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AI Podcasts

December 30, 2025

Your Brain Doesn't Command Your Body. It Predicts It. [Max Bennett]

Machine Learning Street Talk

AI
Key Takeaways:
  1. The macro pivot: The transition from static data training to interactive world models that perform active inference.
  2. The tactical edge: Prioritize AI architectures that incorporate continual learning and hypothesis testing rather than just scaling parameters.
  3. The next decade belongs to those who replicate the biological transition from observation to interactive simulation.
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December 31, 2025

The Algorithm That IS The Scientific Method [Dr. Jeff Beck]

Machine Learning Street Talk

AI
Key Takeaways:
  1. The Macro Transition: Move from Big Data mimicry to Small Data causal reasoning.
  2. The Tactical Edge: Prioritize Active Inference frameworks that track uncertainty.
  3. AGI won't come from bigger LLMs; it will come from agents that possess a physics-grounded world model.
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December 30, 2025

[State of AI Startups] Memory/Learning, RL Envs & DBT-Fivetran — Sarah Catanzaro, Amplify

Latent Space

AI
Key Takeaways:
  1. The transition from stateless chat interfaces to stateful, personalized agents that learn from every interaction.
  2. Prioritize memory. If you are building an application, treat state management and continual learning as your core technical moat to prevent user churn.
  3. Stop chasing clones of existing apps for reinforcement learning. Use real-world logs and traces to build models that solve actual engineering friction.
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December 30, 2025

[State of RL/Reasoning] IMO/IOI Gold, OpenAI o3/GPT-5, and Cursor Composer — Ashvin Nair, Cursor

Latent Space

AI
Key Takeaways:
  1. The transition from internet-scale imitation to environment-scale RL.
  2. Build products that capture the full context of a professional's workflow to make them RL-ready.
  3. Intelligence is no longer the bottleneck. The winner will be whoever builds the best hard drive for professional context.
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December 31, 2025

[State of Post-Training] From GPT-4.1 to 5.1: RLVR, Agent & Token Efficiency — Josh McGrath, OpenAI

Latent Space

AI
Key Takeaways:
  1. The Macro Pivot: Intelligence is moving from a scarce resource to a commodity where the primary differentiator is the cost per task rather than raw model size.
  2. The Tactical Edge: Prioritize building on models that demonstrate high token efficiency to ensure your agentic workflows remain profitable as complexity grows.
  3. The Bottom Line: The next year will be defined by the systems vs. models tension. Success belongs to those who can engineer the environment as effectively as the algorithm.
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December 31, 2025

[State of Evals] LMArena's $100M Vision — Anastasios Angelopoulos, LMArena

Latent Space

AI
Key Takeaways:
  1. The transition from static benchmarks to "Vibe-as-a-Service" means model labs must optimize for human delight rather than just loss curves.
  2. Use Arena’s open-source data releases to fine-tune models on real-world prompt distributions.
  3. In a world of synthetic data and benchmark saturation, human preference is the only remaining scarce resource for validating frontier capabilities.
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December 31, 2025

[State of Context Engineering] Agentic RAG, Context Rot, MCP, Subagents — Nina Lopatina, Contextual

Latent Space

AI
Key Takeaways:
  1. The transition from Model-Centric to Context-Centric AI. As base models commoditize, the value moves to the proprietary data retrieval and prompt optimization layers.
  2. Implement an instruction-following re-ranker. Use small models to filter retrieval results before they hit the main context window to maintain high precision.
  3. Context is the new moat. Your ability to coordinate sub-agents and manage context rot will determine your product's reliability over the next year.
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December 31, 2025

[NeurIPS Best Paper] 1000 Layer Networks for Self-Supervised RL — Kevin Wang et al, Princeton

Latent Space

AI
Key Takeaways:
  1. The convergence of RL and self-supervised learning. As the boundary between "learning to see" and "learning to act" blurs, the winning agents will be those that treat the world as a giant classification problem.
  2. Prioritize depth over width. When building action-oriented models, increase layer count while maintaining residual paths to maximize intelligence per parameter.
  3. The "Scaling Laws" have arrived for RL. Expect a new class of robotics and agents that learn from raw interaction data rather than human-crafted reward functions.
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December 31, 2025

[State of AI Papers 2025] Fixing Research with Social Signals, OCR & Implementation — Team AlphaXiv

Latent Space

AI
Key Takeaways:
  1. The Age of Scaling is hitting a wall, leading to a migration toward reasoning and recursive models like TRM that win on efficiency.
  2. Filter your research feed by implementation ease rather than just citation count to accelerate your development cycle.
  3. In a world of AI-generated paper slop, the ability to quickly spin up a sandbox and verify code is the only sustainable competitive advantage for AI labs.
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Crypto Podcasts

