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I lead an applied AI research team where I work - which is a mid-sized public enterprise products company. I've been saying this in my professional circles quit

by LASR 2y ago

I lead an applied AI research team where I work - which is a mid-sized public enterprise products company. I've been saying this in my professional circles quite often. We talk about scaling laws, superintelligence, AGI etc. But there is another threshold - the ability for humans to leverage super-intelligence. It's just incredibly hard to innovate on products that fully leverage superintelligence. At some point, AI needs to connect with the real world to deliver economically valuable output. The ratelimiting step is there. Not smarter models. In my mind, already with GPT-4, we're not generating ideas fast enough on how best to leverage it. 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. Anyone using a chatbot already has felt the frustration of "it doesn't get what I want". And also "I have to explain so much that I might as well just do it myself" We're seeing much less of "it's making mistakes" these days. If we have open-source models that match up to GPT-4 on AWS / Azure etc, not much point to go with players like OpenAI / Anthropic who may have even smarter models. We can't even use the dumber models fully.

datavirtue 2y ago
"In my mind, already with GPT-4, we're not generating ideas fast enough on how best to leverage it." This is the main bottle neck, in my kind. A lot of people are missing from the conversation because they don't understand AI fully. I keep getting glimpses of ideas and possibilities and chatting through a browser ain't one of them. On e we have more young people trained on this and comfortable with the tech and understanding it, and existing professionals have light bulbs go off in their heads as they try to integrate local LLMs, then real changes are going to hit hard and fast. This is just a lot to digest right now and the tech is truly exponential which makes it difficult to ideate right now. We are still enveloping the productivity boost from chatting. I tried explaining how this stuff works to product owners and architects and that we can integrate local LLMs into existing products. Everyone shook their head and agreed. When I posted a demo in chat a few weeks later you would have thought the CEO called them on their personal phone and told them to get on this shit. My boss spent the next two weeks day and night working up a demo and presentation for his bosses. It went from zero to 100kph instantly.
- Alex-Programs 2y ago
  Just the fact that I can have something proficient in language trivially accessible to me is really useful. I'm working on something that uses LLMs (language translation), but besides that I think it's brilliant that I can just ask an LLM to summarise my prompt in a way that gets the point across in far fewer tokens. When I forget a word, I can give it a vague description and it'll find it. I'm terrible at writing emails, and I can just ask it to point out all the little formalisms I need to add to make it "proper". I can benchmark the quality of one LLM's translation by asking another to critique it. It's not infallible, but the ability to chat with a multilingual agent is brilliant. It's a new tool in the toolbox, one that we haven't had in our seventy years of working on computers, and we have seventy years of catchup to do working out where we can apply them. It's also just such a radical departure from what computers are "meant" to be good at. They're bad at mathematics, forgetful, imprecise, and yet they're incredible at poetry and soft tasks. Oh - and they are genuinely useful for studying, too. My A Level Physics contained a lot of multiple choice questions, which were specifically designed to catch people out on incorrect intuitions and had no mark scheme beyond which answer was correct. I could just give gpt-4o a photo of the practice paper and it'd tell me not just the correct answer (which I already knew), but why it was correct, and precisely where my mental model was incorrect. Sure, I could've asked my teacher, and sometimes I did. But she's busy with twenty other students. If everyone asked for help with every little problem she'd be unable to do anything else. But LLMs have infinite patience, and no guilt for asking stupid questions!
  - skydhash 2y ago
