Hacker News Board Hacker News, browsed like a classic message board
Live data from Hacker News

Let's be honest, Generative AI isn't going all that well

garymarcus.substack.com

Post reply on HN
Print view View original

101–110 of 346 posts

Re: Let's be honest, Generative AI isn't going all that well

#101

Post by sheeh »

habinero wrote: post #66
fzeroracer wrote: post #33

Earlier quoted context omitted.

> Meanwhile, my cofounder is rewriting code we spent millions of salary on in the past by himself in a few weeks. This is one of those statements that would horrify any halfway competent engineer. A cowboy coder going in, seeing a bunch of code and going 'I should rewrite this' is one of the biggest liabilities to any stable system.

Every professional SWE is going to stare off into the middle distance, as they flashback to some PM or VP deciding to show everyone they still got it. The "how hard could it be" fallacy claims another!

As someone who is more involved in shaping the product direction rather than engineering what composes the product - I will readily admit many product people are utterly, utterly clueless.

Most people have no clue the craftsmanship, work etc it takes to create a great product. LLMs are not going to change this, in fact they serve as a distraction.

I’m not a SWE so I gain nothing by being bearish on the contributions of LLMs to the real economy ;)

Re: Let's be honest, Generative AI isn't going all that well

#102

Post by m463 »

I see stuff like this and think of these two things:

1) https://en.wikipedia.org/wiki/Gartner_hype_cycle

or

2) "First they ignore you, then they laugh at you, then they fight you, then you win."

or maybe originally:

"First they ignore you. Then they ridicule you. And then they attack you and want to burn you. And then they build monuments to you"

Re: Let's be honest, Generative AI isn't going all that well

#103

Post by zdragnar »

CjHuber wrote: post #100
falloutx wrote: post #90

Earlier quoted context omitted.

I dispute 1 & 2 more than 4. 1) Is it actually watching a movie frame by frame or just searching about it and then giving you the answer? 2) Again can it handle very long novels, context windows are limited and it can easily miss something. Where is the proof for this? 4 is probably solved 4) This is more on predictor because this is easy to game. you can create some gibberish code with LLM today that is 10k lines lo…

I think all of those are terrible indicators, 1 and 2 for example only measure how well LLMs can handle long context sizes. If a movie or novel is famous the training data is already full of commentary and interpretations of them. If its something not in the training data, well I don't know many movies or books that use only motives that no other piece of content before them used, so interpreting based on what is sim…

Just yesterday I saw an article about a police station's AI body cam summarizer mistakenly claim that a police officer turned into a frog during a call. What actually happened was that the cartoon "princess and the frog" was playing in the background.

Sure, another model might have gotten it right, but I think the prediction was made less in the sense of "this will happen at least once" and more of "this will not be an uncommon capability".

When the quality is this low (or variable depending on model) I'm not too sure I'd qualify it as a larger issue than mere context size.

Re: Let's be honest, Generative AI isn't going all that well

#104

Post by jgalt212 »

gejose wrote: post #42

I believe Gary Marcus is quite well known for terrible AI predictions. He's not in any way an expert in the field. Some of his predictions from 2022 [1] > In 2029, AI will not be able to watch a movie and tell you accurately what is going on (what I called the comprehension challenge in The New Yorker, in 2014). Who are the characters? What are their conflicts and motivations? etc. > In 2029, AI will not be able to r…

This comment or something very close always appears alongside a Gary Marcus post.

Re: Let's be honest, Generative AI isn't going all that well

#105

Post by verse »

bspammer wrote: post #92
merlincorey wrote: post #59

Earlier quoted context omitted.

Which ones are you claiming have already been achieved? My understanding of the current scorecard is that he's still technically correct, though I agree with you there is velocity heading towards some of these things being proven wrong by 2029. For example, in the recent thread about LLMs and solving an Erdos problem I remember reading in the comments that it was confirmed there were multiple LLMs involved as well as…

The bug-free code one feels unfalsifiable to me. How do you prove that 10,000 lines of code is bug-free, and then there's a million caveats about what a bug actually is and how we define one. The second claim about novels seems obviously achieved to me. I just pasted a random obscure novel from project gutenberg into a file and asked claude questions about the characters, and then asked about the motivations of a ran…

I agree with you but I'd point out that unless you've read the book it's difficult to know if the answer you got was accurate or it just kinda made it up. In my experience it makes stuff up.

Like, it behaves as if any answer is better than no answer.

Re: Let's be honest, Generative AI isn't going all that well

#106

Post by tombert »

onlyrealcuzzo wrote: post #83
tombert wrote: post #10

I find it a bit odd that people are acting like this stuff is an abject failure because it's not perfect yet. Generative AI, as we know it, has only existed ~5-6 years, and it has improved substantially, and is likely to keep improving. Yes, people have probably been deploying it in spots where it's not quite ready but it's myopic to act like it's "not going all that well" when it's pretty clear that it actually is g…

> Generative AI, as we know it, has only existed ~5-6 years, and it has improved substantially, and is likely to keep improving. I think the big problem is that the pace of improvement was UNBELIEVABLE for about 4 years, and it appears to have plateaued to almost nothing. ChatGPT has barely improved in, what, 6 months or so. They are driving costs down incredibly, which is not nothing. But, here's the thing, they're…

I think that even if it never improves, its current state is already pretty useful. I do think it's going to improve though I don't think AGI is going to happen any time soon.

