Poik

Hm. I speak like a bot, do I? Maybe I am autistic after all.

I am aware, my boyfriend and I have already had this conversation, but I guess he's not on Lemmy, so you can't ask him.

Yes, DeepSeek caused a drop in the stock price, but you were saying that believing that LLM's are over-hyped would lead to having insider knowledge and could give us an advantage in the stock market. Particularly with their already tanked stock. However, the stock market fluctuates based on hype, not value, and will do whatever the fuck it pleases, so the only way to have insider knowledge is by being on a board who controls the price or by managing to dump hype into the system. That is not something a lot of people have the power to do individually.

But since you think I'm a bot and I have no way to disprove that thanks to what the world is now, I bid you adieu. I hope you're having a good one. And stop antagonizing people for talking differently, please.

Edit: I took a look at your recent comment history, and you do come off as trying to troll and be disingenuous. If you want to have a less inflammatory conversation, you can DM me, but I do recommend you tone it down. You're not helping anyone with how you're approaching this, buddy.

I'm glad we agree. I don't know how much mental energy we should devote to these things, but I guess I'm happy to see discussion on this platform. I kind of miss the days when I had to respond to people who watched I, Robot and think I'm trying to destroy humanity, instead of... I don't know what to call this except basically the same thing they did in the 60's before the first AI winter, but with more drastic consequences.

But also, you were talking about Nvidia in your comment I responded to, not Deepseek, so your rebuttal is non sequitur...

Actually no. As someone who prefers academic work, I very heavily prefer Deepseek to OpenAI. But neither are open. They have open weights and open source interpreters, but datasets need to be documented. If it's not reproducible, it's not open source. At least in my eyes. And without training data, or details on how to collect it, it isn't reproducible.

You're right. I don't like big tech. I want to do research without being accused of trying to destroy the world again.

And how is Deepseek over-hyped? It's an LLM. LLM's cannot reason, but they're very good at producing statistically likely language generation which can sound like its training data enough to gaslight, but not actually develop. They're great tools, but the application is wrong. Multi domain systems that use expert systems with LLM front ends to provide easy to interpret results is a much better way to do things, and Deepseek may help people creating expert systems (whether AI or not) make better front ends. This is in fact huge. But it's not the silver bullet tech bros and popsci mags think it is.

... Statistical engines are older than personal computers, with the first statistical package developed in 1957. And AI professionals would have called them trained models. The interpreter is code, the weights are not. We have had terms for these things for ages.

That... Doesn't align with years of research. Data is king. As someone who specifically studies long tail distributions and few-shot learning (before succumbing to long COVID, sorry if my response is a bit scattered), throwing more data at a problem always improves it more than the method. And the method can be simplified only with more data. Outside of some neat tricks that modern deep learning has decided is hogwash and "classical" at least, but most of those don't scale enough for what is being looked at.

Also, datasets inherently impose bias upon networks, and it's easier to create adversarial examples that fool two networks trained on the same data than the same network twice freshly trained on different data.

Sharing metadata and acquisition methods is important and should be the gold standard. Sharing network methods is also important, but that's kind of the silver standard just because most modern state of the art models differ so minutely from each other in performance nowadays.

Open source as a term should require both. This was the standard in the academic community before tech bros started running their mouths, and should be the standard once they leave us alone.

Because over-hyped nonsense is what the stock market craves... That's how this works. That's how all of this works.

My career is AI. It is over hyped and what the tech bros say is nonsense. AI models are not source, they are artifacts, which can be used by other source to run inference, but they themselves are not source, and anyone who says they are don't know what code is.

These days? Definitely made sense to me even back when I redditted. I am submissive to catsbeingjerks, hmmm, and Noita.

X-Com? Is that you?

I guess X-Ray Vision? Yeah. It's a stretch.

As someone who has professionally done legal reverse engineering. No. No it isn't.

The security you get through vetting your code is invaluable. Closing off things makes it more likely for things to not be caught by good actors, and thus not fixed and taken advantage of by bad actors.

And obscurity does nothing to stop bad actors, if there's money to be had. It will temporarily stop script kiddies though. Until the exploit finds it's easy into their suite of exploits that no one's fixed yet.