This podcast series cuts through AI hype to deliver what technical professionals actually need: honest assessments of what works, what fails, and why it matters. Curated from NeurIPS 2025—the world's premier AI research conference—these 11 episodes translate cutting-edge research into accessible narratives without dumbing down the substance.

NeurIPS 2025 Podcast by Basis Set

AI just decoded dolphin signature whistles. Citizen scientists are identifying frog species with their phones. "Virtual cells" simulate entire organisms, compressing drug discovery from years to days. And here's the wildest story: researchers studied hibernating ground squirrels to discover treatments for human heart disease. You'll discover how AI is accelerating scientific breakthroughs across biology and materials science, from bioacoustics to autonomous lab robots that design and run their own experiments. But there's a darker side—the same techniques enabling therapeutic discoveries could be weaponized. This episode balances inspiring possibilities with honest biosecurity concerns.


Topics Covered
- Bioacoustics: AI understanding animal communication
- Self-supervised learning for acoustic analysis
- Virtual cells and digital organisms
- Drug discovery acceleration (years to days)
- Comparative genomics: learning from animal superpowers
- Autonomous lab agents (robots that run their own experiments)
- Biosecurity: the dual-use risk of biological AI

AI Transforms Scientific Discovery

Why does every naive data scientist who tries to predict stock prices end up depressed? Finance systematically breaks standard AI. You'll discover the four methodological pitfalls: data scarcity (10 years of daily data = only 2,500 observations—laughably insufficient), look-ahead bias (accidentally using future data), the unconditional trap (models validate but can't predict what matters), and heavy tails (the rare crashes that define risk). The analogy that sticks: "It's like having an umbrella that doesn't work when it rains." But there's a solution. Task-driven training matches the P&L of benchmark strategies instead of learning impossible 10,000-dimensional distributions. You'll hear about dynamic portfolios that spontaneously switched hedging instruments during COVID, lasso regression for cost-effective hedging, and the "Persona Ledger" method—LLM-generated synthetic data with accounting rules as constraints. Finance breaks AI, but sophisticated methodologies are fixing it.


Topics Covered
- The "naive data scientist depression": why finance breaks standard AI
- Four methodological pitfalls: data scarcity, look-ahead bias, unconditional trap, heavy tails
- Task-driven training: matching strategy P&L instead of price prediction
- Dynamic vs. static portfolios (encoding timing and regime changes)
- Lasso regression for sparse hedging (minimizing transaction costs)
- Agentic pipelines: GPU-accelerated end-to-end workflows
- LLM challenges: time travel problem, implicit investment biases, stubbornness
- Persona Ledger: LLM-generated synthetic data with stateful verification

Generative AI in Finance

Stop worrying about superintelligence. The real threat? "Good enough" AI deployed at massive scale. Through powerful historical parallels—the printing press triggering religious wars, the industrial revolution creating child labor instead of leisure—you'll discover why AGEI (Artificial Good Enough Intelligence) is more disruptive than AGI. When mediocrity can be deployed instantly and cheaply, the hidden frictions holding society together disappear. This episode reframes how you think about AI risk by focusing on what's actually happening now, not science fiction futures.


Topics Covered
- AGEI: Artificial Good Enough Intelligence vs. AGI
- Historical disruption patterns (printing press, industrial revolution)
- Why we consistently mispreddict technology's native capabilities
- Hidden frictions that hold society together
- The fragility of systems when mediocrity scales instantly

Society's Fragile Equilibrium

OpenAI's o1 and o3 aren't just better language models—they actually think. You'll learn how reinforcement learning creates genuine reasoning capabilities, but also discover the dark side: "mode collapse" creates an artificial hivemind where models converge to eerily similar responses. The uncomfortable truth? Even the best RL refines existing knowledge rather than discovering new concepts, and there's a 1000x gap in data efficiency between AI and human brains. This episode cuts through the hype around reasoning models to show you what's real and what's still missing.


Topics Covered
- Large Reasoning Models (LRMs) vs. traditional LLMs
- Reinforcement learning mechanics (explained accessibly)
- The mode collapse problem (AI converging to similar responses)
- Data scaling wall and synthetic data challenges
- Why small models (32B parameters) are rising in importance
- The verification crisis in AI deployment

The Reasoning Revolution

What if you could train DALL-E 23 times faster by adding a single token? That's RACK, and it's almost free. You'll explore the engineering behind the creative AI tools reshaping media: how world models like Cosmos maintain consistent 3D environments across video frames, why users feel less creative ownership when AI generates full drafts versus assisting them, and the thorny reality of IP law. Is "perceptual similarity" the same as copyright infringement? Should we care about "Fairly Trained" versus "Fairly Deployed"? This episode demystifies the systems creating the images and videos flooding your feeds.


