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dotnet00 parent
You've done nothing but reuse the Sam Altman/Elon Musk playbook of making wild and extremely vague statements.

Maybe say something concrete? What's a positive real world impact of LLMs where they aren't hideously expensive and error prone to the point of near uselessness? Something that isn't just the equivalent of a crypto-bro saying that their system for semi-regulated speculation (totally not a rugpull!) will end the tyranny of the banks.

mikert89
they speak in generalities because the models are profoundly general, a general learning system. below someone asked me to list the capabilities, its the wrong question to ask. its like asking what a baby can do
jay_kyburz
Babies are hopeless. They can't do anything.

Oh, I guess you mean when they grow up.

southernplaces7
So to translate: You want concrete examples of capabilities for something billions are being spent on? What a Silly question! (hand waving about completely speculative future abilities "when they grow up")

The woo is laughable. A cryptobro could have pulled the same nonsense out of their ass about web 3.0

ogogmad
So you're saying that modern LLMs are a just like crypto/Web3, except in all the ways they're not, so they must be useless.

---

Less flippantly, they are excellent for self-studying university-level topics. It's like being able to ask questions to a personal tutor/professor.

zirror
But you need to verify everything unless it’s self evident. The number of times CoPilot (Sonnett 4) still hallucinates Browser APIs is astonishing. Imaging trying to learn something that can’t be checked easily, like Egyptian archeology or something.
bluesnowmonkey
You have to verify everything from human developers too. They hallucinate APIs when they try to write code from memory. So we have:

  - documentation
  - design reviews
  - type systems
  - code review
  - unit tests
  - continuous integration
  - integration testing
  - Q&A process
  - etc.
It turns out when include all these processes, teams of error-prone human developers can produce complex working software. Mostly -- sometimes there are bugs. Kind of a lot actually. But we get things done.

Is it not the same with AI? With the right processes you can get consistent results from inconsistent tools.

dotnet00 OP
Taking the example of egyptian archeology, if you're reading the work of someone who is well regarded as an expert in the field, you can trust their word a lot more than you can trust the word of an AI, even if the AI is provided the text you're reading.

This is a pretty massive difference between the two, and your narrative is part of why AI is proving to be so harmful for education in general. Delusional dreamers and greedy CEOs talking about AI being able to do "PhD level work" have potentially ruined a significant chunk of the next generation into thinking they are genuinely learning from asking AI "a few questions" and taking the answers at face value instead of struggling through the material to build true understanding.

lxgr
The vast majority of people trying to do any given thing simply don’t have access to experts in the field, though.

I’ll take a potential solution I can validate over no idea whatsoever of my own any day.

6 More Comments →
zirror
Sure, I just gave the Browser API example as evidence that the 'hallucination' problem is not gone. OP said it's like "talking to a professor" and you can use it to learn college level stuff. This is where I disagree. I did not double check my professors or text books usually.
lxgr
The trick is to put them in contexts where they can validate their purported solutions and then iterate on them.

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