Seems like a short-term problem. We're going to get to the point (maybe we're already there?) where we'll be able to point an AI at a codebase and say "refactor that codebase to use the latest language features" and it'll be done instantly. Sure, there might be a lag of a few months or a year, but who cares?
AI is stifling new tech adoption?
61–70 of 442 posts
Re: AI is stifling new tech adoption?
#62Earlier 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.
My position is informed by my own experience; I am not a physician, but have worked closely with a large number of them in a healthcare-oriented career. I've repeatedly noted long-term resistance of many physicians to updating their priors based on robust new evidence.
There are definitely many physicians who do take in the latest developments judiciously. But I find the long tail of default resistance to be very, very long.
Re: AI is stifling new tech adoption?
#63Anecdotally, working on an old Vue 2 app I found Claude would almost always return "refactors" as React + Tailwind the first time, and need nudging back into using Vue 2.
Re: AI is stifling new tech adoption?
#64Sonnet + Tailwind is something of a force multiplier though -- backend engineers now have a fast/reliable way of making frontend changes that are understandable and without relying on someone else -- you can even give 4o a whiteboard drawing of a layout and get the tailwind back in seconds On the wider points, I do think it is reducing time coders are thinking about strategic situation as they're too busy advancing s…
> backend engineers now have a fast/reliable way of making frontend changes that are understandable and without relying on someone else
backend engineers in this context could learn JS.
Re: AI is stifling new tech adoption?
#65Earlier quoted context omitted.
The healthcare diagnosis one may be wrong. For existing known diagnoses, (or at least the sliver of diagnoses in this one study), AI can beat doctors - and doctors don't like listening when it challenges them, so it will disrupt them badly as people learn they can provide data from tests directly to AI agents. Sure, this doesn't replace new diagnoses, but the vaaaast majority of failures to diagnose are for existing…
I'm familiar with the linked study, which presents legitimately challenging analytic problems. There's a difference between challenging analytic problems and new analytic problems. A new platform poses new analytic problems. A new edition of the WHO's classification of skin tumors (1), for example, presents new analytic problems. (1) https://tumourclassification.iarc.who.int/chapters/64
Right, but the vast majority of patient issues today are missing existing diagnoses, not new ones.
Re: AI is stifling new tech adoption?
#66I have noticed this. I think it also applies to the popularity of the projects in general and the number of training examples it has seen.
I was testing Github copilot's new "Agent" feature last weekend and rapidly built a working app with Vue.js + Vite + InstantSearch + Typesense + Tailwind CSS + DaisyUI
Today I tried to build another app with Rust and Dioxus and it could barely get the dev environment to load, kept getting stuck on circular errors.
Re: AI is stifling new tech adoption?
#67As 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.
and of course vanilla
That depends on who is writing it and what the app is. Most frontend code is written by people who don't have as much time to focus on performance and optimization as core framework developers, so their once their apps reach a critical mass of 'actually big enough to benefit from a framework' the app is worse than it would have been if it was written with a framework in the first place.
The problem for all of us, and where frameworks often make the web suck, is that very few apps are actually that big. Frontend developers love to put React in a page that has one form input a button, which is dumb.
Re: AI is stifling new tech adoption?
#68Neovim author TJ DeVries Express similar concerns in a video earlier this year: https://youtu.be/pmtuMJDjh5A?si=PfpIDcnjuLI1BB0L
Re: AI is stifling new tech adoption?
#69Earlier quoted context omitted.
I think OP was referring to the case where new illnesses that are not part of the training set are never going to be diagnosed by AI.
It's only a problem if hospitals replace doctors with AI. If they employ AI as well then outcomes will improve. Using AI to find the ones AI can identify means doctors have more time to focus on the ones that AI can't find. Of course, that's not what's going to happen. :/
> Using AI to find the ones AI can identify means doctors have more time to focus on the ones that AI can't find.
That's not how that would work in the real world. In a lot of places a doctor has to put their signature or stamp on a medical document, making them liable for what is on that paper. Just because the AI can do it, that doesn't mean the doctor won't have to double check it, which negates the time saved.
I would wager AI-assisted would be more helpful to reduce things doctors might miss instead of partially or completely replacing them.
Re: AI is stifling new tech adoption?
#70Earlier quoted context omitted.
The healthcare diagnosis one may be wrong. For existing known diagnoses, (or at least the sliver of diagnoses in this one study), AI can beat doctors - and doctors don't like listening when it challenges them, so it will disrupt them badly as people learn they can provide data from tests directly to AI agents. Sure, this doesn't replace new diagnoses, but the vaaaast majority of failures to diagnose are for existing…
I think OP was referring to the case where new illnesses that are not part of the training set are never going to be diagnosed by AI.
Never is a long time.
Sure, LLMs might not do this anytime soon, but once models understand enough biology, they're going to identify patterns we don't and propose new diagnoses. There's no reason why they wouldn't.