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I am here with Dan. Hey, and what do you do for the company here?

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I'm the infrastructure and technical specialist these days. I pretty much just write documentation

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Sounds good. Sounds good. So I'm just asking everyone here at the company what the thoughts on AI is the current state of it

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So I'll ask you first. Sure thoughts on the currency of AI. It's pretty interesting

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there's a lot of cool stuff going on and I'm excited to see it kind of develop over the next I guess a year or a few months even

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So you talk kind of sound like you're for AI more than against AI

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Yeah, I would probably say my thoughts on it are a little bit mixed

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I think it's not maybe as terrifying as people think it is but yeah, certainly certainly for it

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Sounds good. Sounds good. So if you're for it, then what's one thing you're really against in terms of the state of AI at the moment?

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I think probably some of the protectionism. I mean

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Looking at some of the requirements for doing these trainings

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You're spending millions of dollars on like cloud infrastructure GPU time just to actually create a

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reasonable model and so People I think are willing to protect that rather than just open sourcing it and letting any other company who has access to these massive data centers

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Like get in there, right? Okay, okay So have you used any AI currently like that where it's like they have chat GBT the image random readers music

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Have you use any of it? Yeah, I've played with pretty much all of them and I actually run a couple at home

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So I run an LLM as well as stable diffusion for image generation and I run those locally

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I recently just bought a couple more 30 90s and you know upgraded some of them with VRAM so that I could try some of the larger models

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So they're like a chat GBT for

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But you can only talk to them for like I don't know

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Two to five minutes before the like token inference length gets too much and it takes like a minute to respond to you

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But initially they're they're really quite powerful And they're a little bit more entertaining because they're the uncensored varieties. So what do you mean by that?

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So, you know, you say something to chat GBT for and it goes as a large language model

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I can't respond to this the uncensored one the uncensored ones are kind of designed as

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training bed for censorship and so you can kind of get it to talk about whatever you want or

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You know, sometimes chat GBT for will

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Catch things that it thinks are offensive and it isn't

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I have some people have told me some stuff internally

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That they use chat GBT for to have like difficult conversations about difficult topics and practice talking to actual people

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about these difficult subjects and Initially GPT 3 was kind of okay to talk about these

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but GPT 4 just won't even broach these subjects that are kind of like

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You know, they're they're hard to talk about is it cuz like they're trying to market it. I guess I'm assuming or yeah

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I was probably a marketing thing. There's also a liability thing probably

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You know people like to post what they talk about and then of course you also have like

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Really negative sentiment and things like that and also you can ask it dangerous things and get it to tell you dangerous information

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and so it's really kind of Scary in that way and I think as these companies are large and have a lot of money invested in these it's a little bit

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Be a difficult for them to allow that kind of like unfiltered information because they are so

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Confident at all the time. They just will a hundred percent confidence in what they're saying

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Even if they don't know what they're saying and that I think can be really dangerous

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A lot of people don't understand that it's fake information a lot of the time

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Another cool thing about running them locally is that you get to like mess with their brain a little bit

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So you can adjust the level of inference and the level of like token following guys called config scale or sorry configuration scale and

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You can make it those just be like

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Kind of insane if you go too far you can get into something called hallucinations where

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The inference models like feedback into themselves and it just says like random garbage

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That's can be really quite funny and and interesting. Yeah, it's neat watching them tick like that

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Okay, so you use it on a person level, but do you think as a tech slash crave company? We should be using AI on any capacity

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I actually did some training for us. I did a fine tune of chat GPT for

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We were trying to get it to write our with a hell of a cult showcase scripts

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Which are pretty boring and basic videos where a brand will be like

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Write a sponsored segment about our product and here's a bunch of

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Specifications and then we kind of have to turn that into a script and it's not very creative and it's not very fun

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So I made a data set from about 50 of these scripts

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You know because you have to you have to set a Prompt and a response so the prompt was like here's all the data and specifications on the brand and the response is our script

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right and So I went this data set

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I did a quick fine tune and it wasn't performing very well because the minimum data that you need for one of these types of fine

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tunes is 500 Right, so 500 scripts our LTT's we have about 5,000

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so that would be a reasonable data set to feed into a fine tune, but

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you know LTT's are special and You know there they wouldn't really work

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But these showcase scripts are pretty

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Boiler play Unfortunately, I was told after I asked for the other

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450 scripts that we have only ever done 50 of them so that project

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Through It was a it was a waste of a couple days of data compilation

