A Quote by Marcus Sakey
Trying to analyze a situation without enough data was like looking at a photograph of a ball in flight and trying to gauge its direction. Is it going up, down, sideways? Is it about to collide with a baseball bat? Is it moving at all, or is something on the blind side holding it in place? A single frame didn't mean a thing. Patterns were based on data. With enough datapoints, you could predict just about anything.
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The big thing that's happened is, in the time since the Affordable Care Act has been going on, our medical science has been advancing. We have now genomic data. We have the power of big data about what your living patterns are, what's happening in your body. Even your smartphone can collect data about your walking or your pulse or other things that could be incredibly meaningful in being able to predict whether you have disease coming in the future and help avert those problems.
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.
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.
'Sleep' is a project I've been thinking about for many years. It just seems like society has been moving more and more in a direction where we needed it. Our psychological space is being increasingly populated by data. And we expend an enormous amount of energy curating data.
Recruiting is hard. It's just finding the needles in the haystack. You can't know enough in a one-hour interview. So, in the end, it's ultimately based on your gut. How do I feel about this person? What are they like when they're challenged? I ask everybody that: 'Why are you here?' The answers themselves are not what you're looking for. It's the meta-data.
The USA Freedom Act does not propose that we abandon any and all efforts to analyze telephone data, what we're talking about here is a program that currently contemplates the collection of all data just as a routine matter and the aggregation of all that data in one database. That causes concerns for a lot of people... There's a lot of potential for abuse.
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.
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You don't just find an empty museum and say, "I should do something here." I was looking for another kind of venue or exhibition format. I was trying to find a site where something could happen over a long period of time - something that could slowly transform itself and the place as it went. And I was also trying to stand out of the art-world system. Strangely enough, I stumbled on vacant museum.
'Data exhaust' is probably my least favorite phrase in the big data world 'cause it sounds like something you're trying to get rid of or something noxious that comes out of the back of your car.
Machine learning is looking for patterns in data. If you start with racist data, you will end up with even more racist models. This is a real problem.
... 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.
I'm going to say something rather controversial. Big data, as people understand it today, is just a bigger version of small data. Fundamentally, what we're doing with data has not changed; there's just more of it.
And it seemed hard to believe that these people who were so close to me couldn’t see how desperate I was, or if they could they didn’t care enough to do anything about it, or if they cared enough to do anything about it they didn’t believe there was anything they could do, not knowing—or not wanting to know—that their belief might have been the thing that made the difference.
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