September 3, 2025

How Crypto Insiders Are Sidestepping the Law to Dump on Retail

Unchained

Crypto
Key Takeaways:
  1. **The 10-Minute Rule:** If you’re not in a memecoin launch within the first 10 minutes, you are the exit liquidity. The game is rigged by snipers with privileged information.
  2. **Deception is the Default:** Insiders use sophisticated tactics like one-sided LPs to hide their selling, making it crucial for investors to look beyond simple price charts.
  3. **Self-Policing is the Only Way:** Don't wait for regulators. The crypto community must build its own systems of accountability to expose and sideline repeat offenders.
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September 3, 2025

Why Everyone Keeps Misreading The New Macro Regime | Ben Kizemchuk

Forward Guidance

Crypto
Key Takeaways:
  1. **Fiscal Is King.** The government, not the Fed, is in the driver's seat. Higher interest rates are now stimulative, as higher interest payments on government debt inject more cash directly into the private sector.
  2. **The Market Is The Economy.** Passive flows have rewired capital allocation, turning the stock market into an automated utility that concentrates wealth in mega-cap companies, making traditional valuation metrics less relevant.
  3. **Invest in Scarcity.** In a world of unlimited fiat currency and financially repressed bond yields, assets with a fixed supply, such as gold and crypto, become critical portfolio components, while traditional fixed income loses its appeal.
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September 2, 2025

Why Is Everyone So Bearish?

1000x Podcast

Crypto
Key Takeaways:
  1. Fade the Crowd. Widespread retail despair is a signal of an underexposed market, creating a powerful contrarian buying opportunity.
  2. Macro Is the Driver. Pro-crypto deregulation and future rate cuts are the real forces to watch, not short-term price action.
  3. Alpha Demands Work. The era of easy altcoin gains is over. The new "wealth hack" is to develop deep expertise by embedding yourself in a project's ecosystem.
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September 1, 2025

Kraken’s 10 Year Plan | Arjun Sethi

Empire

Crypto
Key Takeaways:
  1. **Incentives Define the Game:** Arjun’s 10-year compensation plan isn't just a detail; it’s a strategy. It forces long-term thinking and aligns the entire organization around monumental growth targets, a stark contrast to the short-term focus of many public companies.
  2. **Win the "Meaty Middle":** While competitors fight over retail users or institutional whales, Kraken is cornering the market of professional traders. This overlooked segment is the engine of global liquidity and the key to building a durable, high-volume exchange.
  3. **On-Chain IPOs Are Coming:** The future of capital markets is global, on-chain, and permissionless. Traditional companies are already looking to bypass Wall Street for venues like Kraken, signaling a fundamental shift in how businesses access capital.
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September 1, 2025

From BlackRock to Ethereum: Why Joseph Chalom is Betting It All on ETH

Bankless

Crypto
Key Takeaways:
  1. **The 2:1 Rule for Valuing ETH:** The simplest institutional valuation model correlates ETH's market cap to the value it secures. For every $2 in assets (stablecoins, RWAs) on Ethereum, ETH's value historically grows by $1, providing a clear framework for its future potential.
  2. **Productive Assets Win:** Ether’s ability to generate yield through staking makes it a fundamentally superior treasury reserve asset compared to non-productive alternatives. This allows companies like Sharplink (ESBET) to generate revenue, compound holdings, and attract public market multiples.
  3. **Tokenization Unlocks Trillions:** The shift to on-chain, atomically settled assets will free up tens of trillions in capital currently locked in settlement risk, counterparty risk, and collateral management, creating an overwhelming incentive for institutional adoption on secure networks like Ethereum.
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August 31, 2025

Hash Rate - Ep 130 - What IS Bittensor -- Actually? The Latest Thinking

Hash Rate pod - Bitcoin, AI, DePIN, DeFi

Crypto
Key Takeaways:
  1. A New Economic Primitive: Bittensor is pioneering "Incentivism," a model that replaces traditional companies with a decentralized network of goals and globally competing workers, creating a system that is described as "capitalism squared.
  2. TAO is an Index on Innovation: The network is designed so all value accrues back to the base TAO token through staking mechanisms. Investing in TAO is effectively an index bet on the entire ecosystem’s innovation.
  3. An Unbeatable Cost Structure: The "Law of Subnet Stacking" enables exponential cost reductions, giving the Bittensor ecosystem a potentially insurmountable competitive advantage over centralized incumbents.
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