And how much do they cost? And how do you like them?

  • 31337
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    11 months ago

    I use ChatGPT premium almost every day, mostly for coding, rarely for image generation. $20/month. It can write/refactor decent (not great) code faster than me if I can type out what I want faster than just writing the code myself. Dalle-3 through ChatGPT produces pretty good images and seems to understand the prompts better than SD (ChatGPT actually writes the prompt for you, so that might have something to do with it). It’s much better than Dalle-2, but they’ve put guardrails on it so you can’t ask to do things like create images in the style of a modern artist.

    I’ve messed around with Automatic1111 and SD a little bit. ControlNet is very nice for when you need to have control over the output. I would draw shitty outlines with Inkscape then used SD+ControlNet to kind of fill everything else in. Free and open source model and software. Ran it on a RTX 3090 which costed me $800 a year ago.

    Messed around with DeepFloyd IF on replicate.ai for a while, which was very nice. It seemed to understand the prompts much better than SD. I think it was $2/hr, with each image generation using something like 30s of GPU time. Cold starts can take minutes though, which is annoying.

    I use OpenAI’s API in a prototype application; both GPT-4 and Dalle-3. GPT-4 is by far the most well-behaved and “knowledgeable” LLM, but all the guardrails put on it can be annoying. Dalle-3 is pretty good, but not sure if it’s the best. The cost isn’t significant yet while prototyping.

    I get ads, news, and video recommendations served to me which probably uses some kind multi-armed bandit AI algorithm. Costs me my privacy. I don’t like it; I rate it 0/10.

    • DominusOfMegadeusOP
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      11 months ago

      I’m actually really curious to see how the 10 core GPU on my M2 Mac Mini performs.

      • 31337
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        11 months ago

        I haven’t tried using Macs. I’ve heard their GPUs are kinda slow (compared to high-end discrete GPU), but have unified memory so you can run very large models.

        I bought 3090s because I needed to train a classifier. It took months of training 24/7, so it was cheaper to buy 3090s than pay for cloud compute time. A 3090 is probably overkill for just running SDXL (unless they release an even larger model in the future).