Caffe2: Deep learning with flexibility and scalability
As the AI landscape continues to evolve, a new version of the popular Caffe open source deep learning framework has been released. Caffe2 is backed by Facebook and features a wide array of partnerships to make it as flexible and scalable as possible. But is that enough to make Caffe2 a winner?
Although artificial intelligence (AI) is more than machine learning (ML), and ML is more than deep learning (DL), DL is an important part of AI that has seen lots of progress and hype as of late. Winning the hearts and minds of developers and creating an ecosystem around frameworks will be very important for this space going forward.
Taking a look at the history of Android can provide some insights, and it looks like Google is the first to learn from its own success there. Open-sourcing TensorFlow in late 2015 caused a commotion, and some go as far as to say that Google has already won the DL framework race with TensorFlow.
It may be a bit early for such claims though, and the people behind Caffe2 beg to differ.
So, what does winning even mean here? What are the criteria for defining a winning DL framework? If it’s mindshare we’re talking about, then yes, it looks like TensorFlow is winning. Although there’s no “official” data as of yet, analyzing sources such as StackOverflow and Github seems to point towards a landslide victory for TensorFlow.