5 ms·

Contrarily, I think the reality is that most of us couldn't care less about this AI soap opera.

danielbln 2y ago
I want the best model at the lowest rate (and preferably lowest energy expenditure) and with the easiest access. Anything else is just background noise.
- bookaway 2y ago
  Some people are wary of enabling ceos of disruptive technologies become the richest people in the world, take control of key internet assets and -- in random bursts of thin-skinned megalomania -- tilt the scales towards politicians or political groups who take action that negatively affect their own quality of life. It sounds absurd, but some are watching such a procession take place live as we speak.
Geezus_42 2y ago
I still haven't seen it do anything actually interesting. Especially when you consider that you have fact check the AI.
- RHSman2 2y ago
  It spends money really well.
- lambdaba 2y ago
  I'm continously baffled by such comments. Have you really tried? Especially newer models like Claude 3.5?
  - dartos 2y ago
    I have, yeah. Still useless for my day to day coding work. Most useful for whipping up a quick bash or Python script that does some simple looping and file io.
    - somenameforme 2y ago
      To be fair, LLMs are pretty good natural language search engines. Like when I'm looking for something in an API that does something I can describe in natural language, but not succinctly enough to show up in a web search, LLMs are extremely handy, at least when they don't just randomly hallucinate the API. On the other hand I think this is more of a condemnation of the fact that search tech has not 'really' meaningfully advanced beyond where it was 20 years ago, more than it is a praise of LLMs.
      - dartos 2y ago
        > LLMs are extremely handy, at least when they don't just randomly hallucinate I work in tech and it’s my hobby, so that’s what a lot of my googling goes towards. LLMs hallucinate almost every time I ask them anything too specific, which at this point in my career is all I’m really looking for. The time it takes for me to realize an llm is wrong is usually not too bad, but it’s still time I could’ve saved by googling (or whatever trad search) for the docs or manual. I really wish they were useful, but at least for my tasks they’re just a waste of time. I really like them for quickly generating descriptions for my dnd settings, but even then they sound samey if I use them too much. Obviously they’d sound samey if I made up 20 at once too, but at that point I’m not really being helped or enhanced by using an LLM, it’s just faster at writing than I am.
        Workaccount2 2y ago
        I don't mean this as a slight, just an observation I have seen many times - people who struggle with utility from SOTA LLM's tend to not have spent enough time with them to feel out good prompting. In the same way that there is a skill for googling information, there is a skill for teasing consistent good responses from LLM's.
        danielbln 2y ago
        People also continue to use them as knowledge databases, despite that not being where they shine. Give enough context into the model (descriptions, code, documentation, ideas, examples) and have a dialog, that's where these strong LLMs really shine.
  - bamboozled 2y ago
    I hear a lot of people say good things about CoPilot too but I absolutely hate it. I have it enabled for some reason still, but it constantly suggests incorrect things. There has been a few amazing moments but man there is a lot of "bullshit" moments.
  - Workaccount2 2y ago
    Even when we get a gen AI that exceeds all human metrics, there will 100% still be people who with a straight face will say "Meh, I tried it and found it be pretty useless for my work."
- snapcaster 2y ago
  Your bar for interesting has to be insane then. What would you consider interesting if nothing from LLMs meets that bar?
  - aleph_minus_one 2y ago
    For example there exist quite a lot of pure math papers that are so much deeper than basically every AI stuff that I have yet seen.
    - snapcaster 2y ago
      So if LLMs weren't surprising to you, it would imply you expected this. If you did, how much money did you make on financial speculation? It seems like being this far ahead should have made you millions even without a lot of starting capital (look at NVDA alone)
      - aleph_minus_one 2y ago
        > So if LLMs weren't surprising to you, it would imply you expected this. I do claim that I have a tendency to be quite right about the "technological side" of such topics when I'm interested in them. On the other hand, events turn out to be different because of "psychological effects" (let me put it this way: I have a quite different "technology taste" than the market average). In the concrete case of LLMs: the psychological effect why the market behaved so much differently is that I believed that people wouldn't fall for the marketing and hype of LLMs and would consider the excessive marketing to be simply dupery. The surprise to me was that this wasn't what happened. Concerning NVidia: I believed that - considering the insane amount of money involved - people/companies would write new languages and compilers to run AI code on GPUs (or other ICs) of various different suppliers (in particular AMD and Intel) because it is a dangerous business practice to make yourself dependent on a single (GPU) supplier. Even serious reverse-engineering endeavours for doing this should have paid off considering the money involved. I was again wrong about this. So here the surprise was that lots of AI companies made themselves so dependent on NVidia. Seeing lots of "unconventional" things is very helpful for doing math (often the observations that you see are the start of completely new theorems). Being good at stock trading and investing in my opinion on the other hand requires a lot of "street smartness".
- claytongulick 2y ago
  I see it do a lot that's interesting but for programming stuff, I haven't found it to be particularly useful. Maybe I'm doing it wrong? I've been writing code for ~30 years, and I've built up patterns and snippets, etc... that are much faster for me to use than the LLMs. A while ago, I thought I had a eureka moment with it when I had it generate some nodejs code for streaming a video file - it did all kinds of cool stuff, like implement offset headers and things I didn't know about. I thought to myself, "self - you gotta check yourself, this thing is really useful". But then I had to spend hours debugging & fixing the code that was broken in subtle ways. I ended up on google anyway learning all about it and rewrote everything it had generated. For that case, while I did learn some interesting things from the code it generated, it didn't save me any time - it cost me time. I'd have learned the same things from reading an article or the docs on effective ways to stream video from the server, and I'd have written it more correctly the first go around.
greenie_beans 2y ago
then why are you reading hacker news comments about it?
- thfjdtsrsg 2y ago
  I guess I have a masochistic streak.