    > I can benchmark the quality of one LLM's translation by asking another to critique it Do you speak two or more languages? Anyone that does is wary of automated translations, especially across estranged cultures. > It's a new tool in the toolbox, one that we haven't had in our seventy years of working on computers, It's data analysis at scale, and reliant on scrapping what humans produced. A word processor does not need TB of eBooks to do it's job. > They're bad at mathematics, forgetful, imprecise, and yet they're incredible at poetry and soft tasks. Because there's no wrong or right about poetry. Would you be comfortable having LLMs managing your bank account? > If everyone asked for help with every little problem she'd be unable to do anything else. That would be hand-holding, not learning.
troupo 2y ago
> In my mind, already with GPT-4, we're not generating ideas fast enough on how best to leverage it. It's a token prediction machine. We've already generated most of the ideas for it, and hardly any of them work because see below > 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. No. Gettin AI to work you need to make an AI, and not a token prediction machine which, however wonderful: - does not understand what it is it's generating, and approaches generating code the same way it approaches generating haikus - hallucinates and generates invalid data > Anyone using a chatbot already has felt the frustration of "it doesn't get what I want". And also "I have to explain so much that I might as well just do it myself" Indeed. Instead of asking why, you're wildly fantasizing about running out of ideas and pretending you can make this work through other means of communication.
- SrslyJosh 2y ago
  > hallucinates and generates invalid data The model is doing the exact same thing when it generates "correct" output as it does when it generates "incorrect" output. "Hallucination" is a misleading term, cooked up by people who either don't understand what's going on or who want to make it sound like the fundamental problems (models aren't intelligent, can't reason, and attach zero meaning to their input or output) can be solved with enough duct tape.
  - Terr_ 2y ago
    I like the analogy of an Ouija board: "This magical conduit to supernatural forces sometimes gives out nonsense, but soon we'll fix it so that it always channels the correct ghosts and spirits."
  - RogerL 2y ago
    It was "cooked up" by people like Joshua Maynez, Shashi Narayan, et al, who I'm going to guess understand what is going on, and adopted by the rest of the field. https://aclanthology.org/2020.acl-main.173/ https://aclanthology.org/2020.acl-main.173/
  - 2y ago
aaron695 2y ago
This comment goes a long way to explaining Jonestown to me. We have a new god (superintelligence) but only the special can see it because it's too intelligent for people to interact with it. It's so advanced all the common ways humans communicate "using mouse / keyboard / voice" don't work The reason we've never seen it help us is we need more ideas (prayers) first. NPC brains are really hard to understand I will say that and they use a lot of electricity.
yibg 2y ago
* We're seeing much less of "it's making mistakes" these days.* Perhaps less than before, but still making very fundamental errors. Anything involving number I'm automatically suspicious. Pretty frequently I'd get different answers for the same question (to a human). e.g. ChatGPT will give an effective tax rate of n for some income amount. Then when asked to break down the calculation will come up with an effective tax rate of m instead. When asked how much tax is owed on that income will come up with a different number such that the effective rate is not n or m. Until this is addressed to a sufficient degree, it seems difficult to apply to anything that involves numbers and can't be quickly verified by a human.
- Animats 2y ago
  > Perhaps less than before, but still making very fundamental errors. Yes. Suppose someone developed a way to get a reliable confidence metric out of an LLM. Given that, much more useful systems can be built. Only high-confidence outputs can be used to initiate action. For low-confidence outputs, chain of reasoning tactics can be tried. Ask for a simpler question. Ask the LLM to divide the question into sub-questions. Ask the LLM what information it needs to answer the question, and try to get that info from a search engine. Most of the strategies humans and organizations use when they don't know something will work for LLMs. The goal is to get an all high confidence chain of reasoning. If only they knew when they didn't know something. There's research on this.[4] No really good results yet, but some progress. Biggest unsolved problem in computing today. [4] https://hungleai.substack.com/p/uncertainty-confidence-and-hallucination https://hungleai.substack.com/p/uncertainty-confidence-and-h...
  - bennettnate5 2y ago
