If you are a recruiter, then you'd agree that the one thing most recruiters would love to have is a recruiting source of top candidates that helps fill all their positions quickly. Imagine you had a gold mine, that one source that is extremely simple to use. That one source where you can just pick out the best hires, present them to your hiring managers and close positions in a jiffy? You'd say "Stop making things up. Nothing like that exists, really.
For science fiction, the multiverse is a gold mine of compelling story ideas. But how could we prove or disprove it? Some physicists like Kleban believe we could detect evidence of the multiverse through something called bubble collisions. If the edges of two universes crashed into each other in the distant past, a signature imprint would be left behind in the sky. The hunt for bubble collisions continues, although Kleban himself has acknowledged finding one would be a long shot.
Faced with growing costs for extraction and processing and increasing competition, mine operators are turning to advanced technology tools to speed the discovery of mineral deposits. For Goldcorp, these tools now include cognitive technology from IBM applied to multiple information sources to help geologists locate high-value exploration targets faster and with greater accuracy, thereby reducing extraction costs and environmental impact. According to Mark Fawcett, partner, IBM global business services and project lead, Goldcorp's Watson initiative was a collective effort that drew on the strengths of both the IBM and Goldcorp organizations in the implementation and training of the Watson system. The gold in any analytics project, the Red Lake project began with the collection of information resources, including structured and unstructured data.
A gold mining company -- Newcrest Mining -- provided operating data for a number of its plants, with the aim that some of the teams attending could provide useful solutions grounded in Data Science. To keep autoclave sizes and capital costs down, Newcrest's autoclaves instead rely on purified oxygen, provided by an air separation unit (ASU). This presents an opportunity to minimise the excess oxygen and therefore reduce ASU electricity consumption -- saving money and reducing GHG emissions. The variables included temperature measurements, ore flow rate, and operating pressure.
The landscape of data is ever-changing, meaning analysts need to evolve both their thinking and data collection methods to stay ahead of the curve. In many cases, data that might have been considered unique, uncommon or unattainably expensive just a few years ago is now widely used and often very affordable. It is the analysts who take advantage of these untapped data sources, while they remain untapped, who can reap the rewards by gaining a competitive advantage before the rest of their industry or peers catch on. This type of data is often referred to as alternative data, and with the ever-increasing levels of data available in the modern world comes the opportunity to gain unique insights, competitive industry advantage, and boosted profits. It is perhaps no surprise then to hear that the scramble to get hold of such data has been dubbed the new gold rush.
Someone called it "a clown car that drove into a gold mine," and like all clown cars, Twitter makes the passengers get out once in awhile. Then we can perform powerful mathematical operations on text to detect patterns and similarities, make predictions and apply categories to it. While media endorsements meant diddly squat this election cycle, the way that media and social media promoted false stories week after week to increase their eyeballs and mindshare had a huge effect. The tech platforms powering social media can help reconcile us with reality in many quiet ways, or they can join the indifferent and venal attention merchants that ushered a conman, a bigot and a sexual predator into the White House for the sake of an earnings report.
Nvidia, a publicly traded company that makes graphics processing units (GPUs), has been focusing its business more and more completely on artificial intelligence (A.I.) But the use of Nvidia's GPUs for A.I., and specifically deep learning -- an approach that involves training artificial neural networks on bunches of data, such as images, and then getting the neural networks to make inferences about new data -- has gained particular traction in the technology industry. Nvidia is hoping that government agencies start to grasp that the technology can outperform more traditional machine learning methods. In around 2011, Nvidia employees took the first steps in collaboration with Stanford computer science professor Andrew Ng to move the then-nascent Google Brain deep learning system from 16,000 CPUs onto 48 GPUs, making it faster and more cost-efficient, Dally said.