I've wondered this myself. There was a post about gumroad a few months ago where the CEO explained the decision to migrate to typescript and react. The decision was in part because of how well AI generated those, iirc.
AI is stifling new tech adoption?
81–90 of 442 posts
Re: AI is stifling new tech adoption?
#82Is this such a bad result? Do we need office CRUD apps to use bleeding edge technologies?
Probably not, but I guess the worry would be, if nobody adopts and uses them, bleeding edge technologies don't become the new normal. Unless you think we've reached perfection, it's almost guaranteed that future developers will look at React/Python/etc as we look at developing in Assembly or COBOL.
Re: AI is stifling new tech adoption?
#83> OpenAI’s latest models have cutoffs of late 2023.
The first paragraph is factually incorrect; the cutoff is June 2024 for 4o.
Awww, no more new JavaScript frameworks and waiting only for established technologies to cut through the noise. I don't see that as a bad thing. Technologies need to mature, and maintaining API backward compatibility is another advantage.
Re: AI is stifling new tech adoption?
#84Earlier quoted context omitted.
I doubt it is easier to retrain a large, dispersed group of humans on a new classification of tumors than it is to retrain a model on the same.
Not if they're trained to work through the problem each time they encounter it and stay up with their clinical training. The day the new classification drops many have already heard about it. You also assume that all the models in use will in fact be retrained. Generally, this position flies in the face of lived experience. AI is in fact stifling adoption of new things across many industries.
> You also assume that all the models in use will in fact be retrained.
And that deploying the retrained models won’t require a costly and time consuming recertification process. This is medicine after all.
Re: AI is stifling new tech adoption?
#85Earlier quoted context omitted.
I doubt it is easier to retrain a large, dispersed group of humans on a new classification of tumors than it is to retrain a model on the same.
Not if they're trained to work through the problem each time they encounter it and stay up with their clinical training. The day the new classification drops many have already heard about it. You also assume that all the models in use will in fact be retrained. Generally, this position flies in the face of lived experience. AI is in fact stifling adoption of new things across many industries.
Where I live, specialists can't even speak English, so I doubt very much that they are up to date on anything. And I live in a first-world country.
Re: AI is stifling new tech adoption?
#86I actually asked this a while back, but got little response: https://news.ycombinator.com/item?id=40263033
> Ask HN: Will LLMs hurt adoption of new frameworks and technology?
> If I ask some LLM/GPT a react question I get good responses. If I ask it about a framework released after the training data was obtained, it will either not know or hallucinate. Or if it's a lesser known framework the quality will be worse than for a known framework. Same with other things like hardware manuals not being trained on yet etc.
> As more and more devs rely on AI tools in their work flows, will emerging tech have a bigger hurdle than before to be adopted? Will we regress to the mean?
Re: AI is stifling new tech adoption?
#87The central issue is high cost of training the models, it seems:
> "Once it has finally released, it usually remains stagnant in terms of having its knowledge updated. This creates an AI knowledge gap. A period between the present and AI’s training cutoff... The cutoff means that models are strictly limited in knowledge up to a certain point. For instance, Anthropic’s latest models have a cutoff of April 2024, and OpenAI’s latest models have cutoffs of late 2023."
Hasn't DeepSeek's novel training methodology changed all that? If the energy and financial cost for training a model really has drastically dropped, then frequent retraining including new data should become the norm.
Re: AI is stifling new tech adoption?
#88> OpenAI’s latest models have cutoffs of late 2023. The first paragraph is factually incorrect; the cutoff is June 2024 for 4o. Awww, no more new JavaScript frameworks and waiting only for established technologies to cut through the noise. I don't see that as a bad thing. Technologies need to mature, and maintaining API backward compatibility is another advantage.
The problem is acute with APIs that move fast and deprecate (Shopify and some of the Google ones)
Re: AI is stifling new tech adoption?
#89>Consider a developer working with a cutting-edge JavaScript framework released just months ago. When they turn to AI coding assistants for help, they find these tools unable to provide meaningful guidance because their training data predates the framework’s release. [... This] incentivises them to use something [older]. That sounds great to me, actually. A world where e.g. Django and React are considered as obvious…
What if it happened just before React, and you therefore got stuck with angular? Should we now be stuck with React forever just because it's okay-ish, never allowing future better framework to emerge?
Re: AI is stifling new tech adoption?
#90Earlier quoted context omitted.
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? If you're asking about performance and memory, then yes, it does. 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 -…
> If you're asking about performance and memory, then yes, it does.
Most places just don't care. I've worked 15 years as a contractor and only in once place have the business cared about optimisation. As long as it wasn't unbearable than it was "good enough".
> 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.
This may have been true back in 2014. 5G networks are pretty fast and the the mobile web is pretty bloated. Performance is way down the list of concerns typically even by places that should care. I can write blazingly fast custom JS frameworks, the number of times anyone cares is exactly one time.
> 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.
I have a 2010 Dell E6410 with 8GB of ram and an i7 640M (Dual Core, 4 thread). Almost every modern phone is faster now.
I am not arguing we should make things bloated. I am just saying there isn't an incentive to optimise for low end devices because low end is better than a reasonably power Business Laptop of 10-15 years ago.
> why would you waste time and energy to create your own calendar component? But if an LLM can generate any bespoke component that you need in The code from the LLM probably hasn't been battle tested. The open source react component library with 1000s of stars on github definitely has been. If you run into a problem with the LLM code you are probably going to be by yourself fixing it. I will take the component library over the LLM code everyday of the week.