    I remember watching IBM's Watson soundly beat Ken Jennings on Jeapordy. One of the things that sticks out most to me about the memory is that Watson had a confidence rating score for each answer it gave (and there were a few questions for which it had very low confidence). I didn't realize it at the time, but that was actually pretty impressive given the overconfidence issues LLMs have nowadays. Of course, citing sources would always trump any kind of confidence rating in my mind; sources provide provenance, while confidence rating can be fudged just like a bogus answer can.
elorant 2y ago
We have ideas on how to leverage it. But we keep them to ourselves for our products and our companies. AI by itself isn’t a breakthrough product the same way that the iPhone or the web was. It’s a utility for others to enhance their products or their operations. Which is the main reason why so many people believe we’re in an AI bubble. We just don’t see the killer feature that justifies all that spending.
Havoc 2y ago
> It's just incredibly hard to innovate on products that fully leverage superintelligence. Once we have actual super intelligence there is no need for humans to innovate anymore. It is by definition better than us anyway. I guess you could still have artisanal innovation
- ang_cire 2y ago
  Today I carved a front panel for my cyberdeck project out of a composite wood board. I hand-drafted everything, and planned out the wiring (though I won't be onto the soldering phase for a while now). It felt good. I don't think having a 3d printer + AI designing my cyberdeck would feel the same.
  - FridgeSeal 2y ago
    Yeah I think the whole “humans won’t need to do <insert creative-adjacent-and-skilled-labour-here>” argument misses is the fundamental human aspect. Computers might do some things “better” than humans, but we’re still going to do things because we _want_ to. Often the fun is in the doing. LLM’s can vomit out code faster than me, I still enjoy writing software. They’ll vomit out a novel or a song, but I still like reading/listening to stuff a human has taken time and effort to create something, because they can.
    - chx 2y ago
      Fifteen was a massive success partially because Taylor was only 19 when she recorded it and so it sounded authentic. It's a human singing about her experiences. Also, the lyrics both on macro and micro levels is exceptionally well done and genuinely new. In other words, in another area: you can take all the art made in the world before Guernica and throw it in any probabilistic network but for sure you won't get Guernica out of that.
  - Spacecosmonaut 2y ago
    Take a look at Nick Bostrom's new book
p1necone 2y ago
We're seeing much less of "it's making mistakes" these days. Is this because it's actually making less mistakes, or is it just because most people have used it enough now to know not to bother with anything complex?
- noisy_boy 2y ago
  They have trained us and we have fine tuned our questions.
SrslyJosh 2y ago
> 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.
mvdtnz 2y ago
> In my mind, already with GPT-4, we're not generating ideas fast enough on how best to leverage it. This is just another way of saying this technology, like Blockchain before it, is a solution in search of a problem.
- unsigner 2y ago
  Or, more drastically, another way of saying it’s useless.
hakfoo 2y ago
The "it's making mistakes" phase might be based on the testing strategy. Remember the old bit about the media-- the stories are always 100% infalliable except strangely in YOUR personal field of expertise. I suspect it's something similar with AI products. People test them with toy problems -- "Hey ChatGPT, what's the square root of 36", and then with something close to their core knowledge. It might learn to solve a lot of the toy problems, but plenty of us are still seeing a lot of hallucinations in the "core knowledge" questions. But we see people then taking that product-- that they know isn't good in at least one vertical-- and trying to apply it to other contexts, where they may be less qualified to validate if the answer is right.
- danielbarla 2y ago
  I think a crucial aspect is to only apply chatbots' answers to a domain where you can rapidly validate their correctness (or alternatively, to take their answers with a huge pinch of salt, or simply as creative search space exploration). For me, the number of times where it's led me down a hallucinated, impossible, or thoroughly invalid rabbit hole have been relatively minimal when compared against the number of times when it has significantly helped. I really do think the key is in how you use them, for what types of problems/domains, and having an approach that maximizes your ability to catch issues early.
