Not really, tons of companies in silicon valley burn through billions in cash and never even reach $100M in revenue, much less 4x on billions in revenue, that’s gotta be single digits in the amount of companies.
Snowflake in there prime when they had the largest IPO ever only got 50% yoy growth after $1b in revenue. 4x is insane
Hate on openai all you want but 4xing your revenue over a year is no small feat. Only 4 companies have gone from $1b to $10b in 3 years, Google, Uber, Cheniere and moderna
Not as bad as I thought honestly. Looks like they’re making a profit on inference, it’s just training the models is costing them a shit ton in R&D.
If we hit a plateau and training new models isn’t worth it and they scale back there R&D the business could be profitable. Not enough to justify there absurd evaluation, but not a money pit that some people in this thread would have you believe.
Haven’t used cursor but I assume it’s like other harnesses where the special sauce is in how it manages context, schedules sub agents, feeds them context, enforces standards, uses tools and skills etc. that make it better then just directly prompting the model.
For example you prompt opus directly with “refactor the auth flow” and it’s going to try and “one shot” it and produce the code from that prompt. Whereas a harness has instructions to say
Which produces way better results
Sounds like googles got a model that can mimic human hand gestures really well and want to prevent other companies from being able to scrape the Internet for AI training
As long as investors keep pumping money into it. Uber lost billions a year until relatively recently, and they didn’t have nearly the same queue of investors ready to pour money into them at an insane markup. You underestimate the tolerance for silicon valley vcs to take in years of loss as long as the companies growing.
Wouldn’t more data centers reduce there cost? More data centers means more capacity and more competition pushing the price down.