4 ms·

I am far from an expert on LLMs and have never used the Rabbit, but wouldn't it be silly to have the llm produce the weather? Wouldn't that mean it must have th

I am far from an expert on LLMs and have never used the Rabbit, but wouldn't it be silly to have the llm produce the weather? Wouldn't that mean it must have the information in either the context window (or the training set, but that seems pretty unlikely to be current), meaning it already had to be gathered from an external source and wouldn't need to be sent to the LLM anyway? What can/does the Rabbit add to it above what a simple string concatenation would?

Aurornis 2y ago
The point of these products is to use a natural language interface to accept freeform questions and produce intuitive and potentially complex responses. Weather was just an example. You can't predict every combination of weather related questions that someone might want to ask and force those into predetermined response strings. The idea is to be able to ask things like "What days this week are best for having an afternoon picnic?" and get a reasonable answer back. If your goal is to hide as much of your personal information as possible from 3rd parties, you're not in the target audience for these products. Nothing wrong with that, it's just targeted at a different demographic of people.
- freedomben 2y ago
  Ah thank you, that does make sense! I appreciate the context you've been able to add (both here and elsewhere in the thread).
d110af5ccf 2y ago
> wouldn't it be silly to have the llm produce the weather? Typically the LLM queries external tools as appropriate and then incorporates the result into the response.
seanhunter 2y ago
As I understand it, you can think of Rabbit's "stack" as a prompt to a standard llm (I think they just used openAI but I could be wrong) to understand what you want, and then a bunch of (brittle) selenium scripts to go call various websites to do the thing. The llm is there to understand that you've said "what's the weather?" not, say "call me an uber", and then to collate the responses from potentially several calls to websites and produce a natural language response. There is a layer of upsell/hustle/scam[1] on top of that where they said they had a "large action model" which learned your preferences and understood how all these websites worked sematically so the actions would be robust etc and a bunch of other stuff which turned out not to be true. [1] depending on your point of view. I would encourage people to watch https://www.youtube.com/watch?v=NPOHf20slZg https://www.youtube.com/watch?v=NPOHf20slZg and https://www.youtube.com/watch?v=zLvFc_24vSM https://www.youtube.com/watch?v=zLvFc_24vSM and do whatever personal research and make their own minds up

Aurornis 2y ago

The point of these products is to use a natural language interface to accept freeform questions and produce intuitive and potentially complex responses. Weather was just an example. You can't predict every combination of weather related questions that someone might want to ask and force those into predetermined response strings. The idea is to be able to ask things like "What days this week are best for having an afternoon picnic?" and get a reasonable answer back. If your goal is to hide as much of your personal information as possible from 3rd parties, you're not in the target audience for these products. Nothing wrong with that, it's just targeted at a different demographic of people.

freedomben 2y ago
Ah thank you, that does make sense! I appreciate the context you've been able to add (both here and elsewhere in the thread).

d110af5ccf 2y ago

> wouldn't it be silly to have the llm produce the weather? Typically the LLM queries external tools as appropriate and then incorporates the result into the response.

seanhunter 2y ago

As I understand it, you can think of Rabbit's "stack" as a prompt to a standard llm (I think they just used openAI but I could be wrong) to understand what you want, and then a bunch of (brittle) selenium scripts to go call various websites to do the thing. The llm is there to understand that you've said "what's the weather?" not, say "call me an uber", and then to collate the responses from potentially several calls to websites and produce a natural language response. There is a layer of upsell/hustle/scam[1] on top of that where they said they had a "large action model" which learned your preferences and understood how all these websites worked sematically so the actions would be robust etc and a bunch of other stuff which turned out not to be true. [1] depending on your point of view. I would encourage people to watch https://www.youtube.com/watch?v=NPOHf20slZg https://www.youtube.com/watch?v=NPOHf20slZg and https://www.youtube.com/watch?v=zLvFc_24vSM https://www.youtube.com/watch?v=zLvFc_24vSM and do whatever personal research and make their own minds up