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AI Podcasts

January 30, 2026

JetBrains + Weights & Biases: Establishing frameworks and best practices for enterprise AI agents

Weights & Biases

AI
Key Takeaways:
  1. The rapid expansion of AI agents from research labs to enterprise production demands a corresponding maturation of development and operational tooling. This mirrors the evolution of traditional software engineering, where observability became non-negotiable for complex systems.
  2. Implement robust observability and evaluation frameworks from day one for any AI agent project. This prevents costly debugging cycles and ensures core algorithms function as intended, directly impacting performance and resource efficiency.
  3. Reliable AI agent development hinges on transparent monitoring and evaluation. Prioritizing these capabilities now will determine which organizations can successfully deploy and scale their AI initiatives over the next 6-12 months.
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January 31, 2026

State of AI in 2026: LLMs, Coding, Scaling Laws, China, Agents, GPUs, AGI | Lex Fridman Podcast #490

Lex Fridman

AI
Key Takeaways:
  1. The Macro Shift: Global AI pivots from raw model size to sophisticated post-training and efficient inference. China's open-weight models force a US strategy re-evaluation.
  2. The Tactical Edge: Invest in infrastructure and talent for RLVR and inference-time scaling. These frontiers enable new model capabilities and economic value.
  3. The Bottom Line: AI's relentless progress amplifies human capabilities. Focus on systems augmenting human expertise and navigating ethical complexities. Real value lies in intelligent collaboration.
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January 31, 2026

Inside a Chinese AI Lab: How MiniMax Builds Open Models

Turing Post

AI
Key Takeaways:
  1. Open-source AI is moving from theoretical research to production-grade agentic systems.
  2. Prioritize deep engineering talent and first-principles problem-solving over chasing algorithmic novelties.
  3. The next 6-12 months will separate the AI builders who can truly operationalize advanced models from those who can't.
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January 30, 2026

Anthropic’s Rise: Is OpenAI Losing Its Lead? w/ Patrick & Duncan

Milk Road AI

AI
Key Takeaways:
  1. Trillion-dollar AI compute investments create market divergence: immediate monetization (Meta) is rewarded, while slower conversion (Microsoft) faces skepticism, as geopolitical tensions rise over open-source model parity.
  2. Prioritize AI models balancing raw intelligence with superior user experience and collaborative features, as developer loyalty and enterprise adoption increasingly hinge on usability.
  3. The AI landscape is rapidly reordering. Investors and builders must assess monetization pathways, geopolitical implications, and AI's social contract over the next 6-12 months.
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January 29, 2026

AI math capabilities could be jagged for a long time – Daniel Litt

Epoch AI

AI
Key Takeaways:
  1. The collapse of trial costs turns scientific discovery into a search problem.
  2. Prioritize verifiable problems where AI can provide a clear reward signal.
  3. AI will solve mildly interesting problems soon, but the Big Ideas still require human marination.
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January 25, 2026

If You Can't See Inside, How Do You Know It's THINKING? [Dr. Jeff Beck]

Machine Learning Street Talk

AI
Key Takeaways:
  1. The Macro Trend: The transition from opaque scaling to verifiable reasoning.
  2. The Tactical Edge: Audit your models for brittleness by testing them on edge cases that require first principles logic rather than historical data.
  3. The Bottom Line: The next winners in AI will not have the biggest models but the most verifiable ones. If you cannot prove how a model reached a conclusion, you cannot trust it in production.
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January 23, 2026

Abstraction & Idealization: AI's Plato Problem [Mazviita Chirimuuta]

Machine Learning Street Talk

AI
Key Takeaways:
  1. Transition from "Spectator Knowledge" (passive data absorption) to "Interactive Knowledge" (agentic engagement).
  2. Prioritize "embodied" AI architectures that integrate sensory feedback loops.
  3. AGI will not be solved by better math alone. It requires accounting for the physical and biological constraints that define intelligence.
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January 23, 2026

Captaining IMO Gold, Deep Think, On-Policy RL, Feeling the AGI in Singapore — Yi Tay 2

Latent Space

AI
Key Takeaways:
  1. The transition from more data to better thinking via inference-time compute. Reasoning is becoming a post-training capability rather than a pre-training byproduct.
  2. Use AI for anti-gravity coding to automate bug fixes and data visualization. Treat the model as a passive aura that buffs the productivity of every senior engineer.
  3. AGI will not be a collection of narrow tools but a single model that reasons its way through any domain. The gap between closed labs and open source is widening as these reasoning tricks compound.
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January 21, 2026

"We Made a Dream Machine That Runs on Your Gaming PC"

Machine Learning Street Talk

AI
Key Takeaways:
  1. The transition from static LLMs to interactive world models marks the move from AI as a tool to AI as a persistent environment.
  2. Monitor the Hugging Face release of the 2B model to build custom image-to-experience wrappers for niche training or spatial entertainment.
  3. Local world models will become the primary interface for spatial computing within the next year, making high-end local compute more valuable than cloud-based streaming.
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Crypto Podcasts

