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I’m skeptical since we’ve heard the same promises of how chatbots will replace our computer interfaces for years now. The systems always seem to break down when

I’m skeptical since we’ve heard the same promises of how chatbots will replace our computer interfaces for years now. The systems always seem to break down when the user needs to do something surprising. Think about trying to navigate an automated phone menu when your option isn’t available. Transformers seem incredibly good at picking up patterns and repeating them, and combining them in new and surprising ways, but my intuition says that the unpredictability of the real world will cause the required training set to grow faster than the models can keep up, at least to get close to anything that “looks a lot like AGI.”

jvm 4y ago
Author here, yeah I agree the real world is very complicated. For any given task I'm imagining something like 1. Use some sort of instruction tuning to get the thing "good enough" that it gives decent results 75% of the time and the other 25% a human has to take over. 2. Use the actual usage data as training input. Punish bad behaviors and show the model what the human did to solve the problem. 3. Use this training loop to progressively have the model take over a larger % of the time. …and I think if you can't get (1) good enough to be worth using it's going to be really hard to get the loop going.
- huijzer 4y ago
  > Use some sort of instruction tuning to get the thing "good enough" that it gives decent results 75% of the time and the other 25% a human has to take over. How does the model know when a human has to take over? I think most extrapolations of current "AI" capabilities into future capabilities are fun and useful in some ways, but also doomed to fail. It's very easy to miss a tiny detail which may in practice be a fundamental problem. > Use the actual usage data as training input. Given that those bigger state-of-the-art models train on terabytes of data, how would you know how much training data to generate to sufficiently change the output? My understanding of "AI" is that it's mostly about some very complex models which are capable of solving previously unsolvable problems. However, those problems are always extremely specific. Going the other way of thinking of problems or future possibilities first and then applying "AI" to it is likely to fail.
  - twaw 4y ago
    AI should be watched by a AI critic (or a AI guard), which goal is to detect harmful, dangerous, stupid, surprising behavior and raise alarm. For example, image generators are watched for NSFW content by a separate AI critic.
  - svnt 4y ago
    > How does the model know when a human has to take over? It’s incredibly easy, you ask “did this answer solve your issue?” and add a max_tries. > … how do you know how much training data to generate …? You don’t, you keep doing it until the results improve to meet your goals, or they stop short and you switch tactics.
    - r2_pilot 4y ago
      That will work incredibly well for the self-driving AI cars that lost control at speed. /sarcasm Not all problems in life have the opportunity to be retried more than once.
      - svnt 4y ago
        You are maybe not thinking flexibly enough. That’s why they have a fleet (parallelization) and why they outfitted the cars with sensors before self-driving was a thing (so they could simulate decision-making and have it corrected by driver action). Their customers’ feedback absolutely trained their models.
  - notahacker 4y ago
    Much of the time knowing the human has to take over isn't one of the more difficult problems: the AI can't map the user input to a possible continuation with any high probability, or the AI interprets the user input as an expression of frustration or an assertion it's wrong. The challenge is when AI has to interpret questions about stuff which can be expressed in syntactically similar ways with very different or precisely opposite meanings so it's very confidently (and plausibly) wrong about stuff like price changes and tax, event timings, refunds etc.