Topics Covered
- RACK: 23x faster diffusion training (almost zero cost!)
- Grafting: modifying trained models without starting over
- World models for consistent video generation
- Physics integration in creative AI
- IP and copyright: Fairly Trained vs. Fairly Deployed
- Human-AI collaboration dynamics
- Why perceptual similarity ≠ legal liability

Engineering Creative AI

"Passes the bar exam" doesn't mean AI can practice law. "Beats humans on ImageNet" doesn't mean it understands images. You'll learn why most AI benchmarks are fundamentally broken through the cautionary tale of the "infant morality study"—researchers thought babies preferred moral helpers, but they just liked bouncing balls. The Clever Hans effect is alive and well in 2025. If you're evaluating AI products, making purchasing decisions, or relying on AI benchmark claims, this episode gives you the critical thinking tools to cut through the nonsense.


Topics Covered
- Construct validity: Are we testing what we think we're testing?
- The anthropomorphism trap: projecting human limitations onto AI
- Why "passing the bar exam" doesn't mean AI can practice law
- The Clever Hans problem in modern AI
- EU AI Act and regulatory approaches
- Testing AI like we test babies and animals (alien intelligence framework)

The Evaluation Crisis

The history of American agriculture is a story of technology improving the efficiency of production. But the volatile global economy of the last decade is showing the industry that efficiency is not everything. Changing consumer taste coupled with increasing pressures of commoditization are forcing farmers to embrace technology as a lever for much needed differentiation.

In this conversation between Matt Nicoletti, the Head of Business Development and Venture Investing at Penny Newman, one of the largest grain distributors in the western United States, and BSV investor John Mannes, we discuss how the agriculture sector is being affected by Covid-19 and the important role technology will play in keeping farms afloat as industry consolidation accelerates amidst a growing economic recession.

Farmers Facing Covid Consolidation Must Differentiate, ft. Head of VC Investing, Penny Newman Grain

73% of companies surveyed in a new report, identify as having encountered major issues in their supply chains as a result of Covid-19. The disruption has been so significant, that major brands are reconsidering once sacred supply chain doctrine. Companies are considering moving operations out of China, holding more inventory in stock and collaborating with competitors to source. 

In this conversation between David Shillingford, the chairman of Resilience360, a supply chain risk software company jointly owned by DHL and Columbia Capital, and BSV investor John Mannes, we discuss a new report quantifying the impact of Covid-19 on global supply chains and discuss the implications for the tech ecosystem.

Quantifying Covid’s F500 Supply Chain Impact ft. Chairman of Resilience360 (DHL + Columbia Cap)

While most industries have had enough to manage with Covid-19, the oil and gas sector has had to manage the pandemic, along with a fierce price war between Russia and Saudi Arabia and broader existential questions about its identity in the face of the energy transition. 

In this conversation between Iain Cooper, a nearly 30 year veteran of multinational oil field services company Schlumberger and current CEO of drone gas emissions inspection startup SeekOps, and BSV investor John Mannes, we discuss how each facet of the oil & gas industry has been impacted by Covid-19 and unpack the impact of these macro shocks on technology adoption.

Making the Business Case for Emissions Reduction

While Covid-19 has pushed technology deeper into the deskless workforce, it’s also elucidating shortcomings of existing tools not optimized for the unique challenges of specific industries and regions of the world. 

In this conversation between Kris Kemeny, Managing Director of the venture arm for Tekfen, one of Turkey’s largest industrial conglomerates, and BSV investor John Mannes, we discuss how founders can build for the global deskless workforce while localizing solutions for customers.

Building for the global deskless workforce: lessons from one of Turkey’s largest conglomerates

This podcast series cuts through AI hype to deliver what technical professionals actually need: honest assessments of what works, what fails, and why it matters. Curated from NeurIPS 2025 — the world's premier AI research conference — these 11 episodes translate cutting-edge research into accessible narratives without dumbing down the substance.

Basisset.com

Generative AI in Finance

NeurIPS 2025 by Basis Set

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