3 ms·
This does kind of make me wonder. It's believable that we might either see an increase in the number of new programming languages since making new languages is
by CMay 1y ago
This does kind of make me wonder.
It's believable that we might either see an increase in the number of new programming languages since making new languages is becoming more accessible, or we could see fewer new languages as the problems of the existing ones are worked around more reliably with LLMs.
Yet, what happens to adoption? Perhaps getting people to adopt new languages will be harder as generations come to expect LLM support. Would you almost need to use LLMs to synthesize tons of code examples that convert into the new language to prime the inputs?
Once conversational intelligence machines reach a sort of godlike generality, then maybe they could very quickly adapt languages from much fewer examples. That still might not help much with the gotchas of any tooling or other quirks.
So maybe we'll all snap to a new LLM super-language in 20 years, or we could be concreting ourselves into the most popular languages of today for the next 50 years.
- hammyhavoc 1y agoFantasy.
- CMay 1y agoCan you elaborate?
- hammyhavoc 1y ago> Once conversational intelligence machines reach a sort of godlike generality, Sums up fantastical inevitablism. Why would they? How could they? The data is telling us that they won't. Anybody who believes otherwise is ignoring the science. The assumed path to "AGI" was more tokens, but more tokens actually means worse output, and if LLMs aren't a total technological dead-end, period, then the data is supporting smaller models meant for more specific things, ergo, LLMs are not giving AGI any time, ever. Pure fantasy. Can't even call it sci-fi when it ignores the science entirely.
- CMay 1y agoAh, so you misread. I said conversational intelligence machines, but you focused on LLMs. I don't know where LLMs will lead, but I haven't ruled out the possibility of improvements continuing to surprise us. If anything is unscientific, it would be overconfidence in one way or the other.
- hammyhavoc 1y agoConfidence comes from statistics. The statistics say that smaller models are better than bigger ones, ergo I have I have confidence in saying what I did. If anyone is overconfident, I'm afraid it is you.
- CMay 1y agoEven if smaller more specialized models outperform larger more generalized models for specific tasks with these architectures, that does not logically support your point or serve as meaningful evidence against my post. These systems can have many models and the systems themselves could eventually arrive at knowledge they know they underperform on, automatically training new models for that subject. The final response wouldn't necessarily come exclusively from the specialized model, it might come through a model specialized at integrating knowledge between multiple models, asking the right questions, verifying and so on. We're barely a few years into this, so it's premature to know what 100 years of developments will bring.