TensorFlow Won the Attention Battle, Who’s Next?
Published on Jun 23, 2018 on Medium.com
(Source: Lucas Amunategui)
At a recent conference, a European university presented a gigantic TensorFlow network cluster. One attendee asked if they tried the same approach with Caffe or MXNet, to which the presenter shrugged and explained that TensorFlow won the attention battle and, for a university program like his that runs on volunteers, that attention, the cool frameworks, things that kids want to learn, is his only currency.
That comment got me thinking; he needs student-volunteers to keep his research going, and he pays them by offering real experience using technologies that will, in turn, get the attention of recruiters.
When do we know that a technology has reached critical mass? How can we measure new comers and gauge their chances of adoption so we can stay a step ahead? I use visualization to help me extend a promising technology into the future.
Each stage is equally interesting and analyzing the “who’s who at what stage” can be strategic in many ways. Let’s work our way backwards and start from the end — the victory stage.
Though a bit obvious after the fact, it can be helpful when you’re searching for developers. If you’re like that university and need volunteers, or have a limited budget or in an industry that has a tough time recruiting, stick to certified ‘cool’ languages and frameworks, you’ll be surprised at how many young folks or those changing careers will appreciate the exposure. It’s a win-win, and its the “victory” stage.
The “battle” stage is the Cambrian explosion of different technologies trying to be first, trying to be different, pounding their chests, and begging for adoption. Here, the idea gained interest but the technologies around it are still emerging and creators are duking it out — think cryptos, blockchains, chatbots, automated ml tools, 3D printing — nobody has won yet and its bloody!! Just look at all those outlandish promises posted on LinkedIn…
You can use all sorts of tools to gauge how a particular implementation is doing. Look at how much money they’ve raised, what people are writing about on Reddit, TechCrunch, or Medium sites. Take a look at their Github pages, the number of forks, comments and related StackOverflow issues. Picking winners at this stage takes observation skills, foresight, and a systematic ear-to-the-ground attitude (and we know it isn’t always the best tech that wins).