101–110 of 176 posts
We should think of something like a blockchain to mark all this sh*t as fake though, because in five years time there will be no way to distinguish reality from invention and we will all be under constant blackmail from malicious agents and rogue governments showing up at our door with whatever made-up accusation they want.
> Using NVIDIA TITAN Xp and GeForce GTX 1080 Ti GPUs, with the cuDNN-accelerated PyTorch deep learning framework for both training and inference > the team based their algorithm on the pix2pixHD architecture developed by NVIDIA researchers Is it me, or is NVIDIA trying very hard to take credit for this UC Berkeley paper? (they're almost taking credit for Pytorch as well). Sure, this kind of work wouldn't be possible…
It's on the nvidia site, it's either been edited by them, or they supplied the cards or part funded the work.
> This work was supported, in part, by NSF grant IIS-1633310 and research gifts from Adobe, eBay, and Google
The fact that people are thinking "it's on the nvidia site, they must have participated somehow" is precisely the reason I wanted to bring this up.
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I don't understand this attitude at all. So something that doesn't seem artistic to you simply isn't artistic for anybody else because you decided that it isn't? Autotune is just another processing like reverb, delay, whatever. You think they didn't use any processing on Beatles' records? You think non-autotuned singers don't use a TC-helicon or whatever when they're performing live? Autotuned songs can sound good, j…
There's a difference between using it deliberately and using it because the singer can't sing. I wonder if in 20 years time it will sound incredibly dated, much like 80s synths do today. I'm not particularly against auto tune and ultimately most people don't even notice it being used, but I do sort of understand where the GP is coming from. If your idol can't actually sing, and you saw them live and it's rubbish, wou…
I personally dislike it too, but I'm not going to say it's not artistic, because to someone else it might be. People get so caught up and passionate with their art of choice that they sometimes forget that it's all just entertainment in the end. Whether it be Hillary Hahn or some teenager making beats in Ableton and throwing in the stock vocal effect.
About 80s synths, I think a lot of us, or at least I personally associate that cheesy sound with mass-produced digital synths put out by Yamaha, Roland etc. It's all variety and I love it. My dad still has a DX7 and a D-50 that I'm hoping to inherit.
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Oh I agree. I think it's possible to dislike or even hate all the over-processed and over-produced commercial music that's been coming out for the last 2-3 decades while at the same time accepting that there are others out there who might genuinely like that kind of music. I definitely understand your point about Hendrix, Knopfler and Slash. There's something beautiful about virtuoso playing that still sounds "raw",…
I've always felt that way about Satriani and Vai to a lesser degree too. It's funny how specific we can be about what we like and don't like. Here I am extolling the virtues of sloppy or "more natural" singing and playing, but I can't listen to 90% of punk music for more than a few minutes.
Need to send this to theresa may
https://www.theguardian.com/politics/2018/aug/30/theresa-may...
Anyone want to get rich developing this for android /w me? haha
> Using NVIDIA TITAN Xp and GeForce GTX 1080 Ti GPUs, with the cuDNN-accelerated PyTorch deep learning framework for both training and inference > the team based their algorithm on the pix2pixHD architecture developed by NVIDIA researchers Is it me, or is NVIDIA trying very hard to take credit for this UC Berkeley paper? (they're almost taking credit for Pytorch as well). Sure, this kind of work wouldn't be possible…
It also seems as UC Berkeley and NVIDIA collaborated on pix2pixHD, judging by the paper
Like competitive sports, art is all about display of human ability under constraints. This is why even in the age of photographs, we still value hand-painted canvases. Such techniques are simply going to make people more discerning between real effort v/s automated means of generating the same outcome.
Rather than thinking AI-assisted style transfers are the end of art, we should think that these are new tools for artists to do even more interesting stuff. See this upcoming tool for example: https://runwayml.com/