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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 12, 2025

Bittensor Novelty Search :: Sub-Subnets + Subnet Deregistration core updates :: + Open Q+A

The Opentensor Foundation | Bittensor TAO

Crypto
Key Takeaways:
  1. **Consolidate or Compete.** Sub-subnets allow teams to build diversified businesses under a single token, while deregistration means underperforming projects will be pruned. The message is clear: innovate and perform, or be replaced.
  2. **Investment Thesis Evolves.** Subnet tokens are no longer "eternal." Deregistration fundamentally changes the risk profile, making active development and market traction paramount for long-term viability.
  3. **Governance is Coming.** The network is on a clear path to decentralization. The planned shift to Proof-of-Stake and a more democratic governance structure will steadily transfer power to subnet owners and stakers, making community participation more critical than ever.
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September 12, 2025

One Chart Determines if We're in a Bull or Bear Market

Bankless

Crypto
Key Takeaways:
  1. Global liquidity is the ultimate macro signal. As long as the global liquidity chart goes up and to the right, the crypto bull market has the fuel it needs to continue its run.
  2. Ethereum isn't losing; it's quietly winning the RWA war. With 93% market share, Ethereum has become the de facto settlement layer for tokenized real-world assets, a lead that continues to grow as institutions like Fidelity build directly on its L1.
  3. The new blockchain business model is asset management. Chains like Hyperliquid and Mega ETH are pioneering a shift away from relying solely on blockspace fees. By integrating native stablecoins, they are capturing a percentage of the yield from assets on-chain, effectively turning the protocol itself into a revenue-generating asset manager.
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September 12, 2025

Sanctum Founder: Solana's Liquid Staking Future | FP Lee

Lightspeed

Crypto
Key Takeaways:
  1. LSTs Are a Distribution Play: For protocols, launching an LST is less about staking yield and more about attracting SOL to gain a strategic advantage in securing blockspace and landing transactions.
  2. Infrastructure Follows the User: Sanctum's pivot to transaction services was not a top-down mandate but a direct response to the needs of its largest partners, proving that the most durable infrastructure is built by solving the immediate, pressing problems of your customers.
  3. Aggregation Is King: Just as Jupiter won by aggregating DEXs for users, Sanctum’s Gateway aims to win by aggregating fragmented transaction delivery networks for developers, creating a simpler and more efficient experience.
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September 10, 2025

Still Time To Be Bullish?

1000x Podcast

Crypto
Key Takeaways:
  1. Patience is Your Superpower. This cycle rewards thesis-driven investing over hyperactive trading. Identify assets with strong value, momentum, and fundamentals, and give them time to play out.
  2. Bet on the On-Chain Casino. The gambling economy is real, profitable, and growing. Look for platforms that facilitate high-asymmetry games (memecoins, raffles) as they capture a powerful cultural trend.
  3. Find Alpha in the Illiquid. The next frontier is tokenizing real-world value. Platforms creating liquid markets for previously stuck assets—from collectibles to crime—are building foundational infrastructure for a much larger on-chain world.
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September 10, 2025

Hyperliquid: The Fastest Growing Exchange in Crypto?

Bankless

Crypto
Key Takeaways:
  1. Revenue Accrual is King. Hyperliquid's model of directing nearly all top-line revenue to token buybacks creates an aggressive and constant bid for the HYPE token, a feature most crypto projects can only dream of.
  2. Product-First Beats VC-First. Its explosive growth comes from building a superior product that attracted a loyal user base first, then leveraging that traction to build an L1 ecosystem—a stark contrast to the typical VC-funded playbook.
  3. A Bet on the Middle Ground. Investing in HYPE is a bet that CEX-level performance and on-chain transparency can outweigh significant centralization and regulatory risks. It’s a category-defining play that sits squarely between DeFi and CeFi.
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September 10, 2025

Former Barclays CEO’s Big Bet on Hyperliquid’s Explosive Growth |  Bob Diamond & David Schamis

Forward Guidance

Crypto
Key Takeaways:
  1. Hyperliquid is a Cash Flow Machine. It is a rare crypto asset with quantifiable fundamentals, generating over $1B in annualized free cash flow with an automated, daily 99% buyback mechanism.
  2. Access is the Arbitrage. The NASDAQ-listed vehicle’s core value proposition is providing regulated access to an asset that US investors cannot easily buy, creating a structural opportunity.
  3. Innovation is Now Permissionless. Hyperliquid’s open architecture allows anyone to build on its rails, enabling new markets like pre-IPO equity trading and accelerating growth without traditional gatekeepers.
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