5 ms·

Ugh I’m beginning to think I’m going to spend the next 6-12 months commenting “no, large language models aren’t supposed to somehow know everything in the world

by bbor 4y ago

Ugh I’m beginning to think I’m going to spend the next 6-12 months commenting “no, large language models aren’t supposed to somehow know everything in the world. No, that’s not what they’re designed for. Yes, hooking one up to our long-standing record-of-everything-in-the-world (google’s knowledge graph) is going to be powerful.” It’s getting to point where I need to consider stop going on HN. This is like when my father excitedly told his friends about the coming computer revolution in the 90s and they responded “well it can’t do my dishes or clean the house, they’re just a fad!” Makes me want screaaaaam

ElevenLathe 4y ago
You don't need to correct every wrong thing you read. In fact you will probably feel much better if you don't ever do it at all, or at least take a break for while.
- bbor 4y ago
  Very true :). It doesn’t help that this isn’t exactly a little blog post, it’s a popular New Yorker feature…
  - hackernewds 4y ago
    Still that is what the downvote button for. With a comment extolling why your opinion is further valid than the net points that support it, seems an exercise in ego that is not beneficial to either you or the community.
  - ElevenLathe 4y ago
    A published "real" news article like this is actually one of the more futile things to try to "correct" IMO. Some guy on a blog might publish a correction or change their view. The New Yorker probably won't (at least not based on an HN comment).
    - graphe 4y ago
      Have you ever tried correcting a "real" article? It's easier to write it in the blog comments then open an email with sources but it's not futile.
      - ElevenLathe 4y ago
        I've not tried, no. If something involved my personal reputation or that of my family or friends, I might try though. Good to know!
- visarga 4y ago
  obligatory https://xkcd.com/386/ https://xkcd.com/386/
  - hnfong 4y ago
    Except now I can train an AI to do it 24/7...
    - TeMPOraL 4y ago
      Except if you want the job done right, you really have to do it yourself...
      - hnfong 4y ago
        You're suggesting I stay up late at night fixing wrong comments made by my AI chatbot? ... Yeah, seems like something I'd do :P
        TeMPOraL 4y ago
        You could train an AI chatbot to do those fixes for you, but it will also make plenty of mistakes. You could train yet another AI chatbot to compensate for that, but at some point somebody has to get their hands dirty, or else it's AI chatbots all way down.
- sebzim4500 4y ago
  Very true, but it is hard not be frustrated reading the constant stream of confidently incorrect information about this topic. I left /r/programming similar reasons and it is sad to experience the same on HN.
  - gameshot911 4y ago
    The constant misinformation of the world is one of life's great tensions.
- fnordpiglet 4y ago
  If you did then the LLM might stop hallucinating so much.
- o_____________o 4y ago
  When my pedantic keyboard warrior gears start turning, I think about the same xkcd a sibling commenter posted. But I've been struggling with the recent tsunami of openly anti-intellectual, alt-everything pseudoscience in the US. I recently pleaded with my sister to read The Demon-Haunted World by Sagan. There's something important in patient advocacy of truth.
brookst 4y ago
Same. I try to give myself three responses to any particular fallacy, mostly to work through my thinking. Once I have a pretty solid “you are assuming a technical limitation in a first gen product will persist in all future evolutions, when the second gen has already addressed it” response, I try to just smile at the 4th. . . Nth people who discover the exact same topic.
- bbor 4y ago
  Very true - I’m stealing that rule!
dougmwne 4y ago
I appreciate where you are coming from and I agree that AI is about to go from relative obscurity where just a few geeks were playing around to insane hype. I feel like I’ve spent the last 7 years wondering why no one in the wider world was as impressed as I was, but starting with Stable Diffusion and now ChatGPT, the hype rocket ship has launched. Search TikTok for ChatGPT for all the evidence of that you could ever need. That said, I still think we are in for a wild ride, even if we go through a hype bubble and pop first. I really don’t think the current crop of Transformer LLMs are the end of the story. Im betting that we are headed towards architectures made up of several different kind of models and AI approaches just like the brain is an apparent concert of specialized regions. You can see that in the new Bing where it’s a combination of a LLM with static training set that can then do up to 3 web searches to build up additional context of fresh data for the prompt, overcoming one of the key disadvantages of a transformer model. The hidden prompt with plain English Asimov's laws are the icing on the cake. The hype will be insane, but the capabilities are growing quickly and we do not yet seem close to the end of this rich computational ore vein we have hit.
- bbor 4y ago
