Bullshit generators do a better job of generating bullshit than the whole “professional class” created to generate bullshit. Most MBAs are just that.
Low to average academic achievers that decide to pursue careers where they won’t have to work too hard or think too hard… The best ones are indeed smart, but mostly at bullshitting other bullshitters.
Maybe not “today” but today is still early days.
I’ve been consuming lots of “build your own local AI coding agent” kind of content lately. No doubt this is the same as the guys that are welding together their own versions of Shelby Cobras and stuff… but in a few years you’ll be able to buy a “server” with enough GPU and ram to host strong open models and serve them to your little office.
I work in a small company, and if AI plays out the way Anthropic sees it’d their AI bill will be $100k every year (fire 2-3 people, pay for AI so that the remaining people do more). At that level of expenditure, why wouldn’t my poss pay as much as a copy machine $25k, lets say, go give “local AI” a chance?
The stock valuations that most tech companies carry (and certainly the 2-3 trillion that is being talked about for Anthropic) speak to potential future revenue.
To me, I see computing and actual “model” advances meeting the need within a few years… if not by entrenched companies like Nvidia, then by insurgent chipmakers or new (Chinese or otherwise) chipmakers.
In 10 years you’ll have “opus” is not better running in your phone and probably something more powerful in a PC.
It is obvious to me that AI computing is a COMMODITY, in that it will inevitably be something that can not be effectively gate-kept.
These two major US companies (OpenAI and Anthropic) are playing the game of “locking in” a monopoly in a product category that has yet to mature. This is a pretty old capitalist game, of course… Uber, Microsoft, facebook,and many others have played this game in the past.
But, unlike OSes or word processing file compatibility I don’t see a “network effect” in that an open source/weight model can/will do 99% of what a proprietary model can, will do it “transparently,” will eventually become so optimized that it can run locally, etc. etc.
I mean: maybe its name recondition that is worth “trillions” but a race to be “Xerox” or “Kleenex” or even “PC” (as in IBM PC) did not really work out well for these companies.
I think that even the established players (MS, Google, etc.) are biding their time, making sure that they don’t get locked out while non-proprietary solutions become feasible.
I means I know that much of the issues have to do with the limited availability of hardware, but locking down supply is not sustainable for the “big 2” and sooner or later more adequate memory and GPU supply will enter the market…
It is clear as day to me that AI compute is a commodity.
Open models are basically equal to the proprietary models now and while running these models locally is still too expensive to be reasonable, this won’t be the case forever.
There IS a market for what the two big US AI firms are doing, but it is quite limited.
Sophisticated businesses will want to keep all of their work-product inside of their networks, just for security reasons, even if they don’t care about runaway compute costs.