- latexr 2y ago
  > Remember the old bit about the media-- the stories are always 100% infalliable except strangely in YOUR personal field of expertise. Gell-Mann amnesia: https://en.wikipedia.org/wiki/Michael_Crichton#GellMannAmnesiaEffect https://en.wikipedia.org/wiki/Michael_Crichton#GellMannAmnes...
smolder 2y ago
Your use of the word superintelligence is jarring to me. That's not yet a thing and not yet visible on the horizon. That aside, the point I like that you seem to be making is along the lines of: we overestimate the short term impact of new tech, but underestimate the long term impact. There is a lot to be done and a lot of refinement to come.
indigoabstract 2y ago
I will be glad to see the day when LLMs will be able to play Minecraft, so I won't have to. Then I can just relax and watch someone else do everything for me without lifting a single finger. Won't that be fun.
- mavhc 2y ago
  Watching people play Minecraft is the main hobby of children these days
  - indigoabstract 2y ago
    Well, I guess you've caught me then. Naturally, adults would be more preoccupied with how they can use AI to improve their lives and get ahead, instead of playing Minecraft.
shafyy 2y ago
> Anyone using a chatbot already has felt the frustration of "it doesn't get what I want". And also "I have to explain so much that I might as well just do it myself Ehm yes. That's because it actually doesn't work as well as the hype suggests, not because it's too "high bandwidth".
- bsenftner 2y ago
  I'd contribute that we, the engineering class, are as a whole terrible communicators that confuse and cannot explain their own work. LLMs require clear communications, while the majority of LLM users attempt to use them with a large host of implied context that anyone would have a hard time following, not to mention a non-human software construct. The key is clear communications, which is a phrase that many in STEM don't have the education to know what that phrase really means, technically, realistically.
  - shafyy 2y ago
    No, this is absolutely not the reason. The reason is that many people benefit financially as long as the hype train keeps going choo choo. So they lie to our faces and sleep like babies at night.
    - bsenftner 2y ago
      There is that too, I agree. The hype train is many people's entire careers. But AI does work, is indeed capable of many of the claims, I'm saying the naysayers are using it wrong. But you know who will use it very well? The hype train.
- Hoasi 2y ago
  It works for some annoyances in life, though. For example, you can get it to write a complaint to an administration. It's good enough unless you'd rather be witty and write it yourself.
  - achenet 2y ago
blitzar 2y ago
Have we surpassed Clippy "It looks like you're trying to write a letter" yet?
bryanrasmussen 2y ago
>Anyone using a chatbot already has felt the frustration of "it doesn't get what I want". And also "I have to explain so much that I might as well just do it myself" the problem is really, can it learn "I need to turn this over to a human because it is such an edge case that there will not be an automated solution."
janoc 2y ago
I.e. long story short - are you saying that this tech is a solution looking for a problem? Makes sense.
madeofpalk 2y ago
> Anyone using a chatbot already has felt the frustration of "it doesn't get what I want". And also "I have to explain so much that I might as well just do it myself" I find this funny because for what I use ChatGPT for - asking programming questions that would otherwise go to Google/StackOverflow - I have a much better time writing queries for ChatGPT than Google, and getting useful results back. Google will so often return StackOverflow results that are for subtly very different questions, or ill have to squint hard to figure out how to apply that answer to my problem. When using ChatGPT, i rarely have to think about how other people asked the question.
Atmael 2y ago
why do you believe that humanity is the habitat for ai and not the other way around?
butterfly42069 2y ago
Yes, this is in my mind where people will find the fabled moat they search for too. SOTA models are impressive, as is the idea of building AGIs that do everything for us, but in the meantime there are a lot of practical applications of the open source and smaller models that are being missed out on in my opinion. I also think business is going to struggle to adapt and existing business is at a disadvantage for deploying AI tools, after all, who wants to replace themselves and lose their salary? Its a personal incentive not to leverage AI at the corporate level.

