In this episode, James and JJ tackle explaining Bittensor's complexity (vs. Bitcoin/stablecoins), its federation of 100K+ TAO holders unbeatable by companies, Bitcoin as inflation solution (not hedge), necessity/constraints driving creativity, US dollar privilege, AI/DeFi as crypto's biggest use cases (e.g., Ridges for code, Bit Minds for deepfakes, 404 Gen for 3D AI), Bittensor's $3B AI leadership vs. Hyperliquid's $12B (with Subnet 35 Kartha launching Hyperliquid on Bittensor), evolution of equity (alpha tokens as permissionless value creation), DCF vs. incentive analysis for valuations, subnets undervalued vs. 200-300 AI unicorns (most failing with negative margins), alpha for buying resources/companies (e.g., Ridges' 1/20th-1/30th compute cost via Shoots/Targon), and investing in alpha over equity.

Key Timestamps & Topics:

• 00:00:00 - Intro: Bittensor's unbeatable federation; Bitcoin as inflation solution; necessity/constraints/creativity.
• 00:01:00 - Explaining Bittensor: Complexity vs. Bitcoin/stablecoins; Satoshi's "convince you" quote.
• 00:02:00 - Money Evolution: Barter to crypto; $27T stablecoin transactions.
• 00:03:00 - Use Cases: Ridges (code gen), Bit Minds (deepfakes), 404 Gen (3D AI); AI/DeFi dominance.
• 00:04:00 - Community: Philosophical vs. trading; Satoshi's properties; Hyperliquid ($12B) vs. Bittensor ($3B AI lead).
• 00:05:00 - Subnet 35 Kartha: Hyperliquid on Bittensor; evolution of equity/alpha tokens.
• 00:10:00 - Alpha Value: Permissionless mining; buying resources/companies (e.g., Ridges' cheap compute).
• 00:15:00 - Valuations: DCF vs. incentive analysis; subnets undervalued vs. AI unicorns (200-300, most fail).
• 00:20:00 - Alpha Utility: Sustainable mechanisms; investing in alpha over equity.
• 00:55:00 - Wrap-Up: Short episode; teaser for subnets.

Key Takeaways:

• Bittensor as 100K+ TAO holder federation unbeatable by companies (e.g., OpenAI/Anthropic); abstracts incentives for any problem, generalizing Bitcoin's proof-of-work.
• AI/DeFi as crypto's top use cases: $27T stablecoin volume; subnets like Ridges/Bit Minds/404 Gen lead globally—philosophical community drives innovation.
• Evolution of equity: Alpha tokens enable permissionless value (mine without vesting, buy resources at 1/20th-1/30th cost)—replaces flawed VC (subnets undervalued vs. 200-300 failing AI unicorns).
• Valuations shift: DCF to incentive analysis; Bittensor's $3B AI lead (vs. Hyperliquid's $12B) undervalued—alpha for buying companies/resources, sustainable off-ramps needed.
• Complexity challenge: Harder than Bitcoin; Bitcoin solves inflation, Bittensor solves equity/VC—optimistic on penetration, like 15-year Bitcoin mainstreaming.

Resources & Links:

• Bittensor Official: bittensor.com
• Taostats (Explorer/TAO App): taostats.io
• 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

Episode Description:

In this live episode from Toronto, James and JJ discuss Bittensor's motivated community delivering competitive results, DeepSeek outcompeting Western labs at a fraction of the cost (e.g., $100M vs. billions), January 2025 market correction/Nvidia collapse, IP/copyright extinction via AI, financialization of compute (options/markets for pricing), Targon/Shoots' low-cost H200 access (~$1.20-1.30/hour vs. $2.50-3+), and Bittensor's profound frictionless propagation.

Key Timestamps & Topics:

• 00:00:00 - Intro: Bittensor's young, motivated community; profound philosophy/impact.
• 00:01:00 - Toronto Recap: Google event, Targon/Dippy talks; live TAO Pod energy.
• 00:02:00 - DeepSeek's Rise: Outcompeting Western labs; $100M model vs. billions.
• 00:03:00 - Market Impact: January 2025 correction; Nvidia's response to supply/demand.
• 00:04:00 - Compute Financialization: Liquid markets/options for pricing; serverless/minute-level utilization.
• 00:05:00 - Targon Pricing: ~$1.20-1.30/hour for H200s (1/20th-1/30th competitors); 2K+ GPUs at zero cost.
• 00:06:00 - Miners/Data Centers: Slack resources/arbitrage; startups leveraging for evals.
• 01:30:00 - IP Extinction: AI makes copyright oxymoronic; maximum distribution/frictionless propagation.
• 01:35:00 - Wrap-Up: Bittensor's danger to overvalued companies; teaser for next episode.

Key Takeaways:

• Bittensor's community harnesses global miners for competitive, low-cost compute (e.g., Targon/Shoots at 1/20th-1/30th prices vs. cloud providers)—financialization enables granular pricing/options.
• DeepSeek's $100M model outpaces Western labs' billions; January 2025 marked hedge funds competing efficiently, triggering market corrections/Nvidia declines.
• AI extinguishes IP/copyright: Becomes arcane/oxymoronic as tech propagates frictionlessly without permission—Bittensor maximizes distribution.
• Bittensor as profound discovery: Like open source but for incentives; reduces friction for innovation/abundance, outcompeting centralized overvaluation.
• Over 200-300 AI unicorns skewed by OpenAI/Anthropic; median underperforms with negative margins—Bittensor enables sustainable, non-subsidized models.

Resources & Links:

• Bittensor Official: bittensor.com
• Taostats (Explorer/TAO App): taostats.io
• 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

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

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.com
• Taostats (Explorer/TAO App): taostats.io

• TAO App: tao.app

• 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

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