3 ms·

The main problem is. Most people cant tell the difference between an expert opinion and random words. So if an LLM shoots a bunch of jargon on the screen then,

The main problem is. Most people cant tell the difference between an expert opinion and random words. So if an LLM shoots a bunch of jargon on the screen then, well so does my senior platform engineer so whats the difference? The LLM is cheaper and is always on call.

RodgerTheGreat 2y ago
I see deeply ominous connections between generations of American children who have been educated in a manner which produces alarming rates of functional illiteracy[0] and the widespread popularity of machine learning models that produce nonsense which resembles plausible text if you skim or don't actually read it. [0] https://www.apmreports.org/episode/2019/08/22/whats-wrong-how-schools-teach-reading https://www.apmreports.org/episode/2019/08/22/whats-wrong-ho...
- treyd 2y ago
  > The theory is known as "three cueing." The name comes from the notion that readers use three different kinds of information — or "cues" — to identify words as they are reading. > The theory was first proposed in 1967, when an education professor named Ken Goodman presented a paper at the annual meeting of the American Educational Research Association in New York City. > In the paper,5 Goodman rejected the idea that reading is a precise process that involves exact or detailed perception of letters or words. Instead, he argued that as people read, they make predictions about the words on the page using these three cues: > graphic cues (what do the letters tell you about what the word might be?) > syntactic cues (what kind of word could it be, for example, a noun or a verb?) > semantic cues (what word would make sense here, based on the context?) This is interesting because this is fairly similar to how LLMs do next-token prediction, but using exclusively backwards-facing clues from the text (although perhaps also the graphic cues if you are talking about multimodal models).
- pixelatedindex 2y ago
  Super fascinating article, thanks for sharing!
- philipswood 2y ago
  Thanks, I think the linked article is worthy of its own submission: https://news.ycombinator.com/item?id=41344613 https://news.ycombinator.com/item?id=41344613
sublinear 2y ago
> Most people cant tell the difference And those people should be fired.
- deleted 2y ago
  [deleted]
- from-nibly 2y ago
  Those people are your bosses.
visarga 2y ago
> Most people cant tell the difference between an expert opinion and random words. That's because humans are stochastic parrots too. We use leaky abstractions we don't fully understand, or their edge cases. So we don't know what we are saying, but keep doing this as long as it doesn't break. When it breaks, we go to experts, another abstraction we don't really grok. What's the difference between using LLM and using a human expert? Not much if you have no clue about the topic. It's a matter of replacing real understanding with trust. Even more, can we say we understand anything down to first principles? Probably not. It's a patchwork of people, each with their limited perspective, like the Elephant and the Blind Men parable. The world is based on functional understanding, combining partial perspectives, it's never fully grokked. And what you don't understand, you can't be conscious of, not in it's real meaning. So we might be unconscious operators of language as well, no better than hallucinating LLMs.
77pt77 2y ago
Finally someone gets it. And then there is status. Since you don;t understand anything anyway, you ascertain value and correctness based on status signals. For you engineer that is going to be, first and foremost the way he looks. Whether he's tall, talks without stuttering, which school he went to. For LLMs it might be a variant of: > No one was ever fired for choosing Google/IBM/Microsoft

RodgerTheGreat 2y ago

I see deeply ominous connections between generations of American children who have been educated in a manner which produces alarming rates of functional illiteracy[0] and the widespread popularity of machine learning models that produce nonsense which resembles plausible text if you skim or don't actually read it. [0] https://www.apmreports.org/episode/2019/08/22/whats-wrong-how-schools-teach-reading https://www.apmreports.org/episode/2019/08/22/whats-wrong-ho...

treyd 2y ago
> The theory is known as "three cueing." The name comes from the notion that readers use three different kinds of information — or "cues" — to identify words as they are reading. > The theory was first proposed in 1967, when an education professor named Ken Goodman presented a paper at the annual meeting of the American Educational Research Association in New York City. > In the paper,5 Goodman rejected the idea that reading is a precise process that involves exact or detailed perception of letters or words. Instead, he argued that as people read, they make predictions about the words on the page using these three cues: > graphic cues (what do the letters tell you about what the word might be?) > syntactic cues (what kind of word could it be, for example, a noun or a verb?) > semantic cues (what word would make sense here, based on the context?) This is interesting because this is fairly similar to how LLMs do next-token prediction, but using exclusively backwards-facing clues from the text (although perhaps also the graphic cues if you are talking about multimodal models).
pixelatedindex 2y ago
Super fascinating article, thanks for sharing!
philipswood 2y ago
Thanks, I think the linked article is worthy of its own submission: https://news.ycombinator.com/item?id=41344613 https://news.ycombinator.com/item?id=41344613

sublinear 2y ago

> Most people cant tell the difference And those people should be fired.

deleted 2y ago
[deleted]
from-nibly 2y ago
Those people are your bosses.

visarga 2y ago

> Most people cant tell the difference between an expert opinion and random words. That's because humans are stochastic parrots too. We use leaky abstractions we don't fully understand, or their edge cases. So we don't know what we are saying, but keep doing this as long as it doesn't break. When it breaks, we go to experts, another abstraction we don't really grok. What's the difference between using LLM and using a human expert? Not much if you have no clue about the topic. It's a matter of replacing real understanding with trust. Even more, can we say we understand anything down to first principles? Probably not. It's a patchwork of people, each with their limited perspective, like the Elephant and the Blind Men parable. The world is based on functional understanding, combining partial perspectives, it's never fully grokked. And what you don't understand, you can't be conscious of, not in it's real meaning. So we might be unconscious operators of language as well, no better than hallucinating LLMs.

77pt77 2y ago

Finally someone gets it. And then there is status. Since you don;t understand anything anyway, you ascertain value and correctness based on status signals. For you engineer that is going to be, first and foremost the way he looks. Whether he's tall, talks without stuttering, which school he went to. For LLMs it might be a variant of: > No one was ever fired for choosing Google/IBM/Microsoft