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> I lead an applied AI research team where I work Your paycheck depends on people believing the hype. Therefore, anything you say about "superintelligence" (LO

> I lead an applied AI research team where I work Your paycheck depends on people believing the hype. Therefore, anything you say about "superintelligence" (LOL) is pretty suspect. > Getting AI to do work involves getting AI to understand what needs to be done from highly bandwidth constrained humans using mouse / keyboard / voice to communicate. So, what, you're going to build a model to instruct the model? And how do we instruct that model? This is such a transparent scam, I'm embarrassed on behalf of our species.

jcgrillo 2y ago
This is absolutely on point, I don't understand why your post is being down-voted.
- gleenn 2y ago
  One of the rules of HN is to assume good intent. People do and say the right thing often even when it's antithetical to their source of income. If there is a substantive way to otherwise then say it, don't immediately write-off people's opinions, especially people in their fields because of a possibility of bias.
  - jcgrillo 2y ago
    OK, but the post this was in response to was bloviating about all kinds of sci-fi stuff like "super-intelligence" and the like. It was the opposite of "antithetical to their source of income", instead it was playing into some techno-futurist faith cult.
    - roenxi 2y ago
      There is a strong argument that super-intelligence is already in the rear-view mirror. My computer is better than me at almost everything at this point; creativity, communication, scientific knowledge, numerical processing, etc. There is a tiny sliver of things that I've spent a life working on where I can consistently outperform a CPU, but it is not at all clear how that could be defensible given the strides AI has made over the last few decades. The typical AI seems more capable than the typical human to me. If that isn't super-intelligence then whatever super-intelligence is can't be far away.
      - passwordoops 2y ago
        >My computer is better than me at almost everything at this point; creativity, communication, scientific knowledge By that logic, libraries, art museums and calculators are "super intelligent"
        roenxi 2y ago
        Are you in the habit of talking to your calculator?
      - threeseed 2y ago
        > The typical AI seems more capable than the typical human to me Your microwave is more capable than a typical human. If of course your definition of capabilities is narrowly defined to computations and ignores the huge array of things humans can do that computers are no where close to.
        roenxi 2y ago
        > the huge array of things humans can do that computers are no where close to. For example?
        achenet 2y ago
        anything involving an interface with the physical world. For example, running a lemonade stand. You'd need thousands, if not millions of dollars to build a robot machine with a computerized brain capable of doing what a 6 year old child can do - produce lemonade from simple ingredients (lemon, sugar, water) and sell it to consumers. Same with basically all cooking/food-service and hospitality tasks, an physical therapy type tasks (massage, chiropractor, etc)... heck, even driving on public roads still doesn't seem to be perfect, despite 10+ years on investment and research by leading tech companies, although there is also a regulatory hurdle here.
        roenxi 2y ago
        You seem to have shifted the conversation's goalposts there - those are things that computers can do, it just costs a lot. And, more to the point, they aren't indicative of intelligence. Computers have cleared the intelligence requirements to run a lemonade stand by a large margin - and the other tasks too for that matter.
- jamilton 2y ago
  1. It's not actually refuting the point being made which is "it's seems hard to take advantage of LLMs' capabilities", which to me seems like a good point that stands on it's own, regardless of who is saying it. 2. The original post is, to my eyes, not implying anything about training a model to help use other models, so the second part seems irrelevant.
  - passwordoops 2y ago
    I disagree. The comment is striking directly at the claim that people aren't taking "advantage of LLMs' capabilities". This is their capability and no amount of "clear communication" is going to change that
KronisLV 2y ago
Snarky tone aside, there are different audiences. For example, I primarily work with web dev and some DevOps and I can tell you that the state of both can be pretty dire. Maybe not as much in my particular case, as in general. Some examples to illustrate the point: supply chain risks and an ever increasing amount of dependencies (look at your average React project, though this applies to most stacks), overly abstracted frameworks (how many CPU cycles Spring Boot and others burn and how many hoops you have to jump through to get thigns done), patterns that mess up the DBs ability to optimize queries sometimes (EAV, OTLT, trying to create polymorphic foreign keys), inefficient data fetching (sometimes ORMs, sometimes N+1), bad security practices (committed secrets, anyone? bad usage of OAuth2 or OIDC?), overly complex tooling, especially the likes of Kubernetes when you have a DevOps team of one part time dev, overly complex application architectures where you have more more services than developers (not even teams). That's before you even get into the utter mess of long term projects that have been touched by dozens of developers over the years and the whole sector sometimes feeling like wild west, as opposed to "real engineering". That's why articles like this ring true: http://www.stilldrinking.org/programming-sucks http://www.stilldrinking.org/programming-sucks However, the difference here is that I wouldn't overwhelm anyone who might give me money with rants about this stuff and would navigate around those issues and risks as best I can, to ship something useful at the end of the day. Same with having constructive discussions about any of those aspects in a circle of technical individuals, on how to make things better. Calling the whole concept a "scam" doesn't do anyone any good, when I already derive value from the LLMs, as do many others. Look at https://www.cursor.com/ https://www.cursor.com/ for example and consider where we might be in 10-20 years. Not AGI, but maybe good auto-complete, codegen and reasoning about entire codebases, even if they're hundreds of thousands of lines long. Tooling that would make anyone using it more productive than those who don't. Unless the funding dries up and the status quo is restored.
- obirunda 2y ago
  I think at its core it's not that there isn't value or future value, but currently there is an assertion, maybe some blind faith, that it's inevitable that a future version will deliver a free lunch for society. I think the testimonies often repeated by coders that use these code completion tools is that "it saved me X amount of time on this one problem I had, therefore it's great value". The issue is that these all fall into a research of n=1 test subjects. It's only useful information for the subject. It appears we don't realize in these moments that when we use those examples, even to ourselves, we are users reviewing a product, as opposed to validating if our workflow is not just different but objectively better. The truth lies in the aggregate data of the quality and crucially the speed by which fixes and requirements are being implemented at scale across code bases. Admittedly, a lot of code is being generated, so I don't think I can say everyone hates it, but until someone can do some real research on this, all we have are product reviews.

