The State of Machine Learning Frameworks in 2019

The State of Machine Learning Frameworks in 2019

Since deep learning regained prominence in 2012, many machine learning frameworks have clamored to become the new favorite among researchers and industry practitioners. From the early academic outputs Caffe and Theano to the massive industry-backed PyTorch and TensorFlow, this deluge of options makes it difficult to keep track of what

226 mentions: @gradientpub@xamat@schrep@reiinakano@marcelsalathe@xsteenbrugge@rajhans_samdani@b0noi
Date: 2019/10/10 16:00

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@xamat "My analysis suggests that researchers are abandoning TensorFlow and flocking to PyTorch in droves. Meanwhile in industry, Tensorflow is currently the platform of choice, but that may not be true for long."
@gradientpub The war between ML frameworks has raged on since the rebirth of deep learning. Who is winning? @cHHillee's data analysis shows clear trends: PyTorch is winning dramatically among researchers, while Tensorflow still dominates industry. #PyTorch #Tensorflow
@arnicas My industry anecdote: I couldn’t get the PyTorch LSTM fast enough in prod, but with a small loss in accuracy I got speed wanted from Tensorflow rewrite + Serving.
@xsteenbrugge It's impressive to see how fast PyTorch came to dominate the ML research landscape, very interested to see this chart evolve now that TF 2.0 is in play!
@rajhans_samdani Pytorch passes Tensorflow in the research community! The lesson: APIs and ease of use matter. No amount of engineering can overcome hard-to-use APIs that keep changing.
@schrep PyTorch long ago became the tool of choice for AI research at fb. It’s now the tool of choice for production as well.
@reiinakano ""ML frameworks don’t just enable machine learning research, they enable and restrict the ideas that researchers are able to easily explore."" Perhaps the next big step forward is something completely inexpressible in the TF/PyTorch paradigm.
@b0noi "The State of Machine Learning Frameworks in 2019" "If you only browsed Reddit, you might assume that everyone’s switching to PyTorch. Judging instead by Francois Chollet’s Twitter, TensorFlow/Keras may appear as the dominant framework ..." amazing read

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