A Quote by Ken Thompson
I wanted to separate data from programs, because data and instructions are very different.
Related Quotes
Any time scientists disagree, it's because we have insufficient data. Then we can agree on what kind of data to get; we get the data; and the data solves the problem. Either I'm right, or you're right, or we're both wrong. And we move on. That kind of conflict resolution does not exist in politics or religion.
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.
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.
We use nearly 5 thousand different data points about you to craft and target a message. The data points are not just a representative model of you. The data points are about you, specifically.
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.
A data scientist is that unique blend of skills that can both unlock the insights of data and tell a fantastic story via the data.
Data!data!data!" he cried impatiently. "I can't make bricks without clay.
They made it very clear that I shouldn't try to be Data because there is only one Data, you can't ever recreate the magic that Brent Spiner made.
Go out and collect data and, instead of having the answer, just look at the data and see if the data tells you anything. When we're allowed to do this with companies, it's almost magical.
Biases and blind spots exist in big data as much as they do in individual perceptions and experiences. Yet there is a problematic belief that bigger data is always better data and that correlation is as good as causation.
I think audiences ultimately want something new. I think the business model for a franchise is such that it's very low risk because you have data and studios love data.
In my view, our approach to global warming exemplifies everything that is wrong with our approach to the environment. We are basing our decisions on speculation, not evidence. Proponents are pressing their views with more PR than scientific data. Indeed, we have allowed the whole issue to be politicized-red vs blue, Republican vs Democrat. This is in my view absurd. Data aren't political. Data are data. Politics leads you in the direction of a belief. Data, if you follow them, lead you to truth.
We all say data is the next white oil. [Owning the oil field is not as important as owning the refinery because what will make the big money is in refining the oil. Same goes with data, and making sure you extract the real value out of the data.]
Scientific data are not taken for museum purposes; they are taken as a basis for doing something. If nothing is to be done with the data, then there is no use in collecting any. The ultimate purpose of taking data is to provide a basis for action or a recommendation for action. The step intermediate between the collection of data and the action is prediction.
TIA was being used by real users, working on real data - foreign data. Data where privacy is not an issue.
People believe the best way to learn from the data is to have a hypothesis and then go check it, but the data is so complex that someone who is working with a data set will not know the most significant things to ask. That's a huge problem.
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