TensorFlow is an open source software library for machine learning written by Google. With TensorFlow, it is possible to create deep neural networks for speech recognition, image classification, and more. We will begin by learning how to perform simple classification tasks in TensorFlow. Once we have covered the basics, we will describe the classification task as a series of matrix operations, making it possible to run our TensorFlow code across a large number of local cores. Finally, we will see that the optimizers built into Tensorflow can be used to train almost any conceivable model in machine learning (provided the model is differentiable).

Speaking to Anton was worrying, it seems that robots are already having better outcomes as psychologists and coaches. Which doesn't bode that well for me, time to consider what other skills I have that a robot doesn't. Artificial intelligence is already being used to deliver services that people once did, however, the surprising impact is that it is the professional services that are currently being hit the hardest. Professional services such as lawyers, doctors, and psychologists are the target of the first wave of the implementation of artificial intelligence. To give you an example, a chatbot lawyer recently overturned 160,000 in parking fines.

Cognitive computing – technologies that can learn and reason – are being applied with increasing frequency by leading Fortune 1000 and Global 2000 companies. IDC, the highly respected technology research firm, estimates that by 2020, 50 percent of all business analytics software will incorporate cognitive computing functionality.[1] It promises a dramatic shift in technology's role in the business. Cognitive technologies go past automation and analytics – providing a solution that can actually understand, learn, and think through any objective, process, problem, or question you present. Having worked in the procurement profession for years, it's clear to me that cognitive technologies will change how procurement operates and disrupt industries, just like major technological innovations that have come before (e.g., e-sourcing, the Internet, cloud-based solutions).

The Stanford Artificial Intelligence Laboratory's Outreach Summer (SAILORS) program was born in 2014 when then-Ph.D. student Olga Russakovsky was in search of a way to make an impact outside of writing another research paper. What she and Fei-Fei Li, director of Stanford University's Artificial Intelligence Lab, created was a two-week summer day camp for 10th grade girls centered on how artificial intelligence can change the world. This July marked the second year of the program. "It seems like a lot of girls are interested in these fields, but then drop out as their education progresses," says Russakovsky. "We created a camp centered around teaching AI from a humanist prospective."

Last week, recently released sci-fi movie Morgan unveiled a new trailer. But there was a twist: the trailer was created by an Artificial Intelligence. Producers enlisted the help of IBM's Watson – an advanced data processing AI – to come up with the clip. Watson poured over hundreds of sample trailers, analysed them all, and used machine learning to come up with an idea of how the perfect trailer should look and sound. Watson was allegedly able to determine what makes a moment eerie, how the music and actors' tone of voice changed the mood, and how technical aspects came together to make a complete trailer.

DEDHAM, MA–(Marketwired – Sep 7, 2016) – Rage Frameworks, a provider of knowledge-based automation technology and services, today announced that a leading multinational financial services firm has selected its Artificial Intelligence platform (RAGE AI) to drive improved results for its investment customers by using artificial intelligence to discover signals captured in a wide variety of data sources with Rage's innovative deep learning capabilities. RAGE AI significantly extends the frontier of deep learning and machine intelligence technology as it incorporates proprietary linguistics-based machine learning innovations to understand market developments in the context of individual companies and interpret those signals as a human would. After demonstrating via historical back-testing that the Rage AI platform repeatedly delivered returns in excess of what the firm's quantitative team was able to produce, Rage's solution was integrated in order to drive significant lift in the returns generated for the firm's clients. In fact, Rage has repeatedly shown that its deep background in computational linguistics and Natural Language Understanding can systematically discover Alpha by forming assessments of a company's financial projections that effectively predict future performance for businesses such as Wal-Mart (attached), where Rage AI predicted an upward trend in stock price months in advance. The RAGE AI platform does this by continuously interpreting unstructured content from over 100,000 sources and translating it into valuable intelligence.

On a summer day in 1968, professor Julian Stanley met a brilliant but bored 12-year-old named Joseph Bates. The Baltimore student was so far ahead of his classmates in mathematics that his parents had arranged for him to take a computer-science course at Johns Hopkins University, where Stanley taught. Having leapfrogged ahead of the adults in the class, the child kept himself busy by teaching the FORTRAN programming language to graduate students. Unsure of what to do with Bates, his computer instructor introduced him to Stanley, a researcher well known for his work in psychometrics--the study of cognitive performance. To discover more about the young prodigy's talent, Stanley gave Bates a battery of tests that included the SAT college-admissions exam, normally taken by university-bound 16- to 18-year-olds in the United States.

Google is now providing more information to website owners whose online properties are temporarily blocked as unsafe by its Safe Browsing technology as a way to help them fix the identified problems faster. Google Safe Browsing is a technology used by Google's search engine, the Google Chrome browser, Mozilla Firefox, Apple Safari, and Android to steer users away from websites that host malicious or deceptive content. On the back-end, Google uses robots to scan the web and build a list of websites that host malware, harmful downloads, or deceptive ads and pages. Software developers can then plug into an API to integrate this list into their own applications. The problem is that many websites hosting malware or bad ads don't do so intentionally but were hacked by attackers.

It's all over but the waiting for Apple fans, who should get to see two new models of the iPhone unveiled Wednesday in San Francisco. The launch event may provide some clues about Apple's future, as the company deals with a slowing smartphone market. Apple's iPhone sales have dropped over the past year for the first time in the device's history. As a result, the company has poured more effort into services such as Apple Music, its voice assistant, Siri, and smart-home management -- all as a way to make users even more reliant on iPhones, regardless of whether they are the latest model. Consumers may already have seen a glimpse of Apple's future this summer when the company showed off how its mobile operating system, iOS 10, which will allow outside developers to use Siri more deeply for their own apps and create new functions for Apple's Messages service.

"The future is independent of the past, given the present." Orthography encapsulates a set of conventions for a written language, which includes spellings, punctuation, hyphenation, capitalisation, and other features. For example, in English, we begin a sentence with a capital letter and have spaces between words; each word is spelt in a unique way (most of the times), and we use commas to separate clauses and mark the end of a sentence with a period. Reading about the history of English spelling is fascinating. You probably know Geoffrey Chaucer for his collection of short stories, The Canterbury Tales.