A Quote by Austan Goolsbee

I am a data hound and so I usually end up working on whatever things I can find good data on. The rise of Internet commerce completely altered the amount of information you could gather on company behavior so I naturally drifted toward it.
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.
If we gather more and more data and establish more and more associations, however, we will not finally find that we know something. We will simply end up having more and more data and larger sets of correlations.
Data isn't information. ... Information, unlike data, is useful. While there's a gulf between data and information, there's a wide ocean between information and knowledge. What turns the gears in our brains isn't information, but ideas, inventions, and inspiration. Knowledge-not information-implies understanding. And beyond knowledge lies what we should be seeking: wisdom.
Every company has messy data, and even the best of AI companies are not fully satisfied with their data. If you have data, it is probably a good idea to get an AI team to have a look at it and give feedback. This can develop into a positive feedback loop for both the IT and AI teams in any company.
When you have a large amount of data that is labeled so a computer knows what it means, and you have a large amount of computing power, and you're trying to find patterns in that data, we've found that deep learning is unbeatable.
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.
Modern statisticians are familiar with the notion that any finite body of data contains only a limited amount of information on any point under examination; that this limit is set by the nature of the data themselves, and cannot be increased by any amount of ingenuity expended in their statistical examination: that the statistician's task, in fact, is limited to the extraction of the whole of the available information on any particular issue.
I'm kind of fascinated by this idea that we can surround ourselves with information: we can just pile up data after data after data and arm ourselves with facts and yet still not be able to answer the questions that we have.
I think there's data, and then there's information that comes from data, and then there's knowledge that comes from information. And then, after knowledge, there is wisdom. I am interested in how to get from data to wisdom.
There is so much information that our ability to focus on any piece of it is interrupted by other information, so that we bathe in information but hardly absorb or analyse it. Data are interrupted by other data before we've thought about the first round, and contemplating three streams of data at once may be a way to think about none of them.
CloudShield did not see itself as a cloak-and-dagger company. It made its name for high-end hardware that could peer deeply into Internet traffic and pull out and analyze 'packets' of data as they flew by.
Data is the new soil, because for me, it feels like a fertile, creative medium. Over the years, online, we've laid down a huge amount of information and data, and we irrigate it with networks and connectivity, and it's been worked and tilled by unpaid workers and governments.
When we look at Huawei and ZTE, there are significant indicators that - because of Huawei's close relationship with the Chinese military and Chinese intelligence, the use of Huawei technologies could create backdoors for areas of access to consumer data or company data that we would find unacceptable.
The librarian isn't a clerk who happens to work in a library. A librarian is a data hound, a guide, a sherpa and a teacher. The librarian is the interface between reams of data and the untrained but motivated user.
The information highway is being sold to us as delivering information, but what it's really delivering is data... Unlike data, information has utility, timeliness, accuracy, a pedigree... Editors serve as barometers of quality, and most of an editor's time is spent saying no.
TIA was being used by real users, working on real data - foreign data. Data where privacy is not an issue.
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