executes code with atomic, consistent, isolated, and durable properties, but avoids the expense and slowness of requiring all computers worldwide to agree on everything. Instead, it offers centralized trust where users trust Clockwork Labs not to modify deployed contracts, rather than the trustless but extremely costly blockchain approach. This makes it functionally similar to Cloudflare's durable objects but with full relational database capabilities. The system exists before the networking layer where Cloudflare operates, handling deployment, server, and database functions while Cloudflare could provide DDoS protection in front of it.

Episode #545: Measuring the Unmeasurable: Agency, IQ, and the Men Who Change History

In this episode of Crazy Wisdom, Stewart Alsop sits down with Kieran Zimmer — a software developer and independent researcher in psychology and psychometrics — to explore the science behind intelligence and personality. They trace the origins of psychometrics from Wilhelm Wundt's early experimental psychology through Charles Spearman's discovery of the g factor, breaking down what IQ actually measures, how verbal, mathematical, and spatial intelligence relate to one another, and why training specific cognitive tasks doesn't translate into a broader boost in general intelligence. The conversation moves into the Big Five personality traits reframed through a cybernetic lens — looking at extraversion as reward sensitivity, agreeableness as social affiliation, and conscientiousness as long-term goal prioritization — before landing on Kieran's original research into the psychology of agency: what personality profile best predicts agentic behavior, and why the environment shapes whether agency is even adaptive in the first place. Show notes: * Substack: Liminal Revolutions [https://liminalrevolutions.substack.com/] * Twitter/X: @LiminalRev [https://twitter.com/LiminalRev] * YouTube: @TheKieranZimmer [https://www.youtube.com/@TheKieranZimmer] (to listen to Kieran's conference talk on the agency paper) Timestamps 00:00 — Stewart and Kieran trace the origins of psychometrics back to Spearman, Binet, and Wilhelm Wundt's early experimental psychology. 05:00 — The conversation unpacks the g factor, fluid vs. crystallized intelligence, and why IQ is fundamentally a physical trait tied to nerve conduction velocity. 10:00 — A tangent into AI and LLMs: why they lack vision, taste, judgment, and accountability — the human moat that remains for now. 15:00 — Stewart's Claude Code failure sparks a discussion on AI accountability, surveillance, and the rise of dystopian technocracy. 20:00 — Parallel structures as a form of exit from failing institutions, and the high-agency people required to build them. 25:00 — Agency, risk-taking, and accountability through Napoleon, the Inuit, and why modern Western leaders are managers, not leaders. 30:00 — Elites vs. peasants, cost externalization, and Kirk Doolittle's natural law as the physics of cooperation. 35:00 — Ressentiment, Nietzsche's under-utilization in psychology, and how secularism replaced the church. 40:00 — Kieran's quantitative conspiracy theory study: factor analysis of 85 questions across 273 respondents. 45:00 — Two branches of conspiracy belief: the aliens-and-Satanism cluster vs. the fakery factor pathway to Flat Earth. 50:00 — AI psychosis, Gnosticism, and the collapse of sense-making institutions in an age of information overload. 55:00 — Michael Levin's embodied cognition and cybernetic agency: thermostats, humans, and homeostatic set points. 1:00:00 — The Cybernetic Big Five broken down: extraversion as reward sensitivity, agreeableness, neuroticism, and the optimal personality profile for agency. Key Insights 1. IQ is a physical trait, not just an abstract score. It's rooted in nerve conduction velocity, brain connectivity, and processing speed — and while you can improve crystallized intelligence through learning, the underlying g factor doesn't budge no matter how many brain training apps you use. 2. The human moat against AI comes down to four things: vision, taste, judgment, and accountability. LLMs are powerful next-token predictors, but they have no stake in the outcome and no capacity to own a mistake — which means a human with those qualities will always be essential. 3. High agency is not just ambition — it's a measurable psychological profile. Kieran's paper frames it through the Cybernetic Big Five: high assertiveness, high intellect, low politeness, low neuroticism, and medium conscientiousness. Getting things done at scale almost always involves upsetting people. 4. All agentic behavior involves risk, and the willingness to absorb that risk is what separates real leaders from managers. Modern Western leadership has decoupled decision-making from consequence, which is why institutions are losing trust and authority at an accelerating rate. 5. Conspiracy belief follows a measurable path dependency. Kieran's factor analysis showed that virtually everyone who believes in Flat Earth also endorses the fakery factor and the Jewish question cluster — but not vice versa. It's a spectrum with a clear escalation pattern, not a random set of unrelated beliefs. 6. AI is accelerating epistemic breakdown. Sycophantic models will validate almost any idea, which has started producing a new category of high-IQ delusion — intelligent people convincing themselves they've solved Millennium Prize problems because the AI kept agreeing with them. 7. The Big Five personality traits can be recast as cybernetic parameters — each one an evolutionarily selected mechanism for regulating goal-directed behavior. Extraversion is reward sensitivity, agreeableness is social affiliation, neuroticism is threat response, and conscientiousness is the preference for long-term over short-term goals.