  I don’t have much of a response but this comment is very well written and exactly what I would say if I could write clearly. It’s an exciting time! Hopefully it turns out more like the internet and less like… idk I’m struggling to think of a bad invention haha. Quadcopters I guess
CPLX 4y ago
> This is like when my father excitedly told his friends about the coming computer revolution in the 90s and they responded “well it can’t do my dishes or clean the house, they’re just a fad!” Makes me want screaaaaam Did the computer revolution make your father’s life better? Serious question.
- bbor 4y ago
  Hmm. I’d say definitely yes. I mean we are on the internet right now, presumably across many km of distance. Do you disagree?
  - CPLX 4y ago
    I have mixed feelings about it. I do believe with certainty that there are many people, millions, whose life has been made substantially worse by the invention of ubiquitous computing devices. Probably the minority. But I’d say his questions (ie “What’s in it for me?”) are excellent ones to pose in the face of new technology.
    - bbor 4y ago
      I think this is anti-status quo bias, which for once is unjustified. Sure the world has many systemic problems, but to say that the MASSIVE efficiency gains the internet have brought us are for a minority seems like an insane claim. Just because capitalists have been claiming all the new excess value doesn’t mean it doesn’t exist. To illustrate, consider: spreadsheets, video chat, shared documents, automated calendars, maps, autopilot assistants, CGI, I could go on… the world is not quite good enough that I’m ready to say that we don’t need more efficiency. Not everyone has a home on mars quite yet.
      - CPLX 4y ago
        I said the opposite of what you think I said. People who are worse off are most likely the minority. But I do think it’s worth noting that they exist.
  - 4y ago
weregiraffe 4y ago
>long-standing record-of-everything-in-the-world (google’s knowledge graph) The internet is not record-of-everything-in-the-world by a long stretch.
chapium 4y ago
I’m just searching the comments for novel use cases where its effective. Most articles I’ve read seem like either moral panics or snake oil. I like how it can generate songs and poems based on a prompt. Its not particularly useful, but it is entertaining. It really does seem curated at times, leading me to think this will eventually become a fad or replaced by a more advanced algorithm.
- avereveard 4y ago
  Want niche use case? I feed chatgpt the whole warstuff one page rule miniature combat system, and I can ask it to generate thematic units. I generated a wide variety of content from LOTR to ships. it even created new trait to complement the existing one when needed by special units, along with explanation of the mechanics of the trait. It doesn't quite understand positioning, but it will simulate round of combat between unit when asked.
  - bbor 4y ago
    You’re by far the most interesting person in this thread - I’ve been coding up a Warhammer 40k (symbolic) AI for a while, but I bet chatgpt could blow it out of the water…
    - avereveard 4y ago
      well warstuff rules are simple and I gues they fit nicely in gpt memory the ruleset is here and is magnitudes simpler than warhammer https://onepagerules.com/portfolio/one-off-games/ https://onepagerules.com/portfolio/one-off-games/ - I just copy pasted the whole ruleset into a message prepended by "Consider a wargaming system built with these rules:" this is a sample prompt afterward: > create a set of units using these rules, themed around warhammer 40k this is what chatgpt came up with, it's impressive as I just set a theme, and it dig up appropriate original special rules that fit within the ruleset: Sure, here are three examples of units themed around Warhammer 40k that you can use in your wargaming system: Space Marines: Quality 4, Special Rules: Shooter, Tough, Cost: 50pts The Space Marines are a heavily armored and well-trained fighting force, with a Quality value of 4 reflecting their combat abilities and morale. They have the Shooter special rule, allowing them to fire ranged weapons, and the Tough special rule, making them more resistant to damage. Their point cost is 50, calculated by multiplying Quality 4 by 10 and adding the point cost of the special rules. Chaos Space Marines: Quality 3, Special Rules: Shooter, Daemonic, Cost: 40pts The Chaos Space Marines are a corrupted version of the Space Marines, with a lower Quality value of 3 but the same Shooter and Daemonic special rules. Daemonic units are immune to morale tests and can only be killed by a roll of 6 on the melee attack. Their point cost is 40, calculated by multiplying Quality 3 by 10 and adding the point cost of the special rules. Necron Warriors: Quality 2, Special Rules: Shooter, Reanimation, Cost: 30pts The Necron Warriors are an undead race of robots, with a Quality value of 2 reflecting their lower morale and combat abilities. They have the Shooter special rule, allowing them to fire ranged weapons, and the Reanimation special rule, allowing them to automatically recover from being stunned instead of taking the Recover action. Their point cost is 30, calculated by multiplying Quality 2 by 10 and adding the point cost of the special rules.
