Comment by kouru225
4 days ago
The fact that machine learning can learn highly detailed patterns is the very reason why AI is so useful. So what you’re saying doesn’t really make much sense
4 days ago
The fact that machine learning can learn highly detailed patterns is the very reason why AI is so useful. So what you’re saying doesn’t really make much sense
> The fact that machine learning can learn highly detailed patterns is the very reason why AI is so useful.
AI doesn't deal with reality, it deals with tokens. This is why all those vibe-coded harnesses, little more than glue between various text IO interfaces, are several hundreds of thousands of source lines of code.
It's why a SOTA model took 100kSLoK to write a C compiler to compile one specific project.
It's why, when I asked for a simple markdown -> ansi escape codes converter (for terminal output) in Python, SOTA Claude and SOTA ChatGPT both give me +- 150 SLoC when my own LUT-based version came to under 10 lines of code + a LUT.
Reality has a surprising amount of detail, but LLMs don't exist in reality, they exist in a virtual world made up off tokens.
The discretization of those tokens can be manipulated to get any result you want. If it meaningfully benefits the AI to have a more fine-grained discretization, then you can do that. AI only compresses as much as we want it to. I understand your sentiment, but the logical conclusion of what you’re saying is that no form of compression is ever valuable. That’s just not a defensible argument.
All information gets compressed. Even your own perception of reality gets compressed.
Do you exist in reality? Or just in a virtual world made up of sensory signals? Do you have access to the Ding an sich any more than a (multimodal) LLM?
> Do you exist in reality?
Yes.
> Or just in a virtual world made up of sensory signals?
No, definitely reality. Things affect my thought whether I sense them or not.
3 replies →
Come on, now. That's irrelevant.
Reality is by definition our physical reality, which is about an infinite number of levels more detailed than the, you know, _virtual_ digital world computers exist in.
Whatever world we construct for LLMs, no matter how detailed we make it, will always be a blocky projection of the real domain onto a virtual one.
It follows then that any insight gained in the virtual world is at best a rough approximation which can be quite useful at times but also utterly faulty on occasion.
How often it is useful vs. wrong is (partially) a function of how complete the real-to-virtual approximation for a given domain.
Certain domains, given their limited degrees of freedom, can be quite accurately modeled, such as a subway map.
But many domains cannot, and it's important to be aware of that inherent limitation in digital models including but not limited to LLM """reasoning"""
9 replies →
Right but the 'surprising level of detail' can often exhibit itself as exactly not a pattern. There are many jobs where you employ a human not because of the rote/pattern based work, but their ability to handle all the edge cases that are just frequent enough to need them, but not frequent enough for AI to be able to handle. That is the events that in this example would require the AI to ask the human to make some decision for them.
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