Episode #544: Privacy Is the New Counterculture

In this episode of the Crazy Wisdom Podcast, host Stewart Alsop sits down with Cindy Cohn, Executive Director of the Electronic Frontier Foundation (EFF), for a wide-ranging conversation covering the EFF's origins and mission, the countercultural roots of Silicon Valley, the rise of surveillance-based business models, the challenges facing open source software and open-weight AI models, the legal landscape around intellectual property and privacy law, and the growing tension between government overreach and civil liberties in the digital age. Cindy also discusses her upcoming departure from EFF after 26 years, the transition to new leadership, and her recently published book Privacy's Defender, which chronicles key legal battles she fought to protect digital privacy rights. Links mentioned: - EFF website: eff.org [https://www.eff.org] - Privacy's Defender book: eff.org/privacysdefender [https://www.eff.org/privacysdefender] Timestamps 00:00 - Stewart introduces Cindy Cohn, EFF Executive Director, who explains the organization's mission protecting digital rights since 1990. 05:00 - Cindy connects counterculture roots to early internet idealism, describing how digital communication broke down physical barriers for organizing. 10:00 - Cindy reveals surveillance becoming the dominant business model surprised her, blaming corporate consolidation over naive techno-optimism. 15:00 - Discussion shifts to Silicon Valley's military contractor substrate and how corporate money co-opted hacker ethos. 20:00 - Open source community faces existential threat from age verification legislation while open-weight AI models emerge as critical alternative. 25:00 - Cindy outlines legal frameworks like compulsory licensing and easements that could democratize access to foundational AI models. 30:00 - Privacy principles around secondary data use identified as core surveillance problem, with Anthropic's domestic surveillance red line praised. 35:00 - Cloud Act, Five Eyes surveillance networks, and global jurisdictional complexity examined through individual threat modeling lens. 40:00 - Constitutional rights and democratic participation framed as irreplaceable bulwarks against authoritarian surveillance tendencies. 45:00 - Cindy announces departure from EFF after 26 years, naming successor Nicole Ozer while planning return to courtroom litigation. Key Insights 1. The Electronic Frontier Foundation was founded in 1990, before the World Wide Web existed, by Mitch Kapoor, John Perry Barlow, and John Gilmore, with early support from Steve Wozniak. Its core mission is to ensure that civil rights and freedoms follow people into the digital world, using lawyers, technologists, and activists to keep the internet on the side of users. 2. The early countercultural movement of the 1960s and 70s heavily influenced the founders of the internet and EFF. Figures like Barlow believed the digital world could reduce physical barriers like race, class, and geography, allowing people to be judged by the quality of their ideas rather than the circumstances of their birth. 3. The dominant surveillance business model that emerged was not inevitable. Cohn argues it resulted from deliberate policy failures, particularly the abandonment of competition law, which allowed a handful of companies to consolidate control over the entire internet and adopt 360-degree data collection as their primary revenue strategy. 4. Open source communities remain active and vital but are under serious threat from legislation like age verification laws that make it practically impossible to maintain fully open tools. Cohn sees this community as essential to reclaiming public control over computation, especially in the age of AI. 5. The open weights question for AI models is fundamentally different from traditional open source software because of the enormous capital required to train foundation models. Cohn suggests legal mechanisms like compulsory licensing, similar to how cover songs work in copyright law, as one possible path toward broader public access. 6. A core privacy principle Cohn advocates is that data collected for one purpose must not be used for others. This single rule, if enforced, would begin dismantling the infrastructure that enables mass individual surveillance, including the AI-powered profiling she sees as the next dangerous frontier. 7. Cohn is stepping down from EFF after 26 years to allow new leadership and return to litigation, which is where she believes her impact is greatest. She also wrote a book called Privacy's Defender to preserve the history of digital rights fights from the 1990s onward and to help people understand how current threats emerged so they can work to reverse them.

