NeurIPS 2025 by Basis Set

AI is a time machine, compressing years of lab work into days. Digital organisms simulate biology at every scale for drug discovery. AI-optimized sensor placement achieves the same results with 1% of traditional compute. Healthcare AI can predict disease 20 years early. But here's the reality check: zero generative AI systems have FDA approval for clinical use. Zero. You'll explore the gap between academic proof-of-concept and clinical deployment, the dual-use risk where the same models design both therapeutics and pathogens, and the central tension this entire series builds toward: we're accelerating discovery at unprecedented speed—but at what risk? How do we regulate systems that constantly learn and evolve? This finale leaves you with the right question to sit with. Topics Covered - Digital organisms: simulating biology at all scales - GNNs vs. transformers for biological discovery - Drug discovery: academic proof of concept vs. clinical reality - Sensor optimization (1% of traditional compute!) - Healthcare AI potential: predicting disease 20 years early - Healthcare AI reality: persistent failures in stress tests - Dual-use risk: same model designs therapeutics and pathogens - FDA's stance: zero approved generative AI, mandatory accountability - Interaction intelligence as a safety variable

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

Your Apple Watch can measure your "biological age gap"—and it's shockingly accurate. Smokers appear 4-6 years older. Pregnancy temporarily ages you 3.5 years. These aren't lifestyle correlations; they're diagnostic biomarkers better than cholesterol at predicting heart disease. You'll discover how self-supervised learning unlocks this power from noisy brain and body signals without requiring expensive manual labels. An elegantly simple trick—teaching models which EEG windows are close or far apart in time—achieves massive data efficiency. But the real breakthrough? Brain-computer interfaces that read your subconscious "oops" signal. When you intend to click but your brain detects an error, the system suppresses it—boosting accuracy from 90% to 99%. The scaling is imminent: from dozens of hours of brain data to millions. Topics Covered - Self-supervised learning (SSL): learning data structure without labels - The relative positioning task for EEG: elegantly simple, incredibly powerful - Scaling laws: more hours per subject > more subjects (depth > breadth) - Dual-branch cognitive decoding: brain activity → semantic meaning - Image reconstruction from brain signals (proving semantic decoding works) - PPG age gap biomarker: 2x heart disease rate in young adults, better than cholesterol - BrainJapa and BrainHarmony for MCI prediction - Synchron's Stentrode: minimally invasive BCI via jugular vein - Error detection primitive: subconscious "oops" signal for 90% → 99% accuracy

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

"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 commerce ecosystem is massive, so massive that the sector can sustain entire infrastructure unicorns building nothing but tools and services enabling commerce businesses. In this conversation between Catherine Stewart, Board Partner at Basis Set and fmr COO of Shippo, and BSV investor John Mannes, we discuss the new APIs, customs automation and cross-border fulfillment and payments infrastructure that will support more streamlined, but globally capable supply chains.

The proposed $2 trillion dollar U.S. infrastructure package will create major incentives for the adoption of climate technology and offer startups many pathways to secure growth funding. In this conversation between Mona Sheth, Senior Director of Federal Government Relations for Schneider Electric, two policy experts from DC-based government affairs firm Lot 16 and BSV investor John Mannes, we discuss how founders can navigate billions in new non-dilutive funding opportunities for climate tech startups.

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.

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.

The 2008 financial crisis catalyzed the most ambitious real estate technology startups ever founded. Airbnb changed the way homeowners conceptualize home value, Opendoor simplified real estate transactions in a way the industry never thought possible and Compass redefined the role technology plays in agent workflows. As we wade deeper into the Covid-19 crisis, we’ll see similar attempts at differentiated businesses models and novel financial products that help homeowners extract greater value, more conveniently, out of their largest assets. In this conversation between Sheila Vashee, the VP of Growth and Marketing at OpenDoor, a real estate unicorn simplifying the process of buying and selling homes, and BSV investor John Mannes, we discuss how the real estate industry is being affected by Covid-19 and the important role technology will play in keeping transactions happening and keeping people in their homes coming out of the crisis.

Covid-19 is disrupting global flows of goods and people at an unprecedented scale. During the War on Terror, the government invested in technology to keep borders open and trade flowing. Our current pandemic requires a similar investment in a new generation of data infrastructure. If we can stitch together the right data, we can put an end to conversations about closing borders or subjecting large numbers of people and goods to draconian one-size-fits all quarantines and travel bans. In this conversation between Ari Schuler, the creator and former head of U.S. Customs and Border Protection’s Innovation Team (INVNT) and VP of Emerging Markets at Daon and BSV investor John Mannes, we discuss how customs and trade are are being affected by Covid-19 and the important role new data streams will play in helping CBP respond to future pandemics.