August 18, 2025

What Liquid Funds Are Buying

Empire

Crypto
Key Takeaways:
  1. Concentrated Bets on Fundamentals Win. The era of "spray and pray" is over. The new meta is building highly concentrated portfolios (10-15 tokens) based on deep fundamental analysis of protocols with clear revenue models and product-market fit.
  2. Digital Asset Treasuries Are TradFi's On-Ramp. DATs are more than a short-term trade; they are the primary bridge for institutional capital to gain crypto exposure. Their marketing power is proving to be as crucial as their financial engineering.
  3. The 24/7 Market Is Coming. The tokenization of equities isn't a matter of *if* but *when*. This shift will create a fiduciary obligation for funds to move to on-chain assets, forcing a rapid, systemic evolution of financial markets.
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August 16, 2025

Why DATs Beyond BTC And ETH Are Risky

Empire

Crypto
Key Takeaways:
  1. **Concentrate on the Winners:** Bitcoin is the established store-of-value asset, and Ethereum is the dominant settlement layer for high-value digital assets. The data shows they have already won their respective categories.
  2. **The Rest is a Long Tail of Risk:** Investing outside of Bitcoin and Ethereum is a bet against powerful, gravity-like market forces. These alternatives are competing for a sliver of the market, increasing their risk of becoming obsolete.
  3. **Power Law is the Rule:** The market isn't about finding the "next" Ethereum; it's about recognizing that power laws are creating a duopoly where the vast majority of value will continue to accrue to the top two assets.
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August 16, 2025

Can ETH Keep Pumping Or Is It All Over?!

Steady Lads Podcast

Crypto
Key Takeaways:
  1. The New Game is Financial Engineering. The market's primary driver is the "Digital Asset Treasury" meta. Bitcoin leverages its "pristine collateral" narrative for debt financing, while Ethereum leverages native yield to justify its premium.
  2. Don't Expect a 2021 Redux. The institutional capital fueling this rally is not here to bid on your favorite altcoin. Their focus is on BTC, ETH, and treasury-related arbitrage, making a widespread, retail-driven altcoin season unlikely.
  3. De-Risk and Secure Profits. After a 3x run, seasoned traders are taking profits on ETH. The consensus is to refuse to round-trip your gains, pay down on-chain debt, and shift to scalping volatility rather than betting on a continued parabolic advance.
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August 15, 2025

The Best of Bell Curve

Bell Curve

Crypto
Key Takeaways:
  1. **Execution Guarantees Trump EVM Compatibility:** For complex financial products like derivatives, the ability to mathematically prove solvency outweighs the benefits of EVM compatibility, driving the rise of purpose-built L1s.
  2. **Memecoins Are a Macro Indicator:** Don't dismiss memecoins as a distraction. They are a direct, high-beta response to monetary debasement, signaling retail's desperation for returns in a broken financial system.
  3. **The Consumer War Is On:** While Ethereum solidifies its hold on institutional finance, the battle for consumer attention is just beginning. The success of its coordinated L2 strategy will determine if it can reclaim the narrative from chains like Solana.
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August 15, 2025

The Ether Machine Chairman: Real Risk of DATs, Who Wins From Stripe & Circle’s Chains | Roundup

Empire

Crypto
Key Takeaways:
  1. Structure Over Speed: In the DAT gold rush, avoid the shells. Reverse takeovers are fraught with hidden liabilities; cleaner de-novo SPACs are built for long-term institutional trust and better financing.
  2. Stick to the Winners: The DAT market will consolidate. Bet on pure-play vehicles for top-tier, liquid assets like ETH, as "Frankenstein" and illiquid-token DATs are destined for M&A or failure.
  3. Distribution is Destiny: In the payments war, Stripe’s direct ownership of millions of merchants gives it a crushing advantage over Circle’s middleware approach. Owning the customer is the only moat that matters.
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August 14, 2025

Bittensor Brief #4: Could $TAO Enter The Top 10?

Hash Rate pod - Bitcoin, AI, DePIN, DeFi

Crypto
Key Takeaways:
  1. Incoming Institutional Tsunami: An estimated $1.5 billion in institutional capital is poised to enter the ecosystem in the next six months, which could single-handedly 5x the price due to limited exchange liquidity.
  2. The Subnet Demand Spiral: The core mechanics of registering and participating in subnets create a flywheel effect where ecosystem growth directly translates into increased demand and reduced circulating supply for $TAO.
  3. The Halving Supply Shock: A December halving will slash new $TAO emissions by 50%, tightening supply just as multiple demand vectors are peaking, creating a potentially explosive supply-demand imbalance.
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