by LASR 2y ago

datavirtue 2y ago

"In my mind, already with GPT-4, we're not generating ideas fast enough on how best to leverage it." This is the main bottle neck, in my kind. A lot of people are missing from the conversation because they don't understand AI fully. I keep getting glimpses of ideas and possibilities and chatting through a browser ain't one of them. On e we have more young people trained on this and comfortable with the tech and understanding it, and existing professionals have light bulbs go off in their heads as they try to integrate local LLMs, then real changes are going to hit hard and fast. This is just a lot to digest right now and the tech is truly exponential which makes it difficult to ideate right now. We are still enveloping the productivity boost from chatting. I tried explaining how this stuff works to product owners and architects and that we can integrate local LLMs into existing products. Everyone shook their head and agreed. When I posted a demo in chat a few weeks later you would have thought the CEO called them on their personal phone and told them to get on this shit. My boss spent the next two weeks day and night working up a demo and presentation for his bosses. It went from zero to 100kph instantly.

Alex-Programs 2y ago
Just the fact that I can have something proficient in language trivially accessible to me is really useful. I'm working on something that uses LLMs (language translation), but besides that I think it's brilliant that I can just ask an LLM to summarise my prompt in a way that gets the point across in far fewer tokens. When I forget a word, I can give it a vague description and it'll find it. I'm terrible at writing emails, and I can just ask it to point out all the little formalisms I need to add to make it "proper". I can benchmark the quality of one LLM's translation by asking another to critique it. It's not infallible, but the ability to chat with a multilingual agent is brilliant. It's a new tool in the toolbox, one that we haven't had in our seventy years of working on computers, and we have seventy years of catchup to do working out where we can apply them. It's also just such a radical departure from what computers are "meant" to be good at. They're bad at mathematics, forgetful, imprecise, and yet they're incredible at poetry and soft tasks. Oh - and they are genuinely useful for studying, too. My A Level Physics contained a lot of multiple choice questions, which were specifically designed to catch people out on incorrect intuitions and had no mark scheme beyond which answer was correct. I could just give gpt-4o a photo of the practice paper and it'd tell me not just the correct answer (which I already knew), but why it was correct, and precisely where my mental model was incorrect. Sure, I could've asked my teacher, and sometimes I did. But she's busy with twenty other students. If everyone asked for help with every little problem she'd be unable to do anything else. But LLMs have infinite patience, and no guilt for asking stupid questions!
- skydhash 2y ago
  > I can benchmark the quality of one LLM's translation by asking another to critique it Do you speak two or more languages? Anyone that does is wary of automated translations, especially across estranged cultures. > It's a new tool in the toolbox, one that we haven't had in our seventy years of working on computers, It's data analysis at scale, and reliant on scrapping what humans produced. A word processor does not need TB of eBooks to do it's job. > They're bad at mathematics, forgetful, imprecise, and yet they're incredible at poetry and soft tasks. Because there's no wrong or right about poetry. Would you be comfortable having LLMs managing your bank account? > If everyone asked for help with every little problem she'd be unable to do anything else. That would be hand-holding, not learning.

troupo 2y ago

> In my mind, already with GPT-4, we're not generating ideas fast enough on how best to leverage it. It's a token prediction machine. We've already generated most of the ideas for it, and hardly any of them work because see below > 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. No. Gettin AI to work you need to make an AI, and not a token prediction machine which, however wonderful: - does not understand what it is it's generating, and approaches generating code the same way it approaches generating haikus - hallucinates and generates invalid data > Anyone using a chatbot already has felt the frustration of "it doesn't get what I want". And also "I have to explain so much that I might as well just do it myself" Indeed. Instead of asking why, you're wildly fantasizing about running out of ideas and pretending you can make this work through other means of communication.

SrslyJosh 2y ago
> hallucinates and generates invalid data The model is doing the exact same thing when it generates "correct" output as it does when it generates "incorrect" output. "Hallucination" is a misleading term, cooked up by people who either don't understand what's going on or who want to make it sound like the fundamental problems (models aren't intelligent, can't reason, and attach zero meaning to their input or output) can be solved with enough duct tape.
- Terr_ 2y ago
  I like the analogy of an Ouija board: "This magical conduit to supernatural forces sometimes gives out nonsense, but soon we'll fix it so that it always channels the correct ghosts and spirits."
- RogerL 2y ago
  It was "cooked up" by people like Joshua Maynez, Shashi Narayan, et al, who I'm going to guess understand what is going on, and adopted by the rest of the field. https://aclanthology.org/2020.acl-main.173/ https://aclanthology.org/2020.acl-main.173/
- 2y ago

aaron695 2y ago

This comment goes a long way to explaining Jonestown to me. We have a new god (superintelligence) but only the special can see it because it's too intelligent for people to interact with it. It's so advanced all the common ways humans communicate "using mouse / keyboard / voice" don't work The reason we've never seen it help us is we need more ideas (prayers) first. NPC brains are really hard to understand I will say that and they use a lot of electricity.

yibg 2y ago

* We're seeing much less of "it's making mistakes" these days.* Perhaps less than before, but still making very fundamental errors. Anything involving number I'm automatically suspicious. Pretty frequently I'd get different answers for the same question (to a human). e.g. ChatGPT will give an effective tax rate of n for some income amount. Then when asked to break down the calculation will come up with an effective tax rate of m instead. When asked how much tax is owed on that income will come up with a different number such that the effective rate is not n or m. Until this is addressed to a sufficient degree, it seems difficult to apply to anything that involves numbers and can't be quickly verified by a human.