- TuringTest 4y ago
  Main problem is that most new commercial AI systems usually aren't really designed to let the human take over. There's a closed loop with a front-up designed experience, and the only option in case of failure is to stop using the system. There's no recourse to manual adjustment of system behavior by the user. Research articles should insist on including the user in the loop from the beginning.
  - svnt 4y ago
    > Main problem is that most new commercial AI systems usually aren't really designed to let the human take over. The ones in business use absolutely are.
tluyben2 4y ago
> needs to do something surprising. In my experience, that’s being incredibly generous. We evaluated the ‘big names’ in AI chatbots for a project recently, and their biggest portfolio examples (not on their site; ones we went through with their consultants) trip up over depressingly trivial but relevant for the business questions. It might have been a surprise for the chatbot but, for instance, at one point the question asked was in the faq of the company but by the way we formulated it, it didn’t understand it was the same thing. FAQs are made by people who understand the business, a question is distilled from many questions that lead to the same answer; regular users won’t ask the question exactly or at all like that, which is where the AI/nlp is supposed to help. In my professional and personal experience it often does not. Anecdotally, no one I personally know has ever been helped by a chatbot, but then again, no one I know would click on chat unless all other options (searching google) are exhausted. Taking a few steps back to your automated phone menu; most systems that I call now use speech recognition to, for instance, have you tell it your account number, shipping code, order number etc. Even this never works for me; it has never understood what I read to it. And these are many different systems. Now sure; this might be because I talk funny or something (although my wife has the same experience and she was a radio and tv journalist), however, the human that comes after that has no issues at all understanding me reading the same information to them.
- monero-xmr 4y ago
  An entire generation of dreamers trying to brute force P=NP. Non-AGI AI tech can get 80-95% of the way there but it can never get to 100% (or even reasonably close) because the nature of the problem is unsolvable. Everyone working on self driving cars is just patching infinity.
- huahaiy 4y ago
  Maybe you should try some "small names" in AI chatbots.
- matkoniecz 4y ago
  > no one I personally know has ever been helped by a chatbot I treat chatbot like stalebot on bug reports list: as someone wishing to tell "go away, you are not wanted here" but not having enough honesty to do it openly.
madsbuch 4y ago
> Think about trying to navigate an automated phone menu when your option isn’t available. I have reached the conclusion that this must be on purpose for many companies. Eg. when I call the airline about a refund, and none of the options presented are fit for that request. This is much more about the airline doing customer harassment to earn an extra bug than the system being broke.
matkoniecz 4y ago
Is there any existing chatbot that is better than manually setup "press 1 for issues related to XYZ, press 2 for foobar issues (...)" menus?
- trekkie1024 4y ago
  When you call the Apple store, you get a much more conversational interface with their chatbot that asks you what you would like: ie. Fix my iPhone, etc.
  - matkoniecz 4y ago
    Interesting, I have no exposure to Apple ecosystem so I would not encounter it - thanks for letting me know!