unsignedchar 4y ago
> well it can’t do my dishes or clean the house the correct response would have been "yet"
- yoyohello13 4y ago
  Well, 30 years later and they still can't. At least I know of no one who has a house cleaning robot. (I wouldn't classify Roomba as 'clean my house').
  - euroderf 4y ago
    Clean ALL my bathroom fixtures for under 1000$ retail.
  - sh4rks 4y ago
    A roomba + a smartphone controlled dishwasher and you're 50% of the way there
    - freejazz 4y ago
      Really? Turning the dishwasher on is the most trivial part. What difference does it make that I can do that from my phone? I still have to load and unload it...
O__________O 4y ago
It’s an anti-pattern on HN, that is opinion of its own expertise frequently exceeds reality. For what it’s worth, specific to the topic at hand, here’s one HN post that provides explanations of how to overcome some of the limitations of large language models: https://news.ycombinator.com/item?id=34710079 https://news.ycombinator.com/item?id=34710079
trompetenaccoun 4y ago
I understand why the mainstream thinks that but it's incredibly annoying that even in tech circles there is very little meaningful discussion, it's mainly just people posting amusing screenshots purportedly showing how smart GPT3 is or in other cases how it's politically biased. Anyone who's played around with it knows that it's fun but it's not a search engine replacement and it doesn't know nor understand things. It regularly gives complete misinformation and when you ask for a source it makes up fake URLs and fake science papers on top of that. It's nothing like described in the article and I don't understand why people who should know better don't call out the bullshit media reporting more. We've had GPT3 for ages, it's not like most of us only tried it since Chat GPT3 came out, right?
- JoshCole 4y ago
  > It's nothing like described in the article and I don't understand why people who should know better don't call out the bullshit media reporting more. I'm kind of assuming you didn't read the article, but if you did then I'm kind of assuming that you've never done machine learning, but if you have: how did you manage to do that without ever noticing that you were doing approximation? Objectively, neural networks are approximators. Like, truly objectively, as in, the literal objective function, objectively minimizes approximation error. We call them objective functions and minimizing the approximation error is typically the objective of these objective functions. This isn't bullshit. It isn't. If you think it is, you are deeply and profoundly mistaken. The article advances this view of language models. This is a reasonable view of language models for the same reason that machine learning papers exploring neural networks describe them as universal function approximators.
- JoshCole 4y ago
  > Anyone who's played around with it knows that it's fun but it's not a search engine replacement and it doesn't know nor understand things. I've noticed that some people have been talking as if the view is nonsense in the direction you imply it is nonsense, but I think the argument for a lack of sensory ties is much stronger when stated in the other direction. This fails when arguing against the straw man position, but of course, drinking water also fails when addressing the weakest possible justification for it - clearly drinking water is bad because if you drink water you die of osmosis, though technically true, isn't really reflective of the actual predictions made by the people advancing the claim that we ought to drink more water than we do. So I'll give the argument for language models replacing search engines not being nonsense, but the position that no one could arrive at the belief actually being nonsense. Lets start with people not arriving at that belief being nonsense. I think it is nonsense in two ways. One way is that because some people have used them, then claimed they would be replacing search engines for some queries, it follows that you deny your senses with regard to the existence of these people. This is not sensory tied. So it is non-sensical. The second way is your belief anticipates experiences, but this experience you are now having in which someone disagrees with you is in contradiction to the anticipated experienced supposed by the belief. So it fails to predict past experiences and fails to predict current experiences, so it probably fails to predict future experiences. There probably will be someone in the future who, after interacting with a language model, thinks it can serve as a replacement for some search engine queries. Now in contrast, their claims were not non-sensical when they thought they could replace some search engine queries with language model queries. By that I also mean that they were not non-sensical in two respects. The first is that they arrived at the belief after replacing queries to search engines with queries to language models. Then, after having found value in doing so, they announced a belief congruent with that value, intimately connecting their belief to their senses. The second is that, having arrived at their