Quotes About Big data

Very simple techniques, when you have a lot of data, work incredibly well.

We know growing technological developments in artificial intelligence, automation and big data mean that democratic socialism in the 21st century must adapt to such a rapidly changing world.

Truly smart technologies will remind us that we are not mere automatons who assist big data in asking and answering questions.

Should Ford succeed in equipping all its cars with information that gets communicated back to its servers, it will become a 'big data' company, a beyond-vehicles opportunity that is as promising as it is murky.

We Facebook users have been building a treasure lode of big data that government and corporate researchers have been mining to predict and influence what we buy and for whom we vote. We have been handing over to them vast quantities of information about ourselves and our friends, loved ones and acquaintances.

The premise and promise of Big Data is that there are no stories, only patterns; that the human preference for story is aligned with the human tendency for error; and that only through dislocations in scale - the scale of sample size and of time - will truth emerge.

While many big-data providers do their best to de-identify individuals from human-subject data sets, the risk of re-identification is very real.

Big data has been used by human beings for a long time - just in bricks-and-mortar applications. Insurance and standardized tests are both examples of big data from before the Internet.

The new economy requires consumers with spending power – just as the old one did. Yet much like the farmer who eats his seed corn, Big Data is gobbling up its source of future revenue.

As Nassim Taleb, the author of The Black Swan: The Impact of the Highly Improbable, writes, "Big data may mean more information, but it also means more false information." And even when the information is not false, the problem is "that the needle comes in an increasingly larger haystack.

People think 'big data' avoids the problem of discrimination because you are dealing with big data sets, but, in fact, big data is being used for more and more precise forms of discrimination - a form of data redlining.

We get more data about people than any other data company gets about people, about anything - and it's not even close. We're looking at what you know, what you don't know, how you learn best. The big difference between us and other big data companies is that we're not ever marketing your data to a third party for any reason.

The people who are thinking most about big data right now are corporations and governments.

It's time to wake up to the fact that you're just another avatar in someone else's MMO. Worse: From where they stand, all-powerful Big Data analysts that they are, you look an awful lot like a bot.

I love that the world is data intensive … unfortunately, it's called 'Big Data.'

Big Data isn't magic, and it doesn't tell the feds who's a terrorist and who's not. But it doesn't have to be magic to generate long lists of people who are in some ways red-flagged, elevated-risk, "people of interest." Most of the people on those lists will have nothing to do with terrorism. How confident are you that you're not one of them?

Often people think of developments in computation as arising when we make our computers more blazingly fast, so they can compute more stuff , bigger data . It's actually just as important to prune away big parts of the data that aren't relevant to the problem at hand! The fastest computation is the one you don't do.

Blockchain is like the new big data or AI - too many people are using it as a buzzword and not focused solving a real problem. We like to call them Blockchain tourists!

With too little data, you won't be able to make any conclusions that you trust. With loads of data you will find relationships that aren't real... Big data isn't about bits, it's about talent.

It is easier to face an emergency than to have those difficult conversations. When we go into crisis mode, we give ourselves permission to defer the kinds of conversations that politics requires. And right now, our politics requires conversations, too long deferred, about being a self and a citizen in the world of big data.

Going forward, with the utilization of artificial intelligence, Big Data and IoT, we want to overcome the challenges coming from an aging society with low fertility. Well, I would say precisely because we live in a greying society with low fertility rate, we have already accumulated data and with the use of artificial intelligence we will make good use of the Big Data that we have.

Much of this data-centric history still haunts us today. We live in an era that presumes Big Data to be the solution to all our problems. Courses in "data science" are proliferating in our universities, and jobs for "data scientists" are lucrative in the companies that participate in the "data economy." But I hope with this book to convince you that data are profoundly dumb.

Extremely large Volumes of data Extremely high Velocity of data Extremely wide Variety of data

All you need is lots and lots of data and lots of information about what the right answer is, and you'll be able to train a big neural net to do what you want.