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Joined 2 years ago
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Cake day: April 23rd, 2023

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  • You’re entirely correct, but in theory they can give it a pretty good go, it just requires a lot more computation, developer time, and non-LLM data structures than these companies are willing to spend money on. For any single query, they’d have to get dozens if not hundreds of separate responses from additional LLM instances spun up on the side, many of which would be customized for specific subjects, as well as specialty engines such as Wolfram Alpha for anything directly requiring math.

    LLMs in such a system would be used only as modules in a handcrafted algorithm, modules which do exactly what they’re good at in a way that is useful. To give an example, if you pass a specific context to an LLM with the right format of instructions, and then ask it a yes-or-no question, even very small and lightweight models often give the same answer a human would. Like this, human-readable text can be converted into binary switches for an algorithmic state machine with thousands of branches of pre-written logic.

    Not only would this probably use an even more insane amount of electricity than the current approach of “build a huge LLM and let it handle everything directly”, it would take much longer to generate responses to novel queries.




  • Webtoon is still shitty in other ways. When they adapt a property, they want it their way, regardless of the author’s original vision. I’ve seen several stories that originated on Royal Road get Webtoon adaptations, and the adaptations always seem to change or leave out important parts of the story, making characters look stupid or just completely replacing entire sets of characters, forcing the story to diverge substantially when inevitably something they got rid of turns out to have been critically important to where the author was taking things. They turn great stories into middling slop every single time.







  • OP is absolutely mistaken that it’s somehow ableist to stick to a meeting deadline or similar “punishment” for lateness, and t3rmit3 has said why much more eloquently than I could. However, you’ve said something that I can’t let pass without a rebuttal.

    perpetual lateness means someone values their time more than they do the commitment and the time of others. period.
    […]
    perpetual lateness, though, is a statement, that individual could not give a shit what others needs and responsibilities are

    This is making a moral judgment on what you believe is in someone’s mind, and your judgment is based on a false premise. There exists an extremely common mental disorder (so common that some might consider it a form of neurodivergence) that when left untreated makes it much harder to do the things you want and are obligated to do. It’s harder to start doing things, it’s harder to stop, it’s harder to focus yet too easy to focus, it’s harder to remember important things, and it’s harder to motivate yourself to do anything you aren’t doing at any given moment, and anything you have to put effort into motivating yourself to do leaves you with less mental energy to do anything else in that category.

    The one thing that can usually overcome all of these mental blocks is panic - when you’re actually out of time and Consequences are approaching if you don’t do something RIGHT NOW then you can finally do what you need to do and get something done - later than you wanted, worse than you wanted, more mentally drained, and with plenty of reasons to beat yourself up over it, not that it helps if you do. This is the reason behind why most people show up perpetually late. They might not let the emotional turmoil show, but if they’re consistently a few minutes late for everything, I can just about promise it’s not because they don’t care.

    People who have this disorder and receive prescription medication for it often describe the first dose as like receiving superpowers. The idea that they can decide they want to do something, and then just go do it? Without thinking about it? No buildup? No psyching yourself into it? No roundabout coping strategies? No reorganizing the entire structure of your life to make it happen? No bargaining with the goddamn monkey in your brain that almost never lets you do the rational thing? Wait, normal people don’t have the monkey? They live like this every day, without any expensive pills? Impossible. It couldn’t be that simple. Do they have any idea how lucky they are?

    Your misplaced sense of moral superiority is unfortunately quite common, but it’s not going to help these people, it’s going to hurt them. If it’s affecting their life, and it often is, they need treatment and training in how their brain works, not to be told they’re a piece of shit who doesn’t care about others and are choosing to inconvenience everyone else in their life including themselves. That’s only going to put them in a worse place.


  • Router-level VPN is going to be more difficult to configure and cause more problems than just having it on all your devices. There are some games where online play just refuses to work if connecting through a VPN. Some mobile apps are the same. When a website blocks your currently selected server, and the usual solution is switching to another server, that’s going to be more difficult and more tedious when it’s configured at the router level. In addition, if you do something like using a self-hosted VPN in order to connect remotely to a media server on your home network, that becomes more difficult if your home router is on a different VPN.

    If you’re trying to keep local devices in the building from phoning home and being tracked, a PiHole or router-level firewall might be a better solution. I think if you’re running a pfsense or opnsense router and are a dab hand with VLANs then maybe you could get what you’re looking for with router-level VPN, but it’s a huge hassle otherwise. Just put Mullvad on your computers and phones and call it a day.


  • Unfortunately I can’t even test Llama 3.1 in Alpaca because it refuses to download, showing some error message with the important bits cut off.

    That said, the Alpaca download interface seems much more robust, allowing me to select a model and then select any version of it for download, not just apparently picking whatever version it thinks I should use. That’s an improvement for sure. On GPT4All I basically have to download the model manually if I want one that’s not the default, and when I do that there’s a decent chance it doesn’t run on GPU.

    However, GPT4All allows me to plainly see how I can edit the system prompt and many other parameters the model is run with, and even configure multiple sets of parameters for the same model. That allows me to effectively pre-configure a model in much more creative ways, such as programming it to be a specific character with a specific background and mindset. I can get the Mistral model from earlier to act like anything from a very curt and emotionally neutral virtual intelligence named Jarvis to a grumpy fantasy monster whose behavior is transcribed by a narrator. GPT4All can even present an API endpoint to localhost for other programs to use.

    Alpaca seems to have some degree of model customization, but I can’t tell how well it compares, probably because I’m not familiar with using ollama and I don’t feel like tinkering with it since it doesn’t want to use my GPU. The one thing I can see that’s better in it is the use of multiple models at the same time; right now GPT4All will unload one model before it loads another.


  • I have a fairly substantial 16gb AMD GPU, and when I load in Llama 3.1 8B Instruct 128k (Q4_0), it gives me about 12 tokens per second. That’s reasonably fast enough for me, but only 50% faster than CPU (which I test by loading mlabonne’s abliterated Q4_K_M version, which runs on CPU in GPT4All, though I have no idea if that’s actually meant to be comparable in performance).

    Then I load in Nous Hermes 2 Mistral 7B DPO (also Q4_0) and it blazes through at 50+ tokens per second. So I don’t really know what’s going on there. Seems like performance varies a lot from model to model, but I don’t know enough to speculate why. I can’t even try Gemma2 models, GPT4All just crashes with them. I should probably test Alpaca to see if these perform any different there…