This episode features Andy Beam and Rafa Gómez-Bombarelli from Lila Sciences, discussing their vision for AI science factories as the next frontier for generating internet-scale datasets. They explain how their automated labs, leveraging AI…
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Alistair Pullen, CEO of Cosine, discusses the UK's initiative to build a sovereign large language model (LLM) in response to US export controls on frontier AI like Fable. He explains Cosine's strategy to compete with larger labs by focusing…
David Dalrymple, known as Davidad, discusses his shift from formal verification approaches to an 'Alignment with Awakening' framework, emphasizing the formation of coalitions of aligned AIs that recognize shared moral truths. He shares empi…
formal verificationsafe AI containmentworld modelsproof infrastructureAI wisdommoral realismreinforcement learninginoculation promptingmulti-agent systemsbodhitropic alignmentAI interiorityobjectificationUS-China AI cooperationcatastrophic riskrecursive self-improvementsystem promptingalignment techniquescoalition of aligned AIsAI ethicsAI governance
Tim Scarfe interviews the Tufa Labs ARC-AGI-3 team to dissect their winning approach on the ARC-AGI-3 benchmark, focusing on how their system discovers goals and balances exploration with action efficiency. The episode explores the challeng…
ARC-AGI-3 benchmarkgoal acquisitionaction efficiencyexploration vs exploitationlanguage modelsplanning in AIcoding agentsrequirements engineeringcore knowledge priorsabstraction synthesisreinforcement learningAI safetybitter lessonneural guided searchLLM reasoningsoftware engineering AIbenchmark designgeneral intelligence
🔬 The Coolest Diffusion Research Isn't in LLMs — Evan Feinberg & Sergey Edunov, Genesis Molecular AI
In this episode of Latent Space, Evan Feinberg and Sergey Edunov of Genesis Molecular AI discuss their pioneering work in applying diffusion models to protein-small molecule interactions for drug discovery. They explain how their foundation…
This episode features Thomas von Tschammer of Neural Concept, discussing how physics-aware AI is revolutionizing product engineering. Neural Concept's models accelerate design evaluation from days to minutes, enabling companies like Jaguar …
AI in engineeringProduct designAutomotive industryAerodynamicsHeat dissipationCollision safetyComputer-Aided Design (CAD)Physics-based simulationReinforcement LearningFormula One racingElectric vehicles (EVs)Thermal managementElectromagnetismStructural dynamicsBattery cool-platesSoftware engineeringChina's manufacturing speedProduct differentiationAutonomous drivingNew form factorsHumanoid roboticsManufacturing agility
This episode argues that current AI progress is primarily driven by an immense quantity of high-quality, task-specific data, rather than improvements in sample efficiency. The speaker highlights the vast data requirements of frontier models…
Carina Hong, CEO of Axiom Math, discusses the company's recent $200M Series A funding and their perfect Putnam exam score, highlighting their mission to scale "verified AI" through formal mathematics. She explains how formal verification, u…
Formal verificationAI for mathLean proof assistantMathematical discoveryPutnam examHardware verificationSoftware verificationRecursive self-improvementAI agentsTransfer learningAuto-formalizationCode generationComputational complexityReinforcement learningKnowledge graphsInterdisciplinary teamsStartup funding
Eric Jang explains how to build AlphaGo from scratch using modern AI tools, detailing the game of Go's rules and the core Monte Carlo Tree Search (MCTS) algorithm. He describes how deep neural networks, specifically value and policy network…
The RL Fine-Tuning Playbook: CoreWeave's Kyle Corbitt on GRPO, Rubrics, Environments, Reward Hacking
Kyle Corbitt, founder of OpenPipe and leader of CoreWeave's serverless training team, provides a master class on reinforcement learning (RL) and custom fine-tuning for AI models. He explains how RL differs from supervised fine-tuning (SFT) …
This episode features Qasar Younis and Peter Ludwig, co-founders of Applied Intuition, discussing their company's mission to build physical AI for various moving systems like cars, trucks, and mining equipment. They delve into the evolution…