They're right about everything, but at the same time it actually has become useful.
Sensible not to depend on it and create a vibe-coded mess, but keep everything modular & review the generated code closely and you can go back to humans-only in future with no problems.
If someone offered a whole team of devs in India for an unknown number of months basically for free, one would be a fool to turn that down even knowing it wouldn't last forever. Claude etc feels like the same kinda deal.
> If someone offered a whole team of devs in India for an unknown number of months basically for free, one would be a fool to turn that down even knowing it wouldn't last forever. Claude etc feels like the same kinda deal.
I've made a lot of money fixing software where people paid for those offshore teams and they would have been better off having not done that and writing maintainable software from the start. They were fools paying for it and they still would have been fools if it had been free.
Sure, I've been part of "in-sourcing" failing projects too, but it was always a sign of management incompetence rather than anything else. It's easy to shift the blame to an outsourcer when it's been GIGO; constantly changing requirements, feature creep, no budget for maintenance, the usual stuff that kills codebases.
Given that all serious artists seem to be extremely anti-AI, I strongly suspect that you may be wrong.
I've been trying Fable for coding in the past week and while it's incrementally better than Opus sometimes, what it's churning out is still far from art - and I do think it's possible for code to be art.
If you're defining "serious artists" as some approximation of "people who have made money with their art" then it's clear that there's a conflict of interest here.
Now I happen to be in the camp that believes that AI on its own isn't really capable of producing art (but like a human creating a collage, there can be art created by humans using AI... there is artistic merit in the arrangement).
I still despise that AI is going to be used to strip creators of their labour value, but that's more related to my objection to capitalism than it is to AI.
I'm simply defining serious artists as people who are serious about their art, whether they're award winning filmmakers or amateur photographers. Roughly nobody out of all those people wants to use AI.
(If you want to define it as professional artists instead, then I don't even see much of a conflict of interest. Professional programmers tend to be cautiously optimistic about the new tool and are finding uses for it, why wouldn't professional artists? But, they largely do not see it that way.)
I think it's more that serious artists who don't want to burn their bridges are keeping their AI experimentation/production a secret. It's difficult to openly talk about that work when your friends and acquaintances are saying things like, "People who use gen-ai should die," or, "If you use gen-ai, I never want to talk to you again, instant block."
That side is quite vocal, and has been effective at resulting their fanbases into a witch hunt for anyone who's ever even touched ChatGPT. So anyone who disagrees just stays quiet, for the most part.
I don't know what you're implying, but that's an incorrect read anyhow. "The people in 'MY camp' want me to die, they just don't know that they're talking about me, and it's bad and consistent enough that I've had to mute mutuals to avoid constant anxiety and demoralization," is better.
This is simply cherry-picking (though of course the parent asked for it, by using the word "all" in their original comment - but that doesn't absolve you of resorting to a "gotcha").
If you consider microdramas as art (who knows what art means to people these days) then the Chinese duanju already has not just full shows using AI but also already have big hits using it.
Yes the people making these are frustrated by how much stress it puts on them (directors managing multiple shows at a time daily must be stressful af) but nobody (neither artists nor audience) are complaining about AI usage. As always they don't hate AI, they hate capitalism.
I think the point people are making is that when the text has an "AI smell" (it does), we immediately lose trust in the veracity of any claim being made and feel like continuing to read what is possibly a hallucinated fiction is a complete waste of time.
At this point we're all used to skimming through thousands of AI-generated sentences every working day and constantly thinking "this is likely to be 20% bullshit", it's hard to turn that off even if I try.
Do you think it would help if I went through and manually rewrote all of the prose? If it would get people to listen, I'd be totally willing to do it. It's not like I don't like writing. I just was focused on something else when I was making this, namely trying to find a good methodology that isn't insane for this low amount of data.
When there's no discernable human filter on the text output, reading the text suggests it's what the LLM produced and not what a human considered.
This is low-quality--every single day I witness Codex and Claude misunderstand, mislead, and hallucinate responses based on "assumptions" and I have to fact-check them.
If I wanted a statistical analysis and to be the human in the loop, I would ask the LLM myself, and I would definitely NOT read an article that just dumps the LLM output as-is.
Alright, I'll do that. Although, sadly, I already posted it here, so I won't be able to post it again — I'll be stuck with this trash comments section that doesn't deal with any of the actual claims, just the aesthetics.
I'm pretty sure more people would read it to the end if it didn't seem like AI output, yes.. At the very least you would have fewer (maybe not 0!) comments here saying it's AI slop.
Yeah the Google AI results are more dangerous than ChatGPT, not only because it uses a smaller model but because Google's knowledge graph used to deliver very accurate and authoritative information but now that's been replaced by a stochastic system in the same place, so people are used to trusting it.
I think we’re getting what we deserve by snarkily telling people to Google stuff instead of answering accurately. Google results have never ever been pure accuracy
The point of LMGTFY is to land people on either the official documentation or a curated site like Stack Overflow. Google used to be able to do that reliably.
