Welcome, humans.

What if every hospital could give patients access to the world’s best surgeon, performing at their absolute best, every single day?

That is the long-term promise of autonomous surgery. But before you picture a robot rolling into the operating room alone, our latest podcast episode explains what the technology can do today, what remains science fiction, and why progress looks more like a ladder than a giant leap.

Grant sat down with Mathias Unberath, CTO and co-founder of Inner Logic, formerly Semaphor, and an award-winning computer vision and simulation researcher at Johns Hopkins Whiting School of Engineering. Inner Logic just announced an $11.5M seed round co-led by General Catalyst and Bison Ventures to build the simulation and validation infrastructure surgical autonomy will need before it reaches patients.

No pressure. It only needs to work while someone is open on the table.

Here’s our favorite parts:

• (20:52) The best surgeon on their best day: Mathias explains how an autonomous system could capture elite surgical skill and reproduce it consistently across hospitals.

• (25:44) The “we’re too squishy” problem: Eyes and bones are relatively predictable. Livers, gallbladders, and other soft organs move and deform, forcing robots to adapt in real time.

• (29:07) Robots fail in deeply unnatural ways: A machine can enter a situation no surgeon would create, so developers must generate mistakes and recovery scenarios that barely exist in real-world training data.

• (33:41) The stroke treatment that cannot wait: Autonomous systems could bring specialized procedures to hospitals that lack the right expert when every minute affects a patient’s outcome.

• (52:40) Surgery’s Waymo moment: One robotic failure might become a viral story, even when the technology produces safer outcomes across the entire population.

Why watch this? The episode covers what “autonomous” really means to the uncomfortable questions that arrive once machines become better at certain surgical tasks than people.

The conversation separates today’s robot-assisted surgery from the future vision of fully autonomous surgery. You will learn why autonomy is easier with bones than soft tissue, how robots learn from demonstrations, and where humans remain essential.

Watch and/or Listen now: YouTube | Spotify | Apple Podcasts

P.S. Jump to 25:44 for Grant’s highly scientific explanation of the core challenge: “We’re too squishy.”

Keep scrolling for info on our upcoming livestream tomorrow and other recent episodes you’ll enjoy.

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JOIN US LIVE TOMORROW FOR…

Live Thursday, July 23 at 10:00 AM PT / 12:00 PM CT / 1:00 PM ET.

Grant and Corey are going live for a practical show-and-tell: the apps, games, extensions, writing systems, mini MMOs, and suspiciously specific tools they have built with AI over the past year and a half.

Corey is bringing Bean Counter, Tab Crusher, Threadline, Circle Back, and On Deck, his personal “what should I eat next?” machine. Grant is bringing FlowState, Orchestrator, LTX CineScript, Sqwirl World, and other experiments that began as tiny annoyances and somehow became real software.

Building something real is one of the fastest ways to learn what AI can actually do. You will see what worked, what broke, what burned too many tokens, and how non-technical builders can get from “this should exist” to a working thing people can use.

Also, the most important part: we’ll share how we got them online so people can actually use them.

Open the live page and hit “Notify Me” to get notified when we begin.

🎙️ In Case You Missed It…

Four recent episodes worth checking out next:

1. Want to open AI’s black box? Watch: Inside the Hidden Geometry of AI

TL;DW: Corey Noles and Grant Harvey sit down with Eric Ho, Cofounder and CEO of Goodfire, to explore what is happening inside neural networks: features, circuits, confidence signals, neural geometry, and why AI may be less of a black box than it looks.

Why you should watch: This is for anyone trying to understand how researchers might inspect, debug, steer, and intentionally design better AI systems instead of guessing what happens inside the model.

• YouTube: Watch Here

• Spotify: Listen Here

• Apple Podcasts: Listen Here

2. Want to see AI leave the browser? Watch: AI That Rides Along With Truck Drivers

TL;DW: Samsara Cofounder and CTO John Bicket explains how AI is moving into fleets, dash cams, dispatching, maintenance, and safety workflows across the physical world.

Why you should watch: This is for anyone wondering what agents look like outside office software, where bad decisions can affect vehicles, workers, equipment, and real-world operations.

• YouTube: Watch Here

• Spotify: Listen Here

• Apple Podcasts: Listen Here

3. Curious what serious AI art workflows look like? Watch: ComfyUI Proves AI Art Is Not Zero Effort

TL;DW: Yannik Marek, cofounder and original creator of ComfyUI, explains how node-based workflows give creators control over models, parameters, memory, hardware, and repeatable visual production.

Why you should watch: If prompt boxes make AI art feel like a slot machine, this shows the other side: visible pipelines, technical choices, iteration, and real creative intent.

• YouTube: Watch Here

• Spotify: Listen Here

• Apple Podcasts: Listen Here

4. Want to learn how OpenAI trains agents to learn from experts? Watch: Can AI Agents Learn From Expert Corrections?

TL;DW: OpenAI engineers John de Wasseige and Arthur Fernandes Araujo explain how Tax AI turns accountant corrections into structured signals, evals, traces, and scoped product improvements.

Why you should watch: Do not let the word “tax” scare you off. This is an AI engineering masterclass on preserving evidence, handling edge cases, and building agents that improve through expert review.

• YouTube: Watch Here

• Spotify: Listen Here

• Apple Podcasts: Listen Here

Bonus: Follow the work

Learn more about Inner Logic’s work on surgical AI and procedural medicine:

• Website: semaphorsurgical.com/innerlogic

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Stay curious,

The Neuron Team

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