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AI Podcasts

August 21, 2025

Can AI Fix Housing and Healthcare Affordability?

a16z

AI
Key Takeaways:
  1. AI is the deflationary force for stagnant sectors. While software ate the world, it skipped housing and healthcare. AI is finally tackling the operational drag that has caused costs to balloon for decades.
  2. To solve the housing crisis, make it profitable. The path to more housing supply runs through better returns. By making property operations radically more efficient, AI attracts the capital required to build.
  3. The future of work is human + AI. Automation won't eliminate jobs; it will transform them. As AI handles the administrative grind, human roles will shift to higher-value work like community engagement and complex problem-solving.
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August 19, 2025

Hash Rate - Ep 129 - Macrocosmos IOTA (sn9) and DataUniverse (sn13)

Hash Rate pod - Bitcoin, AI, DePIN, DeFi

AI
Key Takeaways:
  1. DTO Means Business: Dynamic TAO has forced a Darwinian shift. Subnets must now achieve product-market fit and generate real revenue to survive, transforming from research projects into self-sustaining businesses.
  2. IOTA’s Grand Ambition: IOTA (SN9) isn't just another model trainer; its architecture aims to train trillion-parameter models on decentralized, consumer-grade hardware, directly challenging the dominance of centralized AI labs.
  3. Time to Garden: The protocol's long-term health hinges on active governance. A strong sentiment is emerging to prune low-effort or malicious subnets to focus emissions on projects capable of creating real, lasting value.
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August 19, 2025

Hash Rate - Ep 128 - Ridges ($TAO Subnet 62)

Hash Rate pod - Bitcoin, AI, DePIN, DeFi

AI
Key Takeaways:
  1. AI Is Moving from Copilot to Pilot. Ridges is betting that the future isn't AI assisting humans, but AI replacing them for specific tasks. Their goal is to make hiring a software engineer as simple as subscribing to a service.
  2. Decentralized Economics Are a Moat. By leveraging Bittensor's incentive layer, Ridges outsources a $15M/year R&D budget to a global pool of competing developers, achieving a cost structure and innovation velocity that centralized players cannot match.
  3. The Breakout Subnet Is Coming. Ridges showcases how a Bittensor subnet can solve real-world business problems—privacy, cost, and quality degradation—to build a product that is not just cheaper, but fundamentally better than its centralized counterparts.
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August 18, 2025

Dylan Patel on GPT-5’s Router Moment, GPUs vs TPUs, Monetization

a16z

AI
Key Takeaways:
  1. From Performance to Profit: The AI industry is pivoting from a war of benchmarks to a game of unit economics. Features like GPT-5’s router signal that cost management and monetization are now as important as model capabilities.
  2. Hardware is a Supply Chain Game: Nvidia’s true moat is its end-to-end control of the supply chain. Competitors aren't just fighting a chip architecture; they're fighting a logistical behemoth that consistently out-executes on everything from memory procurement to time-to-market.
  3. The Grid is the Limit: The biggest check on AI’s expansion is the physical world. The speed at which new power infrastructure and data centers can be built will dictate the pace of AI deployment in the US, creating a major advantage for those who can build faster.
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August 18, 2025

Subnet 56 :: Gradients :: Bittensor End-to-end AI Model Training Suite

Opentensor Foundation

AI
Key Takeaways:
  1. Performance is Proven, Not Promised. Gradients isn't just making claims; it’s delivering benchmark-crushing results, consistently outperforming centralized incumbents and producing state-of-the-art models.
  2. Open Source Unlocks the Enterprise. The shift to verifiable, open-source training scripts is a direct solution to customer data privacy concerns, turning a critical vulnerability into a competitive advantage.
  3. The AutoML Flywheel is Spinning. The network's competitive, tournament-style mechanism creates a self-optimizing system that continuously aggregates the best training techniques, ensuring it remains at the cutting edge.
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August 16, 2025

Google DeepMind Lead Researchers on Genie 3 & the Future of World-Building

a16z

AI
Key Takeaways:
  1. **World Models Are a New Modality.** Genie 3 is not just better video; it's an interactive environment generator. This divergence from passive, cinematic models like Veo signals a new frontier focused on agency and simulation, creating a distinct discipline within generative AI.
  2. **Simulation Is the Key to Embodied AI.** The biggest hurdle for robotics is the lack of realistic training environments. Genie 3 tackles this "sim-to-real" gap head-on, providing a scalable way to train agents on infinite experiences before they ever touch physical hardware.
  3. **Emergent Properties Will Drive the Future.** Key features like spatial memory and nuanced physics weren't explicitly coded but emerged from scaling. The next breakthroughs in world models will come from discovering these unexpected capabilities, not just refining existing ones.
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August 15, 2025

