Latent Space: The AI Engineer Podcast

Academia is for Ambition — Alex Zhang, MIT

Last call for regular tickets for AI Engineer NYC! As an exclusive for Latent Space subscribers, the first 30 of you can take a 30% off code if it helps - for new tickets

Why Dwarkesh is Wrong about Computer Use + How OpenAI shipped its Jev competitor in 1 Week

Three months ago Dwarkesh, who has been posting incredible blogs and episodes about RL, posted a framing question for his video essay on RLVR which upset a lot of Compute

Claude Code’s Next Era — Thariq Shihipar, Anthropic

We are excited to have Anthropic share their latest AI x Finance work at AI Engineer New York, coming up in 2 weeks! In case you’ve been under a rock, here’s a non-exhau

OpenRouter: from Seed to Stripe — with OpenRouter’s Alex Atallah & AMP’s Anjney Midha

From the earliest days of open-weight models to becoming the neutral routing layer for more than 10 million developers, OpenRouter is one of the clearest bets that the fu

Runway’s WorldPrompt and the Engineering of Real-Time Worlds

Earlier this month, world model company Runway introduced GWM Worlds 2, a research preview that “turns high-fidelity video and audio generation into real-time interactive

🔬Bio-security is an AI Arms Race - Eric Nguyen (CEO, Radical Numerics)

The OpenAI → Hugging Face attack has people asking “what else do we need to worry about?” and Anthropic’s filters flag two things: cyber-security and biology. The natural

🔬 An Oscar, Two Asteroids, and the Algorithm in Your sklearn: John Platt on AI for Science

How often do you get to talk to a guest who has both an Academy Award and who invented textbook machine learning algorithms? John Platt has an Oscar, two textbook algorit

Jev: System One models for Prod, not God — with Diogo Almeida, CEO, TypeSafe AI

Tickets for AIE NYC now open, and apply for the invite-only AIE CODE. Join us! We have an unusual relationship with today’s guest: for years since coauthoring the Instru

Underwriting Superintelligence: Backing Agents you can Sue — Rune Kvist, AIUC

AIUC first got our attention with the NFDG backing, and have just announced a $40M series A today, with the most impressive industry advisor list we may have ever seen fo

Humanity’s Last Invention — Richard Socher of Recursive

At 1:09:00 we talk about the rise of AI x Finance, and AIE NYC is one month away - our hotel block is 97% sold out, get tix & travel ASAP - we will announce speakers from

🔬“We have foundation models for language, not for physics” — Anima Anandkumar, Bren Professor of Computing

A few years ago, Caltech Prof. and co-founder of Accelerated Understanding, Anima Anandkumar set out to develop the first open-source weather model with AI. Talking to ex

Simulation: the new Scaling Law — Joon Sung Park, Simile AI

When we first dicsussed the Summer of Simulative AI in 2024 we knew it would be a brief summer, but it has recently come back with a vengeance with SimGym in April and no

🔬The BioAI Phase Shift - Matthew McPartlon & Neil Patil, Chai Discovery

This January, four big AI × Pharma tools deals were announced at the huge JPM Pharma conference that takes over San Francisco every year. OpenAI-backed Chai Discovery (no

The Inference Engineering Masterclass — Philip Kiely & Ali Taha, Baseten

Watch the full episode on YouTube: We first covered Baseten last year when DeepSeek mania was at peak hype. Now they have raised a monster $13B round and become one of t

Codex from 0 to 10M Users: Building ChatGPT Work — Akshay Nathan, OpenAI

There are roughly 100x more people who use code than who can write code. As code that “just works” becomes easier to generate, this group may be the biggest prize of all

Inside the Model Factory — Eiso Kant, Poolside AI

In recent months, the open vs closed, and US vs China discussions on model ownership and sovereign/local AI have heated up to a fever pitch. So it is very very good news

🔬Causal Models Need Causal Data - Xaira’s X-Cell model for Drug Discovery (Bo Wang & Ci Chu, Chief Discovery Officer & Chief AI Scientist)

Bet on information If test loss flatlines after 1.5B parameters while training loss continues to drop as you scale, that tells you that your model is limited by the amou

🔬 The Lab of the Future Should Feel Like a Data Center — Andy Beam & Rafa Gómez-Bombarelli, Lila Sciences

Imagine a dark warehouse. Racks and racks of devices with wires, tubes, and electronics sticking out. The next AI data center? No. This is Lila Sciences‘ dream for the fu

Why AI Infrastructure must evolve for Agent Experience — Akshat Bubna, Modal CTO

We’ve been running a bit of an Agent Cloud series surveying all the top inference/compute/cloud providers, from Databricks to Daytona to Railway and, even further back, E

🔬 The Coolest Diffusion Research Isn't in LLMs — Evan Feinberg & Sergey Edunov, Genesis Molecular AI

This episode has a fun personal twist: There’s a counterfactual world where I was employee #1 at Genesis Molecular AI, the company behind today’s episode. A certain intro