The TAO Pod

• EP06: Why Bittensor Will Outpace Bitcoin and VC Funding: Bittensor's Incentive Abstraction

  In this episode, James and JJ discuss Bittensor as a combustion engine-level innovation, the extinction of IP/copyright due to AI, Bittensor solving flawed equity/VC models (e.g., saving $10B in VC for one subnet), abstracting incentives beyond Bitcoin's proof-of-work, Clawed vs. Ridges (billions raised vs. $600K needed), permissionless equity compensation, and Bittensor's profound societal impact.Key Timestamps & Topics:00:00:00 - Intro: Bittensor as combustion engine; IP extinction via AI; replacing capitalism/VC.00:01:00 - Bitcoin vs. Bittensor: Specific vs. abstracted incentives; enormous electricity use vs. problem-solving flexibility.00:02:00 - Bittensor's Generalization: Proof-of-useful-work for any commodity; user-generated incentives like YouTube content.00:05:00 - Equity vs. Alpha Tokens: Permissioned vs. permissionless; subnets as equity-like but different.00:07:00 - Clawed vs. Ridges: $10B+ VC vs. $600K; Bittensor's efficiency in talent/incentives.00:10:00 - Permissionless Compensation: Mine subnets without interviews/vesting; top miners earn $2M+ yearly in days/month.01:22:00 - Themes Recap: Bittensor's abstraction makes it "more valuable Bitcoin"; emerging TaoFi layers.01:25:00 - Unbanked Issues: 9M US households; unfair institutions/gatekeepers vs. incentivism.01:27:00 - Permissionless Tech: Open source/Bittensor reduces friction; turbocharges innovation/abundance.01:28:00 - Wrap-Up: Bittensor's societal change; teaser for Toronto event.Key Takeaways:Bittensor generalizes Bitcoin's proof-of-work into proof-of-useful-work for any problem/digital commodity—user-generated incentives like startups but permissionless.Replaces flawed capitalism/VC: Abstracts equity into alpha tokens; e.g., Ridges achieves billions in value with $600K vs. Clawed's $10B+—saves enormous capital/talent friction.Permissionless equity compensation: Mine subnets asynchronously without permission/vesting; top earners make $2M+ yearly in days/month, disrupting hiring/ownership.IP/copyright extinction: AI makes intellectual property oxymoronic; Bittensor fosters profound, humanity-wide innovation beyond regulated/centralized models.Societal impact: Reduces gatekeepers (e.g., banks/VCs); empowers unbanked/accredited—true incentivism for abundance, outpacing selfish equity.Resources & Links:Bittensor Official: bittensor.comTaostats (Explorer/TAO App): tao.appxAI: x.aiFollow Hosts: @jaltucher & @josephjacks_ on X

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• EP05: Bittensor's Philosophical Ethos: Open Source Freedoms Driving TAO Wealth

