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

Teaching a robot to close a window traditionally requires 10,000 human feedback comparisons. That's three days of tedious labor—per task. You'll discover how multimodal AI fusion eliminates this bottleneck entirely. Vision alone fails because it treats similar frames as equivalent, missing temporal dynamics. Language alone hallucinates success based on commands. But together, with smart conflict resolution using Probabilistic Soft Logic, they become reliable synthetic teachers. The result? Zero-shot robotics training. No human labels required. This is how foundation models are finally making robotics scalable.


Topics Covered
- The human-in-the-loop bottleneck (10,000 labels per task!)
- Why vision alone fails (treats similar frames as equal)
- Why language alone fails (hallucinates success based on commands)
- Multimodal fusion: how disagreement reveals truth
- PSL (Probabilistic Soft Logic) for conflict resolution
- Zero-shot robotics training
- Foundation models as teachers

Robots That Learn Without Humans

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

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

Robots That Learn Without Humans

NeurIPS 2025 by Basis Set