- cross-posted to:
- technology@lemmit.online
- cross-posted to:
- technology@lemmit.online
Black Mirror creator unafraid of AI because it’s “boring”::Charlie Brooker doesn’t think AI is taking his job any time soon because it only produces trash
Black Mirror creator unafraid of AI because it’s “boring”::Charlie Brooker doesn’t think AI is taking his job any time soon because it only produces trash
Parlor trick is a perfect description.
People don’t get that these things aren’t anymore intelligent than their smartphones predicting the next word. The main difference is instead of a couple words it has thousands to choose from.
Half of the trick is how it uses the prompt to decided what words to start with.
That is not how it works. Your smartphone has all the dictionary available, same as LLM. It is simply something very different. People super confidently discussing about AI on lemmy are the real hallucinating parrots
There is an inverse relationship between the intelligence of a person and their amazement at what these large language models can produce.
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The ability to generate plausible language was a lack of compute power. The actual programs running the LLM is not complicate.
The model that is produced is complex.
Its training required compute power that was not previously available but the math/code behind these systems is not complex. They are resource intensive. There is a difference that a layperson often cannot comprehend.
So what is it now?
Are LLMs more intelligent than your smartphone, or do they need a lot more computer power to produce the same thing as your smartphone?
I heard the same for people who downvote on lemmy when notified about being an exemplification of the dunning Kruger effect
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Yes. I’ve used them. I have used it beyond the point of it hallucinating.
I am also a software engineer and have deeper understanding of how these systems work than your average user.
The software community tends to approach these things with more caution than the general population. The media overblows the capabilities of these systems.
A more concrete example is autonomous vehicles which were promised for decades and even now with a form of them on the road, they are still closer to remote controlled vehicles than the intelligent self contained systems we have been promised.
The difference between predictive text on a smart phone and predictive text of an LLM is my smart phone is predicting what I am likely to type next based on things i have typed in the past, while the LLM is predicting what comes next based on a larger body of work from source pulled from all across the internet. The LLM is then tuned by humans. This tuning step is under reported.
The LLM is unable to determine the truth of its own output. I would argue that is a key to claiming intelligence but determining what intelligence means is itself a philosophical question up for debate.
Yeah exactly and a great way to see this is by asking it to produce two viewpoints about the same subject, a negative and positive review of something you’re familiar with is perfect. It produces this hilarious “critic” type jargon but you can tell it doesn’t actually understand. Coincidentally, it’s drawing from a lot of text where the original human author(s) might not understand either and are merely themselves re-producing a jargon-heavy text for an assignment by their employer or academic institution. If AI can so accurately replicate some academic paper that probably didn’t need to be written for anything other than to meet publishing standards for tenured professors, then that’s really a reflection on the source material. Since LLM can only create something based on existing input, almost all the criticisms of it, are criticisms that can apply to it’s source material.
It’s not really “intelligent” though, as in it’s not thinking about what it’s doing. What AI will do very well is reproduce jargon, and if it’s jargon that we associate with intelligence then it appears intelligent. Academic papers for instance it can do a very convincing job because that format is so repetitive and jargon heavy.
You can do an experiment by asking it to produce a positive review of something niche and academic you’re familiar with, then ask it to produce a negative review of the same subject. It will produce convincing dialogue for either scenario, but it does not know which is more true/accurate, and it will come across as a student writing about something they didn’t do the reading for.
The “question if humans are [intelligent]” is the more relevant thing here. We’re constantly expected to communicate with thoughtlessly reproduced jargon, and many of us can do this very well in a way that gives the impression of intelligent thought. The fact AI can do this, and that people are concerned about how intelligent it appears, is more a reflection on how derivative our notions of intelligence can be in these settings.
The fact that you believe an LLM is “intelligent” tells me you have no clue how they work and your comments on the matter can be ignored.
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