9 ms·

We’ll see, but I doubt its because of the election; as another commenter said companies can’t afford to lose that much money by waiting around for months for th

We’ll see, but I doubt its because of the election; as another commenter said companies can’t afford to lose that much money by waiting around for months for the right “moment” to release a product. GPT-4o is good, I’ll grant you that, but its fundenmentally the same tech as GPT3.5 and the fundenmental problem, “hallucination,” is not solved, even if there are more capabilities. No matter what, for anything besides code that may or may not be any good, someone has to go through and read the response and make sure its all tight so they don’t fuck up or embarass themselves (and even then, using AI for coding will introduce long term problems since you’ll have to go back through it for debugging anyway). We all, within a month of ChatGPT getting introduced, caught it in a contradiction or just plain error about some topic of specialist knowledge, and realized that its level of expertise on all topics was at that same level. Sam Altman royallly fucked up when he started believing his own bullshit, thinking AGI was on the horizon and all we needed was to waste more resources on compute time and datacenters. Its done, you can’t make another LLM, all knowledge from here on out is corrupted by them, you can never deliver an epistemic “update.” GPT will become a relic of the 21st century, like a magazine from the 1950s.

cdelsolar 2y ago
I don’t think you’ve used LLMs enough. They are revolutionary, every day. As a coder I’m several times more productive than I was before, especially when trying to learn some new library or language.
- dax_ 2y ago
  Do you perhaps have some resources on how you use AI assistants for coding (I'm assuming Github Copilot). I've been trying it for the past months, and frankly, it's barely helping me at all. 95% of the time the suggestions are just noise. Maybe as a fast typer it's less useful, I just wonder why my experience is so different than what others are saying. So maybe it's because I'm not using it right?
  - kybernetyk 2y ago
    My experience is similar. Most of the results are not really useful so I have to put work in to fix them. But at that point I can do the small extra step of doing it completely myself.
  - inthebin 2y ago
    I think it's your mindset and how you approach it. E.g. some people are genuinely bad at googling their way to a solution. While some people know exactly how to manipulate the google search due to years of experience debugging problems. Some people will be really good at squeezing out the right output from ChatGPT/Copilot and utilize it to maximum potential, while others simply won't make the connection. Its output depends on your input. E.g. say you have an API swagger documentation and you want to generate a Typescript type definition using that data, you just copy paste the docs into a comment above the type, and copilot auto fills your Typescript type definition even adding ? for properties which are not required. If you define clearly the goal of a function in a JSDoc comment, you can implement very complex functions. E.g. you define it in steps, and in the function line out each step. This also helps your own thinking. With GPT 4o you can even draw diagrams in e.g. excalidraw or take screenshots of the issues in your UI to complement your question relating to that code.
    - DiscourseFan 2y ago
      > E.g. you define it in steps, and in the function line out each step. This also helps your own thinking Yeah but there are other ways to think through problems, like asking other people what they think, which you can evaluate based on who they are and what they know. GPT is like getting advice from a cross-section of everyone in the world (and you don’t even know which one), which may be helpful depending on the question and the “people” answering it, but it may also be extroadinarily unhelpful, especially for very specialized tasks (and specialized tasks are where the profit is). Like most people, I have knowledge of things very specific I know that less than a 100 people in the world know better than me, but thousands or even millions more have some poorly concieved general idea about it. If you asked GPT to give you an answer to a question it would bias those millions, the statistically greater quantative solution, to the qualitative one. But, maybe, GPT only has a few really good indexes in its training data that it uses for its response, and then its extremely helpful because its like accidentally landing on a stackoverflow response by some crazy genius who reads all day, lives out of a van in the woods, and uses public library computers to answer queries in his spare time. But that’s sheer luck, and no more so than a regular search will get you.
- jazzyjackson 2y ago
  Are you making several times as much money? IME LLMs are great at giving you the experience of learning, in the same way sugar gives you the experience of nourishment
  - barrkel 2y ago
    Developer productivity doesn't map very directly to compensation. If one engineer is 10x as productive as another, they're lucky if they get 2x the compensation.
    - amelius 2y ago
      The 10x engineer will just start their own company.
      - Rinzler89 2y ago
        A good programmer isn't necessarily also good at business to run his own company. Sure, you have your John Carmaks' or Antirezs' of the industry who are 10x programmers and also successful founders but those guys are 1 in a million. But your usual 10x engineer you'll meet is the guy who knows the ins and outs of all running systems at work giving him the ability to debug and solve issues 10x quicker than the rest, knowledge which is highly specific to the products of that company and is often non-transferrable and also not useful at entrepreneurship. Becoming the 10x engineer at a company usually means pigeonholing yourself in the deep inner workings of the products, which may or may not be useful later. If that stack is highly custom or proprietary it might work in your favor making you the 10x guy virtually unfireable being able to set your own demands since only you can solve the issues, or might backfire against you at a round of layoffs as your knowledge of that specific niche has little demand elsewhere.