  Episode Description: In this episode, James and JJ explore Bittensor's philosophical community (vs. other tokens' trading focus), open source freedoms from Richard Stallman (four freedoms: inspect, modify, distribute, distribute with changes), incentives as a meta-language for problem-solving, Bittensor's neural network parallels, subnet valuations via fully diluted value (FDV) and discounted TAO flow (DTF) analysis, emission schedules (2-3x faster for alpha tokens), and emerging TaoFi opportunities (e.g., borrowing against future tokens).Key Timestamps & Topics:00:00:00 - Intro: Bittensor's cult-like ethos for positive impact; incentives for sustainability.00:01:00 - Community Philosophy: Bittensor's depth (growing intelligence, redefining capitalism) vs. other tokens' trading focus.00:02:00 - Open Source Origins: Richard Stallman's four freedoms; philosophical motivations in tech history.00:06:00 - Operating Systems Roots: Carnegie Mellon's Mach kernel influencing Apple/Microsoft; TCP/IP's open source dominance.00:09:00 - Incentives as Language: Expressing value/motivation; Bittensor's abstraction for problem-solving.00:15:00 - Bittensor as Neural Network: Neurons (miners), axons/dendrites (validators), weights (incentives); continuous learning.00:20:00 - Subnet Valuations: FDV vs. market cap; top subnets undervalued (e.g., $400-500M FDV for Shoots/Liam).00:25:00 - Emission Schedules: Alpha tokens mine faster (63 years at 2x EMA); 95% circulating in 7-8 years.00:30:00 - DTF Analysis: Discounted TAO flow like DCF; valuing future emissions/cash flows.00:35:00 - Value Investing: Gap analysis on subnet productivity; top 10 massively undervalued long-term.02:30:00 - TaoFi Opportunities: Financial layers (collars, options, borrowing) on future tokens; parallels to DeFi.02:36:00 - Wrap-Up: Mathematical path to Bittensor > Bitcoin; teaser for next episode.Key Takeaways:Bittensor's community is philosophically driven (e.g., gnostic wisdom, incentivism) for societal impact, unlike trading-focused token groups—key to long-term success.Open source freedoms (inspect/modify/distribute) empower users over tech; Bittensor extends this to incentives, abstracting value like a meta-language.Subnets as neural components: Miners (neurons) produce value, validators (axons/dendrites) route, incentives (weights) optimize—enabling continuous, humanity-scale problem-solving.Valuations via FDV/DTF: Top subnets undervalued (e.g., billions potential); alpha emission 2-3x faster than TAO, reaching 95% circulation in 7-8 years for rapid price discovery.Emerging TaoFi: Layer for options/collars on future tokens; Bittensor as "more valuable Bitcoin" via incentive abstraction, with DeFi-like financial innovations ahead.Resources & Links:Bittensor Official: bittensor.comTaostats (Explorer/TAO App): taostats.ioTAO App: tao.appxAI: x.aiFollow Hosts: @jaltucher & @josephjacks_ on XSubscribe for more on Bittensor subnets, AI building, and crypto trends! Leave a review and share your thoughts. #TheTaoPod #Bittensor #DecentralizedAI #TAO

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• EP04: Why Bittensor's TAO Demand Will Be Higher Than Ever.

  Hosted by James Altucher and Joseph Jacks.In this episode, James and JJ discuss Bittensor's unbeatable scale against centralized companies, parallels to the internet/crypto revolutions, unregulatable open source AI, demand math for TAO with subnet growth (e.g., 10-15M additional staked TAO for 1,000 subnets), the upcoming halving event in December 2025, alpha token economics/volatility, regulation debates (e.g., Eric Schmidt on open source AI), dual-use tech risks, and rational optimism for AI's future. They also did a small Q&A at the end of the episode.Key Timestamps & Topics:00:00:00 - Intro: Bittensor's humanity-scale advantage; internet/crypto parallels; unregulatable open source creativity.00:01:00 - TAO Demand Math: Staking/users/validators for 1,000+ subnets; 10-15M additional TAO needed (vs. 9.5M circulating).00:02:00 - Halving Event: December 2025 cuts emission from 7,200 to 3,600 TAO/day; scarcity impact.00:03:00 - Alpha Tokens: 21M supply cap; faster emission (1.5-2x TAO); volatility from thin liquidity (e.g., 2M circulating alpha).00:06:00 - Pool Dynamics: Price sensitivity in early stages; stability in 6-9 months as supply reaches 10-20%.00:08:00 - Market Factors: Organic exchange listings; daily volume $100-200M; staking for emission ranking.01:04:00 - Regulating Open Source AI: Eric Schmidt's views critiqued; impossible to regulate human curiosity/creativity.01:05:00 - Dual-Use Tech: AI vs. nuclear weapons; kitchen knife analogy; good intentions vs. bad outcomes (e.g., student loans).01:09:00 - Rational Optimism: History shows good outpaces bad (e.g., internet, Bitcoin); societies at all-time highs despite fears.01:12:00 - Wrap-Up: Relax if not understanding everything; ride the wave of Bittensor's evolution.Key Takeaways:Bittensor scales infinitely like the internet/crypto, outcompeting centralized solutions via permissionless, humanity-wide incentives—no company can match global creativity.TAO demand surges with subnet growth (post-128 cap removal): Back-of-envelope math shows 10-15M additional staked TAO for 1,000 subnets, vs. current 9.5M circulation; halving adds scarcity.Alpha tokens are volatile early due to thin liquidity (2M circulating vs. 21M cap), but stabilize as emission progresses—faster halving (every 2-3 years) accelerates price discovery.Open source AI is unregulatable, as it equates to stifling human curiosity; dual-use fears (e.g., biological weapons) are flawed—history proves innovation's net good outweighs risks.Optimism prevails: Regulations often backfire (e.g., tuition inflation from student loans); AI's progress mirrors societal advances, with good far outpacing bad in unregulated environments.Resources & Links:Bittensor Official: bittensor.comTaostats (Explorer/TAO App): taostats.ioxAI: x.aiFollow Hosts: @jaltucher & @josephjacks_ on X

