Facebook and Google aren’t merely competing for dominance in online advertising. They’re also battling over artificial intelligence.
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.
Although Facebook, like Google, makes no money from its A.I. tools, the company benefits from outsiders using them. For one, the more A.I. researchers use PyTorch, the more Facebook has a pool of A.I. talent that is familiar with its technology and is therefore more attractive to recruit.
Additionally, like many open-source technologies, PyTorch should improve over time as more of its users share feedback with Facebook. And while Facebook, Google, and others would never publicly admit it, they want to be perceived as leading A.I. firms, and the more their A.I. tools are adopted by third parties, the more they can claim the A.I. crown.
Still, Facebook’s director of applied machine learning Srinivas Narayanan told Fortune that it’s still the early days of PyTorch and A.I. tools overall. Despite the buzz, there is still no effort to create technical standards around PyTorch or to create independent groups that would oversee the technology, like how the Linux Foundation oversees an umbrella of open source technologies.
But companies would be wise to pay close attention to the A.I. toolkit wars, because the outcome could be crucial to their A.I. ambitions.
No comments:
Post a Comment