Comment by highfrequency | Hacker News Reader

Comment by highfrequency | Hacker News Reader

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> We manage to dominate the world mainly by using brute force to simplify our environment and then maintaining and building systems on top of that simplified environment. If we didn't have the proper tools to selectively ablate our environment's complexity…

This is very interesting and I feel there is a lot to unpack here. Could you elaborate on this theory with a few more paragraphs (or books / blogs that elucidate this)? In what ways do we use brute force to simplify the environment, and are there not ways in which we use highly sophisticated leveraged methods to simplify our environment tools? What proper tools allow us to selectively ablate complexity? Why does our intelligence only operate on simplified forms?

Also, what would convince you that symbolic intelligence is actually “harder” than embodied intelligence? To me the natural test is how hard it is for each one to create the other. We know it took a few billion years to go from embodied intelligence (ie organisms that can undergo evolution, with enough diversity to survive nearly any conditions on Earth) to sophisticated symbolic intelligence. What if it turns out that within 100 years, symbolic intelligence (contained in LLM like systems) could produce the insights to eg create new synthetic life from scratch that was capable of undergoing self-sustained evolution in diverse and chaotic environments? Would this convince you that actually symbolic intelligence is the harder problem?

Not OP, but several examples:

A. instead of building a house on random terrain with random materials, first we prefer to flatten the place, then we use standard materials (e.g. bricks), which were produced from simple source (e.g. large and relatively homogenous deposit of clay).

B. For mental tasks it’s usual to said, that a person can handle only 7 items at a time (if you disagree multiply by 2-3). But when you ride a bike you process more inputs at the same time (you hear a car behind you, you see person on the right, you feel your balance, you anticipate your direction, if you feel strong wind or sun on your face you probably squint your eyes, you take a breath of air. On top of that all the processes of your body adjust and support your riding: heart, liver, stomach…)

C. “Spherical cows” in physics. (Google this if needed)

> Why does our intelligence only operate on simplified forms?

Part of the issue with discussing this is that our understanding of complexity is subjective and adapted to our own capabilities. But the gist of it is that the difficulty of modelling and predicting the behavior of a system scales very sharply with its complexity. At the end of the scale, chaotic systems are basically unintelligible. Since modelling is the bread and butter of intelligence, any action that makes the environment more predictable has outsized utility. Someone else gave pretty good examples, but I think it's generally obvious when you observe how "symbolic-smart" people think (engineers, rationalists, autistic people, etc.) They try to remove as many uncontrolled sources of complexity as possible. And they will rage against those that cannot be removed, if they don't flat out pretend they don't exist. Because in order to realize their goals, they need to prove things about these systems, and it doesn't take much before that becomes intractable.

One example of a system that I suspect to be intractable is human society itself. It is made out of intelligent entities, but as a whole I don't think it is intelligent, or that it has any overarching intent. It is insanely complex, however, and our attempts to model its behavior do not exactly have a good record. We can certainly model what would happen if everybody did this or that (aka a simpler humanity), but everybody doesn't do this and that, so that's moot. I think it's an illuminating example of the limitations of symbolic intelligence: we can create technology (simple), but we have absolutely no idea what the long term consequences are (complex). Even when we do, we can't do anything about it. The system is too strong, it's like trying to flatten the tides.

> To me the natural test is how hard it is for each one to create the other.

I don't think so. We already observe that humans, the quintessential symbolic intelligences, have created symbolic intelligence before embodied intelligence. In and of itself, that's a compelling data point that embodied is harder. And it appears likely that if LLMs were tasked to create symbolic intelligences, even assuming no access to previous research, they would recreate themselves faster than they would create embodied intelligences. Possibly they would do so faster than evolution, but I don't see why that matters, if they also happen to recreate symbolic intelligence even faster than that. In other words, if symbolic is harder... how the hell did we get there so quick? You see what I mean? It doesn't add up.

On a related note, I'd like to point out an additional subtlety regarding intelligence. Intelligence (unlike, say, evolution) has goals and it creates things to further these goals. So you create a new synthetic life. That's cool. But do you control it? Does it realize your intent? That's the hard part. That's the chief limitation of intelligence. Creating stuff that is provably aligned with your goals. If you don't care what happens, sure, you can copy evolution, you can copy other methods, you can create literally anything, perhaps very quickly, but that's... not smart. If we create synthetic life that eats the universe, that's not an achievement, that's a failure mode. (And if it faithfully realizes our intent then yeah I'm impressed.)

I think a lot of this is true, but not as critical as is being interpreted.

Compare the economics of purely cognitive AI to in-world robotics AI.

Pure cognitive: Massive scale systems for fast, frictionless and incredibly efficient cognitive system deployment and distribution of benefits are solved. On tap even. Cloud computing and the Internet.

What is the amortized cost per task? Almost nothing.

In-world: The cost of extracting raw resources, parts chain, material process chain, manufacturing, distributing, maintaining, etc.

Then what is the amortized cost per task, for one robot?

Several orders of magnitude more expensive, per task! There is no comparison.

Doing that profitably isn’t going to be the norm for many years.

At what price does a kitchen robot make sense? Not at $1,000,000. “Only $100,000?” “Only $25,000? “Only $10k”? Lower than that?

Compared to a Claude plan? That many people still turn down just to use free tier?

Long before general house helper robots makes any economic sense, we will have had walking talking, socializing, profitable-to-build sex robots at higher price points for price insensitive owners.

There are people who will pay high prices for that, when costs come down.

That will be the canary for general robotic servants or helpers.

The cost isn’t intelligence. There isn’t a particular challenge with in-world information processing and control. It’s the cost of the physical thing that processing happens in.

This is a purely economic problem. Not an AI problem at all.

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