Animats 2y ago
> Perhaps less than before, but still making very fundamental errors. Yes. Suppose someone developed a way to get a reliable confidence metric out of an LLM. Given that, much more useful systems can be built. Only high-confidence outputs can be used to initiate action. For low-confidence outputs, chain of reasoning tactics can be tried. Ask for a simpler question. Ask the LLM to divide the question into sub-questions. Ask the LLM what information it needs to answer the question, and try to get that info from a search engine. Most of the strategies humans and organizations use when they don't know something will work for LLMs. The goal is to get an all high confidence chain of reasoning. If only they knew when they didn't know something. There's research on this.[4] No really good results yet, but some progress. Biggest unsolved problem in computing today. [4] https://hungleai.substack.com/p/uncertainty-confidence-and-hallucination https://hungleai.substack.com/p/uncertainty-confidence-and-h...
- bennettnate5 2y ago
  I remember watching IBM's Watson soundly beat Ken Jennings on Jeapordy. One of the things that sticks out most to me about the memory is that Watson had a confidence rating score for each answer it gave (and there were a few questions for which it had very low confidence). I didn't realize it at the time, but that was actually pretty impressive given the overconfidence issues LLMs have nowadays. Of course, citing sources would always trump any kind of confidence rating in my mind; sources provide provenance, while confidence rating can be fudged just like a bogus answer can.

elorant 2y ago

We have ideas on how to leverage it. But we keep them to ourselves for our products and our companies. AI by itself isn’t a breakthrough product the same way that the iPhone or the web was. It’s a utility for others to enhance their products or their operations. Which is the main reason why so many people believe we’re in an AI bubble. We just don’t see the killer feature that justifies all that spending.

Havoc 2y ago

> It's just incredibly hard to innovate on products that fully leverage superintelligence. Once we have actual super intelligence there is no need for humans to innovate anymore. It is by definition better than us anyway. I guess you could still have artisanal innovation

ang_cire 2y ago
Today I carved a front panel for my cyberdeck project out of a composite wood board. I hand-drafted everything, and planned out the wiring (though I won't be onto the soldering phase for a while now). It felt good. I don't think having a 3d printer + AI designing my cyberdeck would feel the same.
- FridgeSeal 2y ago
  Yeah I think the whole “humans won’t need to do <insert creative-adjacent-and-skilled-labour-here>” argument misses is the fundamental human aspect. Computers might do some things “better” than humans, but we’re still going to do things because we _want_ to. Often the fun is in the doing. LLM’s can vomit out code faster than me, I still enjoy writing software. They’ll vomit out a novel or a song, but I still like reading/listening to stuff a human has taken time and effort to create something, because they can.
  - chx 2y ago
    Fifteen was a massive success partially because Taylor was only 19 when she recorded it and so it sounded authentic. It's a human singing about her experiences. Also, the lyrics both on macro and micro levels is exceptionally well done and genuinely new. In other words, in another area: you can take all the art made in the world before Guernica and throw it in any probabilistic network but for sure you won't get Guernica out of that.
- Spacecosmonaut 2y ago
  Take a look at Nick Bostrom's new book

p1necone 2y ago

We're seeing much less of "it's making mistakes" these days. Is this because it's actually making less mistakes, or is it just because most people have used it enough now to know not to bother with anything complex?

noisy_boy 2y ago
They have trained us and we have fine tuned our questions.

SrslyJosh 2y ago

> 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.

mvdtnz 2y ago

> In my mind, already with GPT-4, we're not generating ideas fast enough on how best to leverage it. This is just another way of saying this technology, like Blockchain before it, is a solution in search of a problem.

unsigner 2y ago
Or, more drastically, another way of saying it’s useless.

hakfoo 2y ago

The "it's making mistakes" phase might be based on the testing strategy. Remember the old bit about the media-- the stories are always 100% infalliable except strangely in YOUR personal field of expertise. I suspect it's something similar with AI products. People test them with toy problems -- "Hey ChatGPT, what's the square root of 36", and then with something close to their core knowledge. It might learn to solve a lot of the toy problems, but plenty of us are still seeing a lot of hallucinations in the "core knowledge" questions. But we see people then taking that product-- that they know isn't good in at least one vertical-- and trying to apply it to other contexts, where they may be less qualified to validate if the answer is right.