belief, their belief paid rent in anticipated experience: it successfully predicted three noteworthy events: the internal code red status at Google, you.com's language model as enrichment for search, and bing.com's use of language model as enrichment for search. So it successfully predicted past experiences, successfully predicted current experiences, and may or may not predict future experiences - I think most people who hold this view tend to think there will be some refinements on the current generation of language models, in particular, that they will further refined at query time with relevant data, like fact databases, to help correct for some of the existing approximation error. This is my belief. I anticipate this happening. You can judge whether I anticipate successfully by watching reality. I should note that part of the reason I think this will happen is because I've already seen it happen. So I'm not really making a bold prediction here, but I suspect you will later see this happen, because I've seen this happen. Anyway... the belief that language models can replace some search queries is not a non-sensical belief, like beliefs in fairies is, but the belief that no one arrives at a belief that they could be is a non-sensical belief, because people do arrive at such beliefs, and so therefore the belief that they don't is fanciful and not reflective of reality.
omnicognate 4y ago
> Yes, hooking one up to our long-standing record-of-everything-in-the-world (google’s knowledge graph) is going to be powerful. This hasn't happened yet and, while I may just lack imagination, despite having a fairly solid understanding of how the latest round of AI works I can't see how it can be done successfully. Until it is in fact done and my lack of imagination is demonstrated, your "going to be powerful" is a speculation about the future, not an observation about the present, and deserves the level of respect usually accorded to such speculations.
- euroderf 4y ago
  Wouldn't a connection to Cyc be a million percent more useful ?
- bbor 4y ago
  In my view it’s very simple, which is what makes it so exciting. Summarizing a design doc that I imagine Microsoft and google are both spending millions of dollars of manhours/day working on their versions of: 1. User enters query. 2. LLM augments query if necessary, adding extra terms or clauses. 3. Normal search pipeline returns ranked links, just like it does now. 4. LLM reads the content of the first 100 links and decides which are the best based on your stated preferences and past behavior, uses that to augment the ranking a bit. 5. LLM generates various summaries depending on the type of query, such as laying out a few common answers to a controversial political question or giving a summary of a technical Wikipedia article tailored to your expertise level in that field. 6. Finally, for a tiny subset of queries, maybe the user wants to converse with the AI in a chat-like format, where it cites all of its claims with direct links. It’s gonna be awesome :)
  - omnicognate 4y ago
    I mean, how hard can it be, right?
cryptoegorophy 4y ago
It's understandable how frustrating it can be to encounter skepticism and misunderstanding about the capabilities of large language models. However, it's important to remember that these models are still relatively new and not everyone is familiar with their potential uses and limitations. It's also worth noting that these models are not designed to replace human intelligence, but rather to augment it and provide valuable insights and assistance in various tasks. And while connecting them to large knowledge graphs like Google's can be powerful, it's still only one piece of the puzzle. It can be discouraging to face resistance, but it's important to keep in mind that advancements in technology often encounter initial skepticism before they become widely adopted. Just like the computer revolution in the 90s, it will take time for people to fully understand and appreciate the benefits of large language models.
billiam 4y ago
Powerful for what? To use Chiang's analogy, do you think that an LLM trained on Web content will actually derive the rules of arithmetic, physics, etc. I think it is more likely that in decade or more a majority of Internet content will be generated by machine and search engines will do a great job of indexing increasingly meaningless information.
- bbor 4y ago
  You’re missing an important point - it’s not /trained/ on live internet content, it /reads/ that content at runtime. I mean it is trained on the internet but please try to separate the concerns. Remember that the goal of this model is language, not learning facts about the world - they could’ve trained it completely on fictional novels if there was a big enough corpus. The only way that LLM-enhanced search returns misinformation is if the internet is full of misinformation. So yeah we’re still in trouble, but the inclusion of the LLM isn’t going to affect that factor either way IMO EDIT: this is completely separate from using LLMs to, say, write political statements for Facebook bots and drown out all human conversations. That’s obviously terrifying, but not related to their use in search engines IMO.

