291–300 of 422 posts
If all you’ve done with AI is just use it for autocomplete, you’re missing out big time. I built a slick react app using Lovable yesterday and then created a Node BE using Claude Code today. I told Claude Code to look through the FE code to understand the requirements and purpose of the site, and to build a detailed plan (including proposed DB schemas) for a system that could support that functionality. It generated…
For example, working on my project (https://mudg.fly.dev) I wanted to experiment with a new FE graph library. I asked an llm the fantastic (https://tidewave.ai) and it completely implemented a solution, which turned out to be worse than the current solution.
If I had spent many hours working on a solution I might have been more "attached" to the solution and kept with it.
Perhaps this is a good thing? (https://en.wikipedia.org/wiki/Nonattachment_(philosophy))
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My parents could have said your first paragraph when I tried to teach them they could Google their questions and find answers. Technology moves forward and productivity improves for those that move with it.
Why is productivity so important? When do regular people get to benefit from all this "progress?"
> My former colleague Rebecca Parsons, has been saying for a long time that hallucinations aren’t a bug of LLMs, they are a feature. Indeed they are the feature. All an LLM does is produce hallucinations, it’s just that we find some of them useful. This is an example of my least favorite style of feigned insight: redefining a term into meaninglessness just so you can say something that sounds different while not actu…
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Technology does not always help people, in fact often it creates new problems that didn't exist before. Also telling someone to "adapt to the times" is a bit silly. If it helped as much as its claimed, there wouldn't be any need to try and convince people they should be using it. A LOT of parallels with crypto, which is still trying to find its killer app 16 years later.
Paul Krugman (Nobel laureate in economy) said in 1998 that the internet is no biggie. Many companies needed convincing to adopt the internet (heck, some still need convincing). Would you say the same thing ("If it helped as much as its claimed, there wouldn't be any need to try and convince people they should be using it.") about the internet?
Thing's called a self-fulfilling prophecy. Next level to a MLM scheme: total bootstrap. Throwing shit at things in innate primate activity, use money to shift people's attention to a given thing for long enough and eventually they'll throw enough shit at the wall for something to stick. At which point it becomes something able to roll along with the market cycles.
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I don’t think anyone needs to be convinced at this point. Every developer is using LLM and I really can’t believe someone who has made a career out of automating things wouldn’t be immediately drawn to trying them at least. Every single company seems convinced and using it too. The comparison to crypto makes no sense.
> Every developer is using LLM Citation needed. In my circles, Senior engineer are not using them a lot, or in very specific use cases. My company is blocking LLMs use apart from a few pilots (which I am part of, and while claude code is cool, its effectiveness on a 10-year old distributed codebase is pretty low). You can't make sweeping statements like this, software engineering is a large field. And I use claude co…
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You might as well say it's interpolating or extrapolating. That's what people are usually doing too, even when recalling situations that they were personally involved in. I think we call it "hallucinating" when the machine does this in an un-human-like way.
The longer term for this is "stochastic parrot". See another HN comment here comparing LLMs to theater actors or movie actors. LLMs just spew words. It just so happens that human beings can decode them into something related, useful, and meaningful surprisingly often. Might even be a useful case of pareidolia (a term I dislike, because a world without any pattern matching whatsoever would not necessarily be "better")…
We can trace which neurons activate for a face recognition model and see that a certain neuron does light up when it sees a face. The correct features are active for the sentence “the word parrots is plural”.
If you stop assuming the LLMs have no internal representations of the data, then everything makes a lot more sense! The LLM is FORCED to answer questions… just like a high school student filling out the SAT is forced to answer questions.
If a high school student fills out the wrong answer on the SAT, is that a hallucination?
Hallucinations are expected behaviors if you RLHF a high schooler to always guess an answer on the SAT because that’ll get them the highest score. This applies to ML model reward functions as well.
