Latent Space: The AI Engineer Podcast

The First Mechanistic Interpretability Frontier Lab — Myra Deng & Mark Bissell of Goodfire AI

Goodfire's Mark Bissell and Myra Deng join the Latent Space podcast to discuss interpretability in AI, defining it as a set of methods to understand, learn from, and design AI models, emphasizing its application in production scenarios and high-stakes industries. The conversation explores the challenges and opportuniti...

🔬 Automating Science: World Models, Scientific Taste, Agent Loops — Andrew White

The podcast explores the intersection of AI and science, particularly the automation of scientific discovery. Andrew White, co-founder of Future House and Edison Scientific, discusses his journey from academia to industry, highlighting the potential of AI agents in automating the cognitive processes of scientific resea...

🔬 Automating Science: World Models, Scientific Taste, Agent Loops — Andrew White

⚡️ Prism: OpenAI's LaTeX "Cursor for Scientists" — Kevin Weil & Victor Powell, OpenAI for Science

OpenAI is launching Prism, a free AI-native LaTeX editor designed to accelerate scientific writing and collaboration. Kevin Weil, VP of OpenAI for Science, and Victor Powell, Prism's product lead, discuss how Prism embeds AI directly into the writing workflow, demonstrated by features such as AI-powered proofreading, d...

Captaining IMO Gold, Deep Think, On-Policy RL, Feeling the AGI in Singapore — Yi Tay

Reasoning and reinforcement learning (RL) represent the current frontier of AI development, shifting from imitation-based training to on-policy methods where models refine their own trajectories through self-generated rewards. This paradigm shift enabled the development of end-to-end models capable of achieving IMO Gol...

Captaining IMO Gold, Deep Think, On-Policy RL, Feeling the AGI in Singapore — Yi Tay 2

The conversation centers on the progress and future directions of AI research, particularly within Google's DeepMind. Yi Tay, from the Gemini team in Singapore, reflects on his return to Google, the shift towards reasoning and reinforcement learning (RL), and the pursuit of AGI. The discussion highlights the IMO gold m...

Brex’s AI Hail Mary — With CTO James Reggio

Brex’s AI Hail Mary — With CTO James Reggio

Brex CTO James Reggio discusses Brex's AI transformation, focusing on a three-pillar strategy: corporate AI adoption, operational cost reduction, and product AI features. Brex embraces hiring ex-founders, offering them opportunities to build AI applications with instant distribution to a vast customer base. The enginee...

Artificial Analysis: The Independent LLM Analysis House — with George Cameron and Micah Hill-Smith

Artificial Analysis founders Micah Hill-Smith and George Cameron discuss the evolution and future of AI benchmarking with Swyx. They detail their journey from a side project to a company providing independent AI model analysis, emphasizing their commitment to unbiased metrics. They address the challenges of evaluating ...

Artificial Analysis: The Independent LLM Analysis House — with George Cameron and Micah-Hill Smith

The podcast explores the evolution and business model of Artificial Analysis (AA), a company specializing in independent AI benchmarking. Founders Micah-Hill Smith and George Cameron discuss AA's origins as a side project born from the need for objective model evaluation, detailing their transition to a sustainable bus...

Artificial Analysis: Independent LLM Evals as a Service — with George Cameron and Micah-Hill Smith

Artificial Analysis founders Micah-Hill Smith and George Cameron discuss the evolution and future of AI benchmarking with Swyx. They detail their journey from a side project to a company providing independent AI model analysis, emphasizing the importance of objective metrics. They cover their business model, which incl...

[State of Evals] LMArena's $1.7B Vision — Anastasios Angelopoulos, LMArena

In this interview, Swyx speaks with Anastasios Angelopoulos from Arena, discussing Arena's journey from LMSys at Berkeley to a standalone company, its recent $100 million funding, and the principles guiding its platform. Anastasios explains that the funding will primarily support inference costs and platform developmen...

[State of Evals] LMArena's $1.7B Vision — Anastasios Angelopoulos, LMArena

[NeurIPS Best Paper] 1000 Layer Networks for Self-Supervised RL — Kevin Wang et al, Princeton

[NeurIPS Best Paper] 1000 Layer Networks for Self-Supervised RL — Kevin Wang et al, Princeton

In this episode of Latent Space, the host interviews Kevin Wang and his team (Benjamin Eysenbach, and Ishaan) from Princeton about their NeurIPS best paper award-winning project on scaling deep reinforcement learning (RL). Kevin discusses the motivation behind exploring deeper networks in RL, drawing parallels to the s...

[State of Code Evals] After SWE-bench, Code Clash & SOTA Coding Benchmarks recap — John Yang

In this podcast episode, John Yang discusses the evolution and extensions of SWE-bench, including multilingual and multimodal versions, and addresses the emergence of independent benchmarks like SWE-bench Pro. He introduces CodeClash, a programming tournament for language models, and highlights other related works such...

[State of Code Evals] After SWE-bench, Code Clash & SOTA Coding Benchmarks recap — John Yang

[State of Post-Training] From GPT-4.1 to 5.1: RLVR, Agent & Token Efficiency — Josh McGrath, OpenAI

[State of Post-Training] From GPT-4.1 to 5.1: RLVR, Agent & Token Efficiency — Josh McGrath, OpenAI

This podcast features an interview with Josh McGrath from OpenAI, who discusses his work on thinking models and search-related projects. He reflects on the shift from pre-training to post-training, highlighting the challenges and excitement of influencing model behavior. McGrath shares insights on RL runs, the use of C...

[State of RL/Reasoning] IMO/IOI Gold, OpenAI o3/GPT-5, and Cursor Composer — Ashvin Nair, Cursor