With the power of LLMs you can Google a standard library function and get an inaccurate summarisation of a Reddit discussion where neither side knows what they're talking about
Stack Overflow and Reddit for years have told people to just Google it. And then the Google result is people saying to just Google it, instead of actually being helpful.
To be fair - for all of those years Google has been serving up some atrocious results - remember when googling health symptoms got you rabies or pregnancy.
There's even the meme where people ask if the code was the result of a stack overflow question, or answer
It seems to me one needs to consider the complexity of the question they are asking before searching it.
To stick with your post, consider people asking medical or financial questions. For a wide variety of reasons, many of such questions don't have an answer. In such cases, AI is still going to take a crack at it. AI shouldn't be blamed for "bullshit answers" to such questions.
Before using AI, I think people should stop and ask themselves, "Is there really a single answer to this question? Is AI the right choice?"
The problem is Google's AI results get even simple factual questions wrong all the time.
Earlier today, I searched "pixel 10 wifi 7" because I was confused that GSMArena showed my Pixel 8 supports Wifi 7, but the Pixel 10 only Wifi 6. Gemini confidently claimed that the Pixel 10 does support Wifi 7 -- but that's not true at all. Only the Pixel 10 _Pro_ supports it, as I discovered when actually reading the non-AI search results.
I had a similar thing when I was gooling a few days ago, I can't remember exactly but it was like "why does [product] not support [feature]" and the AI summary was confidently wrong, saying "The product does support [feature]", which knew was completely incorrect, and I did find a Reddit discussion or something in the actual results with discussions that were actually about what I was looking for!
It's really depressing how bad things are getting...
It’s hilariously persistent in this, esp. for anything even slightly divergent from the beaten path. Discount everything the AI box says about emacs to zero.
Admittedly I’m unsure if it was Google or DuckDuckGo. I switch between both. I quickly asked the in search AI for a UTC time conversion like a lazy fool and it got it off by almost a day wrong.
I avoid any asking any agent a fact-based (especially math) request. It's a great compression algorithm and a great language generator, and I guess the intersection of those two things is "an answer". Calculation doesn't intersect.
My google search for 'pixel 10 wifi 7' immediately shows the right answer. (10 Pro and 10 Pro XL support it but, but base Pixel 10 only supports Wifi 6E).
Though the inconsistency of results between users is definitely another frustrating thing.
Because LLMs aren't sentient, they don't draw on facts, and they don't have nuance. The answer given is similar to answers you might expect to see for similar questions.
It's really amazing we can make machines do that, and it's really depressing that we think a stochastic bullshit machine is going to give us something we can rely on.
Or… the default LLM Google uses for search has been quantized to s**. Ask a proper Thinking model, with browsing enabled, and odds of a correct answer are much higher. There’s been substantial improvement in AI in even the last year.
Ask a human a question like this, and they also have a chance of getting it wrong, even when confident.
Why would a human know specs for a random phone off the top of their head? The human response is either "I don't know" or "let me look that up", not a hallucination.
I think that it feels a little wasteful to go to Google search to ask a question like this, only for the AI that's giving you an answer instead of page results to perform its own web search to get you the response.
Also, I asked a thinking model with browsing enabled and got this:
> The Google Pixel 10 is expected to support Wi-Fi 7 (802.11be), based on the Qualcomm Snapdragon 8 Gen 4 / Tensor G5 chipset it will likely use, which includes an integrated Wi-Fi 7 modem. Specific finalized specs aren't confirmed until Google's official announcement.
(Model GLM-5-Turbo - two months old - using Kilo Code in the "Ask" profile; in its thinking token churn it reasoned that it should keep the response brief and direct. Perhaps not the best suite of model+harness for this task, but it's what I had to hand that's not quantized to shit, is a thinking model, and has a web search tool available to it.)
> Ask a human a question like this, and they also have a chance of getting it wrong, even when confident.
We google something specifically because the humans within reach don't know. The goal of searching is, well, to search pages - we're trying to find a site when we use google search.
The goal when using an LLM is generally different; we want an answer, not a site.
LLMs can not point you to sites, only in a general direction. That is because complete URLs do not exist as single tokens in any of the large models. It can synthesize a plausible-looking url, and if you're lucky that URL might even exist. But that doesn't mean that there is any relation between between the text surrounding a hyperlink in LLM output and the text on the linked page.
AI agents can verify and summarize URLs, but a plain LLM can not.
its bad in dev as well... i've seen llm code review bots tell me things that are flat-out not true; this like "this wont compile because windows 11 doesn't exist" like wtf am i paying for this again?
They are this wrong about everything, but you don't usually notice it when using it to look for things you aren't an expert in. The default stance really does need to be "do not trust, verify" at all times.
They can still be useful, e.g. they're significantly better at finding "I want a thing that does x but not y and it must be blue, or maybe two things that can be glued together to do that" than classic search. But they'll routinely miss extremely obvious answers because the related search it ran didn't find it, or completely screw up what something can actually do. Checking more pages of results by hand or asking humans who know even a little about those fields is still wildly more useful... but they're absolutely slaughtering the sites where people do that, by stealing all the real traffic and sending DDoS-level automated requests.
How can you say they are wrong about "everything"?
