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AI Podcasts

December 31, 2025

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

Latent Space

AI
Key Takeaways:
  1. The Macro Trend: The transition from static benchmarks to live human-in-the-loop evaluation. As models saturate fixed tests, the only remaining signal is subjective human preference at scale.
  2. The Tactical Edge: Monitor secret model drops on Arena to spot frontier capabilities before official releases. This provides a lead time advantage for builders choosing their tech stack.
  3. The Bottom Line: Arena is the new kingmaker. If you are building AI products, their expert-tier data is the most reliable map for navigating the frontier.
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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 move from small models to medium models (15B to 70B) suggests that reasoning capability is outstripping the desire for low-latency edge deployment.
  2. Implement instruction-following re-rankers to prune your context window. This prevents the model from getting confused by irrelevant data.
  3. Stop building toys. The next year belongs to those who can build full agentic systems that handle billions of tokens without losing the plot.
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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 wall between RL and self-supervised learning is crumbling, leading to a unified "representation-first" approach to AI.
  2. Swap your reward-heavy objectives for contrastive representation learning to access deeper, more stable architectures.
  3. If you aren't planning for RL models with 100x the current depth, you're building for the past.
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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. Academic research is transitioning from a "publish or perish" PDF culture to an "implement or ignore" code culture.
  2. Use AlphaXiv to filter research by social signal and implementation ease rather than just keyword relevance.
  3. The PDF is an antiquated artifact. In 2025, the value of a paper is measured by the speed at which a developer can spin up its Docker container.
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December 31, 2025

[State of MechInterp] SAEs in Production, Circuit Tracing, AI4Science, "Pragmatic" Interp — Goodfire

Latent Space

AI
Key Takeaways:
  1. The Macro Trend: The transition from black box scaling to transparent steering. As models enter regulated industries, the ability to prove why a model made a decision becomes more valuable than the decision itself.
  2. The Tactical Edge: Deploy sidecar models for monitoring. Instead of using expensive LLM-as-a-judge prompts, probe specific internal features to catch hallucinations at the activation level.
  3. The Bottom Line: The next year belongs to the pragmatic researchers. If you cannot explain your model's reasoning, you will not be allowed to deploy it in high-stakes environments.
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December 31, 2025

[State of Code Evals] After SWE-bench, Code Clash & SOTA Coding Benchmarks recap — John Yang

Latent Space

AI
Key Takeaways:
  1. The transition from completion to agency requires moving from static repos to active, economically valuable environments.
  2. Prioritize agentic workflows that emphasize codebase understanding over simple code generation.
  3. The next 12 months will see a move from stunt autonomy to integrated human-AI systems that handle long-running tasks without losing the human intent.
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December 31, 2025

[State of Research Funding] Beyond NSF, Slingshots, Open Frontiers — Andy Konwinski, Laude Institute

Latent Space

AI
Key Takeaways:
  1. The transition from monolithic models to compound systems means the value is migrating to the orchestration and context layer.
  2. Prioritize tools like DSPy and context management frameworks to build high-leverage applications that do not depend on proprietary model updates.
  3. Open research is the only way to maintain a competitive edge. If the US stops publishing, it stops leading.
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December 31, 2025

Infinity, Paradoxes, Gödel Incompleteness & the Mathematical Multiverse | Lex Fridman Podcast #488

Lex Fridman

AI
Key Takeaways:
  1. From Singular Logic to Pluralistic Systems. As we build complex AI, we must move from seeking one "correct" model to managing a multiverse of conflicting but internally consistent logical frameworks.
  2. Audit for Incompleteness. When designing protocols, identify the "independent" variables that your system cannot prove or settle internally.
  3. Truth is bigger than code. Over the next year, the winners will be those who stop trying to "solve" the universe and start navigating the multiverse of possible truths.
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December 31, 2025

AI in 2026: 3 Predictions For What’s To Come (a16z Big Ideas)

a16z

AI
Key Takeaways:
  1. Outcome-Based Intelligence. We are moving from AI as a Service to AI as an Outcome where value is tied to results rather than usage.
  2. Target Non-Public Data. Build applications in sectors like law or lending where the most valuable data is private and un-crawlable.
  3. The next two years will separate companies that use AI to save pennies from those that use AI to capture entire markets through autonomous systems and proprietary data loops.
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Crypto Podcasts

January 13, 2026

Providing Token holders with Real Economic Rights with SOAR | Thomas Curry

Proof of Coverage Media

Crypto
Key Takeaways:
  1. The unification of rights. The industry is moving away from "vague utility" toward hard-coded economic claims that institutional capital can actually model.
  2. Audit your portfolio for "Seniority." Prioritize projects that establish legal or smart-contract-based links to the underlying business entity rather than just "community" vibes.
  3. Real economic rights are the only way to attract the next wave of capital. If a token doesn't represent a claim on value, it is just a meme with extra steps.
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January 14, 2026

Hash Rate - Ep 152 - Loosh Subnet 78

Hash Rate Podcast

Crypto
Key Takeaways:
  1. The transition from "World Models" to "Reasoning Models" marks the end of the LLM-as-chatbot era. Capital is migrating toward systems that prioritize deterministic safety over raw statistical probability.
  2. Integrate deterministic ontologies into your agentic workflows to stop hallucinations at the architectural level. Use graph databases to provide structure that vector search lacks.
  3. The winner of the robotics race won't have the best motors. They will have the most relatable, ethically sound "brain" that humans actually trust in their homes.
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January 13, 2026

Playing the Right Games: Why Scores Quietly Replace Meaning

Bankless

Crypto
Key Takeaways:
  1. The Legibility Crisis: Global systems demand data which creates a gap between measurable outputs and actual value.
  2. Audit Your Scoreboards: List the metrics you track and identify the true beneficiary of that data.
  3. The Bottom Line: Success belongs to those who use high-scale systems without letting the numbers dictate their internal worth.
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January 13, 2026

Why Venezuela Likely Doesn't Have a $60 Billion Bitcoin Stash

Unchained

Crypto
Key Takeaways:
  1. Monetary Sovereignty Migration. When states weaponize the financial system, capital migrates to censorship-resistant stablecoin layers.
  2. Monitor Remittance Corridors. Watch for the growth of non-custodial stablecoin wallets in high-inflation regions as a leading indicator for broader DeFi adoption.
  3. The Venezuelan story proves that while state-led crypto projects fail, the utility of Bitcoin and stablecoins is a permanent fixture in the global south.
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January 12, 2026

Marc Graczyk: Numinous, Bittensor Subnet 6, AI Forecasting Agents, Polymarket Predictions | Ep. 78

Ventura Labs

Crypto
Key Takeaways:
  1. Verifiable intelligence is replacing black-box predictions. As AI agents become the primary participants in prediction markets, the value moves from the prediction itself to the verifiable logic behind it.
  2. Integrate real-time news APIs like Darch to give agents a qualitative edge over pure quant models.
  3. Forecasting is the ultimate utility for LLMs. If Numinous succeeds, Bittensor becomes the world's most accurate, explainable source of truth for investors and researchers.
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January 13, 2026

How Claude Code is Changing the World with Nick Emmons

The Rollup

Crypto
Key Takeaways:
  1. The transition from human-centric interfaces to agent-first protocols. As agents become the primary users, the internet will be rebuilt around machine-readable data and crypto-native payment rails.
  2. Integrate Model Context Protocol (MCP) servers into your workflow immediately. Use parallel Claude instances to act as both programmer and reviewer to bypass context window degradation.
  3. Software is no longer a product: it is a utility. Over the next year, the winners will be those who control the data graphs and the distribution channels, not the ones writing the code.
See full notes