[mraison]

> 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 without their hardware, but in that case Intel could probably take credit for most of science in the last few decades.

[twtw]

It's a company blog. It exists to highlight applications of the company's products. I don't see why you are bothered, both of those statements are factually true.

[mraison]

Normally I wouldn't be bothered, but in this case I saw people being misled into thinking Nvidia did this work. Given Nvidia publishes a lot at computer vision conferences, there's a higher than usual potential for confusion.

[anjc]

How does that seem like taking credit? They aren't saying they're using NVIDIA hardware, they're saying it developed it from NVIDIA work, i.e. pix2pixHD, no?

It also seems as UC Berkeley and NVIDIA collaborated on pix2pixHD, judging by the paper

[mraison]

> They aren't saying they're using NVIDIA hardware

They are, see quote above. They're also going out of their way to mention that Pytorch is using cuDNN, which is true but off-topic.

[boomlinde]

I think he meant that they aren't just saying that they're using NVIDIA hardware

[mattmanser]

It's on the nvidia site, it's either been edited by them, or they supplied the cards or part funded the work.

[mraison]

There's no mention of it in the paper. The acknowledgements section says:

> 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.