        kybernetyk 2y ago
        >A good programmer isn't necessarily also good at business to run his own company. AI can help with that.
- ardaoweo 2y ago
  They are revolutionary for use cases where hallucinated / wrong / unreliable output is easy and cheap to detect & fix, and where there's enough training data. That's why it fits programming so well - if you get bad code, you just throw it away, or modify it until it works. That's why it work for generic stock images too - if you get bad image, you modify the prompt, generate another one and see if it's better. But many jobs are not like that. Imagine an AI nurse giving bad health advice on phone. Somebody might die. Or AI salesman making promises that are against company policy? Company is likely to be held legally liable, and may lose significant money. Due to legal reasons, my company couldn't enable full LLM generative capabilities on chatbot we use, because we would be legally responsible for anything it generates. Instead, LLM is simply used to determine which of the pre-determined answers may fit the query the best, which it indeed does well when more traditional technologies fail. But that's not revolutionary, just an improvement. I suspect there are many barriers like that, which hinder its usage in many fields, even if it could work most of the time. So, nearly all use cases I can think of now will still require a human in the loop, simply because of the unreliability. That way it can be a productivity booster, but not a replacement.
  - pennomi 2y ago
    A product doesn’t have to be useful for everything to still be useful.
  - mewpmewp2 2y ago
    To me those usecases are already revolutionary. And human in the loop doesn't mean it is not revolutionary. I see it multiplying human productivity rather than as immediate replacement. And it can take some time before it is properly iterated and integrated everywhere in a seamless manner.
  - sirspacey 2y ago
    If you adjust your standard to the level of human performance in most roles, including nursing, you’ll find that AI is reasonably similar to most people in that in makes errors, sometimes convincing ones, and that recovering from those errors is something all social/org systems must do & don’t always get right. Human in the loop can add reliability, but the most common use cases I’m seeing with AI are helping people see the errors they are making/their lack of sufficient effort to solve the problem.
- lumenwrites 2y ago
  This comment doesn't deserve the downvotes its getting, the author is right, and I'm having the same experience. LLM outputs aren't always perfect, but that doesn't stop them from being extremely helpful and massively increasing my productivity. They help me to get things done with the tech I'm familiar with much faster, get things done with tech I'm unfamiliar with that I wouldn't be able to do before, and they are extremely helpful for learning as well. Also, I've noticed that using them has made me much more curious. I'm asking so many new questions now, I've had no idea how many things I was casually curious about, but not curious enough to google.
  - Workaccount2 2y ago
    Good luck telling a bunch of programmers that their skills are legitimately under threat. No one wants to hear that. Especially when you are living a top 10% lifestyle on the back of being good at communicating to computers. There is an old documentary of the final days of typesetters for newspapers. These were the (very skilled) people who rapidly put each individual carved steel character block into the printing frame in order print thousands of page copies. Many were incredulous that a machine could ever replicate their work. I don't think programmers are going to go away, but I do think those juicy salaries and compensation packages will.
    - JohnFen 2y ago
      > I do think those juicy salaries and compensation packages will. I think that's inevitable with or without LLMs in the mix. I also think the industry as a whole will be better for it.
      - DiscourseFan 2y ago
        Horses before the automobile
    - selimthegrim 2y ago
      What’s the title of the documentary?
- JohnFen 2y ago
  > I don’t think you’ve used LLMs enough. They are revolutionary, every day. How much is "enough"? Neither myself nor my coworkers have found LLMs to be all that useful in our work. Almost everybody has stopped bothering with them these days.
  - carbine 2y ago
    what line of work are you in?
Agentus 2y ago
even if the datacenter increase was a waste because the potential of LLMs never pan out relative to the massive investment, i think the flood of gpu and compute will definitely enable whatever could benefit from it. The next better AI application will be very thankful that gpu compute is abundant.
- nuc1e0n 2y ago
  GPUs are easily and irreparably broken by overheating, so GPU compute is something that's high maintenance. It won't stick around like a building or a bridge.
  - tekknik 2y ago
    Luckily data centers have this thing called “air conditioning”…
    - DiscourseFan 2y ago
      Air conditioning is just heat displacement. It doesn't get rid of the heat, and if it gets hot enough it becomes physically impossible to remove enough heat to cool a building down, no matter how many air conditioners are installed.
      - tekknik 2y ago
        Yea that’s why we have this problem today with data centers overheating. Don’t put chips on top of each other and you’re fine.

