With Amazon Machine Learning (Amazon ML), you can build and train predictive models and host your applications in a scalable cloud solution. In this project, you will use the visualization tools and wizards of Amazon ML to guide you through the process of creating a new machine learning (ML) model without having to learn complex ML algorithms and technology. To complete this project, you will download freely-available sample customer data and upload the data to an Amazon S3 bucket to create a datasource. You will then create an ML model from this datasource, from which you can then evaluate and adjust the ML model's performance, and then use it to generate predictions.

Databricks, corporate provider of support and development for the Apache Spark in-memory big data project, has spiced up its cloud-based implementation of Apache Spark with two additions that top IT's current hot list. The new features -- GPU acceleration and integration with numerous deep learning libraries -- can in theory be implemented in any local Apache Spark installation. But Databricks says its versions are tuned to avoid the resource contentions that complicate the use of such features. Apache Spark isn't configured out of the box to provide GPU acceleration, and to set up a system to support it, users must cobble together several pieces. To that end, Databricks offers to handle all the heavy lifting. Databricks also claims that Spark's behaviors are tuned to get the most out of a GPU cluster by reducing the number of contentions across nodes.

Today, the virtual assistant landscape is exploding with innovation: New applications and new forms of interaction are constantly emerging. Although the idea of a virtual assistant is decades old, it went mainstream with Apple's introduction of Siri. Siri was created at SRI International based on years of AI research, spun off as an independent venture-backed company in 2007, and acquired by Apple in 2010. The Siri that the world knows enables users to quickly find information and execute important device functions in a fast and friendly way. But Siri was first developed as a "do engine," similar to the emerging crop of AI assistants.

The CEO and founder of cloud-based accountancy software giant Xero says artificial intelligence (AI) and machine learning technologies will be "transformational" for finance over the next few years. Rod Drury told Business Insider during a recent interview in London: "We'll see more innovation in the next 2 years than we have in the last 10 years, all driven by AI." The Xero founder says: "We're getting a massive hit on the R&D we've done around machine learning and AI. We think it's going to be transformational for the industry. "If you capture information from the bank statement and the invoice and the bills that are flying through, you can actually programme things to do a whole lot of work for you and you're just checking and making fixes, which trains the machine." Xero's accountancy software helps small and medium-sized businesses manage their accountants in the cloud but Drury believes much of the management -- things like categorizing expenditure and sending accounts to be checked -- could be automated by "smart" AI and machine learning programmes, which learn the habits of your business. "You can build unique system for each business," says Drury. "The first innovation in cloud accounting was actually getting these transactions into the cloud.

Artificial Intelligence (AI) has always been the subject of dreams and visions about the distant future of humankind. Even though we are nowhere near a conscious robotic system, nowadays, AI systems are ubiquitous and showing tremendous successes in various fields of our everyday life. We are using these on a daily basis, often without even noticing. Whether it is the Virtual Personal Assistants on our mobile phones (such as Siri, Google Now, and Cortana), self-driving cars, the ranking of the web pages given your search query, or the classical textbook examples such as spam filtering and recommendation systems of online media providers and marketplaces like Amazon. Various fields of AI have made a major leap forward in the recent years. As most AI systems are too complex to be defined manually, we have to resort to automatically learning rules and patterns from data using sophisticated Machine Learning (ML) techniques.

But that is not to say it is perfect by any stretch of the imagination. "Deep learning has led to some big advances in computer vision, natural language processing, and other areas," Tommi Jaakkola, a Massachusetts Institute of Technology professor of electrical engineering and computer science, told Digital Trends. "It's tremendously flexible in terms of learning input/output mappings, but the flexibility and power comes at a cost. That is it that it's very difficult to work out why it is performing a certain prediction in a particular context." This black-boxed lack of transparency would be one thing if deep learning systems were still confined to being lab experiments, but they are not.

One of the biological side effects of being a human is the will to live. Luckily for us, one of the ways in which our brain gives the heads up to inform us of potentially dangerous situations is by invoking that little old survival instinct called "fear". Have you ever been stuck sitting next to someone in a cinema, completely unfazed by a horror movie, while you diverted your attention to the closest escape door? Everyone gets spooked by out by different stimuli – whether rational or irrational – clowns, gigantic spiders, or even marshmallows. Since we know that stimuli can evoke varying psychological responses, one group of researchers from our team at Data61 and MIT Media lab, set out to find what unites us in our phobia and terrifies us on a universal scale.

Columnist Ed Baig reviews Pixel, which features the high-IQ Google Assistant and a competitive, high-end smartphone camera. A. When Google introduced its Pixel and Pixel XL phones in early October, it picked a hybrid distribution strategy. Instead of selling these $649-and-up smartphones only on its own site, as it had with its earlier Nexus phones, it also signed up Verizon Wireless as a distribution partner. To judge from the ads during the World Series, only the second purchase option exists. They keep touting the Pixel -- "a winner for anyone looking for an excellent phone," USA TODAY's Ed Baig wrote -- as "only on Verizon," something Verizon's own page about the phones repeats.

Jefferson Graham reports on the new, higher price-tags for Apple computers, and compares them to Windows and Chromebook competitors on #TalkingTech. SAN FRANCISCO -- A funny thing happened when Microsoft and Apple held dueling product events last week. In Cupertino, Calif., the iPhone maker was making a small tweak to the way we work today with the unveiling of a slim interactive function bar to its MacBooks. In New York, the onetime software giant was unveiling tools for the way we will work that included a massive interactive drafting table and 3-D design software. But evidence is mounting that the software giant, a foil to Apple for decades, is now the more compelling, innovative company with forays into virtual reality and artificial intelligence.

Robots are learning to create zombie faces and apocalyptic landscapes, and with your help, they can make them even more terrifying. Researchers from MIT and Australia's CSIRO have created the Nightmare Machine, an AI algorithm that can transform a normal face or landscape into nightmare fuel. The AI analyzed 200,000 normal human faces and was soon able to generate its own, but the team wanted to take it in another, freakier direction. "We want to produce scary faces," Dr. Manuel Cebrian told the Sydney Morning Herald. "So we take a zombie face –- a really scary one –- and feed it into the neural network."