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Joined 1 year ago
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Cake day: July 25th, 2023

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  • Perhaps we’re talking to different points. Parent comment said that investors are always looking for better and better returns. You said that’s how progress works. This sentiment is was my quibble.

    I took the “investors are always looking for better returns” to mean “unethically so” and was more talking about what happens long term. Reading your above I think you might have been talking about good faith.

    In a sound system that’s how things work, sure! The company gets investment into tech and continue to improve and the investors get to enjoy the progress’s returns.


  • You’re conflating creating dollar value with progress. Yes the technology moves the total net productivity of humankind forward.

    Investing exists because we want to incentive that. Currently you and the thread above are describing bad actors coming in, seeing this small single digit productivity increase and misrepresenting it so that other investors buy in. Then dipping and causing the bubble to burst.

    Something isn’t a ‘good’ investment just because it makes you 600% return. I could go rob someone if I wanted that return. Hell even if then killed that person by accident the net negative to human productivity would be less.

    These bubbles unsettle homes, jobs, markets, and educations. Inefficiency that makes money for anyone in the stock market should have been crushed out.


  • I don’t disagree with everything you said but wanted to just weigh in on the more degrees of freedom.

    One major thing to consider is that unless we have 24/7 sensor recording with AI out in the real world and a continuous monitoring of sensor/equipment health, we’re not going to have the “real” data that the AI triggered on.

    Version and model updates will also likely continue to cause drift unless managed through some sort of central distribution service.

    Any large Corp will have this organization and review or are in the process of figuring it out. Small NFT/Crypto bros that jump to AI will not.

    IMO the space will either head towards larger AI ensembles that tries to understand where an exact rubric is applied vs more AGI human reasoning. Or we’ll have to rethink the nuances of our train test and how humans use language to interact with others vs understand the world (we all speak the same language as someone else but there’s still a ton of inefficiency)








  • I haven’t been in decision analytics for a while (and people smarter than I are working on the problem) but I meant more along the lines of the “model collapse” issue. Just because a human gives a thumbs up or down doesn’t make it human written training data to be fed back. Eventually the stuff it outputs becomes “most likely prompt response that this user will thumbs up and accept”. (Note: I’m assuming the thumbs up or down have been pulled back into model feedback).

    Per my understanding that’s not going to remove the core issue which is this:

    Any sort of AI detection arms race is doomed. There is ALWAYS new ‘real’ video for training and even if GANs are a bit outmoded, the core concept of using synthetically generated content to train is a hot thing right now. Technically whomever creates a fake video(s) to train would have a bigger training set than the checkers.

    Since we see model collapse when we feed too much of this back to the model we’re in a bit of an odd place.

    We’ve not even had a LLM available for the entire year but we’re already having trouble distinguishing.

    Making waffles so I only did a light google but I don’t really think chatgpt is leveraging GANs for it’s main algos, simply that the GAN concept could be applied easily to LLM text to further make delineation hard.

    We’re probably going to need a lot more tests and interviews on critical reasoning and logic skills. Which is probably how it should have been but it’ll be weird as that happens.

    sorry if grammar is fuckt - waffles