Greg Brockman on OpenAI's Road to AGI

Latent Space

AI
Key Takeaways:
  1. AGI is a Compute Game. The primary bottleneck is compute. The process is one of "crystallizing" energy into compute, then into the potential energy of a trained model. More compute means more intelligence.
  2. The Future is a "Manager of Models." AGI won't be a single entity. It will be an orchestrator that delegates tasks to a fleet of specialized models, from fast local agents to powerful cloud reasoners.
  3. Build for Your AI Coworker. To maximize leverage, structure codebases for AI. This means self-contained modules, robust unit tests, and clear documentation—treating the AI as a team member, not just a tool.
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August 15, 2025

Novelty Search August 14, 2025

taostats

AI
Key Takeaways:
  1. Performance is a Solved Problem. For post-training tasks, Gradients has established itself as the best in the world. Developers should stop writing custom training loops and leverage the platform to achieve superior results faster and cheaper.
  2. Open Source Unlocks Trust and Revenue. The pivot to open source directly addresses the biggest enterprise adoption hurdle—data privacy. This move positions Gradients to capture significant market share and drive real revenue to the subnet.
  3. The Bittensor Flywheel is Real. Gradients didn't just beat a major AI lab; its incentive mechanism ensures it will continue to improve at a pace traditional companies cannot match. Miners who don’t innovate are automatically replaced, creating a relentless drive toward optimization.
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August 15, 2025

Subnet 56 :: Gradients :: Bittensor End-to-end AI Model Training Suite

Opentensor Foundation

AI
Key Takeaways:
  1. **Training is a Solved Problem.** For users and developers, the message is clear: stop building custom training loops. Gradients offers superior performance out-of-the-box, turning the complex art of model training into a simple API call.
  2. **Open Source is the Ultimate Competitive Moat.** By making top training scripts public, Gradients accelerates its own innovation flywheel, creating a continuously compounding advantage that closed-source competitors cannot replicate.
  3. **The Best 8B Model is Now from Bittensor.** Gradients has moved beyond theoretical benchmarks to produce a state-of-the-art model that beats a leading industry player. This is a powerful proof-of-concept for the entire Bittensor ecosystem.
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Crypto Podcasts

January 6, 2026

Markets React to U.S. Capture of Maduro

Unchained

Crypto
Key Takeaways:
  1. Production for Security. As globalization fractures, the US is trading ESG idealism for hard-asset reality.
  2. Buy Energy Infrastructure. Focus on SMR nuclear and solar companies that bypass traditional regulatory bottlenecks.
  3. Dollarized tech. This secures the energy needed for the AI and crypto buildout over the next decade.
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January 5, 2026

Bitcoin’s Back, Venezuela Regime Change, Memecoins, 2026 Mega Trends

1000x Podcast

Crypto
Key Takeaways:
  1. The Macro Transition: Geopolitical realignment is turning Bitcoin from a speculative asset into a tool of statecraft.
  2. The Tactical Edge: Buy Bitcoin calls dated for late January to capture the $125k target.
  3. The Bottom Line: The next six months will reward those who recognize that the "printing money" era has evolved into a "seizing assets" era.
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January 5, 2026

Inside SharpLink's Massive Ethereum Bet With CEO Joseph Chalom

The Rollup

Crypto
Key Takeaways:
  1. The migration from "Crypto" to "Digital Finance" where the underlying tech becomes invisible.
  2. Audit your protocol's risk disclosures. Prioritize security and third-party code reviews to attract institutional capital.
  3. Ethereum is the leading candidate for the world's financial operating system because it has ten years of zero downtime and a massive validator base.
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January 5, 2026

How the Stablecoin Milkshake will Redollarize the World

Bankless

Crypto
Key Takeaways:
  1. The US is moving from "analog" dollar dominance to a high-velocity digital network that absorbs global liquidity faster than ever.
  2. Maintain exposure to US equities and gold while keeping dollar-denominated cash in short-term bonds to capitalize on the next volatility spike.
  3. The dollar isn't dying; it is being upgraded. Expect the "Milkshake" to suck up global capital as foreign economies struggle with debt and declining growth.
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January 3, 2026

Predictions for 2026

Bell Curve

Crypto
Key Takeaways:
  1. The movement from casino to utility means capital will flow toward protocols with high revenue quality and durability.
  2. Prioritize DeFi products that bridge institutional assets to retail front-ends.
  3. 2026 is the year crypto stops being a promise and starts being a product.
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January 2, 2026

Crypto Only Has 2 Real Business Models | Ejaaz Ahamadeen

The DCo Podcast

Crypto
Key Takeaways:
  1. Value is migrating from raw infrastructure to the model layer. As compute becomes a commodity, the economic winner is the entity that owns the weights and the inference interface.
  2. Audit your portfolio for projects with Visa-style fee structures. Prioritize protocols that generate revenue from external usage rather than internal token circularity.
  3. Sustainable crypto AI requires moving past speculative emissions toward actual service fees. The next year will separate apps that use AI to solve problems from protocols that use AI to sell tokens.
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