Quotes About Data

We have a large amount of data that shows playing fast-paced games improves hand-eye co-ordination, the ability to focus on the task at hand, and your ability to make decisions, as gaming improves your brain's allocation of resources.

We want to build systems that can generalize to a new task. Being able to do things with much less data and with much less computation is going to be interesting and important.

I can only speak for particle physics. But it has become obvious that on the experimental side, there has been a huge evolution in the number of people who have to collaborate because of the gigantic size of the instruments used, but also because of the enormous task that is data analysis.

Rapid development in areas like machine-to-machine communications and the Internet of Things, coupled with the proliferation of big data, means higher-skilled professions, such as lawyers, journalists and accountants, are changing too. Some of their tasks are being replaced.

In China, Internet surveillance has already become a profitable industry. In fact, a growing number of private firms eagerly assist the local police by aggregating this data and presenting it in easy-to-browse formats, allowing humans to pursue more analytical tasks.

Making more sense out of my data, my needs, my tasks - to me, that's the future of Office.

Most economies have a fair amount of tax evasion, depending on how their data systems are.

Anybody who is familiar with the historical data from the IRS knows that raising income tax rates will likely actually reduce federal revenues.

Whether we look at capitalism, taxes, business, or government, the data show a clear and consistent pattern: 70 percent of Americans support the free enterprise system and are unsupportive of big government.

First, the security and privacy of sensitive taxpayer information is absolutely essential.

Even the best data security systems can't protect private taxpayer information from entrepreneurial foreign businesses than can make huge profits selling U.S. taxpayer information.

Ultimately, taxpayers deserve a government that leverages technology to serve them, rather than one that deploys unsecure, decades old technology, and keeps sensitive information in non-encrypted databases.

Data indicate that taxpayers may be paying their public servants more than a little too much.

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.

However, popular culture defines Nature as an "other," a near-sentient force operating beyond the bounds of human community. I was raised with that notion and can empathize with the nostalgia often accompanying it, but I can't accept the idea of a separate Nature any more than I believe digital data resides in "The Cloud" (the data resides in machinery that is typically plugged into a wall socket).

In God we trust, everybody else brings data.

Thus empiricism directed attention away from abstract principles to the data of experience. Hence, while the philosophers of the pre-Enlightenment period favoured the geometric method, reasoning deductively from first principles, their successors worked by induction, first observing particular details and arriving eventually at general truths.

Price is a powerful data point – what a customer is willing to pay for a product or service in a competitive market. Having customers, people that have made that decision, is a valuable thing.

more than one in three young families with children (headed by someone thirty or under) were living in poverty in 2010, according to an analysis of census data by Northeastern University's

Objects hide their data behind abstractions and expose functions that operate on that data. Data structure expose their data and have no meaningful functions.

Procedural code (code using data structures) makes it easy to add new functions without changing the existing data structures. OO code, on the other hand, makes it easy to add new classes without changing existing functions.

The complement is also true: Procedural code makes it hard to add new data structures because all the functions must change. OO code makes it hard to add new functions because all the classes must change.

The SOLID principles tell us how to arrange our functions and data structures into classes, and how those classes should be interconnected. The use of the word "class" does not imply that these principles are applicable only to object-oriented software. A class is simply a coupled grouping of functions and data. Every software system has such groupings, whether they are called classes or not. The SOLID principles apply to those groupings.

The critical rules and critical data are inextricably bound, so they are a good candidate for an object. We'll call this kind of object an Entity.1