At the core of their fight is the underlying software for creating
neural networks, the software that learns on its own to recognize patterns within data. Although neural networks have been
around for decades, it wasn’t until recently that researchers discovered that the technology could be useful for helping computers with tasks like automatically translating languages and recognizing people and objects in photos.
Currently, there’s no easy way for companies to create neural networks, like there is for developing more conventional software. But, in recent years, several big companies have introduced so-called developer “frameworks” that are a first stab at helping coders build neural networks and at making the technology more practical to use widely in apps.
In 2015, Google debuted
TensorFlow, the leading toolkit for building neural networks, according to researchers who track the software. TensorFlow’s popularity has so far eclipsed rival toolkits from the likes of
Amazon and
Microsoft.
Until now, that is.
Last week’s annual Facebook developer conference highlighted several updates to PyTorch, Facebook’s neural network construction kit that succeeded an older and less sophisticated version. PyTorch has emerged as one of the fastest growing free open source technologies, according to some surveys, and is used by a handful of big companies like Genentech, Toyota, and Airbnb