jcgrillo 2y ago

This is absolutely on point, I don't understand why your post is being down-voted.

gleenn 2y ago
One of the rules of HN is to assume good intent. People do and say the right thing often even when it's antithetical to their source of income. If there is a substantive way to otherwise then say it, don't immediately write-off people's opinions, especially people in their fields because of a possibility of bias.
- jcgrillo 2y ago
  OK, but the post this was in response to was bloviating about all kinds of sci-fi stuff like "super-intelligence" and the like. It was the opposite of "antithetical to their source of income", instead it was playing into some techno-futurist faith cult.
  - roenxi 2y ago
    There is a strong argument that super-intelligence is already in the rear-view mirror. My computer is better than me at almost everything at this point; creativity, communication, scientific knowledge, numerical processing, etc. There is a tiny sliver of things that I've spent a life working on where I can consistently outperform a CPU, but it is not at all clear how that could be defensible given the strides AI has made over the last few decades. The typical AI seems more capable than the typical human to me. If that isn't super-intelligence then whatever super-intelligence is can't be far away.
    - passwordoops 2y ago
      >My computer is better than me at almost everything at this point; creativity, communication, scientific knowledge By that logic, libraries, art museums and calculators are "super intelligent"
      - roenxi 2y ago
        Are you in the habit of talking to your calculator?
    - threeseed 2y ago
      > The typical AI seems more capable than the typical human to me Your microwave is more capable than a typical human. If of course your definition of capabilities is narrowly defined to computations and ignores the huge array of things humans can do that computers are no where close to.
      - roenxi 2y ago
        > the huge array of things humans can do that computers are no where close to. For example?
        achenet 2y ago
        anything involving an interface with the physical world. For example, running a lemonade stand. You'd need thousands, if not millions of dollars to build a robot machine with a computerized brain capable of doing what a 6 year old child can do - produce lemonade from simple ingredients (lemon, sugar, water) and sell it to consumers. Same with basically all cooking/food-service and hospitality tasks, an physical therapy type tasks (massage, chiropractor, etc)... heck, even driving on public roads still doesn't seem to be perfect, despite 10+ years on investment and research by leading tech companies, although there is also a regulatory hurdle here.
        roenxi 2y ago
        You seem to have shifted the conversation's goalposts there - those are things that computers can do, it just costs a lot. And, more to the point, they aren't indicative of intelligence. Computers have cleared the intelligence requirements to run a lemonade stand by a large margin - and the other tasks too for that matter.
jamilton 2y ago
1. It's not actually refuting the point being made which is "it's seems hard to take advantage of LLMs' capabilities", which to me seems like a good point that stands on it's own, regardless of who is saying it. 2. The original post is, to my eyes, not implying anything about training a model to help use other models, so the second part seems irrelevant.
- passwordoops 2y ago
  I disagree. The comment is striking directly at the claim that people aren't taking "advantage of LLMs' capabilities". This is their capability and no amount of "clear communication" is going to change that

