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CEO Pleads With AI Industry to Stop Charging So Much to Replace Human Labor (finance.yahoo.com)
submitted 2 months ago by to c/fuck_ai@lemmy.world
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Speaking during an interview on CNBC's "Squawk on the Street" segment earlier this week, CEO of cybersecurity giant Palo Alto Networks Nikesh Arora implored the tech industry to lower the cost of AI.

During the segment, the chief executive argued that the cost to use large language models (LLMs) has to drop by 20 percent by 2027 — and 90 percent by 2028 — for the tech to be useful to enterprises.

"We need to see the pricing for AI come down," Arora said.

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[–] 5 points 2 months ago (3 children)

oh yea only if the hallucination sources from veribel fact sources, like legitimate research papers, official medical/govt,,,etc sites. but most of the time its REDDIT, blogs, or other forums.

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  • [–] 10 points 2 months ago (2 children)

    No. You are making a mistake. Here are two sentences.

    The orange tree is a tall plant that produces sweet fruits. The giraffe is a tall animal that eats sweet fruits.

    These are both true statements. But using statistical generation I could easily, from these, generate "The orange tree is a tall animal that eats sweet fruits."

    EVERYTHING that comes from an LLM, no matter how it is trained, is hallucinatory. NO EXCEPTIONS. The more often that the statistics match reality, the more likely it is that it will match reality, but even if 100% of the input is factual there is always a path in the stochastic generation that will yield (highly fluent) garbage.

    Also, remember that Piltdown Man was written about as a real thing in the scientific journal Nature...

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  • [–] 7 points 2 months ago

    I think that it's more simple to just say that LLMs are highy advanced electronic parrots - they put sentences together out of sentences that they've been exposed to before, the more often they've been exposed to them the more likely they'll produced it.

    LLMs and Parrots are both just copying stuff without understanding it, it's just that the LLM has a very deep multi-level mathematical engine to find correlations between words and even between word assemblies of various sizes, all in much larger windows of text (literally within tens of tousands and even hundreds of thousands of words) whilst the Parrot's "correlation detection" isn't mathematically strict or all that deep or wide (about enough to output "Polly wants a cracker" if they hear the word "cracker").

    Curiously, of both the Parrot is the one which actually has some cognition (i.e. they think), whilst the LLM is a purelly statistical engine.

    IMHO the whole use of "hallucination" just muddles the waters because when we hear the word "hallucination" we think the human version of it (seeing that which isn't there) which makes us think of human cognition because it's generally a cognitive problem, whilst the LLM hallucination is something very different - producing a seemingly truthful piece of text which is in fact not truthful.

    LLMs don't hallucinate in the traditional sense of the word because as unthinking statistical text analysis and production engines they have no cognition to malfunction in that way.

    So in a way by using the word "hallucination" for LLMs we are indirectly supporting in people's minds the false idea that LLMs have cognition.

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