A Quote by Ben Parr

Google is famous for making the tiniest changes to pixel locations based on the data it accrues through its tests. Google will always choose a spartan webpage that converts over a beautiful page that doesn't have the data to back it up.
AIs are only as good as the data they are trained on. And while many of the tech giants working on AI, like Google and Facebook, have open-sourced some of their algorithms, they hold back most of their data.
The biggest mistake is an over-reliance on data. Managers will say if there are no data they can take no action. However, data only exist about the past. By the time data become conclusive, it is too late to take actions based on those conclusions.
Facebook collects a lot of data from people and admits it. And it also collects data which isn't admitted. And Google does too. As for Microsoft, I don't know. But I do know that Windows has features that send data about the user.
Google+ was, to my mind, all about creating a first-party data connection between Google most important services - search, mail, YouTube, Android/Play, and apps.
Removed from 'Gmail' doesn't necessarily mean removed from all Google servers. In fact, your old emails are the data set from which Google models our behaviors - the real product it is offering its advertisers.
In short, Now is Google's attempt at becoming the real time interface to our lives - moving well beyond the siloed confines of 'search' and into the far more ambitious world of 'experience.' As in - every experience one has could well be lit by data delivered through Google Now.
I worry about Google's data ethics and about the idea of handing over the corpus of my life, but I can't deny that it is exceptional at making sense of my ever-growing photo library.
Google's competitors argue that Google designs its search display to promote Google 'products' like Google Maps, Google Places, and Google Shopping, ahead of competitors like MapQuest, Yelp, and product-search sites.
One of the myths about the Internet of Things is that companies have all the data they need, but their real challenge is making sense of it. In reality, the cost of collecting some kinds of data remains too high, the quality of the data isn't always good enough, and it remains difficult to integrate multiple data sources.
... negative feelings are not true feelings at all; rather, they are your thoughts about something, based always on the previous experience of yourself and others. You will not find Truth in your past data, only past data that is based on other past data that is based on other past data, and so forth. Forget your "past experience" and look directly at the experience you are having. Right Here, Right Now. There is your Truth.
Watson augments human decision-making because it isn't governed by human boundaries. It draws together all this information and forms hypotheses, millions of them, and then tests them with all the data it can find. It learns over time what data is reliable, and that's part of its learning process.
What can we learn from the battle between data and design? What can we learn from the relationship between Google and Apple? Clearly no one school of thought is right: Apple and Google are both wildly successful and profitable companies that changed the world.
Corporations like Google, Facebook, Amazon, all of these large companies, are making tens or hundreds of billions of dollars off of monetising people's data.
Apple and Google will compete like crazy for our data because once they have it we'll be their customers forever.
Definitely there's growing use of machine learning across Google products, both data-center-based services, but also much more of our stuff is running on device on the phone.
In the past, Google has used teams of humans to 'read' its street address images - in essence, to render images into actionable data. But using neural network technology, the company has trained computers to extract that data automatically - and with a level of accuracy that meets or beats human operators.
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