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Technology does not always help people, in fact often it creates new problems that didn't exist before. Also telling someone to "adapt to the times" is a bit silly. If it helped as much as its claimed, there wouldn't be any need to try and convince people they should be using it. A LOT of parallels with crypto, which is still trying to find its killer app 16 years later.
My parents could have said your first paragraph when I tried to teach them they could Google their questions and find answers. Technology moves forward and productivity improves for those that move with it.
Just by having lived longer, they might've had the chance to develop some intuition about the true cost of disruption, and about how whatever Google's doing is not a free lunch. Of course, neither them, nor you (nor I for that matter) had been taught the conceptual tools to analyze some workings of some Ivy League whiz kinds that have been assigned to be "eating the world" this generation.
Instead we've been incentivized to teach ourselves how to be motivated by post-hoc rationalizations. And ones we have to produce at our own expense too. Yummy.
Didn't Saint Google end up enshittifying people's very idea of how much "all of the world's knowledge" is; gatekeeping it in terms of breadth, depth and availability to however much of it makes AdSense. Which is already a whole lot of new useful stuff at your fingertips, sure. But when they said "organizing all of the world's knowledge" were they making any claims to the representativeness of the selection? No, they made the sure bet that it's not something the user would measure.
In fact, with this overwhelming amount of convincing non-experientially-backed knowledge being made available to everyone - not to mention the whole mass surveillance thing lol (smile, their AI will remember you forever) - what happens first and foremost is the individual becomes eminently marketable-to, way more deeply than over Teletext. Thinking they're able to independently make sense of all the available information, but instead falling prey to the most appealing narrative, not unlike a day trader getting a haircut on market day. And then one has to deal with even more people whose life is something someone sold to them, a race to the bottom in the commoditized activity (in the case of AI: language-based meaning-making).
But you didn't warn your parents about any of that or sit down and have a conversation about where it means things are headed. (For that matter, neither did they, even though presumably they've had their lives altered by the technological revolutions of their own day.) Instead, here you find yourself stepping in for that conversation to not happen among the public, either! "B-but it's obvious! G-get with it or get left behind!" So kind of you to advise me. Thankfully it's just what someone's paid for you to think. And that someone probably felt very productive paying big money for making people think the correct things, too, but opinions don't actually produce things do they? Even the ones that don't cost money to hold.
So if it's not about the productivity but about the obtaining of money to live, why not go extract that value from where it is, instead of breathing its informational exhaust? Oh, just because, figuratively speaking, it's always the banks have AIs that don't balk at "how to rob the bank"; and it's always we that don't. Figures, no? But they don't let you in the vault for being part of the firewall.
In my company I feel that we getting totally overrun with code that's 90% good, 10% broken and almost exactly what was needed. We are producing more code, but quality is definitely taking a hit now that no-one is able to keep up. So instead of slowly inching towards the result we are getting 90% there in no time, and then spending lots and lots of time on getting to know the code and fixing and fine-tuning everything…
This is painfully similar to what happens when a team grows from 3 developers to 10 developers. All of sudden, there's a vast pile of coding being written, you've never seen 75% of it, your architectural coherence is down, and you're relying a lot more on policy and CI.
Where LLM's differ is that you can't meaningfully mentor them, and you can't let them go after the 50th time they try turn off the type checker, or delete the unit tests to hide bugs.
Probably, the most effective way to use LLMs is to make the person driving the LLM 100% responsible for the consequences. Which would mean actually knowing the code that gets generated. But that's going to be complicated to ensure.
As per typical, Martin is so late to the party that he projects his own lack of understanding of the subject to be the general state of matters.
People are, and have been for a while, using LLMs as very effective accelerators or augmentations of themselves.
Claude Code, is a great example of something that can easily one-shot most trivial-to-average programming tasks.
While some wait for the "bubble to burst", a lot of people are gaining significant benefits from using LLMs to boost their speed in software development.
It's not a good idea to muddy the expectations for AI by mixing AGI and LLMs into the same bucket. LLMs are already useful for many purposes, even if they didn't lead to AGI, whatever the definition is.