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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

February 2, 2026

Gavin Zaentz & Pranav Ramesh: Leadpoet, Lead Generation, Intent-Driven Sales Automation | Ep. 79

Ventura Labs

Crypto
Key Takeaways:
  1. The shift from centralized, static data aggregation to decentralized, real-time, incentivized intelligence networks is fundamentally changing how data-intensive industries operate.
  2. Investigate subnet opportunities where incumbent data quality is low and validation is a core challenge.
  3. The future of sales is not just about more leads, but smarter, fresher, and more relevant ones.
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February 3, 2026

Gold Crashes, Bitcoin Slides, and the Fed Shock Markets

Unchained

Crypto
Key Takeaways:
  1. The Macro Shift: As trust erodes in traditional financial systems and geopolitical risks rise, capital is flowing towards more efficient, permissionless DeFi markets. This is forcing traditional finance to adapt or lose market share.
  2. The Tactical Edge: Evaluate DATs trading below NAV for potential M&A or activist plays, as these discounts often reflect management misalignment rather than fundamental asset weakness.
  3. The Bottom Line: The current market volatility, Fed policy shifts, and the rise of DeFi are not just noise; they are reshaping capital allocation. Investors and builders must understand these structural changes to position for the next cycle of institutional adoption.
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February 2, 2026

Metals Crash & Bitcoin Breaks $80k

1000x Podcast

Crypto
Key Takeaways:
  1. Global economic uncertainty and tariff threats are triggering a broad risk-off sentiment, creating dislocations where fundamentally strong assets are sold indiscriminately.
  2. Reallocate capital from speculative metals positions into Bitcoin at current levels and high-conviction, revenue-producing crypto platforms like Hyperliquid.
  3. The current market turbulence is separating the signal from the noise. Focus on assets with strong fundamentals and organic usage, as they are poised for significant gains once the broader market stabilizes.
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February 3, 2026

Is BTC A Buy, Metals Crash, Hyperliquid RWAs, New Fed Chair

1000x Podcast

Crypto
Key Takeaways:
  1. Global market indigestion is creating a flight to quality and a re-evaluation of speculative assets. This environment favors fundamentally strong assets and platforms with clear utility over pure FOMO plays.
  2. Consider tax-loss harvesting Bitcoin positions that are out of the money and reallocate to high-conviction, revenue-producing crypto assets like Hyperliquid.
  3. The "crypto portfolio" concept is evolving; focus on individual assets with strong organic usage and mega-trend tailwinds. This strategic shift will differentiate winners from losers in the coming market cycles.
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February 2, 2026

Why BitGo Went Public | Mike Belshe

Empire

Crypto
Key Takeaways:
  1. Regulatory clarity and institutional demand are converging, driving a fundamental re-architecture of financial market infrastructure. This shift will see traditional finance increasingly rely on regulated crypto-native service providers.
  2. Builders and investors should prioritize infrastructure providers that offer robust regulatory compliance and fiduciary protection, as these are the non-negotiable requirements for the next wave of institutional capital.
  3. The digital asset industry is poised for massive growth, driven by Wall Street's entry. Companies like BitGo, by building transparent, regulated infrastructure, are not just participating in this growth; they are actively shaping the future of finance, making now the time to understand these foundational shifts.
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February 2, 2026

Curated Credit: How Maple and Morpho Approach DeFi Lending | Sid Powell & Merlin Egalite

0xResearch

Crypto
Key Takeaways:
  1. Institutional capital is eyeing DeFi, pushing for tokenized real-world assets like private credit and bonds to diversify yield sources beyond crypto-backed loans. This requires robust risk isolation at the smart contract level and a new generation of independent risk assessors to bridge TradFi and DeFi.
  2. Prioritize protocols that offer explicit risk profiles and transparent fee structures, especially those building towards intent-based lending. For builders, focus on creating infrastructure that supports isolated risk and attracts independent rating agencies.
  3. The future of DeFi lending hinges on transparency and sophisticated risk management. As institutions enter, the demand for clear, independently verified risk assessments will intensify, making protocols that embrace these principles the winners in the next market cycle.
See full notes