• 10 Posts
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Joined 1 year ago
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Cake day: July 4th, 2023

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  • Yeah, I agree. And I appreciate your perspective.

    I don’t think growing Lemmy and funnelling in users works out. We don’t grow. We’re somewhere between 40k and 50k active users and there is no trend in either direction.

    Last year, I despised beehaw for doing their own thing and not respecting how federation is supposed to work. That is connecting people and not being a patchwork of small spaces that don’t talk to each other because of small minds/perspectives… I think I changed my mind a bit. Their way of doing things turned out to foster better behaviour than on other instances. It’s still detrimental to the idea of a federated platform, but still… The effects aren’t just negative.

    I think we have lots of issues here. The culture is a bit different from what I’d like it to be. It’s a tiny bit above Reddit in atmosphere, but on the downside it lacks the (niche) experts. It’s more average people here and just the most predominant opinions. Furthermore, it’s too much discussing the news and not much else that’d be meaningful for my life. It’s too small for lots of things that this place could excel in and that you won’t find anywhere else.

    And the technology really isn’t that good. Progress is super slow, they don’t implement the things the users need and wish for. And it doesn’t foster growth or nice behaviour.

    And I think that’s the main issue. We’d need a solid basis to build something upon. It needs to be shiny, have excellent moderation tools and user-facing features. All of this has been requested but except for things like instance blocking by the user, that doesn’t even block their users, we didn’t get much.

    My personal wish is that new approaches like PieFed will go ahead and provide that to us. I think I’d like to host an instance with that and then invite some people. As of now I didn’t advertise for Lemmy because I think neither the software, nor the atmosphere/community, nor the content here is worth convincing anyone to join. At this point I’m just waiting for one of the three to get anywhere. But I think I’d also like to defederate from a few people. And force them to be nice, upvote replies, not just dump any random links but provide some text in a post, and have some niche interest communities, because just dumping links to news and posting memes isn’t cutting it. We already have X and Mastodon for that…

    And a little disclaimer: I’m being negative in this comment. But that’s not all there is to it. There is a reason why I’m here. I regularly have nice interactions, learn new things and have good conversations. It’s just that it’s far between and I see lots of potential for more. And I’d really like that to become reality.



  • I think most people use something like exllamav2 or vllm or use GGUF to do inference and it seems neither of those projects have properly implemented multimodality or this specific model architecture, yet.

    You might just be at the forefront of things and there isn’t yet any beaten path you could follow.

    The easiest thing you could do is just use something that already exists, be it 4bit models, wait a few weeks and then upgrade. And I mean you can also always quantize models yourself and set the parameters however you like, if you have some inference framework that supports your model including the adapters for vision and has the quantization levels you’re interested in…


  • Well, I’d say there is information in language. That’s kinda the point of it and why we use it. And language is powerful. We can describe and talk about a lot of things. (And it’s an interesting question what can not be described with language.)

    I don’t think the stochastical parrot thing is a proper debate. It’s just that lots of people don’t know what AI is and what it can and cannot do. And it’s neither easy to understand nor are the consequences always that obvious.

    Training LLMs involves some clever trickery, limit their size etc so they can’t just memorize everything, but instead are forced to learn concepts behind those texts.

    I think they form models of the world inside of them. At least of things they’ve learned from the dataset. That’s why they can for example translate text. They have some concept of a cat stored inside of them and can apply that to a different language that uses entirely different characters to name that animal.

    I wouldn’t say they are “tools to learn more aspects about nature”. They aren’t a sensor or something. And they can infer things, but not ‘measure’ things like an X-ray.






  • I’m pretty sure he did this out of this own motivation because he thinks/thought it’s a fascinating topic. So, sure this doesn’t align with popularity. But it’s remarkable anyways, you’re right. And I always like to watch the progression. As far as I remember the early videos lacked professional audio and video standards that are nowadays the norm on Youtube. At some point he must have bought better equipment, but his content has been compelling since the start of his Youtube ‘career’. 😊

    And I quite like the science content on Youtube. There are lots of people making really good videos, both from professional video producers and also from scientists (or hobbyists) who just share their insight and interesting perspective.




  • Yeah, doesn’t really work. I mean it has a rough idea of that it needs to go east. And I’m surprised that it knows which interstates are in an area and a few street names in the cities. I’m really surprised. But I told it to get me from Houston to Montgomery as in your example. And in Houston it just tells random street names that aren’t even connected and in different parts of the city. Then it drives north on the I-45 and somehow ends up in the south on the I-610-E and finally the I-10-E. But then it makes up some shit, somehow drives to New Orleans, then a bit back and zig-zags it’s way back onto the I-10. Then some more instructions I didn’t fact check and it gets that it needs to go through Mobile and then north on the I-65.

    I’ve tested ChatGPT on Germany. And it also gets which Autobahn is connected to the next. It still does occasional zig-zags and in between it likes to do an entire loop of 50km (30 miles) that ends up 2 cities back where it came from… Drives east again and on the second try takes a different exit.

    However: I’m really surprised by the level of spatial awareness. I wouldn’t have expected it to come up with mostly correct cardinal directions and interstates that are actually connected and run through the mentioned cities. And like cities in between.

    I don’t think I need to try “phi”. Small models have very limited knowledge stored inside of them. They’re too small to remember lots of things.

    So, you were right. Consider me impressed. But I don’t think there is a real-world application for this unless your car has a teleporter built in to deal with the inconsistencies.