cdelsolar 2y ago

I don’t think you’ve used LLMs enough. They are revolutionary, every day. As a coder I’m several times more productive than I was before, especially when trying to learn some new library or language.

dax_ 2y ago
Do you perhaps have some resources on how you use AI assistants for coding (I'm assuming Github Copilot). I've been trying it for the past months, and frankly, it's barely helping me at all. 95% of the time the suggestions are just noise. Maybe as a fast typer it's less useful, I just wonder why my experience is so different than what others are saying. So maybe it's because I'm not using it right?
- kybernetyk 2y ago
  My experience is similar. Most of the results are not really useful so I have to put work in to fix them. But at that point I can do the small extra step of doing it completely myself.
- inthebin 2y ago
  I think it's your mindset and how you approach it. E.g. some people are genuinely bad at googling their way to a solution. While some people know exactly how to manipulate the google search due to years of experience debugging problems. Some people will be really good at squeezing out the right output from ChatGPT/Copilot and utilize it to maximum potential, while others simply won't make the connection. Its output depends on your input. E.g. say you have an API swagger documentation and you want to generate a Typescript type definition using that data, you just copy paste the docs into a comment above the type, and copilot auto fills your Typescript type definition even adding ? for properties which are not required. If you define clearly the goal of a function in a JSDoc comment, you can implement very complex functions. E.g. you define it in steps, and in the function line out each step. This also helps your own thinking. With GPT 4o you can even draw diagrams in e.g. excalidraw or take screenshots of the issues in your UI to complement your question relating to that code.
  - DiscourseFan 2y ago
    > E.g. you define it in steps, and in the function line out each step. This also helps your own thinking Yeah but there are other ways to think through problems, like asking other people what they think, which you can evaluate based on who they are and what they know. GPT is like getting advice from a cross-section of everyone in the world (and you don’t even know which one), which may be helpful depending on the question and the “people” answering it, but it may also be extroadinarily unhelpful, especially for very specialized tasks (and specialized tasks are where the profit is). Like most people, I have knowledge of things very specific I know that less than a 100 people in the world know better than me, but thousands or even millions more have some poorly concieved general idea about it. If you asked GPT to give you an answer to a question it would bias those millions, the statistically greater quantative solution, to the qualitative one. But, maybe, GPT only has a few really good indexes in its training data that it uses for its response, and then its extremely helpful because its like accidentally landing on a stackoverflow response by some crazy genius who reads all day, lives out of a van in the woods, and uses public library computers to answer queries in his spare time. But that’s sheer luck, and no more so than a regular search will get you.
jazzyjackson 2y ago
Are you making several times as much money? IME LLMs are great at giving you the experience of learning, in the same way sugar gives you the experience of nourishment
- barrkel 2y ago
  Developer productivity doesn't map very directly to compensation. If one engineer is 10x as productive as another, they're lucky if they get 2x the compensation.
  - amelius 2y ago
    The 10x engineer will just start their own company.
    - Rinzler89 2y ago
      A good programmer isn't necessarily also good at business to run his own company. Sure, you have your John Carmaks' or Antirezs' of the industry who are 10x programmers and also successful founders but those guys are 1 in a million. But your usual 10x engineer you'll meet is the guy who knows the ins and outs of all running systems at work giving him the ability to debug and solve issues 10x quicker than the rest, knowledge which is highly specific to the products of that company and is often non-transferrable and also not useful at entrepreneurship. Becoming the 10x engineer at a company usually means pigeonholing yourself in the deep inner workings of the products, which may or may not be useful later. If that stack is highly custom or proprietary it might work in your favor making you the 10x guy virtually unfireable being able to set your own demands since only you can solve the issues, or might backfire against you at a round of layoffs as your knowledge of that specific niche has little demand elsewhere.
      - kybernetyk 2y ago
        >A good programmer isn't necessarily also good at business to run his own company. AI can help with that.
ardaoweo 2y ago
