[financypants]

This person is not saying success -> more success. I think they’re just pointing out that Altman is smart and is surrounded by smart people and a company that understands the demand because they make up the majority of the demand (and they have a strong thesis).

[startupsfail]

Is he raising for OpenAI or for another venture? If he is using deep knowledge from OpenAI to raise money for another venture, this sounds wrong.

[Atotalnoob]

He is rich and powerful, of course it isn’t wrong

/s

[startupsfail]

Or broke and powerful? Because of spending a fortune on WorldCoin, working at a nonprofit and heavily investing into early AI startups?

[aorloff]

No way OpenAI makes up even a plurality of chip demand

[latency-guy2]

OpenAI not itself, but Microsoft is.

For 2022 and 2023, Microsoft bought a significant portion of NVIDIA's available hardware. They spent quite a bit of 2023 trying to figure out how to even power the multiple fleets of GPUs. Just now with the mild to expected wild adoption of Azure OpenAI are they getting around to servicing all their (potential) customers.

[ffsm8]

[citation needed]

Seriously, this is am outlandish claim just from looking at Microsoft and Nvidias market cap.

I am sure that Microsoft is gonna be one of Nvidias largest customers, but I sincerely doubt it's even a double digit percentage of their revenue.

[latency-guy2]

All of this is public information, its estimated Microsoft bought ~150k H100s from old reports, we also know today that Meta actually bought 500k units

To reach double digit revenue of NVIDIA's 2023 at $26.97 billion, you'd only need to hit ~$2.7B in sales.

H100's are priced anywhere between $20k - $35k, so required to purchase ~77k - ~135k units.

That is singularly H100s, Microsoft also offers lower compute, and they have the rest of Azure to service with a variety of solutions.

Being at #1 or #2 market cap worldwide is not a farfetched position to be a significant controller of chips, especially since they directly work in the space as a platform.

[verdverm]

This ignores Google's in house chips and their internal usage. They've been at this much longer. I doubt we have the visibility to know how they compare in terms of available flops and the unit costs

[latency-guy2]

> They've been at this much longer.

.. but is that true?

MSR has been putting out research in all derivatives of modern large neural network architectures (NLP, CV, etc.) for the same amount of time that Google has. If there was a drift between timelines, its not large IMO.

What you could argue is that Google historically was more successful in their research outputs.

However, historical consumption of resources may not compare to current resources consumption.

> I doubt we have the visibility to know how they compare in terms of available flops and the unit costs

Completely agreed, unfortunately, this is all guesswork at best

[financypants]

Perhaps. I have no idea and am not purporting to know.