These images by Swedish photographer, artist, and Photoshop genius Erik Johansson are anything but ordinary. What at first appears to be a room, house, or street quickly shifts into a mind-boggling optical illusion, using creative manipulations of perspective to keep the viewer perplexed. From cars driving on the underside of the freeway to people living on their ceilings, Johansson’s strikingly convincing realizations of spatial impossibilities will have you second-guessing your surroundings.
They are very impressive photo work to reflect our electronic life today.
IBM announced in June that it has embarked on a quest to create a million new data scientists. It will be adding about 230 of them during its Datapalooza educational event this week in San Francisco, where prospective data scientists are building their first analytics apps.
The ability to use data to achieve enterprise goals requires advanced skills that many organizations don’t yet have. But they are looking to add them – and fast. The question is, what type of big data expert is needed? Does an organization need a data scientist or does it need a business analyst? Maybe it even needs both. These two titles are often used interchangeably, and confusion abounds.
Business analysts typically have educational backgrounds in business and humanities. They find and extract valuable information from a variety of sources to evaluate past, present, and future business performance – and then determine which analytical models and approaches will help explain solutions to the end users who need them.
With educational backgrounds in computer science, mathematics, and technology, data scientists are digital builders. They use statistical programming to actually construct the framework for gathering and using the data by creating and implementing algorithms to do it. Such algorithms help businesses with decision making, data management, and the creation of data visualizations to help explain the data that they gather.
Another data analysis about jobs which will be phased out as time goes. It is an interesting analysis of historical job data. However, after I glanced through the bank report referenced in the article, I am not sure robots are the reason of the job replacement. For example, it could be replaced by cheap labor in foreign countries. The bank report shows only the jobs subject to be phased out due to technology advancement. People could just become productive. So, do not take robots too seriously!
… Benford’s Law says that naturally occurring numbers that span several orders of magnitude (i.e., differing numbers of digits, or differing powers of 10 when written in scientific notation like 3.15 x 102) should start with “1” 30.1% of the time, and they should start with “9” only 4.6% of the time.
Put together by Keith Collins for Quartz using data from the Astronomical Applications Department of the U.S. Naval Observatory, the interactive lets you select what time you typically wake up and go to bed. That shifts the axes, to show you how much light you get to see (in blue) and how much dark you experience (in black). Then, you can press a button to see what difference Daylight Saving has on your experience. What’s the verdict?