I have no idea what this is called, but it feels like a lot of people assume that progress will continue at a linear pace for forever for things, when I think that generally progress is closer to a "staircase" shape. A new invention or discovery will lead to a lot of really cool new inventions and discoveries in a very short period of time, eventually people will exhaust the low-to-middle-hanging fruit, and progress kind of levels out.

I suspect it will be the same way with AI; I don't now if we've reached the top of our current plateau, but if not I think we're getting fairly close.

Re: Let's be honest, Generative AI isn't going all that well

#107

Post by CjHuber »

zdragnar wrote: post #103
CjHuber wrote: post #100

Earlier quoted context omitted.

I think all of those are terrible indicators, 1 and 2 for example only measure how well LLMs can handle long context sizes. If a movie or novel is famous the training data is already full of commentary and interpretations of them. If its something not in the training data, well I don't know many movies or books that use only motives that no other piece of content before them used, so interpreting based on what is sim…

Just yesterday I saw an article about a police station's AI body cam summarizer mistakenly claim that a police officer turned into a frog during a call. What actually happened was that the cartoon "princess and the frog" was playing in the background. Sure, another model might have gotten it right, but I think the prediction was made less in the sense of "this will happen at least once" and more of "this will not be…

My point was not that those video to text models are good like they are used for example in that case, but more generally I was referring to that list of indicators. Like surely when analysing a movie it is alright if some things are misunderstood by it, especially as the amount of misunderstanding can be decreased a lot. That AI body camera surely is optimized on speed and inference cost. but if you give an agent 10 1s images along with the transcript of that period and the full prior transcript, and give it reasoning capabilities, it would take almost endlessy for that movie to process but the result surely will be much better than the body cameras. After all the indicator talks about "AI" in general so judge a model not optimized for capability but something else to measure on that indicator

Re: Let's be honest, Generative AI isn't going all that well

#108

Post by tombert »

1970-01-01 wrote: post #96
tombert wrote: post #10

I find it a bit odd that people are acting like this stuff is an abject failure because it's not perfect yet. Generative AI, as we know it, has only existed ~5-6 years, and it has improved substantially, and is likely to keep improving. Yes, people have probably been deploying it in spots where it's not quite ready but it's myopic to act like it's "not going all that well" when it's pretty clear that it actually is g…

>and is likely to keep improving. I'm not trying to be pedantic, but how did you arrive at 'keep improving' as a conclusion? Nobody is really sure how this stuff actually works. That's why AI safety was such a big deal a few years ago.

Totally reasonable question, and I only am making an assumption based on observed progress. AI generated code, at least in my personal experience, has gotten a lot better, and while I don't think that will go to infinity, I do think that there's still more room for improvement that could happen.

I will acknowledge that I don't have any evidence of this claim, so maybe the word "likely" was unwise, as that suggests probability. Feel free to replace "is "likely to" with "it feels like it will".

Re: Let's be honest, Generative AI isn't going all that well

#109

Post by maccard »

tombert wrote: post #22
maccard wrote: post #14

Earlier quoted context omitted.

> Generative AI, as we know it, has only existed ~5-6 years, and it has improved substantially, and is likely to keep improving. Every 2/3 months we're hearing there's a new model that just blows the last one out of the water for coding. Meanwhile, here I am with Opus and Sonnet for $20/mo and it's regularly failing at basic tasks, antigravity getting stuck in loops and burning credits. We're talking "copy basic exam…

Sure, but think about what it's replacing. If you hired a human, it will cost you thousands a week. Humans will also fail at basic tasks, get stuck in useless loops, and you still have to pay them for all that time. For that matter, even if I'm not hiring anyone, I will still get stuck on projects and burn through the finite number of hours I have on this planet trying to figure stuff out and being wrong for a lot of…

You’ve missed my point here - I agree that gen AI has changed everything and is useful, _but_ I disagree that it’s improved substantially - which is what the comment I replied to claimed.

Anecdotally I’ve seen no difference in model changes in the last year, but going from LLM to Claude code (where we told the LLMs they can use tools on our machines) was a game changer. The improvement there was the agent loop and the support for tools.

In 2023 I asked v0.dev to one shot me a website for a business I was working on and it did it in about 3 minutes. I feel like we’re still stuck there with the models.

Re: Let's be honest, Generative AI isn't going all that well

#110

Post by maccard »

BeetleB wrote: post #91
drewbug01 wrote: post #32

Earlier quoted context omitted.

> If your metric is an LLM that can copy/paste without alterations, and never hallucinate APIs, then yeah, you'll always be disappointed with them. I struggle to take comments like this seriously - yes, it is very reasonable to expect these magical tools to copy and paste something without alterations. How on earth is that an unreasonable ask? The whole discourse around LLMs is so utterly exhausting. If I say I don't…

For a long time, I've wanted to write a blog post on why programmers don't understand the utility of LLMs[1], whereas non-programmers easily see it. But I struggle to articulate it well. The gist is this: Programmers view computers as deterministic . They can't tolerate a tool that behaves differently from run to run. They have a very binary view of the world: If it can't satisfy this "basic" requirement, it's crap.…

I’m perfectly happy for my tooling to not be deterministic. I’m not happy for it to make up solutions that don’t exist, and get stuck in loops because of that.

I use LLMs, I code with a mix of antigravity and Claude code depending on the task, but I feel like I’m living in a different reality when the code I get out of these tools _regularly just doesn’t work, at all_. And to the parents point, I’m doing something wrong for noticing that?

Post reply on HN