They are revolutionary for use cases where hallucinated / wrong / unreliable output is easy and cheap to detect & fix, and where there's enough training data. That's why it fits programming so well - if you get bad code, you just throw it away, or modify it until it works. That's why it work for generic stock images too - if you get bad image, you modify the prompt, generate another one and see if it's better. But many jobs are not like that. Imagine an AI nurse giving bad health advice on phone. Somebody might die. Or AI salesman making promises that are against company policy? Company is likely to be held legally liable, and may lose significant money. Due to legal reasons, my company couldn't enable full LLM generative capabilities on chatbot we use, because we would be legally responsible for anything it generates. Instead, LLM is simply used to determine which of the pre-determined answers may fit the query the best, which it indeed does well when more traditional technologies fail. But that's not revolutionary, just an improvement. I suspect there are many barriers like that, which hinder its usage in many fields, even if it could work most of the time. So, nearly all use cases I can think of now will still require a human in the loop, simply because of the unreliability. That way it can be a productivity booster, but not a replacement.
- pennomi 2y ago
  A product doesn’t have to be useful for everything to still be useful.
- mewpmewp2 2y ago
  To me those usecases are already revolutionary. And human in the loop doesn't mean it is not revolutionary. I see it multiplying human productivity rather than as immediate replacement. And it can take some time before it is properly iterated and integrated everywhere in a seamless manner.
- sirspacey 2y ago
  If you adjust your standard to the level of human performance in most roles, including nursing, you’ll find that AI is reasonably similar to most people in that in makes errors, sometimes convincing ones, and that recovering from those errors is something all social/org systems must do & don’t always get right. Human in the loop can add reliability, but the most common use cases I’m seeing with AI are helping people see the errors they are making/their lack of sufficient effort to solve the problem.
lumenwrites 2y ago
This comment doesn't deserve the downvotes its getting, the author is right, and I'm having the same experience. LLM outputs aren't always perfect, but that doesn't stop them from being extremely helpful and massively increasing my productivity. They help me to get things done with the tech I'm familiar with much faster, get things done with tech I'm unfamiliar with that I wouldn't be able to do before, and they are extremely helpful for learning as well. Also, I've noticed that using them has made me much more curious. I'm asking so many new questions now, I've had no idea how many things I was casually curious about, but not curious enough to google.
- Workaccount2 2y ago
  Good luck telling a bunch of programmers that their skills are legitimately under threat. No one wants to hear that. Especially when you are living a top 10% lifestyle on the back of being good at communicating to computers. There is an old documentary of the final days of typesetters for newspapers. These were the (very skilled) people who rapidly put each individual carved steel character block into the printing frame in order print thousands of page copies. Many were incredulous that a machine could ever replicate their work. I don't think programmers are going to go away, but I do think those juicy salaries and compensation packages will.
  - JohnFen 2y ago
    > I do think those juicy salaries and compensation packages will. I think that's inevitable with or without LLMs in the mix. I also think the industry as a whole will be better for it.
    - DiscourseFan 2y ago
      Horses before the automobile
  - selimthegrim 2y ago
    What’s the title of the documentary?
JohnFen 2y ago
> I don’t think you’ve used LLMs enough. They are revolutionary, every day. How much is "enough"? Neither myself nor my coworkers have found LLMs to be all that useful in our work. Almost everybody has stopped bothering with them these days.
- carbine 2y ago
  what line of work are you in?

Agentus 2y ago

even if the datacenter increase was a waste because the potential of LLMs never pan out relative to the massive investment, i think the flood of gpu and compute will definitely enable whatever could benefit from it. The next better AI application will be very thankful that gpu compute is abundant.

nuc1e0n 2y ago
GPUs are easily and irreparably broken by overheating, so GPU compute is something that's high maintenance. It won't stick around like a building or a bridge.
- tekknik 2y ago
  Luckily data centers have this thing called “air conditioning”…
  - DiscourseFan 2y ago
    Air conditioning is just heat displacement. It doesn't get rid of the heat, and if it gets hot enough it becomes physically impossible to remove enough heat to cool a building down, no matter how many air conditioners are installed.
    - tekknik 2y ago
      Yea that’s why we have this problem today with data centers overheating. Don’t put chips on top of each other and you’re fine.