That's a good analogy. Makes a lot of sense. The only caveat I see is that there is a lot of context locked up in proprietary data sets (e.g. YT, books, podcasts) and I'm not sure how OSS models get access to that.
Those were way simpler projects in the beginning when that happened. Like do you think a new browser would catch up today chrome now?
The tech behind LLMs has been open source for a very long time. Look at DeepSeek and LLAMA for example. They aren’t yet as capable as say Gemini but they aren’t “miles behind” either, especially if you know how to tune the models to be purpose built[0].
The time horizons will be different as they always are, but I believe it will happen eventually.
I’d also argue that browsers got complicated pretty fast, long cry from libhtml in a few short years.
[0]: of which I contend most useful applications of this technology will not be the generalized ChatGPT interface but specialized highly tuned models that don’t need the scope of a generalized querying
Another way to put it, is that over time you see this, it usually takes a little while for open source projects to catch up, but once they do they gain traction quite quickly over the closed source counter parts.