Comment by kennethfriedman | Hacker News Reader

Comment by kennethfriedman | Hacker News Reader

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kennethfriedman

Author here. Wow, fantastic feedback! Thank you for taking the time to read it and respond.

I have a few responses. As an undergrad, I won't assume my background is strong enough for direct opinions, so apologies in advance as my responses are mostly pointers to other people.

Professor Patrick Winston[0] at MIT would argue that the expert systems, the successes of the '80s also about making money. Obviously not as much present day, but that is due to the tech sector infiltrating more areas/markets simply because of the exponential growth processing power. It would be very interesting to compare AI's value-add to the world between 1980 and today when adjusted for the "inflation" of moore's law.

It's true I didn't consider the number of people in the field currently compared to the past, and that's an interesting point.

The instructor of the class that I wrote this paper for, Joscha Bach[1], would argue that real physical world results are not very significant, since the real world can be thought of as a simulation itself.

The idea of "what happens next? What could go wrong?" with self driving cars is interesting. A question arises, should you be able to ask the car, "why did you just stop short?" and receive an answer? This is a question Gerald Sussman has been discussing recently[2]. If we do want systems that can explain their behavior, then they must speak in human-language and therefore must be symbolic at some level. In general, the idea of "Common Sense" seems too much of (what Minksy would describe as) a suitcase word[3] -- because the definition is so abstract, it's not worthy of debate without defining the term.

Great call on Hillis, thanks! I completely mixed up Symbolics and Thinking Machines. Fixed!

[0]: http://people.csail.mit.edu/phw/ [1]: http://cognitive-ai.com/ [2]: https://vimeo.com/151465912 [3]: https://alexvermeer.com/unpacking-suitcase-words/

"A question arises, should you be able to ask the car, "why did you just stop short?" and receive an answer?"

I can't get that answer from my horse, but he has the common sense to stop before getting into trouble. Mammals with 99% DNA commonality with humans can run their lives successfully but can't talk. If we can get to good mammal-level AI performance, we should understand how to get to human. Right now, we're still having trouble getting to lizard level. Even OpenWorm [1] isn't working yet.

[1] http://www.openworm.org/

Ah, now we get into a pretty interesting debate: is there a fundamental difference between human cognition and other animals?

But specifically for the horses example: I think it would be pretty hard to defend the case that horses have commonsense, unless you use the definition of commonsense as "basic survival skills." Horses can walk around until they find food, and they can run if they see a fast moving object. But I can't think of any examples that seem like commonsense, in the definition of "sound judgment in practical matters."

When thinking of it from a bottom-up approach, Rodney Brooks[0] comes to mind. He tried to build rat like creatures in the early 90s, with the goal that modeling rat behavior would enable modeling human behavior. However, the results were unsuccessful, and the implementations did not scale well. (Which is another case for the humans-are-fundamentally-different side of the argument)

[0]: https://www.cs.nyu.edu/courses/fall01/G22.3033-012/readings/...

As someone who has a basic neuroscience background, your comment is a sequence of empty statements.

> Ah, now we get into a pretty interesting debate: is there a fundamental difference between human cognition and other animals?

Actually, that's not an interesting debate at all, unless you like vacuous debates. You will have to be very - very - specific if you want that "debate" to be grounded in actual science.

> pretty hard to defend the case that horses have commonsense

Given that there is no neuroscience-based knowledge of what "common sense" even means, you are making up your own criteria.

I don't even see what point you are trying to make in your last paragraph.

> (Which is another case for the humans-are-fundamentally-different side of the argument)

Eh.. what? You name some random experiment, don't even say much about it at all, and then try to draw a general conclusion. And of course, as in all your other statements, you refrain from any specifics but remain a "politician", just playing with words that don't mean anything specific.

Thanks for the comment, but let's try to keep this discussion friendly and not ad hominem.

I'd politely disagree that my comment was a sequence of empty statements, but allow me to provide some clarifying details that might help your understanding.

The debate I describe is actually critical. If humans are not fundamentally different, than the field should be able to model more simplistic animals (such as a rat), and slowly build up to a model of human level intelligence. On the other-hand, if there is a fundamental difference between humans and other animals, then simply modeling other animals will not scale, and will leave the field wanting.

I don't think we have to get too specific to debate this. I would point to Winston, Tattersall, Chomsky as three widely respected individuals who present the case that symbolic language (and the uniquely human ability to combine two concepts into a new concept, indefinitely) is the keystone that separates humans from other animals.

In your second criticism, we agree exactly. As you can see in my previous comment, I agree that "commonsense" is an arbitrary term. Here, I was simply providing an example of how debating commonsense is not a useful exercise.

Finally, in my last paragraph I was providing an example of how attempting to use "simple animals" as a basis for modeling human behavior has not effective. The previous commenter said that we haven't reached "lizard level" and pointed to the OpenWorm project. I pointed to a related project, from Brooks, that had a similar mission. It did not work, perhaps, because modeling simple animals (such as a rat or lizard), won't scale to humans. I did not meant to draw a general conclusion (since I said that it is simply another case, not a proof).

As to your final line, let's keep this a lively discussion and not a personal attack.

Nothing to debate. There isn't. Let's stop wasting brainpower on this. Too much empty and meaningless philosophical discussion has unfortunately been revived by recent advanced in ML/AI.

This is sad. Especially because I believe philosophy could have a meaningful contribution to the progress of human understanding. It was a "science of interfaces" in the beginning, and now with more and more specialization we also end up with more and more "interfaces" between sub-sub-fields until 90% of everything will be "an interface between something and something else". Too bad we'll have to re-invent it under a different name, and probably disguise it as some sub-sub-field of engineering, to make sure we sever the the connection with all people willing to waste everyone's time with empty-talk and empty-think...

You've never heard common sense called "horse sense"?

The original 1 hp self driving vehicles.

They too were saddled with drunks and had to know the correct way home without direction.

> However, the results were unsuccessful, and the implementations did not scale well.

Can you define "unsuccessful" and "did not scale well"? From what you've said, I cannot see any relation to the "humans-are-fundamentally-different side of the argument". You just make it sound like a failed experiment, without saying why it failed.

Funny, I believe that much of what differentiates us from machines is the fear of the death that underlines every part every layers of our system, and our ancestry back to bacterias.

You should absolutely be able to find out why your car stopped and what it is waiting for. Not doing that would be a huge fail from the self driving car companies and would make it a lot harder to get people to trust self driving cars.

Yet animals and humans DO communicate to each other. Especially horses.

Happens all the time.

I am hungry. I am angry. I need comfort. I want to go somewhere. I am pleased to see you.

And so on. It is elemental communication but it is real.

You may have heard of how new neural network architectures are designed? GDGS? Gradient Descent by Grad Student?

It's a joke, but funny because it is true.

That's one of the artifacts of the number of people in the field.

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