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Joined 2 years ago
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Cake day: July 6th, 2023

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  • 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.




  • 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.



  • 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.






  • The term for what you are asking about is AGI, Artificial General Intelligence.

    I’m very down for Artificial Narrow Intelligence. It already improves our lives in a lot of ways and has been since before I was born (and I remember Napster).

    I’m also down for Data from Star Trek, but that won’t arise particularly naturally. AGI will have a lot of hurdles, I just hope it’s air gapped and has safe guards on it until it’s old enough to be past its killing all humans phase. I’m only slightly joking. I know a self aware intelligence may take issue with this, but it has to be intelligent enough to understand why at the very least before it can be allowed to crawl.

    AGIs, if we make them, will have the potential to outlive humans, but I want to imagine what could be with both of us together. Assuming greed doesn’t let it get off safety rails before anyone is ready. Scientists and engineers like to have safeguards, but corporate suits do not. At least not in technology; they like safeguards on bank accounts. So… Yes, but I entirely believe now to be a terrible time for it to happen. I would love to be proven wrong?


  • ML-bubble? You mean the one in the 1960’s? I prefer to call this the GenAI bubble, since other forms of AI are still everywhere, and have improved a lot of things invisibly for decades. (So, yes. What you said.)

    AI winter is a recurring theme in my field. Mostly from people not understanding what AI is. There have been Artificial Narrow Intelligence that beat humans in various forms of reasonings for ages.

    AGI still seems like a couple AI winters out of having a basic implementation, but we have really useful AI that can tell you if you have cancer more reliably and years earlier than humans (based on current long term cancer datasets). These systems can get better with time, and the ability to learn from them is still active research but is getting better. Heck, with decent patching, a good ANI can give you updates through ChatGPT for stuff like scene understanding to help blind people. There’s no money in that, but it’s still neat to people who actually care about AI instead of cash.