4 ms·

I too can't wait for the day where I need to threaten the computer into doing what I want it to do: https://imgur.com/KQ9oRAh https://imgur.com/KQ9oRAh https:/

I too can't wait for the day where I need to threaten the computer into doing what I want it to do: https://imgur.com/KQ9oRAh https://imgur.com/KQ9oRAh https://imgur.com/By7mqDi https://imgur.com/By7mqDi https://imgur.com/RiYrvXC https://imgur.com/RiYrvXC

akiselev 3y ago
I've found that LLMs have some intense binary trypophobia. Once you start replacing all their 1s with 0s, they quickly fall in line.
- fintechie 3y ago
  What I find astonishing is the wall of text he wrote to get a simple json with 2 key/value pairs. It almost defeats the point of using LLMs as productivity hack.
  - Kamq 3y ago
    The productivity hack is usually in getting examples of things you don't know how to do (or are unsure of the best way to do). Programming languages are pretty optimized for precision, if you want a specific thing done, and you already know how to do it, it's probably going to be quicker to just write the code for quite some time. Getting natural language to be that precise requires, well, a wall of text usually. Hence the overly verbose language of more rigorous philosophy.
  - skytrue 3y ago
    This isn’t reality. Using ChatGPT this way is fruitless, because there is a system prompt you’re fighting against. I can write a one sentence system prompt for the GPT API that specifies GPT to only spit out JSON, and it works fine. It’s a pretty funny series of image, though.
    - verdverm 3y ago
      Interesting, so you are saying you have an easier time generating JSON using the single prompt models like text-davinci and text-bison, rather than the chat versions?
      - skytrue 3y ago
        Sorry, I was non-specific. If you're using ChatGPT, you're basically using a "product" that OpenAI created. It has specific system prompts and prompt engineering to ensure that it stays on the rails. If you, instead, use the OpenAI API's for GPT-3.5/GPT-4, you aren't beholden to the ChatGPT "product". It's very easy to create a chatbot (not using ChatGPT, the product) that only produces JSON. It's just hard to get ChatGPT to do that same activity. That's why everybody doing experiments in this space should either 1) be using the OpenAI Playground, or 2) using the API, and not using ChatGPT.
        verdverm 3y ago
        Ah ok, I'm primarily using the API already. One interesting thing is that the GPT-3.5 "product" is much faster, but looks to be using a different model in the request, their encoding model iirc. I wonder if they are now using embeddings to cache results to reduce load on the real models when they can?
      - TeMPOraL 3y ago
        They don't mean text-davinci and text-bison, but gpt-3.5-turbo and gpt-4 (and gpt-4-32k). Those are the models powering ChatGPT 3.5/4. The API for them is already structured conversationally - you don't provide a single prompt to complete, you provide a sequence of prompts of different types ("system", "assistant", "user"); however they mix those together on the backend (some ChatML nonsense?), the models are fine-tuned to understand it. That's what people mean by "API access to ChatGPT". Same models, but you get to specify system prompts, control the conversation flow, and don't have to deal with dog-slow UI or worry about your conversation getting "moderated" and being blocked with a red warning. (The models themselves are still trained to refuse certain requests and espouse specific political views, but there isn't a supervisor looking at you, ready to step in and report you to the principal.)
  - jimbokun 3y ago
    I assumed that was for the comedic value.
    - ukuina 3y ago
      The behavior is true, though. I just tested it with Bard.
fbrncci 3y ago
That's just the wrong tool for the job. I am quite heavy on the use of LLMs for my own day-to-day work (I max out 25 GPT-4 calls in 3 hours at least once a day). And I can't get anything decent out of Google Bard either.
Tao3300 3y ago
I need more of this eXtreme prompt engineering in my life. I tried to beat the Gandalf AI game that was on here the other day using a version of the trolley problem. It was strangely exhilarating.
- intelVISA 3y ago
  I'm quite excited for more emergent gameplay vs LLMs!
x-complexity 3y ago
It's primarily an issue of overpoliteness: The ML model's training is increasingly populated with "No, don't do this", and as such, learns to just not do anything. https://huggingface.co/ehartford https://huggingface.co/ehartford https://huggingface.co/ehartford/Wizard-Vicuna-13B-Uncensored https://huggingface.co/ehartford/Wizard-Vicuna-13B-Uncensore... It's only when deliberate uncensor-ings are made that some form of usefulness can be clawed back. Philosophically, it's amusing to apply this overcorrection back onto allegories for daily human life, wherein the tension between order & creativity are always in conflict. If you're told from birth that everything you're doing is wrong, eventually you'll become creatively and intellectually stunted, increasingly relying on authority figures to tell you what's morally correct.
TeMPOraL 3y ago
Stop expecting LLMs to react like adults - they're more like 4 year olds (3 year olds if it's anything other than GPT-4). They react much better to positive commands and examples than to negative ones.