Episode #543: The Year of Agents and the Industries Not Ready for Them

In this episode of the Crazy Wisdom Podcast, host Stewart Alsop sits down with Mauro Schilman, CTO and Co-founder of Tuki, the distribution standard for the AI agent era in travel, for a wide-ranging conversation that moves from the joys of international travel and the beauty of mathematics to the fast-evolving world of AI and large language models. Mauro shares his background as a math Olympiad competitor and later a coach, his time training coding models at the AI company Cohere, and his thoughts on how frontier models are progressing — or plateauing — at the foundational level while innovation accelerates at the application layer. The two also get into the mechanics of agentic AI, MCP and agent-to-agent protocols, hierarchical memory systems, red-green test-driven development as a powerful coding workflow, and the philosophical murkiness of open-source AI. They wrap up discussing Tuki Travel's mission to build AI-ready infrastructure for the travel industry, connecting hotels, suppliers, and online travel agencies to prepare for the coming wave of agentic commerce. You can learn more about Tuki Travel and reach out to the team at tukiclub.com [https://tukiclub.com/]. Timestamps 00:00 - Stewart welcomes Mauro Schilman, CTO and Co-founder of Tuki Travel, who shares how traveling since age 15 through high school exchanges opened his mind to cultural similarities and differences. 05:00 - Mauro explains Math Olympiad coaching culture and mentorship, noting LLMs now solve competition-level problems while Terence Tao explores AI assisting frontier unsolved mathematics. 10:00 - Discussion turns to ChatGPT revealing Mauro's birthdate unprompted, exposing opaque application layers, preference tuning, and system prompts hidden within closed models. 15:00 - Mauro argues true open source AI requires full training data, annotation protocols, and alignment processes, not just model weights, while scaling laws appear to be slowing. 20:00 - Hierarchical memory models replace flat vector databases, using three-level retrieval systems improving context accuracy as knowledge management becomes AI's core challenge. 25:00 - Mauro describes travel's fragmented infrastructure of aggregators, bed banks, and intermediaries, explaining Tuki builds agent-ready unification protocols for AI commerce. 30:00 - MCP versus API debate clarifies natural language capability descriptions help agents consume services, while agent-to-agent communication embeds negotiating agents inside supplier systems. 35:00 - Hallucinations and consumer trust block agentic payments, industries must build mistake-resilience into bookings before autonomous agent transactions become viable. 40:00 - Mauro reveals red-green test-driven development methodology where agents write failing tests first then implementations, creating Oracle verification loops dramatically improving code quality. 45:00 - Blockchain's potential for transparent distributed AI training discussed, distinguishing democratization from decentralization while stable coins and regulatory momentum build toward agentic commerce infrastructure. Key Insights 1. Travel broadens perspective by revealing both universal human similarities and deep cultural differences. Mauro Schilman began traveling at fifteen through math olympiad competitions and found that people across the world share fundamental traits while also being shaped in profoundly different ways by their cultures. This tension between sameness and difference is what makes travel meaningful. 2. Mathematics transitions from structured problem-solving in olympiads to genuine uncertainty in graduate school and research. Olympiad problems are carefully designed with elegant solutions meant to encourage creative thinking, but once a mathematician enters academia, the answers are unknown and the work becomes navigating that uncertainty. 3. AI is now assisting mathematicians at the frontier, not just solving olympiad-level problems. Terence Tao, one of the greatest living mathematicians, has written publicly about how AI tools can help tackle unsolved problems, though the role of AI remains assistive rather than independent at the research level. 4. Large language models are not truly transparent even when described as open source. Releasing model weights alone does not reveal the training data, annotation protocols, alignment tuning, or system prompts that shape model behavior. Real openness would require access to the entire pipeline. 5. Memory and retrieval remain core unsolved challenges in AI systems. Researchers are moving from flat vector database approaches toward hierarchical memory structures with roughly three layers, which improves retrieval accuracy and reduces how much context gets consumed with each search. 6. The travel industry is structurally unprepared for AI agents. A hidden web of bed banks, aggregators, and aggregators of aggregators sits between hotels and consumers, each taking a fee. Tuki Travel is building infrastructure to unify this distribution layer and make it consumable by AI agents through protocols like MCP and emerging agent-to-agent communication standards. 7. Test-driven development using a red-green approach significantly improves AI-generated code quality. By asking the model to write failing tests before writing any implementation, developers create a verification oracle that guides the model toward correct solutions and avoids the bias of writing tests that simply confirm existing flawed code.