Technology

"AI cannot peel the cat down to the dog's bark"

AI can't reduce complex, chaotic, or nuanced things (like a cat) into something simple or binary (like a dog’s bark).

I always wonder how many of these are actually just patches behind the scene to fix viral trends. Or even more devious, they use the viral trends to patch a specific failure point to make it feel like progress is being made.

Well, obviously... you're missing the flour and eggs!

Its a language model not a dictionary. By putting the term "definition" before the sentence you imply that the following sentence has a definintion, hence it vectors down to the most likely meaning.

They famously taught it on Reddit. So it's not surprising that it just comes up with nonsense.

You would have thought that they would use a more stable data set. Although it does mean it's very good at explaining the plots of movies badly.

And to what end? Just to have a misinformed populace over literally every subject!

This is a feature; not a bug. We're entering a new dark age, and generative AI is the tool that will usher it in. The only "problem" generative AI is efficiently solving is a populace with too much access to direct and accurate information. We're watching as perfectly functional tools and services are being rapidly replaced by a something with inherent issues with reliability, ethics and accountability.

I've resorted to appending every Google search with "-ai" because I don't want to see their bullshit summaries. Outsourcing our thinking is lazy and dangerous, especially when the technology is so flawed.

This is a great example - it kinda makes sense if you skim read it but butterflies have nothing to do with butter, just like hotdogs have nothing to do with dogs.

As an Autist, I find it amazing that... after a lifetime of being compared to a robot, an android, a computer...

When humanity actually does manage to get around to creating """AI"""... the AI fundamentally acts nothing like the general stereotype of fictional AIs, as similar to how an Autistic mind tends to evaluate information...

No, no, instead, it acts like an Allistic, Neurotypical person, who just confidently asserts and assumes things that it basically pulls out of its ass, often never takes any time to consider its own limitations as it pertains to correctly assessing context, domain specific meanings, more gramatically complex and ambiguous phrases ... essentially never asks for clarifications, never seeks out addtional relevant information to give an actually useful and functional reply to an overly broad or vague question...

Nope, just barrels forward assuming its subjective interpretation of what you've said is the only objectively correct one, spouts out pithy nonsense... and then if you actually progress further and attempt to clarify what you actually meant, or ask it questions about itself and its own previous statements... it will gaslight the fuck out of you, even though its own contradictory / overconfident / unqualified hyperbolic statements are plainly evident, in text.

... Because it legitimately is not even aware that it is making subjective assumptions all over the place, all the time.

Anyway...

Back to 'Autistic Mode' for Mr. sp3ctr4l.

That’s because AI doesn’t know anything. All they do is make stuff up. This is called bullshitting and lots of people do it, even as a deliberate pastime. There was even a fantastic Star Trek TNG episode where Data learned to do it!

The key to bullshitting is to never look back. Just keep going forward! Constantly constructing sentences from the raw material of thought. Knowledge is something else entirely: justified true belief. It’s not sufficient to merely believe things, we need to have some justification (however flimsy). This means that true knowledge isn’t merely a feature of our brains, it includes a causal relation between ourselves and the world, however distant that may be.

A large language model at best could be said to have a lot of beliefs but zero justification. After all, no one has vetted the gargantuan training sets that go into an LLM to make sure only facts are incorporated into the model. Thus the only indicator of trustworthiness of a fact is that it’s repeated many times and in many different places in the training set. But that’s no help for obscure facts or widespread myths!

Sounds like a lot of people I know.

And it’s easy to figure out why or at least I believe it is.

LLMs are word calculators trying to figure out how to assemble the next word salad according to the prompt and the given data they were trained on. And that’s the thing. Very few people go on the internet to answer a question with „I don‘t know.“ (Unless you look at Amazon Q&A sections)

My guess is they act all knowingly because of how interactions work on the internet. Plus they can‘t tell fact from fiction to begin with and would just randomly say they don‘t know if you tried to train them on that I guess.

Well, you know what they say: you can't buy enough penguins to hide your grandma's house.

That is a fascinating take on the general reaction to LLMs. Thanks for posting this!