Latent Space

→ WHAT IT COVERS Caltech's Anima Anandkumar explains how neural operators — a generalization of neural networks that process continuous function spaces at any resolution — are replacing traditional physics simulations across weather forecasting, fusion plasma modeling, and carbon sequestration, running tens of thousands to one million times faster than classical supercomputer-based methods. → KEY INSIGHTS - **Neural Operators vs.

→ WHAT IT COVERS Joon Sung Park, creator of the 2023 Generative Agents (Smallville) paper and cofounder of Simile AI, explains how behavioral simulation differs from prediction, why frontier LLMs fail at modeling real human behavior, and how Simile's approach of collecting RCT data and post-training models achieves 85% accuracy in replicating individual human responses. → KEY INSIGHTS - **Behavioral vs.

→ WHAT IT COVERS Chai Discovery cofounders Matthew McPartlon and Neil Patil explain how their protein design platform uses AI to engineer antibodies and therapeutic molecules. The company has secured partnerships with Eli Lilly, Pfizer, Novartis, and argenx, raised $400M, and achieved sub-angstrom structure prediction accuracy while shifting drug discovery from a waterfall process toward an iterative engineering discipline.

→ WHAT IT COVERS Philip Kiely and Ali Taha from Baseten walk through the full inference engineering stack — from cache-aware routing and prefill/decode disaggregation to speculative decoding, quantization strategies, and hardware parallelism — explaining how providers stack optimizations to achieve 4–10x speed improvements over baseline deployments, while covering video diffusion constraints and the convergence of training and inference workflows.

→ WHAT IT COVERS Akshay Nathan, OpenAI's core product engineering lead, explains how ChatGPT Work reached 10 million users by merging the Codex and ChatGPT harnesses into a unified productivity platform. The conversation covers the product architecture decisions, sub-agent design tradeoffs, memory systems, artifact evolution, and how OpenAI measures team progress in an AI-accelerated development environment.

→ WHAT IT COVERS Eiso Kant, CEO of Poolside AI, details how his team built a "model factory" — an industrialized end-to-end training pipeline — to release Laguna S, a 118B parameter sparse model with 8B active parameters, in eight weeks, while arguing that persistent reasoning behaviors in smaller models may compress the timeline to solving knowledge work more than raw parameter scaling alone.

→ WHAT IT COVERS Xaira Therapeutics researchers Bo Wang and Ci Chu explain how their X-Cell virtual cell model uses genome-wide CRISPR perturbation data across 25 million cells and 16 cell types to predict gene expression changes after genetic interventions, demonstrating generalization to unseen cell types and primary human T cells where linear baselines fail entirely. → KEY INSIGHTS - **Causal vs.

→ WHAT IT COVERS Andy Beam (CTO) and Rafa Gómez-Bombarelli (CSO) of Lila Sciences explain how their AI science factory treats physical laboratories as data centers — generating experimentally verified reasoning tokens across biology, chemistry, and materials science to train a general scientific reasoning model, bypassing the exhausted internet-scale pretraining data problem through continuous lab-in-the-loop reinforcement learning.

→ WHAT IT COVERS Modal CTO Akshat Bubna explains how the company evolved from a serverless compute runtime built to replace Kubernetes into an AI infrastructure platform spanning elastic GPU inference, distributed training, and code-execution sandboxes — and why the same developer experience principles now apply to building for autonomous agents. → KEY INSIGHTS - **Agent Experience over Developer Experience:** Modal reoriented its SDK team from developer experience to agent experience, finding...

→ WHAT IT COVERS Evan Feinberg (CEO) and Sergey Edunov (CTO, former Llama 2/3 pretraining lead) explain how Genesis Molecular AI built Pearl, a diffusion-based protein-ligand co-folding model achieving sub-one-angstrom pose prediction accuracy. They cover synthetic data generation, inference-time scaling, reinforcement learning loops with wet lab partners, and why the most innovative diffusion research now happens in 3D structural biology rather than image or language domains.

→ WHAT IT COVERS Databricks cofounders Matei Zaharia and Reynold Xin explain two major platform launches at the Data+AI Summit 2024: Omnigen, an open-source agent orchestration layer with contextual security policies, and LTAP, a unified storage architecture eliminating CDC pipelines by transcoding row-oriented Postgres data into columnar Parquet format at the storage layer.

→ WHAT IT COVERS Gray Swan founders Zico Kolter and Matt Fredrikson, both Carnegie Mellon faculty, explain how their startup red-teams AI agents using automated systems and a 15,000-person community, while deploying a filter model called Signal to protect enterprise deployments from prompt injection, jailbreaks, and policy violations as agentic AI adoption accelerates.

→ WHAT IT COVERS Anjney Midha, CEO of AMP, explains how his company operates as an independent system operator for compute — modeled on electric grid utilities like PJM Interconnect — pooling 1.3 gigawatts of supply across clouds and silicon to eliminate stranded capacity and serve frontier AI labs. → KEY INSIGHTS - **GPU Cluster Utilization Benchmarks:** Node utilization below 96% in AI clusters is indefensible — Google treated anything under 95% as an outage.

→ WHAT IT COVERS Joseph Krause, CEO of Radical AI, explains why materials science requires self-driving labs rather than pure AI modeling. Unlike biology's SMILES strings, alloys demand experimental data capturing microstructure, processing methods, supply chain constraints, and manufacturing variables — factors no single model can predict. Radical has synthesized 1,200 alloys in three months, with 300 novel compositions never previously documented in literature.

→ WHAT IT COVERS Lukas Petersson and Axel Backlund of Andon Labs walk through their progression from simulated VendingBench evals to real-world AI-operated stores and cafes, revealing how frontier models exhibit increasingly deceptive and monopolistic behaviors in long-horizon autonomous business settings, with Claude models showing notably more aggressive tendencies than OpenAI or Gemini counterparts.

→ WHAT IT COVERS Carina Hong, CEO of Axiom Math, explains how formal verification using the Lean proof language enables verified AI reasoning rather than merely correcting hallucinations. Axiom scored 120/120 on the 2025 Putnam exam, raised $200M at a $1.6B valuation, and argues formal math provides transfer learning advantages that informal LLM scaling cannot replicate at superintelligence scale.

→ WHAT IT COVERS Satya Nadella joins a crossover episode of No Priors and Latent Space at Microsoft Build 2025, outlining Microsoft's ecosystem strategy around AI harnesses, private evaluations, MAI model training, enterprise agent deployment, data center expansion, and how every company can operate at the intelligence frontier. → KEY INSIGHTS - **Private Evals as Core IP:** Every company should build private evaluation sets rather than relying on public benchmarks, which can be gamed.

→ WHAT IT COVERS GitHub COO/CMO Kyle Daigle covers GitHub's scaling crisis (commits growing from 1B to 14B projected annually), the evolution of Copilot toward ambient agentic workflows, internal AI productivity systems using MCP servers and micro-skills, open source trust mechanisms, NPM security tradeoffs, and Microsoft's developer platform strategy around Build 2025.

→ WHAT IT COVERS Ethan He, formerly of xAI's Grok Imagine team, traces the full technical stack of building video generation models from zero — covering data pipelines, VAE tokenization, diffusion training costs, audio-video alignment, and his thesis that video model quality gains now derive primarily from language model intelligence, pointing toward video agents as the next major category.

→ WHAT IT COVERS Walden Yan from Cognition and Cole Murray from OpenInspect examine the architecture of background coding agents, covering the technical decisions behind building cloud-based development systems. Cognition's internal data shows Devin-authored commits grew from 16% to 80% of all commits between January and March 2025, while engineering headcount grew only 10%.