I built a retro game clone once and I used that project as a way to try out AI. While it wasn't perfect, it definitely wasn't wrong about everything. I'd go so far as to say it was probably correct (or damn close) 75% of the time.
I see people on HN all the time saying AI is terrible, but that just isn't the experience I'm having. I'm willing to admit it may have something to do with me not being able to recognize I'm being fed bullshit. Or, I may be asking really simple questions. Who knows? But AI seems like a pretty useful tool for average people.
Your profile says you're a guitarist. Take the model and talk to it about guitars. Not like "what's a good Stratocaster clone", talk to it about materials, physics and playing techniques and see if it feels like a reliable source of information (or even a solid thinking buddy), or someone who read a lot about guitars but has actually never played one.
I know bits from non-IT fields like RC planes and quads, electric motors, aerodynamics, mountain biking, cars. I often use Claude (Opus 4.7 on Max sub atm) to brainstorm new ideas or refine my understanding of some phenomena, and almost without fail, I can get it to claim something ridiculously stupid or contradictory 5-10 messages in. I can usually catch it, because I don't venture far from what I'm already familiar with, and I also need explanations to be thorough and things to make total sense to me before I accept them, but not everyone is that pedantic.
I’d make assumptions about how the cheapest and fastest possible flash model optimized for being extra cheap and extra fast would get something wrong based on its limited context (which can be very incomplete summaries of search results)
I often have the expensive models give relatively simple inaccurate answers, even when they cite sources that directly contradict them. The error rate is lower, but you can’t have confidence with llm answers.
It somehow seems to interpret whatever sources it's grepping as the exact opposite of what those sources say fairly often. I've lost track of how many times I've clicked on the sources it cites, and every single one is in agreement, but the AI claims the opposite.
In watching the demo, I didn't come away with the impression that they were removing search results. Yes, they are pushing AI hard, but users can still opt to use Google in the more traditional way. Unless I misunderstood the demo, it's definitely possible to choose.
An interesting aspect of this is the decrease in quality feedback on th organic links. If most people never get down to the actual links there is very little to tell which ones were good or if they had any relevance.
There is also that less incentive to properly maintain the search algorithms to fight SEO and spam.
For all intents and purpose, organic search results have been given a death sentence and are just waiting for the last moment.
> one needs to consider the complexity of the question they are asking before searching...consider people asking medical or financial questions...many of such questions don't have an answer. In such cases, AI is still going to take a crack at it. AI shouldn't be blamed for "bullshit answers"...people should stop and ask themselves, "Is there really a single answer to this question?
It's a bold position to say that it's the users fault for being lied to by Google. There isn't a "single answer" to most questions. It's still Google's job to provide answers that are accurate and reflect the best information available on complicated topics. That's what they're trying to sell us anyway. When google's AI can't live up to the hype "You shouldn't be asking AI such difficult questions" is not a great response, especially when people are just trying to get web search results and AI is suddenly interrupting with an opinion nobody asked for.
They didn't say "nobody can replace the battery themselves", and "you" here was probably intended to mean "a normal consumer". Relative to items with replaceable batteries (a TV remote control, a camera, a pre-iPhone mobile phone), the batteries are extremely hard to replace.
The batteries are also not safe to replace, relative to items with replaceable batteries. There is a very low chance of me accidentally damaging my TV remote control while replacing the batteries.
None of the information you're responding to is false, and it's perhaps worth asking yourself why you're here defending Apple.
There's an easier argument that is simply "But Samsung!".
A "normal consumer", at least in most of the US, can take their iPhone to an Apple store, a Best Buy, and probably several small phone repair services that have small stores or kiosks in a nearby mall or inside a Walmart.
From an environmental point of view it doesn't matter if you do the repair yourself or you have it done by someone else.
> and "you" here was probably intended to mean "a normal consumer".
Which is why I used a normal consumer as an example.
> None of the information you're responding to is false, and it's perhaps worth asking yourself why you're here defending Apple.
I’m not defending Apple, I’m defending accuracy. When someone says something inaccurate about someone or something I oppose, I try to correct that too. It’s important that arguments are based on truth, because when they are not people start dismissing the true with the false.
My comment history shows I’m an Apple user but am constantly criticising its current state and Tim Cook. You’ll find more comments of mine criticising than praising them.
Perhaps it’s worth asking yourself why you see someone making an argument once and immediately assume they may have ulterior motives, and why you’re actively ignoring the arguments which do not feed your view, including my clear and repeated assertions in the thread that Apple should absolutely do better.
> There's an easier argument that is simply "But Samsung!".
Which was not once my argument. I abhor whataboutism.
I thought the same when I got a Fuji, but the issue is support for the X-Trans sensor. Turns out that converting to DNG doesn't change that and software that opens the DNG still needs to understand how to use the data in it.
Sensible not to depend on it and create a vibe-coded mess, but keep everything modular & review the generated code closely and you can go back to humans-only in future with no problems.
If someone offered a whole team of devs in India for an unknown number of months basically for free, one would be a fool to turn that down even knowing it wouldn't last forever. Claude etc feels like the same kinda deal.