zlacker

>>mdszy+(OP)
last time I looked at OpenCyc's knowledge base, the information encoded was all strangely specific academic stuff - like very fine classifications and relationships between species of tapeworms and of fungus. There was very little daily-life common-sense knowledge, even though that's often the hook in interviews and articles about Cyc's purpose. I'm not sure why that's true - maybe it's hard to decide what the 'facts' are about normal human life, but the more academic something is, the more there's a consensus, rationalized 'reality'

>>jes519+yy
Employee of Cycorp here. A few thoughts:

- At least right now, we have a good amount of common-sense information about the world (I don't know when "last time" was for you).

- That said, we have a lot of highly specialized knowledge in various domains, so if you took a random sample of the knowledge base (KB) it may not be as common-sense-centric as you'd hope. But the KB is also incredibly large, so that doesn't mean we don't have much common-sense, just that we have even more other stuff.

- Often for contracts we get paid to construct lots of domain-specific knowledge, even if the project also uses the more general knowledge, so this biases the distribution some.

- Information that's already well-taxonomized is low-hanging fruit for this kind of system; its representation doesn't take nearly as much extra thought and consideration, so it's a faster process, which also biases the distribution some.

>>brundo+3C
What are some interesting examples of common-sense that has been formalized and encoded?

>>jey+qC
One of our primary test suites is what we call "Common Sense Tests". They comprise a set of common-sense questions that require some leaps of reasoning to answer, and we use them as a metric of our common-sense knowledge. So for example:

  Would a human dislike touching a/an incandescent bulb while the electric lamp is powered on?

  Yes.

  ?HUMAN dislikes being a performer in the ?TOUCHING.
    • Embodied agents dislike performing acts that cause them discomfort.
    • ?HUMAN is an embodied perceptual agent.
      • ?HUMAN is a human.
        • Every human is an embodied perceptual agent.
    • ?HUMAN deliberately performed ?TOUCHING.
    • ?TOUCHING causes some discomfort.
      • Touching something that is too hot to touch causes pain.
      • The quantity range pain includes all points in some discomfort.
      • ?PART is too hot to touch.
        • When an incandescent bulb is on, it is too hot to touch.
        • ?PART is an incandescent bulb.
        • ?PART’s current state is powered on.
          • When a lamp with a bulb is on, so is the bulb.
          • ?PART is a physical part of ?DEVICE.
            • ?PART is a physical part of ?DEVICE.
            • ?PART is a physical part of ?PART.
          • ?DEVICE’s current state is powered on.
          • ?PART is a light bulb.
            • ?PART is an incandescent bulb.
            • Every incandescent bulb is a light bulb.
          • ?DEVICE is an electric lamp.
      • ?PART was affected during ?TOUCHING.

We have a couple thousand of these, which we've aimed to make as diverse as possible

>>_bxg1+sE
So to "change a lightbulb", so to speak, the system decides something like "turn off the lamp first". But then the evaluation above says that the human would not dislike touching the bulb, but, in reality, it's still too hot.

So you could incorporate some kind of cooling rate, then change the above to "When an incandescent bulb has been on x of the last y minutes it is too hot to touch".

This all seems just impossibly complicated (not that I can think of something simpler!) - am I missing anything?

>>jkaptu+bH
It is very complicated, yes. The goal is to be AI's "left brain"; the slower, more methodical (and explainable!) end of the spectrum. We see our place as being complementary to ML's "right brain", fast-but-messy thinking.

I will say also that our focus on "common sense" means we make deliberate choices about where to "bottom out" the granularity with which we represent the world; otherwise we'd find ourselves reasoning about literal atoms in every case. We generally try to target the level at which a human might conceive of a concept; humans can treat a collection of atoms as roughly "a single object", but then still apply formal logical to that object and its properties (and "typical" properties). In one sense it isn't a perfect representation, but in another sense it strikes the right balance between perfect and meaningful.

>>_bxg1+UH
Thanks so much for the explanation!