Three big themes at CES in Las Vegas for enterprises to watch look to be big data, connected devices or the Internet of Things, and artificial intelligence (AI), and sometimes the combination of all three. CES is one of the largest and most popular technology trade shows offering the latest gadgets for both consumers and IT business professionals and the 2017 edition opens to the public Jan. 5. This year, enterprise IT department specialists can expect to see the continued reign of data collection, connected devices and artificial intelligence (AI) – and combinations of all three. IBM Corp., for example, has placed a special focus on encouraging companies to become what it calls a "cognitive business" through using its Watson AI system to understand, reason, learn and make sense of collected data. IBM says this will allow companies to "improve business outcomes and increase revenue."

Not a day goes by when we don't hear of something related to artificial intelligence in the news. But AI (sometimes confused with machine learning, which is simply a technique within AI) wouldn't be where it is today if it weren't for one seminal event in 2016: AlphaGo beating Lee Sedol. In March last year, an AI program that trained itself to play the ancient game of Go beat the 18-time world champion. The reason it was such a feat for AI, was because Go is about feel, strategic judgment and winning multiple battles across the board – and a computer cannot simply memorise all possible combinations of board pieces, assess the situation, construct and execute a strategy to win, like chess. So the programmers of AlphaGo, from Google DeepMind, set up the basic heuristics of the game, allowed AlphaGo to analyse previous games and then split its brain so it could play itself millions of times.

NEVADA – Toyota Motor Corp. has unveiled a concept car with built-in artificial intelligence and autonomous driving technology designed to interact with the driver. The Wednesday unveiling of the Concept-i, which the automaker says can read its driver's personality and emotions, came ahead of the opening Thursday of the Consumer Electronics Show, an annual global trade show held in Las Vegas. By learning about the driver through "chats" using its AI system and monitoring facial expressions, the car will engage in conversations on topics that suit the driver's taste and propose driving routes that include their favorite areas, the carmaker said. The car will also flash lights if it detects a certain level of driver fatigue, play relaxing music to reduce tension and shift to autonomous driving if the driver is at risk. Toyota is aiming to build an experimental vehicle that features some aspects of the Concept-i within the next several years and test its performance in Japan.

Amazon's Alexa and Google's virtual assistant have already made their way into our living rooms, but Chinese tech giant Baidu is betting that verbal answers may not always be enough. The company is launching a new home-centric computer that includes a screen for displaying helpful information in response to voice commands. Baidu is teaming up with Chinese consumer tech company Ainemo to launch the device, called Little Fish, which is being positioned as a voice-centric home robot. Ainemo created the hardware, while Baidu created the operating system that powers it. The computer, about the size of a lamp, is designed to handle many of the same tasks one might expect from such a device: managing calendars, answering questions, getting news updates, and ordering food, among other tasks.

Wearables are ubiquitous; everyone worth their salt is jumping on the Internet of Things (IoT) bandwagon; and Augmented Reality (AR) is here to stay. These are the current favorite trends in the industry; and based on what we've seen in the recent years, we think it'll be mostly how businesses apply these trends that will drive the growth of these technologies, not the end users. And here is why - the data generated by these three technologies is incredibly voluminous, we all know that. It might not be of much use to an individual user, but in large volumes can be incredibly useful to businesses. If we can handle its relentless onslaught, this data can especially provide us deep real-time analytical insights that can help brands understand their consumers far better and make data-driven decisions. Data-converging platforms that will converge the influx of all connected data will rise in 2017, fuelled by the demand to tame this massive data.

So, you want to learn how to build machine learning algorithms? But where do you start? Becoming a data scientist is a really smart career move – it's possibly one of the most valuable jobs out there. That's just one of the reasons it was hailed by the Harvard Business Review as the'sexiest job of the twentieth century' back in 2012. But learning the skills you need to become a truly great data scientist, capable of building powerful machine learning systems with languages like Python and R, isn't easy.

In 2016, the White House recognized the importance of AI at its Frontiers Conference. The concept of driverless cars became a reality, with Uber's self-driving fleet in Pittsburgh and Tesla's new models equipped with the hardware for full autonomy. Google's DeepMind platform, AlphaGo, beat the world champion of the game--10 years ahead of predictions. "Increasing use of machine learning and knowledge-based modeling methods" are major trends to watch in 2017, said Marie desJardins, associate dean and professor of computer science at the University of Maryland, Baltimore County. How will this play out?

Michio Kaku, a noted theoretical physicist and futurist, predicts, "The job market of the future will consist of those jobs that robots cannot perform." Robots have recently entered the legal workplace, performing several tasks once assigned to newly minted law grads. What does this mean for current and future lawyers? Simple answer: robots will not replace lawyers but they will work with them. Technology has already produced a new class of support professionals that work with lawyers -- just as techs work with doctors in healthcare delivery.

Intel has been on a multi-year journey to diversify themselves from a PC and server play to an IoT leader spanning the endpoint to the datacenter and everything in-between. So far, the company has seen its biggest differential success in the data center maintaining their giant compute share and growing in networking and storage and just laid out their AI strategy. They've done well in industrial strength IoT gateways and end points like security cameras where performance matters but of course, intend to go further. Intel has one big tier 1 4G LTE design win in the Apple iPhone 7 and needs to prove it's more than a one hit wonder. In 5G, Intel is way ahead of where they were with 4G at this point in the standard development process, too.

Here is where we take advantage of AzureMl's newest feature: the Create R Model module. Now we can use R's randomForest library and take advantage of its large number of adjustable parameters directly inside AzureML studio. Then, the model can be deployed in a web service. Previously, R models were nearly impossible to deploy to the web. For a detailed explanation of setting up data partitions and model training checkout our other tutorial here.