“Machine Learning” is the tech topic du jour these days, the subject of endless blogs, news articles and press releases, it has even earned the top position on the “Gartner Hype Cycle” – a sure sign that we are still years away from any hope of a return on investment.
But there is another possibility: recent announcements made by Google, regarding Google Assistant, Pixel and Google Home, suggest that the advent of Machine Learning is not only imminent . . . it is already here.
Consider Google Assistant the powerful new alternative to Siri, Alexa, and Cortana. Like the others, you simply speak and Google Assistant responds. But there is much more to Assistant. The value of its Machine Learning technology becomes evident when Assistant remembers information from your previous requests, your current context (time, location, events), as well as combines requests from all other Google Assistant users to provide you with the best answer to your query.
Google is not the only market leader to invest heavily in Machine Learning. Facebook has successfully built a $350 billion Market Capitalization, and one of the world’s leading brands, not least because the company uses Machine Learning to recognize and “tag” images. Moreover, FBLearner Flow’s models help define what content appears in your News Feed and what advertisements you see. Think of it as Machine Learning for the masses; a stealth technology that has made its way into our private lives before we even knew about it.
All of this suggests that the most powerful Internet and tech companies will continue to invest heavily in Machine Learning to deliver a significantly more valuable personal experience from our personal and professional engagement with technology. And that in turn suggests an interesting question:
How can Machine Learning add real value to personal productivity in business?
At Synqq, we leverage the same rule-based Machine Learning models as those used by Facebook, Google and IBM Watson. For example, Synqq offers to the user hints about how to facilitate completion of common activities. It also derives inferences from the data sets for each user and his or her business domains. Moreover, Synqq’s proprietary Smart Tags offer the ability to retrieve information with a single finger tap by doing the relevant entity extraction from Synqq notes, and using an arcane statistical process known as ‘Bayesian posterior probabilistic inferences’ (we’ll spare you an explanation – it would take several pages).
These are just a few of the many applications of Machine Learning that promise to add significant value to the most common features of smartphones and browsers – in the process transforming the way we create, capture, share and retrieve information essential to our personal productivity. Machine Learning also provides an easy and intuitive way to create and share content from ad hoc meetings –those unplanned, but often decisive, encounters which occur far more often in the business day than scheduled meetings.
Don’t look now, but the Age of Machine Learning is here. It is destined to make our daily activities fast, fun — and done right, infinitely more productive. It is our avowed goal to deliver to you all three.