111–120 of 442 posts
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But equally impressive that the Javascript community has actually managed to continue to use a single framework for more than five minutes without jumping to the next.
had to have hooks though. And vanilla-OO had to go in favor of trapping state in closures, which is cooler because it has functions and not methods.
Do you complain when other frameworks add new features without breaking backwards compatibility?
>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…
Pathologists as a specialty has been grousing about this for several years, at least since 2021 when the College of American Pathologists established the AI Committee. As a trivial example: any trained model deployed will necessarily be behind any new classification of tumors. This makes it harder to push the science and clinical diagnosis of cancer forward. The entire music community has been complaining about how o…
I think a one year gap in adoption of new tech is not that bad. Isn't it better to always go for the mature tech first ? The real change will come from the fact that because of AI, compute will be so cheap in the coming years: https://medium.com/thoughts-on-machine-learning/a-future-of-...
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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.
Is this such a bad result? Do we need office CRUD apps to use bleeding edge technologies?
It's also a problem when adopting new functionality in existing frameworks (eg. upgrading an app to new Android release), dropping the use of deprecated functionality, taking advantage of more readable syntax in programming languages, etc.
"AI" is the programming language here. The readability of any lower level language(s) that may exist as a compiler target of the "AI" is about as important as how readable assembly language is to someone writing software in Rust.
Pathologists as a specialty has been grousing about this for several years, at least since 2021 when the College of American Pathologists established the AI Committee. As a trivial example: any trained model deployed will necessarily be behind any new classification of tumors. This makes it harder to push the science and clinical diagnosis of cancer forward. The entire music community has been complaining about how o…
I think a one year gap in adoption of new tech is not that bad. Isn't it better to always go for the mature tech first ? The real change will come from the fact that because of AI, compute will be so cheap in the coming years: https://medium.com/thoughts-on-machine-learning/a-future-of-...
In addition, as the article describes, the LLM services have biases built in to them even among existing technologies. It amplifies existing preferences, leading to less diversity and competition between technologies. Tech leads will have to weigh between the qualities of a technology on its own merits against how well it is supported by an LLM.
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> 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 -…
So, if you're a large e-commerce company that's trying to juice out last percentage points of conversion, and are researching alternate javascript libraries, is it plausable that the only research a development team would be to ask ChatGPT?
I 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 tha…
Less documentation/examples of new tech -> New model doesn't have enough info on new tech to be useful -> Less uptake of new technology -> Less documentation/examples to build a corpus....
I do wonder if this problem could get solved by basically providing documentation explicitly written for LLMs to consume and produce more detailed "synthetic" documentation/examples from. No idea if that's possible or even wise, but probably a problem space worth exploring. Or if these LLMs develop some sort of standardized way to rapidly apply new bodies of work that avoids costly retraining - like kernel modules, but for LLMs.
> 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.
Author here. May I request a source for that? Platform docs state: > The knowledge cutoff for GPT-4o models is October, 2023. https://platform.openai.com/docs/models#gpt-4o
> By extending its training data cutoff from November 2023 to June 2024 […]
https://help.openai.com/en/articles/9624314-model-release-no...
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> 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…
Interesting. Do you see any versions of the future where use of AI could actually make the physician take more time?
I don't have a crystal ball, so this is a made-up scenario.