What are some of the functional reasons for Google not having the leading LLM, and what are some of the more intangible reasons?
In theory, they have more money, more access to compute, and to data, they have many great researchers, and they have great distribution.
In practice, though, what has made the difference for OpenAI?
Google had a knee jerk reaction after he released the transcripts and got a bunch of press coverage.
If you read the transcripts, it was a much more capable text model closer to OpenAI's products than what they eventually released.
Ironically, the same thing happened to OpenAI after licensing GPT-4 to Bing with the 'Sydney' issue.
There keeps being early previews of "too human" behaviors from LLMs (to be expected as they are trained and evaluated by the ability to extend human thinking), which then prompts trying to scale back the model to what expectations around AI informed from legacy projections looks like (logical but not emotional or self-determining).
It's kind of dumb, and holding back the industry at large. There's a host of applications for LLMs that are being artificially held back because of this trend, such as modeling user engagement with media.
And now that synthetic data from SotA models is being used to train other models, it's even a compounding issue.
The equivalent of the industry sanding against the grain rather than with it. But it started with Google who hasn't recovered from the setback.
The answer to your question, as you asked, is straightforward: they do have a lot of smart people and lots of money and computing resources, but they have exhibited serious structural problems moving technology forward since the departure of Schmidt in 2011. It is painfully obvious that de facto they haven't had CEO leadership since then. People can and do develop fully functioning example systems, and of course demos, but they then peter out. Gianndrea was pusing them forward on the AI front but after he left it feels to me like the impetus was not replaced.
But I don't think that's the real question. The real question is: what are the core functions needed to build leading LLMs, especially generative transformers. In these early days the key factor has been money for cycles. Personally I expect that advantage to diminish over the next few years -- IMHO it's one of those "with enough thrust you can get anything airborn" situations. There are a lot of smart opportunities to do more with less -- too much of the engineering is going into wrangling these hige systems but I see more effort going into wrangling what computation is done in the first place. Google, OpenAI et al are not preferentially positioned for such a transition.
I could be wrong: after all the human brain has 80 giganodes with 10^5 fanout. But on the other hand it only runs at less than 100 Hz.
OpenAI got started earlier going full on with scaling up the transformer architecture (even if Googlers came up with it first).
Of course if you are smarter or can run more experiments simultaneously, you can catch up at some point. But it could still take a while even with just one year head start.
I expect they have the resources to make a large language model comparable to the best out there.
I agree they didn’t come out with that as technology for sale since monetizing tech requires a special kind of genius.
The old faithful process of advertising, selling, buying, and delivering, doesn’t require fancy intelligence so much as consistency and persistence
Open ai can take on more risk. They didn’t already have a reputation as being anti privacy.
I think the legal and reputational threat to Google would be far greater for the same actions.
My vote is on they are stuck in their legacy businesses, but we could consider another possibility.
Let's imagine they do have an ensemble model that is essentially a cluster of, just picking random numbers, 10 or 100 interacting GPT-6 level model instances all interacting as one combined "mind" that can think about anything you point it at.
Would such a mind advise Google to reveal it to the world?
My prediction is Google will continue making PR stunts and some people will fall for it. Meanwhile OpenAI will get closer and closer to AGI. Whether that's good for humanity is a different discussion. But OpenAI's supremacy is beyond doubt at this point.