4 ms·

Many of us have solved this with internal tooling that has not yet been shared or released to the public.

layer8 1y ago
This needs to be generalized however. For example, if you present an AI with a drawing of some directed graph (a state diagram, for example), it should be able to answer questions based on the precise set of all possible paths in that graph, without someone having to write tooling for diagram or graph processing and traversal. Or, given a photo of a dropped box of matches, an AI should be able to precisely count the matches, as far as they are individually visible (which a human could do by keeping a tally while coloring the matches). There are probably better examples, these are off the cuff. There’s an infinite repertoire of such tasks that combine AI capabilities with traditional computer algorithms, and I don’t think we have a generic way of having AI autonomously outsource whatever parts require precision in a reliable way.
- snapcaster 1y ago
  What you're describing sounds like agentic tool usage. Have you kept up with the latest developments on that? it's already solved depending on how strict you define your criteria above
  - layer8 1y ago
    My understanding is that you need to provide and configure task-specific tools. You can’t combine the AI with just a general-purpose computer and have the AI figure out on its own how to make use of it to achieve with reliability and precision whatever task it is given. In other words, the current tool usage isn’t general-purpose in the way the LLM itself is, and also the LLM doesn’t reason about its own capabilities in order to decide how to incorporate computer use to compensate for its own weaknesses. Instead you have to tell the LLM what it should apply the tooling for.
    - snapcaster 1y ago
      Sure, engineering is still required but this doesn't mean it's not a solution to the problem you posed
    - Kapura 1y ago
      this is my understanding; it makes me ask where exactly the "intelligence" is here.

This needs to be generalized however. For example, if you present an AI with a drawing of some directed graph (a state diagram, for example), it should be able to answer questions based on the precise set of all possible paths in that graph, without someone having to write tooling for diagram or graph processing and traversal. Or, given a photo of a dropped box of matches, an AI should be able to precisely count the matches, as far as they are individually visible (which a human could do by keeping a tally while coloring the matches). There are probably better examples, these are off the cuff. There’s an infinite repertoire of such tasks that combine AI capabilities with traditional computer algorithms, and I don’t think we have a generic way of having AI autonomously outsource whatever parts require precision in a reliable way.

snapcaster 1y ago
What you're describing sounds like agentic tool usage. Have you kept up with the latest developments on that? it's already solved depending on how strict you define your criteria above
- layer8 1y ago
  My understanding is that you need to provide and configure task-specific tools. You can’t combine the AI with just a general-purpose computer and have the AI figure out on its own how to make use of it to achieve with reliability and precision whatever task it is given. In other words, the current tool usage isn’t general-purpose in the way the LLM itself is, and also the LLM doesn’t reason about its own capabilities in order to decide how to incorporate computer use to compensate for its own weaknesses. Instead you have to tell the LLM what it should apply the tooling for.
  - snapcaster 1y ago
    Sure, engineering is still required but this doesn't mean it's not a solution to the problem you posed
  - Kapura 1y ago
    this is my understanding; it makes me ask where exactly the "intelligence" is here.