Curtis "Ovid" Poe (he/him)

@earthquake You’re correct that projecting agency to the LLM is problematic, but in doing so, we get better quality results. I’ve argued that we need new words for LLMs instead of “think,” “understand,” “learn,” etc. We’re anthropomorphizing them and this makes people less critical and gradually shifts their attitudes in incorrect directions.

Unfortunately, I don’t think we’ll ever develop new words which more accurately reflect what is going on.

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@zogwarg

Consider traditional databases which let you search for strings. Vector databases let you search the meaning.

For one client, someone could search for “videos about cats”. With stemming and stop words, that becomes “cat” and the results might be lists of videos about house cats and maybe the unix “cat” command. Tigers, lions, cheetahs? Nope.

Vector database will return tigers/lions/cheetahs because it “knows” they are cats. A much smarter search. I’ve built that for a client.

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@froztbyte As for the issue of transparency, it’s ridiculously hard in real life. For example, for my website, I used a format I created called “blogdown”, which is Markdown combined with a template language to make it easy to write articles. I never cited my sources, nor do I think I could. From decades of programming, how can I cite everything I’ve ever learned from?

As for how AI is transparent for arriving at decisions, this falls into a separate category and requires different thinking.

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@froztbyte Yeah, having in-depth discussions are hard with Mastodon. I keep wanting to write a long post about this topic. For me, the big issues are environmental, bias, and ethics.

Transparency is different. I see it in two categories: how it made its decisions and where it got its data. Both are hard problems and I don’t want to deny them. I just like to push back on the idea that AI is not providing value. 😃

@zogwarg OK, my grammar may have been awkward, but you know what I meant.

Meanwhile, those of us working with AI and providing real value will continue to do so.

I wish people would start focusing on the REAL problems with AI and not keep pretending it’s just a Markov Chain on steroids.

@froztbyte Given that I am currently working with GenAI every day and have been for a while, I’m going to have to disagree with you about “failed to deliver on promises” and “worthless.”

There are definitely serious problems with GenAI, but actually being useful isn’t one of them.

@bitofhope Absolutely agree, but this is where technology is evolving and we have to learn to adapt or not. Since it’s not going away, I’m not sure that not adapting is the best strategy.

And I say the above with full awareness that it’s a rubbish response.

@FRACTRANS @gerikson

Nice job! This is a fairly common trick with AI. In traditional programming, there’s a clear separation between code and data. That’s not the case for GenAI, so these kinds of hacks have worked all over the place.