jvm 4y ago

Author here, yeah I agree the real world is very complicated. For any given task I'm imagining something like 1. Use some sort of instruction tuning to get the thing "good enough" that it gives decent results 75% of the time and the other 25% a human has to take over. 2. Use the actual usage data as training input. Punish bad behaviors and show the model what the human did to solve the problem. 3. Use this training loop to progressively have the model take over a larger % of the time. …and I think if you can't get (1) good enough to be worth using it's going to be really hard to get the loop going.

huijzer 4y ago
> Use some sort of instruction tuning to get the thing "good enough" that it gives decent results 75% of the time and the other 25% a human has to take over. How does the model know when a human has to take over? I think most extrapolations of current "AI" capabilities into future capabilities are fun and useful in some ways, but also doomed to fail. It's very easy to miss a tiny detail which may in practice be a fundamental problem. > Use the actual usage data as training input. Given that those bigger state-of-the-art models train on terabytes of data, how would you know how much training data to generate to sufficiently change the output? My understanding of "AI" is that it's mostly about some very complex models which are capable of solving previously unsolvable problems. However, those problems are always extremely specific. Going the other way of thinking of problems or future possibilities first and then applying "AI" to it is likely to fail.
- twaw 4y ago
  AI should be watched by a AI critic (or a AI guard), which goal is to detect harmful, dangerous, stupid, surprising behavior and raise alarm. For example, image generators are watched for NSFW content by a separate AI critic.
- svnt 4y ago
  > How does the model know when a human has to take over? It’s incredibly easy, you ask “did this answer solve your issue?” and add a max_tries. > … how do you know how much training data to generate …? You don’t, you keep doing it until the results improve to meet your goals, or they stop short and you switch tactics.
  - r2_pilot 4y ago
    That will work incredibly well for the self-driving AI cars that lost control at speed. /sarcasm Not all problems in life have the opportunity to be retried more than once.
    - svnt 4y ago
      You are maybe not thinking flexibly enough. That’s why they have a fleet (parallelization) and why they outfitted the cars with sensors before self-driving was a thing (so they could simulate decision-making and have it corrected by driver action). Their customers’ feedback absolutely trained their models.
- notahacker 4y ago
  Much of the time knowing the human has to take over isn't one of the more difficult problems: the AI can't map the user input to a possible continuation with any high probability, or the AI interprets the user input as an expression of frustration or an assertion it's wrong. The challenge is when AI has to interpret questions about stuff which can be expressed in syntactically similar ways with very different or precisely opposite meanings so it's very confidently (and plausibly) wrong about stuff like price changes and tax, event timings, refunds etc.
TuringTest 4y ago
Main problem is that most new commercial AI systems usually aren't really designed to let the human take over. There's a closed loop with a front-up designed experience, and the only option in case of failure is to stop using the system. There's no recourse to manual adjustment of system behavior by the user. Research articles should insist on including the user in the loop from the beginning.
- svnt 4y ago
  > Main problem is that most new commercial AI systems usually aren't really designed to let the human take over. The ones in business use absolutely are.

tluyben2 4y ago

> needs to do something surprising. In my experience, that’s being incredibly generous. We evaluated the ‘big names’ in AI chatbots for a project recently, and their biggest portfolio examples (not on their site; ones we went through with their consultants) trip up over depressingly trivial but relevant for the business questions. It might have been a surprise for the chatbot but, for instance, at one point the question asked was in the faq of the company but by the way we formulated it, it didn’t understand it was the same thing. FAQs are made by people who understand the business, a question is distilled from many questions that lead to the same answer; regular users won’t ask the question exactly or at all like that, which is where the AI/nlp is supposed to help. In my professional and personal experience it often does not. Anecdotally, no one I personally know has ever been helped by a chatbot, but then again, no one I know would click on chat unless all other options (searching google) are exhausted. Taking a few steps back to your automated phone menu; most systems that I call now use speech recognition to, for instance, have you tell it your account number, shipping code, order number etc. Even this never works for me; it has never understood what I read to it. And these are many different systems. Now sure; this might be because I talk funny or something (although my wife has the same experience and she was a radio and tv journalist), however, the human that comes after that has no issues at all understanding me reading the same information to them.

monero-xmr 4y ago
An entire generation of dreamers trying to brute force P=NP. Non-AGI AI tech can get 80-95% of the way there but it can never get to 100% (or even reasonably close) because the nature of the problem is unsolvable. Everyone working on self driving cars is just patching infinity.
huahaiy 4y ago
Maybe you should try some "small names" in AI chatbots.
matkoniecz 4y ago
> no one I personally know has ever been helped by a chatbot I treat chatbot like stalebot on bug reports list: as someone wishing to tell "go away, you are not wanted here" but not having enough honesty to do it openly.

madsbuch 4y ago

> Think about trying to navigate an automated phone menu when your option isn’t available. I have reached the conclusion that this must be on purpose for many companies. Eg. when I call the airline about a refund, and none of the options presented are fit for that request. This is much more about the airline doing customer harassment to earn an extra bug than the system being broke.

matkoniecz 4y ago

Is there any existing chatbot that is better than manually setup "press 1 for issues related to XYZ, press 2 for foobar issues (...)" menus?

trekkie1024 4y ago
When you call the Apple store, you get a much more conversational interface with their chatbot that asks you what you would like: ie. Fix my iPhone, etc.
- matkoniecz 4y ago
  Interesting, I have no exposure to Apple ecosystem so I would not encounter it - thanks for letting me know!