11–20 of 442 posts
As the saying goes: while (React.isPopular) { React.isPopular = true } It's actually quite sad because there are objectively better models both for performance and memory including Preact, Svelte, Vue, and of course vanilla.
If AI stifles the relentless churn in frontend frameworks then perhaps it's a good thing.
I currently AI-coma / tab-complete C++17 with decent results for stuff ridiculously far away from frontend, but I do wonder who is providing the training data for C++23 and onwards as there isn't wide adaptation yet.
Is this such a bad result? Do we need office CRUD apps to use bleeding edge technologies?
Is this such a bad result? Do we need office CRUD apps to use bleeding edge technologies?
As the saying goes: while (React.isPopular) { React.isPopular = true } It's actually quite sad because there are objectively better models both for performance and memory including Preact, Svelte, Vue, and of course vanilla.
Does that really matter to most companies/developers? I’d much rather have a good enough solution with a large ecosystem built around it. It also takes a lot of investment for companies to change their tech stack
> Does that really matter to most companies/developers?
This is especially true in e-commerce where many studies have shown that overall page performance has a correlation to conversion. Add to that the fact that a lot of e-commerce has moved to mobile web, there's a strong case for picking the best performing technologies versus developer preference -- especially if AI is generating it.
But even outside of e-comm, consider government websites where you may have low income users that are using cheaper, older, lower capability devices to access information and services using lower speed networks to boot.
I do my day-to-day work on an M3 Max with 64GB RAM and fiber to the home; it's easy for developers to forget that many times, their end users can be on older devices, on low performing networks, and other factors that affect performance and usability of web applications.
> ...with a large ecosystem built around it
Perhaps reasoning will help?
I noticed this too. Anyone found out how to make Claude work better?
Eventually it will go either of the two ways, though:
- models will have enough generalization ability to be trained on new stuff that has passed the basic usefulness test in the hands of enthusiasts and shows promise
- models will become smart enough to be useful even for obscure things
LLMs should not have hard-wired preferences through providers' prompt structure.
And while LLMs are stochastic parrots, and are likely to infer React if a lot of the training corpus mentions React, work should be done to actively prevent biases like this. If we can't get this right with JS frameworks, how are we going to solve it for more nuanced structural biases around ethnicity, gender, religion or political perspective?
What I'm most concerned about here is that Anthropic is taking investment from tech firms who vendor dev tooling - it would not take much for them to "prefer" one of those proprietary toolchains. We might not have much of a problem with React today, but what if your choice of LLM started to determine if you could or couldn't get recommendations on AWS vs Azure vs GCP vs bare metal/roll your own? Or if it suggested only commercial tools instead of F/LOSS?
And to take that to its logical conclusion, if that's happening, how do I know that the history assignment a kid is asking for help with isn't sneaking in an extreme viewpoint - and I don't care if it's extreme left or right, just warped by a political philosophy to be disconnected from truth - that the kid just accepts as truth?