Elon Musk — "In 36 months, the cheapest place to put AI will be space”

Dwarkesh Podcast

In this episode, John and I got to do a real deep-dive with Elon. We discuss the economics of orbital data centers, the difficulties of scaling power on Earth, what it would take to manufacture humanoids at high-volume in America, xAI’s business and alignment plans, DOGE, and much more.

Watch on YouTube; read the transcript.

Sponsors

* Mercury just started offering personal banking! I’m already banking with Mercury for business purposes, so getting to bank with them for my personal life makes everything so much simpler. Apply now at mercury.com/personal-banking

* Jane Street sent me a new puzzle last week: they trained a neural net, shuffled all 96 layers, and asked me to put them back in order. I tried but… I didn’t quite nail it. If you’re curious, or if you think you can do better, you should take a stab at janestreet.com/dwarkesh

* Labelbox can get you robotics and RL data at scale. Labelbox starts by helping you define your ideal data distribution, and then their massive Alignerr network collects frontier-grade data that you can use to train your models. Learn more at labelbox.com/dwarkesh

Timestamps

(00:00:00) - Orbital data centers

(00:36:46) - Grok and alignment

(00:59:56) - xAI’s business plan

(01:17:21) - Optimus and humanoid manufacturing

(01:30:22) - Does China win by default?

(01:44:16) - Lessons from running SpaceX

(02:20:08) - DOGE

(02:38:28) - TeraFab



Get full access to Dwarkesh Podcast at www.dwarkesh.com/subscribe
2026-02-05 169 min

Available Results

Generated results are saved to the knowledge database for reuse and search.

No generated results are available for this episode yet.

Extract Knowledge

Pick what you want extracted first. Model, scope, and chapter options appear after a template is selected.

Generated results for public episodes are saved to the knowledge database so they can be reused and searched later.

Transcript

No transcript is available for this episode yet.
Sign in to generate a transcript for review.
Sign in

Chapters

No chapters available.