Comment by Traster
3 hours ago
People can correct me if I'm wrong, but I think the core logic behind OpenAI's valuation was essentially that AI would work like search. Google had the best search engine, it became a centre of gravity that sucked everything in and suddenly network effects meant it was the centre of the universe. There seem to be 2 big problems with that though. The first is that for search, queries are both demand for the product and a way of making the product better. The second, is that Google was genuinely the best product for a very long time.
Maybe point (1) was unclear at some point, but I think it's mostly clear today that's not happening. Training the model is modestly distinct from inference.
Point (2) is really funny - because sure, at some point OpenAI was the best, and then Sam Altman blew the place up and spawned a whole host of competitors who could replicate and eventually surpass OpenAI's state of the art.
It now looks like AI is a death march. You must spend billions of dollars to have the best model or you won't be able to sell inference. But even if you do, a whole host of better funded competitors are going to beat you within months so your inference charges better pay off extremely quickly. When the gap between models starts to drop, distribution becomes king and OpenAI can't compete in that field either.
Google can do that. Meta can do that. MSFT probably can do that. Amazon can do that. OpenAI cannot. They do not have the cash to do it.
I think a large part of its valuation was it's ability to compete with search but thats understating it a bit. Unlike search it could/can be the platform users primarily interact with (ala a social media replacement) while having huge impacts on enterprise work and automation. I think its the combination of the ability for effectively one company to compete on every front in the modern web ecosystem thats contributed to the valuation.
It's also important to note the valuation is not just based off of its possible concrete economic implications in these areas but also future "unknown" possibility ( I.E. whatever "agi" means to investors ). Thats not to say I believe it's possible to achieve this but rather a huge part of Sam Altman's job is increasing valuation through unfounded claims of AGI's possibility and possible impact.
I've almost forgotten about AGI, that was suppose to be the reason for the valuations and all the hope/fear. Then, it just sort of went away and AI turned into the Software Developer doomsday machine. We're on month 4 since the models got really good at code and we were all going to be out of a job in 6 months. I guess we only have 2 more months of employment left /s
"Google had the best search engine, it became a centre of gravity..."
Almost no one made serious attempts at competing with Google. And not because of network effects or any other hard blocker. In the early 2000s, the industry just wasn't mature enough to heavily fund serious competition.
By the 2020s the industry has funding and founders ready to jump on any huge opportunity that presents itself.
There are of course downsides, but this competitive landscape in AI seems like a huge net win for users in terms of lower costs and faster progress.
Yahoo? MSN Search?
that's been my feeling for a while now. Google just has to keep up while OpenAI and Anthropic go bankrupt. I can see MSFT and Amazon eventually consuming OpenAI and Anthropic respectively when the money runs out but I still think Google is the eventual winner. I also have been pointing out that Apple making a deal with Google vs trying to do it on their own is another vote in that direction.
I'm just sad Google was intent on ruining their own product, whether removing + operator (seriously - Google+ is not an excuse, I don't care if it conflicts with search, don't do that) or some of their political censorship
For actual searching, it seems like RAG would be the way. Instead of rebuilding models, focus on curating datasets and sources.