1) The winner immediately becomes a monopoly
2) All investments are directed from competitors, to the winner
3) Research on AGI/ASI ceases
I don't see how any of these would be viable. Right now there's an incremental model arms race, with no companies holding a secret sauce so powerful that they're miles above the rest.
I think it will continue like it does today. Some company will break through with some sort of AGI model, and the competitors will follow. Then open source models will be released. Same with ASI.
The things that will be important and guarded are: data and compute.
We are already seeing diminishing returns from compute and training costs going up, but as more and more AI is used in the wild and pollutes training data, having validated data becomes the moat.
So maybe the issue is more about staying in the top N, and being willing to pay tons to make sure that happens.
That's probably true, but at the moment the only thing that creates something resembling a moat is the fact that progress is rapid (i.e. the top players are ~6-12 months ahead of the already commoditized options, but the gap in capabilities is quite large): if progress plateaus at all, the barrier to be competitive with the top dogs is going to drop a lot, and anyone trying to extra value out of their position is going to attract a ton of competition even from new players.
Yes, but just like in an actual arms race, we don't know if this can evolve in a winner takes all scenario very quickly and literally.
In an actual arms race you use your arms to actually physically wipe out your enemy.
It's not just like an arms race.
AI? Do you mean LLMs, GPTs, both, or other?
Why won't AI follow the technology life cycle?
It'll always be stuck in the R&D phase, never reach maturity?
It's on a different life cycle?
Once AI matures, something prevents consolidation? (eg every nation protects its champions)
Maybe it's just me but I haven't been model-hopping one bit. For my daily chatbot usage, I just don't feel inclined to model-hop so much to squeeze out some tiny improvement. All the models are way beyond "good enough" at this point, so I just continue using ChatGPT and switching back and forth from o3 and 4o. I would love to hear if others are different.
Maybe others are doing some hyper-advanced stuff where the edging out makes a difference, but I just don't buy it.
A good example is search engines. Google is a pseudo-monopoly because google search gives obviously better results than bing or duckduckgo. In my experience this just isn't the case for LLM's. Its more nuanced than better or worse. LLM's are more like car models where everyone makes a personal choice on which they like the best.
OpenAI has a limited protective moat because ChatGPT is synonymous with generative AI at the moment, but that isn’t any more baked in than MySpace (certainly not in the league of Twitter or Facebook).
At work we are optimising cost by switching in different models for different agents based on use case, and where testing has demonstrated a particular model's output is sufficient.
> If the very best LLM is 1.5x as good as good as the next-best, then pretty much everyone in the world will want to use the best one
Is it? Gemini is arguably better than OAI in most cases but I'm not sure it's as popular among general public
I think what we're seeing here is superstar economics, where the market believes the top players are disproportionately more valuable than average. Typically this is bad, because it leads to low median compensation but in this rare case it is working out.
If this were winner-take-all market with low switching costs, we'd be seeing instant majority market domination whenever a new SOTA model comes out every few weeks. But this isn't happening in practice, even though it's much easier to switch models on OpenRouter than many other inference providers.
I get the perception of "winner-take-all" is why the salaries are shooting up, but it's at-odds with the reality.
These are all coding assistants. While they can be turned into waifus they're not intended as such.
You are not one random hyperparameter away from the SciFi singularity. You are making iterative improvements and throwing more compute at the problem, as are all your competitors, all of which are to some degree utterly exchangeable.
Well only if the price is the same. Otherwise people will value price over quality, or quality over price. Like they do for literally every other product they select...
It would be unfortunate if something like Grok takes the cake here.
I tried multiple and they all fail and some point so I let another LLM take over.
As soon it’s not some boilerplate thing it becomes harder to get the correct result
Hint: Researchers from both companies said publicly they employ generalized reasoning techniques in these IMO models.
"Fancy chatbots" is a classic AI use case. ELIZA is a well-known example of early AI software.
It's the same reason that sports stars, musicians, and other entertainers that operate on a global scale make so much more money now than they did 100 years ago. They are serving a market that is thousands of times larger than their predecessors did, and the pay is commensurately larger.