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Joined 1 year ago
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Cake day: September 25th, 2023

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  • FWIW I did try a lot (LLMs, code, generative AI for images, 3D models) in a lot of ways (CLI, Web based, chat bot) both locally and using APIs.

    I don’t use any on a daily basis. I find it exciting that we can theoretically do a lot “more” automatically but… so far the results have not been worth the efforts. Sadly some of the best use cases are exactly what you highlighted, i.e low effort engagement for spam. Overall I find that either working with a professional (script writer, 3D modeler, dev, designer, etc) is a lot more rewarding but also more efficient which itself makes it cheaper.

    For use cases where customization helps while quality does matter much due to scale, i.e spam, then LLMs and related tools are amazing.

    PS: I’d love to hear the opinion of a spammer actually, maybe they also think it’s not that efficient either.














  • I agree but I don’t watch TV so I don’t bother. Yet… I still hate product placement so I might be interested in such a solution. Anyway here is how I would do it :

    • evaluate what exists, e.g SponsorBlock, and see what’s the closest that fit my need, try it, ask in forum or repository issues if modifications are possible
    • gather videos of the typically problematic content, say few hours to start
    • annotate them by adding the time stamps then the location on the image
    • replace problematic content with gradually complex solutions, e.g black, average color of the area, denoising (quite compute intensive)
    • honestly evaluate the result
    • consider the biggest problem, e.g here on first pass fixed content so a detector based on machine learning for the type of content could help
    • iterate, sharing my result back with the closest interested community

    Honestly it’s a worthwhile endeavor but be mindful it’s an arm race. There are a LOT of smart people paid to add ads everywhere… but there are even more people, like you and I, eager to remove them. IMHO the key trick is, like SponsorBlock, to federate the efforts.


  • Right, and I mentioned CUDA earlier as one of the reason of their success, so it’s definitely something important. Clients might be interested in e.g Google TPU, startups like Etched, Tenstorrent, Groq, Cerebras Systems or heck even design their own but are probably limited by their current stack relying on CUDA. I imagine though that if backlog do keep on existing there will be abstraction libraries, at least for the most popular ones e.g TensorFlow, JAX or PyTorch, simply because the cost of waiting is too high.

    Anyway what I meant isn’t about hardware or software but rather ROI, namely when Goldman Sachs and others issue analyst report saying that the promise itself isn’t up to par with actual usage for paying customers.



  • I’m not sure if you played PCVR in the Summer but imagine that in a tiny room… it’s just way too hot. Again I’m NOT saying it’s good, or bad, I’m only saying you made assumption about OP usage. I’m not sure if you tried CloudXR but basically, it works and it’s not that complex to setup (e.g 1h) so it’s relatively faster and cheaper than building and owning a gaming PC.

    I don’t understand why you are even arguing about a legitimate usage.



  • Can’t help but wonder what has been the impact of the support, e.g through subsidies, for automaker industry both nationally and internationally.

    We keep on hearing that it’s a huge industry, that it “creates” lots of jobs, that people buy cars from their own country as a form or pride, etc. I bet some of it is true but I also bet the negative impact is not communicated as clearly. Any research on the topic? I imagine it might highlight precisely how the EV transition (which in itself is also problematic due to car usage, battery recycling, etc) has been radically slow down, maybe also public transport usage, CO2 emission, etc. Anyway I’d love to read a paper on the topic.