Happy 2023 ✨ The Best Is Yet To Come!!!! #UnrealTimes💠

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In awe of SpaceX and its story - past, present and the future. You can think about it in 10 different ways and continue re-blowing your mind in circles. Huge congrats to the team! 🚀

To train a GPT class 1T model from scratch - including failed runs, data acq clean rlhf, post-training, team/people will likely req $250M of compute on an aggressive 3-4mo schedule (i.e. more reserved GPUs), $500-600M all-in IF you do a dense one. MoE fp8 will cut costs by 1/10th depending on how many active params you have. If you want SOTA however, the budgets go significantly higher on test-time compute, post-training RL, and data/synthetic generations..and v. high on talent. Maybe $2-4B all-in. After that comes serving the model. The talent is key to get to SOTA/beat it - and then you have to ensure this is useful enough to have inference vol over time - for which the capital will come if there is usage / TAM. So this is not as much about raising $50-60B, or raising it all at once as the OP says - we are investors in mistral, sarvam, reflection and anthropic - and they all scaled capital over time as models got adoption, but the early bottleneck is more on talent GPUs at that scale where you can do interesting things.

The person who solves the biggest, hardest problems in society should be rewarded with the most economic gain. That is ultimately why Elon Musk has become the world's first trillionaire. No one has solved problems at the frequency and scale that he has.

RT @GoldmanSachs: Go for Launch 🚀

$SPCX. Now trading on Nasdaq.

Most work conversations are now being recorded by default. You should probably assume that everything you say at work is getting recorded from here on out. What’s emerging is a new category of enterprise software, organized around voice instead of text. The system of record today is structured data: CRM entries, tickets, docs. But the highest-value context lives in conversation: the nuance on a customer call, the real argument in a product review, the offhand comment in a leadership meeting that quietly changes the roadmap. LLMs are uniquely good at taking that unstructured voice data and making it structured, searchable, and queryable. That’s a large enterprise opportunity, and we’re still early in understanding what the software layer looks like and who owns it. a16z GP David Haber on what AI recording means for the future of work: a16z.news/p/everything-is-re…

instead of watching 2 hours of Netflix tonight, watch this 2010 SpaceX tour where Elon Musk walks you through the exact factory that launched the most valuable private company on earth it's the clearest window I've seen into how SpaceX started from nothing and built the infrastructure worth $3.4 trillion by 2040 useful whether you've never followed SpaceX in your life or have been watching every launch for the past decade and if you want to understand what the SpaceX IPO on June 12 actually means — I ran the 300-page S-1 through Kimi so you don't have to. full breakdown is below.

RT @jpmorgan: Live from our global headquarters: Jamie Dimon and Elon Musk discuss SpaceX and more. x.com/i/broadcasts/1NGarrMYj…

Elon Musk on building a self-growing city on the Moon: "You don't necessarily have to go through the moon to get to Mars. We can build a self-growing city on the moon faster than we could do so on Mars, and there's also the potential, if you say you want to scale far beyond what you can do from Earth, is that because the moon has no atmosphere and about 1/6 Earth's gravity, you can use an electromagnetic accelerator, a rail gun or mass driver, basically you don't need to use rockets to do AI data centers into deep space from the moon, you can literally just shoot them like a, like a rail gun type of thing, and and you can manufacture the solar, the solar and the radiators, solar power and radiators on the moon from moon materials that would allow scaling potentially to beyond 1000 terawatts a year, which is a truly staggering number. I think we can do probably do somewhere around one terawatt per year of AI space compute from Earth, but we can do 1000 terawatts or more from the moon."

SpaceX AI Satellites

JUST IN: Kalshi launches new LINK perps in an industry first for a U.S. company regulated by the CFTC

If you have worked on ads in the past, on any part of the stack, and want 10x the impact, please apply here: job-boards.greenhouse.io/xai… Curent team has just 18 engineers.

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This applies to many niche skills. I didn’t learn astrophotography from school, I learned it by getting my hands dirty & spent every night learning how NOT to do it. If you want to do something, just start doing it. Waiting for someone to teach you might leave you with nothing.

Read books, talk to people & iterate rapidly with hardware & software

Anthropic and Google are now paying @SpaceX a combined $2.17 billon per month for compute capacity. That's a revenue run rate of $26 billion per year. BIG MONEY.