KronisLV 2y ago

Snarky tone aside, there are different audiences. For example, I primarily work with web dev and some DevOps and I can tell you that the state of both can be pretty dire. Maybe not as much in my particular case, as in general. Some examples to illustrate the point: supply chain risks and an ever increasing amount of dependencies (look at your average React project, though this applies to most stacks), overly abstracted frameworks (how many CPU cycles Spring Boot and others burn and how many hoops you have to jump through to get thigns done), patterns that mess up the DBs ability to optimize queries sometimes (EAV, OTLT, trying to create polymorphic foreign keys), inefficient data fetching (sometimes ORMs, sometimes N+1), bad security practices (committed secrets, anyone? bad usage of OAuth2 or OIDC?), overly complex tooling, especially the likes of Kubernetes when you have a DevOps team of one part time dev, overly complex application architectures where you have more more services than developers (not even teams). That's before you even get into the utter mess of long term projects that have been touched by dozens of developers over the years and the whole sector sometimes feeling like wild west, as opposed to "real engineering". That's why articles like this ring true: http://www.stilldrinking.org/programming-sucks http://www.stilldrinking.org/programming-sucks However, the difference here is that I wouldn't overwhelm anyone who might give me money with rants about this stuff and would navigate around those issues and risks as best I can, to ship something useful at the end of the day. Same with having constructive discussions about any of those aspects in a circle of technical individuals, on how to make things better. Calling the whole concept a "scam" doesn't do anyone any good, when I already derive value from the LLMs, as do many others. Look at https://www.cursor.com/ https://www.cursor.com/ for example and consider where we might be in 10-20 years. Not AGI, but maybe good auto-complete, codegen and reasoning about entire codebases, even if they're hundreds of thousands of lines long. Tooling that would make anyone using it more productive than those who don't. Unless the funding dries up and the status quo is restored.

obirunda 2y ago
I think at its core it's not that there isn't value or future value, but currently there is an assertion, maybe some blind faith, that it's inevitable that a future version will deliver a free lunch for society. I think the testimonies often repeated by coders that use these code completion tools is that "it saved me X amount of time on this one problem I had, therefore it's great value". The issue is that these all fall into a research of n=1 test subjects. It's only useful information for the subject. It appears we don't realize in these moments that when we use those examples, even to ourselves, we are users reviewing a product, as opposed to validating if our workflow is not just different but objectively better. The truth lies in the aggregate data of the quality and crucially the speed by which fixes and requirements are being implemented at scale across code bases. Admittedly, a lot of code is being generated, so I don't think I can say everyone hates it, but until someone can do some real research on this, all we have are product reviews.