Caffe2: Open Source Cross-Platform Machine Learning Tools
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Re: Caffe2: Open Source Cross-Platform Machine Learning Tools
#2Re: Caffe2: Open Source Cross-Platform Machine Learning Tools
#3I think Caffe2 is especially suited to machine learning that runs on mobile devices, so I wouldn't be surprised to see it become more popular as that mode of machine learning becomes more popular.
Re: Caffe2: Open Source Cross-Platform Machine Learning Tools
#4This is the library that powers the "style transfer" feature in Facebook Messenger: http://caffe2.ai/docs/AI-Camera-demo-android.html I think Caffe2 is especially suited to machine learning that runs on mobile devices, so I wouldn't be surprised to see it become more popular as that mode of machine learning becomes more popular.
Re: Caffe2: Open Source Cross-Platform Machine Learning Tools
#5Re: Caffe2: Open Source Cross-Platform Machine Learning Tools
#6Re: Caffe2: Open Source Cross-Platform Machine Learning Tools
#7Hey guys - Yangqing here, worked on Caffe and Caffe2 over the years, super excited to have continuous contribution to the OSS community. I am more than happy to answer questions if you are curious.
Cheers and congrats on the release!
Re: Caffe2: Open Source Cross-Platform Machine Learning Tools
#8Hey guys - Yangqing here, worked on Caffe and Caffe2 over the years, super excited to have continuous contribution to the OSS community. I am more than happy to answer questions if you are curious.
A super inexperienced observer here, so just a very basic question - how does Caffe(2) differ from TF/Theano/Torch etc.? What are the obvious upsides and potential downsides? A tweet-sized answer will do, I'm just curious as to what the high level differences are. Cheers and congrats on the release!
> Caffe2 is built to excel at mobile and at large scale deployments. While it is new in Caffe2 to support multi-GPU, bringing Torch and Caffe2 together with the same level of GPU support, Caffe2 is built to excel at utilizing both multiple GPUs on a single-host and multiple hosts with GPUs. PyTorch is great for research, experimentation and trying out exotic neural networks, while Caffe2 is headed towards supporting more industrial-strength applications with a heavy focus on mobile. This is not to say that PyTorch doesn’t do mobile or doesn’t scale or that you can’t use Caffe2 with some awesome new paradigm of neural network, we’re just highlighting some of the current characteristics and directions for these two projects. We plan to have plenty of interoperability and methods of converting back and forth so you can experience the best of both worlds.
Re: Caffe2: Open Source Cross-Platform Machine Learning Tools
#9Is ARM, and in particular the NVIDIA TK1/TX1/TX2 supported? Ease of use on these platforms with Theano vs Tensorflow/PyTorch is the main thing keeping me on Theano.
Re: Caffe2: Open Source Cross-Platform Machine Learning Tools
#10Hey guys - Yangqing here, worked on Caffe and Caffe2 over the years, super excited to have continuous contribution to the OSS community. I am more than happy to answer questions if you are curious.
A super inexperienced observer here, so just a very basic question - how does Caffe(2) differ from TF/Theano/Torch etc.? What are the obvious upsides and potential downsides? A tweet-sized answer will do, I'm just curious as to what the high level differences are. Cheers and congrats on the release!