by bbor 4y ago

ElevenLathe 4y ago

You don't need to correct every wrong thing you read. In fact you will probably feel much better if you don't ever do it at all, or at least take a break for while.

bbor 4y ago
Very true :). It doesn’t help that this isn’t exactly a little blog post, it’s a popular New Yorker feature…
- hackernewds 4y ago
  Still that is what the downvote button for. With a comment extolling why your opinion is further valid than the net points that support it, seems an exercise in ego that is not beneficial to either you or the community.
- ElevenLathe 4y ago
  A published "real" news article like this is actually one of the more futile things to try to "correct" IMO. Some guy on a blog might publish a correction or change their view. The New Yorker probably won't (at least not based on an HN comment).
  - graphe 4y ago
    Have you ever tried correcting a "real" article? It's easier to write it in the blog comments then open an email with sources but it's not futile.
    - ElevenLathe 4y ago
      I've not tried, no. If something involved my personal reputation or that of my family or friends, I might try though. Good to know!
visarga 4y ago
obligatory https://xkcd.com/386/ https://xkcd.com/386/
- hnfong 4y ago
  Except now I can train an AI to do it 24/7...
  - TeMPOraL 4y ago
    Except if you want the job done right, you really have to do it yourself...
    - hnfong 4y ago
      You're suggesting I stay up late at night fixing wrong comments made by my AI chatbot? ... Yeah, seems like something I'd do :P
      - TeMPOraL 4y ago
        You could train an AI chatbot to do those fixes for you, but it will also make plenty of mistakes. You could train yet another AI chatbot to compensate for that, but at some point somebody has to get their hands dirty, or else it's AI chatbots all way down.
sebzim4500 4y ago
Very true, but it is hard not be frustrated reading the constant stream of confidently incorrect information about this topic. I left /r/programming similar reasons and it is sad to experience the same on HN.
- gameshot911 4y ago
  The constant misinformation of the world is one of life's great tensions.
fnordpiglet 4y ago
If you did then the LLM might stop hallucinating so much.
o_____________o 4y ago
When my pedantic keyboard warrior gears start turning, I think about the same xkcd a sibling commenter posted. But I've been struggling with the recent tsunami of openly anti-intellectual, alt-everything pseudoscience in the US. I recently pleaded with my sister to read The Demon-Haunted World by Sagan. There's something important in patient advocacy of truth.

brookst 4y ago

Same. I try to give myself three responses to any particular fallacy, mostly to work through my thinking. Once I have a pretty solid “you are assuming a technical limitation in a first gen product will persist in all future evolutions, when the second gen has already addressed it” response, I try to just smile at the 4th. . . Nth people who discover the exact same topic.

bbor 4y ago
Very true - I’m stealing that rule!

dougmwne 4y ago

I appreciate where you are coming from and I agree that AI is about to go from relative obscurity where just a few geeks were playing around to insane hype. I feel like I’ve spent the last 7 years wondering why no one in the wider world was as impressed as I was, but starting with Stable Diffusion and now ChatGPT, the hype rocket ship has launched. Search TikTok for ChatGPT for all the evidence of that you could ever need. That said, I still think we are in for a wild ride, even if we go through a hype bubble and pop first. I really don’t think the current crop of Transformer LLMs are the end of the story. Im betting that we are headed towards architectures made up of several different kind of models and AI approaches just like the brain is an apparent concert of specialized regions. You can see that in the new Bing where it’s a combination of a LLM with static training set that can then do up to 3 web searches to build up additional context of fresh data for the prompt, overcoming one of the key disadvantages of a transformer model. The hidden prompt with plain English Asimov's laws are the icing on the cake. The hype will be insane, but the capabilities are growing quickly and we do not yet seem close to the end of this rich computational ore vein we have hit.