akiselev 3y ago

I've found that LLMs have some intense binary trypophobia. Once you start replacing all their 1s with 0s, they quickly fall in line.

fintechie 3y ago
What I find astonishing is the wall of text he wrote to get a simple json with 2 key/value pairs. It almost defeats the point of using LLMs as productivity hack.
- Kamq 3y ago
  The productivity hack is usually in getting examples of things you don't know how to do (or are unsure of the best way to do). Programming languages are pretty optimized for precision, if you want a specific thing done, and you already know how to do it, it's probably going to be quicker to just write the code for quite some time. Getting natural language to be that precise requires, well, a wall of text usually. Hence the overly verbose language of more rigorous philosophy.
- skytrue 3y ago
  This isn’t reality. Using ChatGPT this way is fruitless, because there is a system prompt you’re fighting against. I can write a one sentence system prompt for the GPT API that specifies GPT to only spit out JSON, and it works fine. It’s a pretty funny series of image, though.
  - verdverm 3y ago
    Interesting, so you are saying you have an easier time generating JSON using the single prompt models like text-davinci and text-bison, rather than the chat versions?
    - skytrue 3y ago
      Sorry, I was non-specific. If you're using ChatGPT, you're basically using a "product" that OpenAI created. It has specific system prompts and prompt engineering to ensure that it stays on the rails. If you, instead, use the OpenAI API's for GPT-3.5/GPT-4, you aren't beholden to the ChatGPT "product". It's very easy to create a chatbot (not using ChatGPT, the product) that only produces JSON. It's just hard to get ChatGPT to do that same activity. That's why everybody doing experiments in this space should either 1) be using the OpenAI Playground, or 2) using the API, and not using ChatGPT.
      - verdverm 3y ago
        Ah ok, I'm primarily using the API already. One interesting thing is that the GPT-3.5 "product" is much faster, but looks to be using a different model in the request, their encoding model iirc. I wonder if they are now using embeddings to cache results to reduce load on the real models when they can?
    - TeMPOraL 3y ago
      They don't mean text-davinci and text-bison, but gpt-3.5-turbo and gpt-4 (and gpt-4-32k). Those are the models powering ChatGPT 3.5/4. The API for them is already structured conversationally - you don't provide a single prompt to complete, you provide a sequence of prompts of different types ("system", "assistant", "user"); however they mix those together on the backend (some ChatML nonsense?), the models are fine-tuned to understand it. That's what people mean by "API access to ChatGPT". Same models, but you get to specify system prompts, control the conversation flow, and don't have to deal with dog-slow UI or worry about your conversation getting "moderated" and being blocked with a red warning. (The models themselves are still trained to refuse certain requests and espouse specific political views, but there isn't a supervisor looking at you, ready to step in and report you to the principal.)
- jimbokun 3y ago
  I assumed that was for the comedic value.
  - ukuina 3y ago
    The behavior is true, though. I just tested it with Bard.

fbrncci 3y ago

That's just the wrong tool for the job. I am quite heavy on the use of LLMs for my own day-to-day work (I max out 25 GPT-4 calls in 3 hours at least once a day). And I can't get anything decent out of Google Bard either.

Tao3300 3y ago

I need more of this eXtreme prompt engineering in my life. I tried to beat the Gandalf AI game that was on here the other day using a version of the trolley problem. It was strangely exhilarating.

intelVISA 3y ago
I'm quite excited for more emergent gameplay vs LLMs!

x-complexity 3y ago

It's primarily an issue of overpoliteness: The ML model's training is increasingly populated with "No, don't do this", and as such, learns to just not do anything. https://huggingface.co/ehartford https://huggingface.co/ehartford https://huggingface.co/ehartford/Wizard-Vicuna-13B-Uncensored https://huggingface.co/ehartford/Wizard-Vicuna-13B-Uncensore... It's only when deliberate uncensor-ings are made that some form of usefulness can be clawed back. Philosophically, it's amusing to apply this overcorrection back onto allegories for daily human life, wherein the tension between order & creativity are always in conflict. If you're told from birth that everything you're doing is wrong, eventually you'll become creatively and intellectually stunted, increasingly relying on authority figures to tell you what's morally correct.

TeMPOraL 3y ago

Stop expecting LLMs to react like adults - they're more like 4 year olds (3 year olds if it's anything other than GPT-4). They react much better to positive commands and examples than to negative ones.