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.com
• Taostats (Explorer/TAO App): taostats.io
• xAI: x.ai
• Follow Hosts: @jaltucher & @josephjacks_ on X

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.com
• Taostats (Explorer/TAO App): taostats.io
• Subnet 14 (TAO Hash): taostats.io/subnets/14
• Subnet 5: taostats.io/subnets/5
• Subnet 19 (Bitcast): taostats.io/subnets/19
• xAI: x.ai
• Follow Hosts: @jaltucher & @josephjacks_ on X

Subscribe for more on Bittensor subnets, AI building, and crypto trends! Leave a review and share your thoughts.

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:

1. Bittensor Official: bittensor.com
2. Taostats (Explorer/TAO App): taostats.io
3. Subnet 56 (Gradients): taostats.io/subnets/56
4. Subnet 3 (Templar): taostats.io/subnets/3
5. Subnet 64 (Chutes): taostats.io/subnets/64
6. Subnet 4 (Targon): taostats.io/subnets/4
7. Subnet 13 (Dataverse): macrocosmos.ai/sn13
8. xAI: x.ai
9. Follow Hosts: @jaltucher & @josephjacks_ on X

Subscribe for more on Bittensor subnets, AI building, and crypto trends! Leave a review and share your thoughts. #TheTaoPod #Bittensor #DecentralizedAI #TAO

Hosted by James Altucher (serial entrepreneur, bestselling author of "Choose Yourself," podcaster, hedge fund manager, chess master, and investor in over 20 companies, with expertise in crypto and AI) and Joseph Jacks (founder and general partner of OSS Capital, the world's first VC firm dedicated to commercial open-source software; early-stage investor in AI and open-source tech, previously Entrepreneur-in-Residence at Quantum Corporation).

In the premiere episode, James and Joe explore Bittensor's decentralized AI ecosystem, contrasting it with centralized giants like xAI's Grok 4. They discuss subnets providing GPUs, datasets, and models; proof-of-useful-work mining; building custom AI agents; and Bittensor's potential to outpace Big Tech in achieving superintelligence.

Plus, tokenomics, real-world apps, capitalism parallels, and bold predictions on TAO's future value.

Key Timestamps & Topics:

• 00:00:00 - Intro: Podcast overview, AI/crypto news (Grok 4, Bitcoin ATH), centralized vs. decentralized AI.
• 00:09:00 - Proof of Useful Work: Mining datasets, models, inference on Bittensor.
• 00:10:00 - Subnet Deep Dives: Dataverse (13) for data scraping; building trading models.
• 00:16:00 - Chutes (64): Cheap AI inference, e.g., Bible chatbot at 1/50th OpenAI cost.
• 00:23:00 - Agentic AI: Building owned agents, avoiding Big Tech biases/control.
• 00:28:00 - Scaling & Future: Decentralization's infinite potential; Bitcoin compute parallels.
• 00:33:00 - Superintelligence Path: Bittensor faster than Elon; energy/chip challenges.
• 00:34:00 - Bittensor's Early Stage: Like 1990s internet, needs better user interfaces.
• 00:38:00 - Chutes Economics: 10T+ tokens served, 4.4K H100 GPUs, user growth.
• 00:50:00 - Valuation & Growth: Subnets as companies; TAO potentially 5-10x Bitcoin.
• 01:02:00 - Bittensor as Pure Capitalism: Incentives for supply/demand; upgrading equity models.
• 01:09:00 - Centralization Risks: Elon/Meta control; Bittensor's global solution.
• 01:13:00 - Wrap-Up: Teasing future episodes on subnets, AI ventures.

Key Takeaways:

• Bittensor incentivizes ~20-100K GPUs permissionlessly, rivaling xAI at zero CapEx.

• Subnets like Chutes (inference) and Dataverse (data) enable cheap, owned AI models for anyone.
• Decentralization democratizes AI talent/compute, potentially building AGI faster than centralized efforts.
• Quote: "Bittensor is the most expressive language of value in the history of languages of value." – Joseph Jacks

Resources & Links:

1. Bittensor Official: bittensor.com
2. Taostats (Explorer/TAO App): taostats.io
3. Subnet 64 (Chutes): taostats.io/subnets/64
4. Subnet 13 (Dataverse): macrocosmos.ai/sn13
5. Akash Network: akash.network
6. xAI: x.ai

Follow Hosts: @jaltucher & @josephjacks_ on X

Subscribe for more on Bittensor subnets, AI building, and crypto trends! Leave a review and share your thoughts. #TheTaoPod #Bittensor #DecentralizedAI #TAO

Get ready for The TAO Pod—the ultimate podcast on Bittensor (TAO), decentralized AI, crypto, and tech's future! Hosted by James Altucher and Joseph Jacks, we explore how Bittensor's subnets are revolutionizing AI access, from GPUs and datasets to custom models and agents.In this trailer, catch highlights from our first episode: Bittensor vs. xAI's Grok, superintelligence predictions, tokenomics, and why decentralization beats Big Tech.Full episodes dropping soon—subscribe now for deep dives, AI startup tips, and bold insights!#Bittensor #DecentralizedAI #Crypto #TAO #xAIFollow:- X: @jaltucher @JosephJacks_
- Bittensor: https://bittensor.com