I want the best model at the lowest rate (and preferably lowest energy expenditure) and with the easiest access. Anything else is just background noise.

bookaway 2y ago
Some people are wary of enabling ceos of disruptive technologies become the richest people in the world, take control of key internet assets and -- in random bursts of thin-skinned megalomania -- tilt the scales towards politicians or political groups who take action that negatively affect their own quality of life. It sounds absurd, but some are watching such a procession take place live as we speak.

Geezus_42 2y ago

I still haven't seen it do anything actually interesting. Especially when you consider that you have fact check the AI.

RHSman2 2y ago
It spends money really well.
lambdaba 2y ago
I'm continously baffled by such comments. Have you really tried? Especially newer models like Claude 3.5?
- dartos 2y ago
  I have, yeah. Still useless for my day to day coding work. Most useful for whipping up a quick bash or Python script that does some simple looping and file io.
  - somenameforme 2y ago
    To be fair, LLMs are pretty good natural language search engines. Like when I'm looking for something in an API that does something I can describe in natural language, but not succinctly enough to show up in a web search, LLMs are extremely handy, at least when they don't just randomly hallucinate the API. On the other hand I think this is more of a condemnation of the fact that search tech has not 'really' meaningfully advanced beyond where it was 20 years ago, more than it is a praise of LLMs.
    - dartos 2y ago
      > LLMs are extremely handy, at least when they don't just randomly hallucinate I work in tech and it’s my hobby, so that’s what a lot of my googling goes towards. LLMs hallucinate almost every time I ask them anything too specific, which at this point in my career is all I’m really looking for. The time it takes for me to realize an llm is wrong is usually not too bad, but it’s still time I could’ve saved by googling (or whatever trad search) for the docs or manual. I really wish they were useful, but at least for my tasks they’re just a waste of time. I really like them for quickly generating descriptions for my dnd settings, but even then they sound samey if I use them too much. Obviously they’d sound samey if I made up 20 at once too, but at that point I’m not really being helped or enhanced by using an LLM, it’s just faster at writing than I am.
      - Workaccount2 2y ago
        I don't mean this as a slight, just an observation I have seen many times - people who struggle with utility from SOTA LLM's tend to not have spent enough time with them to feel out good prompting. In the same way that there is a skill for googling information, there is a skill for teasing consistent good responses from LLM's.
        danielbln 2y ago
        People also continue to use them as knowledge databases, despite that not being where they shine. Give enough context into the model (descriptions, code, documentation, ideas, examples) and have a dialog, that's where these strong LLMs really shine.
- bamboozled 2y ago
  I hear a lot of people say good things about CoPilot too but I absolutely hate it. I have it enabled for some reason still, but it constantly suggests incorrect things. There has been a few amazing moments but man there is a lot of "bullshit" moments.
- Workaccount2 2y ago
  Even when we get a gen AI that exceeds all human metrics, there will 100% still be people who with a straight face will say "Meh, I tried it and found it be pretty useless for my work."
snapcaster 2y ago
Your bar for interesting has to be insane then. What would you consider interesting if nothing from LLMs meets that bar?
- aleph_minus_one 2y ago
  For example there exist quite a lot of pure math papers that are so much deeper than basically every AI stuff that I have yet seen.
  - snapcaster 2y ago
    So if LLMs weren't surprising to you, it would imply you expected this. If you did, how much money did you make on financial speculation? It seems like being this far ahead should have made you millions even without a lot of starting capital (look at NVDA alone)
    - aleph_minus_one 2y ago
      > So if LLMs weren't surprising to you, it would imply you expected this. I do claim that I have a tendency to be quite right about the "technological side" of such topics when I'm interested in them. On the other hand, events turn out to be different because of "psychological effects" (let me put it this way: I have a quite different "technology taste" than the market average). In the concrete case of LLMs: the psychological effect why the market behaved so much differently is that I believed that people wouldn't fall for the marketing and hype of LLMs and would consider the excessive marketing to be simply dupery. The surprise to me was that this wasn't what happened. Concerning NVidia: I believed that - considering the insane amount of money involved - people/companies would write new languages and compilers to run AI code on GPUs (or other ICs) of various different suppliers (in particular AMD and Intel) because it is a dangerous business practice to make yourself dependent on a single (GPU) supplier. Even serious reverse-engineering endeavours for doing this should have paid off considering the money involved. I was again wrong about this. So here the surprise was that lots of AI companies made themselves so dependent on NVidia. Seeing lots of "unconventional" things is very helpful for doing math (often the observations that you see are the start of completely new theorems). Being good at stock trading and investing in my opinion on the other hand requires a lot of "street smartness".
claytongulick 2y ago
I see it do a lot that's interesting but for programming stuff, I haven't found it to be particularly useful. Maybe I'm doing it wrong? I've been writing code for ~30 years, and I've built up patterns and snippets, etc... that are much faster for me to use than the LLMs. A while ago, I thought I had a eureka moment with it when I had it generate some nodejs code for streaming a video file - it did all kinds of cool stuff, like implement offset headers and things I didn't know about. I thought to myself, "self - you gotta check yourself, this thing is really useful". But then I had to spend hours debugging & fixing the code that was broken in subtle ways. I ended up on google anyway learning all about it and rewrote everything it had generated. For that case, while I did learn some interesting things from the code it generated, it didn't save me any time - it cost me time. I'd have learned the same things from reading an article or the docs on effective ways to stream video from the server, and I'd have written it more correctly the first go around.

greenie_beans 2y ago

then why are you reading hacker news comments about it?

thfjdtsrsg 2y ago
I guess I have a masochistic streak.