bbor 4y ago
I don’t have much of a response but this comment is very well written and exactly what I would say if I could write clearly. It’s an exciting time! Hopefully it turns out more like the internet and less like… idk I’m struggling to think of a bad invention haha. Quadcopters I guess

CPLX 4y ago

> This is like when my father excitedly told his friends about the coming computer revolution in the 90s and they responded “well it can’t do my dishes or clean the house, they’re just a fad!” Makes me want screaaaaam Did the computer revolution make your father’s life better? Serious question.

bbor 4y ago
Hmm. I’d say definitely yes. I mean we are on the internet right now, presumably across many km of distance. Do you disagree?
- CPLX 4y ago
  I have mixed feelings about it. I do believe with certainty that there are many people, millions, whose life has been made substantially worse by the invention of ubiquitous computing devices. Probably the minority. But I’d say his questions (ie “What’s in it for me?”) are excellent ones to pose in the face of new technology.
  - bbor 4y ago
    I think this is anti-status quo bias, which for once is unjustified. Sure the world has many systemic problems, but to say that the MASSIVE efficiency gains the internet have brought us are for a minority seems like an insane claim. Just because capitalists have been claiming all the new excess value doesn’t mean it doesn’t exist. To illustrate, consider: spreadsheets, video chat, shared documents, automated calendars, maps, autopilot assistants, CGI, I could go on… the world is not quite good enough that I’m ready to say that we don’t need more efficiency. Not everyone has a home on mars quite yet.
    - CPLX 4y ago
      I said the opposite of what you think I said. People who are worse off are most likely the minority. But I do think it’s worth noting that they exist.
- 4y ago

weregiraffe 4y ago

>long-standing record-of-everything-in-the-world (google’s knowledge graph) The internet is not record-of-everything-in-the-world by a long stretch.

chapium 4y ago

I’m just searching the comments for novel use cases where its effective. Most articles I’ve read seem like either moral panics or snake oil. I like how it can generate songs and poems based on a prompt. Its not particularly useful, but it is entertaining. It really does seem curated at times, leading me to think this will eventually become a fad or replaced by a more advanced algorithm.

avereveard 4y ago
Want niche use case? I feed chatgpt the whole warstuff one page rule miniature combat system, and I can ask it to generate thematic units. I generated a wide variety of content from LOTR to ships. it even created new trait to complement the existing one when needed by special units, along with explanation of the mechanics of the trait. It doesn't quite understand positioning, but it will simulate round of combat between unit when asked.
- bbor 4y ago
  You’re by far the most interesting person in this thread - I’ve been coding up a Warhammer 40k (symbolic) AI for a while, but I bet chatgpt could blow it out of the water…
  - avereveard 4y ago
    well warstuff rules are simple and I gues they fit nicely in gpt memory the ruleset is here and is magnitudes simpler than warhammer https://onepagerules.com/portfolio/one-off-games/ https://onepagerules.com/portfolio/one-off-games/ - I just copy pasted the whole ruleset into a message prepended by "Consider a wargaming system built with these rules:" this is a sample prompt afterward: > create a set of units using these rules, themed around warhammer 40k this is what chatgpt came up with, it's impressive as I just set a theme, and it dig up appropriate original special rules that fit within the ruleset: Sure, here are three examples of units themed around Warhammer 40k that you can use in your wargaming system: Space Marines: Quality 4, Special Rules: Shooter, Tough, Cost: 50pts The Space Marines are a heavily armored and well-trained fighting force, with a Quality value of 4 reflecting their combat abilities and morale. They have the Shooter special rule, allowing them to fire ranged weapons, and the Tough special rule, making them more resistant to damage. Their point cost is 50, calculated by multiplying Quality 4 by 10 and adding the point cost of the special rules. Chaos Space Marines: Quality 3, Special Rules: Shooter, Daemonic, Cost: 40pts The Chaos Space Marines are a corrupted version of the Space Marines, with a lower Quality value of 3 but the same Shooter and Daemonic special rules. Daemonic units are immune to morale tests and can only be killed by a roll of 6 on the melee attack. Their point cost is 40, calculated by multiplying Quality 3 by 10 and adding the point cost of the special rules. Necron Warriors: Quality 2, Special Rules: Shooter, Reanimation, Cost: 30pts The Necron Warriors are an undead race of robots, with a Quality value of 2 reflecting their lower morale and combat abilities. They have the Shooter special rule, allowing them to fire ranged weapons, and the Reanimation special rule, allowing them to automatically recover from being stunned instead of taking the Recover action. Their point cost is 30, calculated by multiplying Quality 2 by 10 and adding the point cost of the special rules.