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But did you learn a lot like what to do what not to do kind of thing? Yeah. Yeah, I learned a lot about how fine tunes function and

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You know, there's there's also a lot of issues with model overfitting

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So you can you can train a model too much and then it can only do

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One thing and that's kind of a dangerous balance to and so you know if you feed in that 50 data set and you like

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You really try to make it Do that 50 data set then you'll just get garbage because it's over fit

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And if you try to go anywhere outside of that entire limited data set like if you train on an LLM on

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100,000 pictures of dogs and their only face on

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Then you ask it to do a side-on picture of a dog and it can't because it's over fit for like front-facing dogs

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Or if you ask it to make a cat it can't do that like we couldn't feed in 50 showcase scripts

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Or 5,000 showcase scripts and then have it make an LTT because it would just make showcase scripts

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Sorry, so we should Didn't use it for a company or

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Well, I mean this is kind of the problem and this is something that I've realized more

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playing with them at home and getting it to let it spend a lot of time with them that you wouldn't be able to do with like a

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Chat GPT-4 or one of these web things because I'm sending like a hundred thousand or two hundred thousand tokens through

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These platforms and that would cost me like a five hundred dollars a day to actually get to play with them

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But I think even more now. I'm more convinced that they are just tools

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I know some artists friends of mine have been concerned about them

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but what I've noticed is that Because these LLMs and the image diffusion models are trained on massive quantities of data

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the Massive quantities of data that they have are like the most generic pictures

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Right there the generic pictures. There are single sort of style of picture

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there are sort of a You know, it's it's one thing and so I think at least for artists what's gonna happen is maybe there'll be less of a demand for

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This basic art, you know, I want, you know a pin-up of a girl or I want a scene of a mountain that sort of thing

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You know, there's already a massive quantity of art out there that has those and you can use a diffusion model to create that kind of

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Either like a background or like I want a space station and then you have a space station

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but a student is to start getting to like weirder things or like more niche things or

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more unique things like I Don't know a mountain that's upside down, but in a space station that sort of thing a language model and

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and Diffusion model might like start to struggle with that because there's never been any data on that and it can only smush

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Different data points together so well and I do expect it to get better

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But it's also really difficult to prompt those That kind of creativity

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However, saying that you can use diffusion models as a tool

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So I know some artists who use them to create characters or like you want to do D&D art that sort of thing

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Or you need inspiration Or you would like, you know, 500 different dynamic poses that feature

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You know, like a ballet dancer or something like that. I want 500 ballet poses so that I can

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Get an immediate mood board as inspiration to do my own drawings or my own digital art or you know, even analog art, right?

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I think The same can kind of be said for the LLMs

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the large language models because they

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They spit out text, but you can't really have a conversation with them for very long

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Their brains don't work. I think that there's some

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There's some like papers out right now and there's also some

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Like prize pools if you can get it to go over like a hundred thousand token

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Inference length so like a history so you could have a conversation with it

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that would be about the length of Lord of the Rings and it would be able to remember and

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Make reference to anything in that entire block of text, right? That's kind of the that's the goal

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Right, you can you can actually have real conversations with them for a long time

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the The local models also support characters

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So I'm trying to create a D&D character for a friend of mine so that he can actually have a

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Conversation with the character and you do that with a bunch of different prompts and things like that

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There's already a bunch of like web stuff that you can do online

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Like a lot of people have already like taken this and go like D&D. We can do that on the internet hell

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Yeah, and so these are available like through web portals and stuff like that, but running them at home is fun

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So, yeah, that's a long-winded answer. I don't remember where the question was. I'm sorry. I'll go

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Should we use them should we use them? I think using them as a tool is fine

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I think there's no danger in them like replacing people

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But they're gonna work with people and there's no there's no escape from that now that genie is out of the bottle forever

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All right, all right We talked a lot, but is there anything that we haven't said that you like to say to the float planers?

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I was what is this video about? I'm sorry

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It's just like I just want to get people's thoughts on AI because you know We are a tech slash creative company, which I think aligns with both with AI

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So it's like I think people have some opinions and I think it's good to share. Yeah

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Try it at home. It's fun at home. It's a fun little exercise. It's really really simple to get going and

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It's it's a fun little break playground and you don't have to like

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Spend money on chat GPT. I mean chat GPT is still the best, but if you play with it at home, you're yours

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You can play with it as much as you want. Yeah. All right, Dan. Thanks for any of you. I'm still sweaty. It's hot

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Thank you