In case you hadn’t heard, we here at Google Cloud Platform released the Cloud Natural Language API this week, and an open beta of the Speech API.
Both the Natural Language and Speech APIs are just the latest examples in the Cloud Machine Learning technologies that we’ve made available to the public, following on the heels of the Vision API and Translate API. But what exactly do these latest APIs allow you to do?
Natural Language is all about parsing written text — you know, the kind that you’re looking at right now. By way of introduction, check out Google Developer Advocate Sara Robinson’s post on how she used the Natural Language API to analyze stories in The New York Times, while introducing us to the NL concepts of “sentiment” and “entities.”
Google Developer Advocate Guillaume Laforge dives deeper into sentiments by color coding tweets as strong positive, strongly negative — or somewhere in between — according to the polarity and magnitude unearthed by Natural Language. Turns out that @googlecloud tweets are all over the map, sentiment-wise, judging by this many-colored chart.
|Positive tweets are green, negative tweets are red and neutral tweets are yellow|
But how reliable are these latest machine learning offerings? Make no mistake, it’s early days, and natural language processing is an imperfect science. Over on Hacker News, some people reported mixed results with Natural Language. Check out the conversation with Google Natural Language Product Manager Dave Orr, who explains why a sentence that is so easy for a human “wetware” brain to understand can still trip up a computer. “It's the curse of [natural language processing], really,” he says. “All the easy things are hard. (And the hard things are nigh impossible.)”
We hope you’ll be the judge. Scroll down to the bottom of the Cloud Natural Language API page, and enter a snippet of text and try the API.