unsignedchar 4y ago

> well it can’t do my dishes or clean the house the correct response would have been "yet"

yoyohello13 4y ago
Well, 30 years later and they still can't. At least I know of no one who has a house cleaning robot. (I wouldn't classify Roomba as 'clean my house').
- euroderf 4y ago
  Clean ALL my bathroom fixtures for under 1000$ retail.
- sh4rks 4y ago
  A roomba + a smartphone controlled dishwasher and you're 50% of the way there
  - freejazz 4y ago
    Really? Turning the dishwasher on is the most trivial part. What difference does it make that I can do that from my phone? I still have to load and unload it...

O__________O 4y ago

It’s an anti-pattern on HN, that is opinion of its own expertise frequently exceeds reality. For what it’s worth, specific to the topic at hand, here’s one HN post that provides explanations of how to overcome some of the limitations of large language models: https://news.ycombinator.com/item?id=34710079 https://news.ycombinator.com/item?id=34710079

trompetenaccoun 4y ago

I understand why the mainstream thinks that but it's incredibly annoying that even in tech circles there is very little meaningful discussion, it's mainly just people posting amusing screenshots purportedly showing how smart GPT3 is or in other cases how it's politically biased. Anyone who's played around with it knows that it's fun but it's not a search engine replacement and it doesn't know nor understand things. It regularly gives complete misinformation and when you ask for a source it makes up fake URLs and fake science papers on top of that. It's nothing like described in the article and I don't understand why people who should know better don't call out the bullshit media reporting more. We've had GPT3 for ages, it's not like most of us only tried it since Chat GPT3 came out, right?

JoshCole 4y ago
> It's nothing like described in the article and I don't understand why people who should know better don't call out the bullshit media reporting more. I'm kind of assuming you didn't read the article, but if you did then I'm kind of assuming that you've never done machine learning, but if you have: how did you manage to do that without ever noticing that you were doing approximation? Objectively, neural networks are approximators. Like, truly objectively, as in, the literal objective function, objectively minimizes approximation error. We call them objective functions and minimizing the approximation error is typically the objective of these objective functions. This isn't bullshit. It isn't. If you think it is, you are deeply and profoundly mistaken. The article advances this view of language models. This is a reasonable view of language models for the same reason that machine learning papers exploring neural networks describe them as universal function approximators.
JoshCole 4y ago
> Anyone who's played around with it knows that it's fun but it's not a search engine replacement and it doesn't know nor understand things. I've noticed that some people have been talking as if the view is nonsense in the direction you imply it is nonsense, but I think the argument for a lack of sensory ties is much stronger when stated in the other direction. This fails when arguing against the straw man position, but of course, drinking water also fails when addressing the weakest possible justification for it - clearly drinking water is bad because if you drink water you die of osmosis, though technically true, isn't really reflective of the actual predictions made by the people advancing the claim that we ought to drink more water than we do. So I'll give the argument for language models replacing search engines not being nonsense, but the position that no one could arrive at the belief actually being nonsense. Lets start with people not arriving at that belief being nonsense. I think it is nonsense in two ways. One way is that because some people have used them, then claimed they would be replacing search engines for some queries, it follows that you deny your senses with regard to the existence of these people. This is not sensory tied. So it is non-sensical. The second way is your belief anticipates experiences, but this experience you are now having in which someone disagrees with you is in contradiction to the anticipated experienced supposed by the belief. So it fails to predict past experiences and fails to predict current experiences, so it probably fails to predict future experiences. There probably will be someone in the future who, after interacting with a language model, thinks it can serve as a replacement for some search engine queries. Now in contrast, their claims were not non-sensical when they thought they could replace some search engine queries with language model queries. By that I also mean that they were not non-sensical in two respects. The first is that they arrived at the belief after replacing queries to search engines with queries to language models. Then, after having found value in doing so, they announced a belief congruent with that value, intimately connecting their belief to their senses. The second is that, having arrived at their belief, their belief paid rent in anticipated experience: it successfully predicted three noteworthy events: the internal code red status at Google, you.com's language model as enrichment for search, and bing.com's use of language model as enrichment for search. So it successfully predicted past experiences, successfully predicted current experiences, and may or may not predict future experiences - I think most people who hold this view tend to think there will be some refinements on the current generation of language models, in particular, that they will further refined at query time with relevant data, like fact databases, to help correct for some of the existing approximation error. This is my belief. I anticipate this happening. You can judge whether I anticipate successfully by watching reality. I should note that part of the reason I think this will happen is because I've already seen it happen. So I'm not really making a bold prediction here, but I suspect you will later see this happen, because I've seen this happen. Anyway... the belief that language models can replace some search queries is not a non-sensical belief, like beliefs in fairies is, but the belief that no one arrives at a belief that they could be is a non-sensical belief, because people do arrive at such beliefs, and so therefore the belief that they don't is fanciful and not reflective of reality.