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• EP03: Why Humanity Needs Permissionless AI Incentives Now: Bittensor's Revolution Against Control | EP03

  Episode Description: Hosted by James Altucher and Joseph Jacks. In this episode, James and Joe explore perverse incentives in centralized tech (e.g., Google, Apple), Bittensor's permissionless model for front ends and innovation, subnet ownership as "stocks for ideas," incentives as a meta-language transcending currencies ("incentivism"), trustless systems, tech monopolies and market collapse, historical revolutions, Nvidia's risks, escape velocity challenges, scaling Bittensor via subscriptions, opportunities like Bitcast (decentralized ads) and TAO Hash, Bittensor as a neural network (neurons, axons, dendrites), Metcalfe/Reed's Law for exponential value, reinforcement learning (AlphaZero), the "Age of Experience" for continuous AI, and why Bittensor's success ensures humanity's control over AI—failure means monopolistic dominance.Key Timestamps & Topics:00:00:00 - Intro: Perverse tech incentives; Bittensor's uniqueness for humanity's control.00:01:00 - Permissionless Front Ends: Building user-friendly interfaces without subnet approval.00:03:00 - Subnet Ownership: Like stocks for ideas; equity vs. alpha tokens; manipulation risks.00:07:00 - Incentives as Language: Transcending currencies; "incentivism" vs. capitalism.00:09:00 - Bitcoin's Origins: Response to financial crises; interdisciplinary foundations.00:15:00 - Trustless/Permissionless: Abstracting incentives from currency; self-choice in entrepreneurship.00:18:00 - Multi-Layer Permissionlessness: Beyond usage—improvement, monetization, collaboration.00:22:00 - Tech Monopolies: iPhone/Android duopoly; vertical integration (Tesla, Elon).00:25:00 - Market Collapse: Advanced tech reduces choices; historical revolutions (steam, oil, AI).00:28:00 - Nvidia's Monopoly: Supply chain lock-in; geopolitical implications.00:31:00 - Escape Velocity: Centralized AI's capital/talent advantages vs. decentralization.00:33:00 - Scaling Bittensor: $10/month subscriptions from 2B users for trillions in value.00:36:00 - Front End Opportunities: Chicken-egg growth; expanding beyond technical users.00:39:00 - Bitcast Example: Decentralized ad agency flipping trillion-dollar industry.00:43:00 - TAO Hash: Decentralized Bitcoin mining; meta-incentives and pool co-ownership.00:50:00 - Bittensor as Neural Network: Neurons, axons, dendrites—weights via incentives.00:53:00 - Metcalfe/Reed's Law: Exponential value from subnets/interconnections.00:55:00 - Age of Experience: Continuous learning AI; Bittensor as reinforcement models.00:59:00 - Reinforcement Learning: AlphaZero; less human input for superior results.01:02:00 - YouTube Data: Google's real-time training edge; Bittensor alternatives.01:05:00 - Bittensor's Imperative: Success for humanity's control; failure risks monopoly.01:09:00 - Open Source Limits: Commercial issues; Bittensor as sustainable upgrade.01:15:00 - Wrap-Up: Evangelizing Bittensor; teaser for next episode.Key Takeaways:Bittensor creates multi-layered permissionlessness, enabling anyone to build/improve/monetize without gatekeepers—countering centralized tech's perverse incentives.As "incentivism," Bittensor is a meta-language for incentives, transcending currencies and fostering trustless, interdisciplinary innovation like Bitcoin but for AI/computation.Historical revolutions show monopolization; Bittensor mitigates via scalable, continuous-learning models through reinforcement incentives.Subnets like Bitcast/TAO Hash disrupt trillions (e.g., ads, mining); unified front ends could drive adoption via $10/month TAO subscriptions, yielding 5-10x Bitcoin's value.Resources & Links:Bittensor Official: bittensor.comTaostats (Explorer/TAO App): taostats.ioSubnet 14 (TAO Hash): taostats.io/subnets/14Subnet 5: taostats.io/subnets/5Subnet 19 (Bitcast): taostats.io/subnets/19xAI: x.aiFollow Hosts: @jaltucher & @josephjacks_ on XSubscribe for more on Bittensor subnets, AI building, and crypto trends! Leave a review and share your thoughts.