danielbarla 2y ago
I think a crucial aspect is to only apply chatbots' answers to a domain where you can rapidly validate their correctness (or alternatively, to take their answers with a huge pinch of salt, or simply as creative search space exploration). For me, the number of times where it's led me down a hallucinated, impossible, or thoroughly invalid rabbit hole have been relatively minimal when compared against the number of times when it has significantly helped. I really do think the key is in how you use them, for what types of problems/domains, and having an approach that maximizes your ability to catch issues early.
latexr 2y ago
> Remember the old bit about the media-- the stories are always 100% infalliable except strangely in YOUR personal field of expertise. Gell-Mann amnesia: https://en.wikipedia.org/wiki/Michael_Crichton#GellMannAmnesiaEffect https://en.wikipedia.org/wiki/Michael_Crichton#GellMannAmnes...

smolder 2y ago

Your use of the word superintelligence is jarring to me. That's not yet a thing and not yet visible on the horizon. That aside, the point I like that you seem to be making is along the lines of: we overestimate the short term impact of new tech, but underestimate the long term impact. There is a lot to be done and a lot of refinement to come.

indigoabstract 2y ago

I will be glad to see the day when LLMs will be able to play Minecraft, so I won't have to. Then I can just relax and watch someone else do everything for me without lifting a single finger. Won't that be fun.

mavhc 2y ago
Watching people play Minecraft is the main hobby of children these days
- indigoabstract 2y ago
  Well, I guess you've caught me then. Naturally, adults would be more preoccupied with how they can use AI to improve their lives and get ahead, instead of playing Minecraft.

shafyy 2y ago

> Anyone using a chatbot already has felt the frustration of "it doesn't get what I want". And also "I have to explain so much that I might as well just do it myself Ehm yes. That's because it actually doesn't work as well as the hype suggests, not because it's too "high bandwidth".

bsenftner 2y ago
I'd contribute that we, the engineering class, are as a whole terrible communicators that confuse and cannot explain their own work. LLMs require clear communications, while the majority of LLM users attempt to use them with a large host of implied context that anyone would have a hard time following, not to mention a non-human software construct. The key is clear communications, which is a phrase that many in STEM don't have the education to know what that phrase really means, technically, realistically.
- shafyy 2y ago
  No, this is absolutely not the reason. The reason is that many people benefit financially as long as the hype train keeps going choo choo. So they lie to our faces and sleep like babies at night.
  - bsenftner 2y ago
    There is that too, I agree. The hype train is many people's entire careers. But AI does work, is indeed capable of many of the claims, I'm saying the naysayers are using it wrong. But you know who will use it very well? The hype train.
Hoasi 2y ago
It works for some annoyances in life, though. For example, you can get it to write a complaint to an administration. It's good enough unless you'd rather be witty and write it yourself.
- achenet 2y ago

blitzar 2y ago

Have we surpassed Clippy "It looks like you're trying to write a letter" yet?

bryanrasmussen 2y ago

>Anyone using a chatbot already has felt the frustration of "it doesn't get what I want". And also "I have to explain so much that I might as well just do it myself" the problem is really, can it learn "I need to turn this over to a human because it is such an edge case that there will not be an automated solution."

janoc 2y ago

I.e. long story short - are you saying that this tech is a solution looking for a problem? Makes sense.

madeofpalk 2y ago

> Anyone using a chatbot already has felt the frustration of "it doesn't get what I want". And also "I have to explain so much that I might as well just do it myself" I find this funny because for what I use ChatGPT for - asking programming questions that would otherwise go to Google/StackOverflow - I have a much better time writing queries for ChatGPT than Google, and getting useful results back. Google will so often return StackOverflow results that are for subtly very different questions, or ill have to squint hard to figure out how to apply that answer to my problem. When using ChatGPT, i rarely have to think about how other people asked the question.

Atmael 2y ago

why do you believe that humanity is the habitat for ai and not the other way around?

butterfly42069 2y ago

Yes, this is in my mind where people will find the fabled moat they search for too. SOTA models are impressive, as is the idea of building AGIs that do everything for us, but in the meantime there are a lot of practical applications of the open source and smaller models that are being missed out on in my opinion. I also think business is going to struggle to adapt and existing business is at a disadvantage for deploying AI tools, after all, who wants to replace themselves and lose their salary? Its a personal incentive not to leverage AI at the corporate level.