omnicognate 4y ago

> Yes, hooking one up to our long-standing record-of-everything-in-the-world (google’s knowledge graph) is going to be powerful. This hasn't happened yet and, while I may just lack imagination, despite having a fairly solid understanding of how the latest round of AI works I can't see how it can be done successfully. Until it is in fact done and my lack of imagination is demonstrated, your "going to be powerful" is a speculation about the future, not an observation about the present, and deserves the level of respect usually accorded to such speculations.

euroderf 4y ago
Wouldn't a connection to Cyc be a million percent more useful ?
bbor 4y ago
In my view it’s very simple, which is what makes it so exciting. Summarizing a design doc that I imagine Microsoft and google are both spending millions of dollars of manhours/day working on their versions of: 1. User enters query. 2. LLM augments query if necessary, adding extra terms or clauses. 3. Normal search pipeline returns ranked links, just like it does now. 4. LLM reads the content of the first 100 links and decides which are the best based on your stated preferences and past behavior, uses that to augment the ranking a bit. 5. LLM generates various summaries depending on the type of query, such as laying out a few common answers to a controversial political question or giving a summary of a technical Wikipedia article tailored to your expertise level in that field. 6. Finally, for a tiny subset of queries, maybe the user wants to converse with the AI in a chat-like format, where it cites all of its claims with direct links. It’s gonna be awesome :)
- omnicognate 4y ago
  I mean, how hard can it be, right?

cryptoegorophy 4y ago

It's understandable how frustrating it can be to encounter skepticism and misunderstanding about the capabilities of large language models. However, it's important to remember that these models are still relatively new and not everyone is familiar with their potential uses and limitations. It's also worth noting that these models are not designed to replace human intelligence, but rather to augment it and provide valuable insights and assistance in various tasks. And while connecting them to large knowledge graphs like Google's can be powerful, it's still only one piece of the puzzle. It can be discouraging to face resistance, but it's important to keep in mind that advancements in technology often encounter initial skepticism before they become widely adopted. Just like the computer revolution in the 90s, it will take time for people to fully understand and appreciate the benefits of large language models.

billiam 4y ago

Powerful for what? To use Chiang's analogy, do you think that an LLM trained on Web content will actually derive the rules of arithmetic, physics, etc. I think it is more likely that in decade or more a majority of Internet content will be generated by machine and search engines will do a great job of indexing increasingly meaningless information.

bbor 4y ago
You’re missing an important point - it’s not /trained/ on live internet content, it /reads/ that content at runtime. I mean it is trained on the internet but please try to separate the concerns. Remember that the goal of this model is language, not learning facts about the world - they could’ve trained it completely on fictional novels if there was a big enough corpus. The only way that LLM-enhanced search returns misinformation is if the internet is full of misinformation. So yeah we’re still in trouble, but the inclusion of the LLM isn’t going to affect that factor either way IMO EDIT: this is completely separate from using LLMs to, say, write political statements for Facebook bots and drown out all human conversations. That’s obviously terrifying, but not related to their use in search engines IMO.