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• EP02: Here’s Why Bittensor’s Incentives Crush Big Tech’s AI Monopolies for Good

  Hosted by James Altucher and Joseph Jacks.In this episode, James and Joe brainstorm real-world AI use cases on Bittensor, like building an ER diagnostic model. They explore Bittensor as an upgrade to open source through incentives, distributed training (e.g., Templar subnet), off-chain computation parallels to Bitcoin, repricing AI/commodities, and its potential to disrupt centralized tech via "incentivism" and continuous learning.Key Timestamps & Topics:00:00:00 - Intro: Bittensor's disruption to AI incentives, governance, and improvement; early internet parallels.00:01:00 - Real-World Use Case: Brainstorming an ER AI diagnostic model using Bittensor subnets (storage, training, inference).00:07:00 - Commoditization: Bittensor surpasses open source by aligning intrinsic/extrinsic incentives.00:17:00 - Search Engine Example: Reimagining Google via Bittensor's competitive subnets for spiders and categorization.00:22:00 - Off-Chain Computation: Bittensor's Bitcoin-inspired design for infinite scalability.00:33:00 - Consensus & Corruption: Probabilistic validation, subjective outputs, and real-world parallels.00:40:00 - Templar Subnet: Distributed training for trillion-parameter models; Jensen Huang's views on decentralization.00:46:00 - Repricing Assets: Bittensor democratizes AI superpowers, protects against arbitrary valuations.00:50:00 - Inflation & Productivity: Fiat vs. Bitcoin/Bittensor; human error in monetary policy.01:02:00 - Bittensor's Future: As "incentivism"—redefining capitalism without regulation.01:09:00 - User Interfaces & Opportunity: Bittensor's "1991 internet" stage; need for better front ends.01:15:00 - Open Source Limits: Missing economic models; Bittensor as successor with liquidity.01:21:00 - Templar Economics: Speculation on scalable training; subnet competition.01:26:00 - Distributed Challenges: Heterogeneous hardware vs. centralized homogeneity.01:35:00 - Age of Experience: Continuous learning AI; Bittensor's evolving incentives.01:36:00 - Jensen's Pushback: Slowing open source/decentralization to protect monopolies.01:39:00 - Energy Subnets Idea: Incentivizing renewables/SMRs for AI power needs.01:41:00 - Wrap-Up: Bittensor as carbon credits alternative; teaser for next episode.Key Takeaways:Bittensor upgrades open source by adding extrinsic economic incentives, enabling commoditization beyond centralized labs.Off-chain computation allows infinite scalability for distributed training, potentially surpassing giants like Google in heterogeneous environments.As "incentivism," Bittensor reprices AI and protects against arbitrary valuations/inflation, democratizing tech participation.Subnets like Templar could achieve trillion-parameter models permissionlessly, addressing energy/compute bottlenecks via incentives.Resources & Links:Bittensor Official: bittensor.comTaostats (Explorer/TAO App): taostats.ioSubnet 56 (Gradients): taostats.io/subnets/56Subnet 3 (Templar): taostats.io/subnets/3Subnet 64 (Chutes): taostats.io/subnets/64Subnet 4 (Targon): taostats.io/subnets/4Subnet 13 (Dataverse): macrocosmos.ai/sn13xAI: x.aiFollow Hosts: @jaltucher & @josephjacks_ on XSubscribe for more on Bittensor subnets, AI building, and crypto trends! Leave a review and share your thoughts. #TheTaoPod #Bittensor #DecentralizedAI #TAO

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