The Generative AI Con
www.wheresyoured.at
It's been just over two years and two months since ChatGPT launched, and in that time we've seen Large Language Models (LLMs) blossom from a novel concept into one of the most craven cons of the 21st century — a cynical bubble inflated by OpenAI CEO Sam Altman built to sell

I refuse to sit here and pretend that any of this matters. OpenAI and Anthropic are not innovators, and are antithetical to the spirit of Silicon Valley. They are management consultants dressed as founders, cynical con artists raising money for products that will never exist while peddling software that destroys our planet and diverts attention and capital away from things that might solve real problems.

I’m tired of the delusion. I’m tired of being forced to take these men seriously. I’m tired of being told by the media and investors that these men are building the future when the only things they build are mediocre and expensive. There is no joy here, no mystery, no magic, no problems solved, no lives saved, and very few lives changed other than new people added to Forbes’ Midas list.

None of this is powerful, or impressive, other than in how big a con it’s become. Look at the products and the actual outputs and tell me — does any of this actually feel like the future? Isn’t it kind of weird that the big, scary threats they’ve made about how AI will take our jobs never seem to translate to an actual product? Isn’t it strange that despite all of their money and power they’re yet to make anything truly useful?

My heart darkens, albeit briefly, when I think of how cynical all of this is. Corporations building products that don’t really do much that are being sold on the idea that one day they might, peddled by reporters that want to believe their narratives — and in some cases actively champion them. The damage will be tens of thousands of people fired, long-term environmental and infrastructural chaos, and a profound depression in Silicon Valley that I believe will dwarf the dot-com bust.

And when this all falls apart — and I believe it will — there will be a very public reckoning for the tech industry.

  • Greg ClarkeEnglish
    1·
    3 hours ago

    It is the best option for certain use cases. OpenAI, Anthropic, etc sell tokens, so they have a clear incentive to promote LLM reasoning as an everything solution. LLM read is normally an inefficient use of processor cycles for most use cases. However, because LLM reasoning is so flexible, even though it’s inefficient from a cycle perspective, it is still the best option in many cases because the current alternatives are even more inefficient (from a cycle or human time perspective).

    Identifying typos in a project update is a task that LLMs can efficiently solve.

    • sem@lemmy.blahaj.zoneEnglish
      1·
      2 hours ago

      Yes I think it’s a good option for spell check, or for detecting when the word it sees seems unlikely given the context.

      For things where it’s generating text, or categorizing things, It might be the easiest option. Or currently the cheapest option. But I don’t think it’s the best option if you consider everyone involved.

      • Greg ClarkeEnglish
        1·
        2 hours ago

        But I don’t think it’s the best option if you consider everyone involved.

        Can you expand on this? Do you mean from an environmental perspective because of the resource usage, social perspective because of jobs losses, and / or other groups being disadvantaged because of limited access to these tools?