Exactly. Present success means the ability to forecast what’s needed for future success — see the Pierce-Arrow Motor Car Company and their dominance in the market to this very day
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).
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.
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.
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
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
> Using Pierce-Arrow Motor Car Company as an example of such success is historically inaccurate. Pierce-Arrow was an American automobile manufacturer based in Buffalo, New York, which was known for producing luxury cars. It was indeed a dominant and prestigious brand in the early 20th century. However, the company did not manage to maintain its success and ultimately failed to adapt to changing market conditions. It faced financial difficulties during the Great Depression and eventually went bankrupt in 1938. Pierce-Arrow's inability to forecast and adapt to the economic changes and shifts in consumer preferences of the time led to its decline.
From the very answer ChatGPT gave you, it's evident that GP is saying that current success does not imply future success, using that company as an example. What needs elaboration?