flaque

Of course? On average, companies that are still standing after ~15 to 20 years are going to be a lot larger than the companies who started more recently.

they're a replacement for cargoships. If done right, they're faster than a cargoship, but could (maybe) carry lots of capacity for cheap, while also not requiring them to take the same routes as a ship.

This seems broadly good. If you told me a democratic admin had recruited these people, I would think "wow! what a positive signal for the current admin!"

This only makes sense if you think scaling laws won't hold.

If someone gets something to work with 1k h100s that should have taken 100k h100s, that means the group with the 100k is about to have a much, much better model.

> put a note where people will see those prices so that they understand those prices are unlikely to remain.

Yup, shall do!

> Also, I'm really impressed at how great your replies about your product are! You're a gem.

Thank you! :D

Hi! I run sfcompute.

We don't have a limited number of slots!

We just go down a lot. It's VERY beta at the moment; we literally take the whole thing down about once a week. So if we know of some major problem, or we're down, we just don't let people on (since they'll have a bad experience).

You're right though that the prices are probably lower because of this. That's why we have a thing on our website that says "*Prices are from the sfcompute private beta and don’t represent normal market conditions."

If you'd like on anyway, I can let you on, just email me at evan at sfcompute, but it may literally break!

If OpenAI has merely 10% margins, they've recouped their costs by 3x.

> Tech giants and beyond are set to spend over $1tn on AI capex in coming years, with so far little to show for it.

Regardless of whether or not the implicit claim here is true (the claim being "all this spend won't produce an ROI"), the explicit claim here is nonsensical.

Of course the $1tn in capex has nothing to show for it! The spend has not happened yet! Of the spend that _has_ happened, most of the chips are not physically in data centers yet. Of the chips that _are_ in data centers, most of the models are not yet trained!

And of the models that _have_ been trained, many have clearly had a significant ROI. GPT-4 cost $100m, and OpenAI's revenue is now reported to be $3.4 billion a year.

Saying there's "little to show for it" is an absurd claim; the products are _printing_ cash! We beat the turing test! You can drive around in a self-driving car!

It's perfectly reasonable to say "where does the ROI come from when you spend $1tn on capex", but it's hard to argue against the success of the spend of the last generation of models.

> Whether (people) get insurance, or what the rate for their insurance is, or legal decisions or employment decisions, whether you get fired or hired, could be up to an AI algorithm

This is a bit like trying to regulate horseshoes while everyone else is talking about speed limits & seat belts. Both parties say the word "carriage" and "passenger", but they have completely different ideas in their heads about what is about to happen.

Ah! Whoops apologies :( I don’t think we were clear that this is a launch of the second cluster, not like a rehash of the previous one.

Not trying to repost, just is a poorly explained launch.

This is great! Keep going with this!