"Microsoft Monday" is a weekly column that focuses on all things Microsoft. This week, Microsoft Monday includes details about the new Xbox dashboard rolling out, the KRACK Wi-Fi vulnerability being patched, new tree house offices, four new Xbox One S bundles, 62 vulnerabilities fixed in the "Patch Tuesday" update, Cortana integration in Skype, a machine learning partnership with Amazon, several major LinkedIn updates and much more! Microsoft is now rolling out the new Xbox dashboard for all users. The new Xbox dashboard features Microsoft's "Fluid Design" interface. There are four areas in the Xbox dash: the first area lets you resume what you were playing quickly, the second and third areas are suggestions for friends and the fourth area highlights deals and offers. And there is a horizontal strip at the bottom with most recently used content. The new Xbox Dashboard also has a new feature called "Content Blocks." Each content block has large visuals focused on a game, a friend or what is happening in the Gold Lounge.

It was found out over the weekend that Samsung Electronics apparently invested in a Chinese artificial intelligence startup called DeePhi Tech in August. Industry sources are now claiming that the South Korean company's move was likely due to political consideration. In an interview with The Korea Herald, one industry source disclosed that Samsung made a big investment in the Tsinghua-based startup that focuses on deep learning technologies. However, the decision to invest in the 1-year-old company is said to be not primarily due to DeePhi Tech's expertise. Instead, it is believed to be politically motivated.

The study analyzes how the advancements in technology and its increased penetration in the education market, institutions have begun to experience a rapid change in the teaching delivery model. Governments over the world are concentrating on building up a computerized instruction condition through gifts and subsidizes, bringing about an expansion in the money related help for instructive foundations particularly those working in developing regions. This has helped numerous foundations to adjust to current and progressed instructive techniques. The 76-paged, comprehensive report added to the Education archive offers predictions and future prospects of the industry, including market size and share on account of risk factors, market trends and opportunities, pipeline products and technological innovations. NLP is the field of software engineering, counterfeit consciousness and computational semantics that are related with the collaborations amongst PCs and human.

The Big Data Professors at IE are all working professionals or researchers in the field, so they use countless examples to show us how the concepts taught in class are being applied in the real world. Use cases will be divided by "function", but you can expect to see examples of big companies, startups, NGOS, and individuals. The focus is to understand not just the impact, but also the Ripple Effect of AI and IOT innovations. The UN predicts that half the world's population will live in a water-stressed area by 2030. Therefore, private and public organizations are coming together to find solutions.

IBM has spent the past several years putting a laser focus on what it calls cognitive computing, using its Watson platform as the foundation for its efforts in such emerging fields as artificial intelligence (AI) and is successful spinoff, deep learning. Big Blue has leaned on Watson technology, its traditional Power systems, and increasingly powerful GPUs from Nvidia to drive its efforts to not only bring AI and deep learning into the cloud, but also to push AI into the enterprise. The technologies are part of a larger push in the industry to help enterprises transform their businesses to take advantage of such trends as the rise of the cloud, the increasing use of mobile technologies and the skyrocketing growth of data that is being generated by these companies and needs to be processed and analyzed. Much of the work with AI, deep learning and analytics have been done in the cloud, promoted by hyperscale cloud providers like Amazon Web Services (AWS), Microsoft Azure and Google Cloud. IBM also has put many of its capabilities into its own cloud.

Deep learning is having a large impact on the field of natural language processing. But, as a beginner, where do you start? Both deep learning and natural language processing are huge fields. What are the salient aspects of each field to focus on and which areas of NLP is deep learning having the most impact? In this post, you will discover a primer on deep learning for natural language processing.

The pace of technology-driven change is accelerating for enterprises all around the world. While the idea of artificial intelligence (AI) has been around for nearly 70 years, it wasn't until 2017 that we found 72 percent of business leaders believed AI to be a competitive advantage in the future (if not already), according to a recent PwC AI survey. In response, it's critical for companies to iteratively shift paradigms from legacy approaches to better compete in the age of digital transformation. Evolving software algorithms, capable of performing tasks typically requiring human intelligence, are fueling a wave of advancements in visual perception, speech recognition, decision-making, language translation, robotics and autonomous vehicle capability. Though AI is the catchphrase for numerous subfields, machine learning and deep learning are garnering the most attention as they teach themselves to learn, reason, plan and ultimately become more intelligent when exposed to bigger, more refined data sets and a standard predictive analytics model.

Text Classification is the task of assigning the right label to a given piece of text. This text can either be a phrase, a sentence or even a paragraph. Our aim would be to take in some text as input and attach or assign a label to it. Since we will be using Tensorflow deep learning library, we can call this the Tensorflow text classification system. This task involves training a neural network with lots of data indicating what a piece of text represents.

Suddenly, artificial intelligence is everywhere. Are you AI ready if not then be ready to be read in history books. Are we not missing the fact that artificial intelligence is about the people, not the machines. Technology and non technology companies are now investing and brining out the real and materialistic values of Artificial Intelligence to the real world. Its almost after a frustrating and hard work of decade AI has started delivering values.