Hacker News new | ask | show | jobs
by observation 3241 days ago
> Look around, most organisms in our world communicate using extremely simple binary language or don't communicate verbally at all.

Yes.

> Yet, they are intelligent enough to do very complicated tasks which current robots fail to do.

True.

> Intelligence is an easier problem than language, and thus should be solved before language.

Wrong.

This is the classic mistake everybody makes, including people in Computer Science.

Because if that were so our robots would already be clambering backwards through chairs (per the metaphor in the article).

You have to think of deep evolutionary history. It took centuries to come up with advanced mathematics, so in some strange to humans sense, this isn't that hard. Same with language, it only took tens of thousands of years.

For Nature to learn how to develop a nervous system capable of flexibly interacting with the environment, culminating in our brains, took hundreds of millions of years.

This isn't an claim that we have to wait that long to re-engineer such powers, but it is to point out that if the possibility space for developing a nervous system was much larger than for the same organisms to learn language...

tldr; Walking is hard.

We have been conflating what is easy for us, with what is objectively easy, because we don't appreciate the Deep Time that Nature has been working with. I suspect we will develop EMs (brain emulations, a sort of short cut) before we understand what we are doing but I hope that is wrong.

4 comments

If I am following you correctly, you are arguing that walking is a harder problem than language because it took much longer to evolve.

This seems to assume that a facility for language and advanced mathematics is independent of the existence of a nervous system capable of flexibly interacting with the environment, but it seems plausible, indeed probable, that language, consciousness and math depend heavily on the prior neural infrastructure, and their development was the most recent step in a process that has been going on since the evolution of the first synapse.

On the other hand, I am skeptical of the somewhat popular view that the key to generalized AI is to make robots that interact more thoroughly with their environment, and that they will then find their own way to language and consciousness. Partly, this is because I do not think that if you intentionally pursue the robotic goal, you will necessarily create the sort of infrastructure that is generalized enough to be the basis for the emergence of language.

> If I am following you correctly, you are arguing that walking is a harder problem than language because it took much longer to evolve.

This is a thorny subject. So I am saying that in some objective way, walking is harder than language because Nature took millions/billions of years to traverse the solution space. Then... once we had a huge number of preconditions existing, then we had the development of language.

I am not saying that this means if it takes 10 years to develop language with some artificial means that it will take 100,000 years to develop walking.

What I am pointing to is that we ought to appreciate that if even blind natural selection took that long, then the possibility space to develop a nervous system must be much larger than we have anticipated.

As evidence of this: consider how (at least in popular culture, but also in comp sci in the old days) we developed chess playing computers and it was broadly assumed that breakthroughs in getting robots to walk and talk would soon follow through. That did not happen. It was a natural assumption but it was wrong.

> This seems to assume that a facility for language and advanced mathematics is independent of the existence of a nervous system capable of flexibly interacting with the environment, but it seems plausible, indeed probable, that language, consciousness and math depend heavily on the prior neural infrastructure, and their development was the most recent step in a process that has been going on since the evolution of the first synapse.

I don't know the answer to that. On different days I think one or the other is true. On Day #1 I think Nature obviously required walking before talking, but we could develop them differently, just has we didn't need to develop better horses to produce cars. On Day #2 I think to myself there's a deeper sense in which you really do require walking before talking because otherwise why didn't Nature develop biological microlife which evolved communications ability long before it developed legs. So...

> On the other hand, I am skeptical of the somewhat popular view that the key to generalized AI is to make robots that interact more thoroughly with their environment, and that they will then find their own way to language and consciousness.

We cannot be certain consciousness or intelligence are high probability events once you have life. We could be like those French artifact makers who made such exquisite mechanical toys for the aristocracy but ultimately got nowhere whereas the English inventors meddling with water and steam power really kicked off a revolution.

Who is Silicon Valley is genuinely looking at the fundamentals of A-Life or AI? OpenAI? MIRI? Stanford? DARPA?

> For Nature to learn how to develop a nervous system capable of flexibly interacting with the environment, culminating in our brains, took hundreds of millions of years.

Nature never learned anything. Nature is not a force that chooses what features it wants to implement in living things. We evolve in periods of punctuated equilibrium, when the average individual within a population cannot reproduce successfully. Then species change very quickly(sometimes sub-1000 years) to fit their environment. We're not sure why humans evolved to be so intelligent, but one possible reason is that our environment was changing very quickly, so quickly that we had to change our core behaviors within the course of a life time.

It can be very confusing to anthropomorphize Nature. Since Nature never tried to make intelligence, the speed at which intelligence evolved in Nature is pretty irrelevant to the difficulty of the problem of intelligence.

Are you nature? Did you learn? Are you not a force?

It's true nature never "tried" anything except to keep going but I posit it does learn, it's memory is our genes and our own memory, and we are the effect of it's force. I also don't see man and nature as separate. If we created AGI, then nature created AGI. AGI can look back and say the step from biological to machine was akin to single to multi celled organisms.

Yeah that's interesting, it does have some kind of memory with all the genes we have. I mostly just meant that Nature is not an intelligent agent with an agenda (unless you believe that in a spiritual way, which is cool too).

>If we created AGI, then nature created AGI. AGI can look back and say the step from biological to machine was akin to single to multi celled organisms. I do think it's interesting to consider AGI as a similar step from single to multi celled organism, but I also feel like if we consider everything manmade as part of nature, the term nature doesn't really mean anything. If it refers to all man-made things as well as all non man-made things, it kinda just becomes a synonym for "things"

Interesting that highly successful AI like AlphaGo essentially trained itself the evolutionary way by playing against itself.

I wonder if simulations are the right way to efficiently train artificial intelligences

Almost certainly, I think all sentient life has some kind of imagination, even if rudimentary.
well we have the advantage of only copying nature that already works the hardest part is already done the Zero to One.

Nost of human technology today is based on replicating nature.

"Based on replicating nature"? Fiber optic cable? Microchips? Mass spectrometers? Atomic weapons? Even humans first technology, sharp stone tools, isn't really a replication of nature. Maybe some examples would help me understand what you mean.
Six ways nature has inspired tech innovations

http://www.bbc.com/news/business-34676930

On AI is probably the best way to approach the problem, nature already as figured it out we jyst have to understand it and replicate it.
Stone tools is replication of beak and claws.