IBM (NYSE:IBM) has launched a new Watson initiative, called "Project DataWorks." For growing revenues and profitability, modern businesses depend on extracting insights from data, which is an extremely complex job. Project DataWorks is a comprehensive solution aiming to eliminate the complexities. Project DataWorks is available on IBM's cloud platform Bluemix. I believe this new offering will help IBM significantly grow its business analytics revenue, which was 17.9 billion in 2015.

The WHERE clause in SAS is a powerful mechanism for selecting observations as you read or write a data set. The WHERE clause supports many operators, including the IN operator, which enables you to compactly specify multiple conditions for a categorical variable. A common use of the IN operator is to specify a list of US states and territories that should be included or excluded in an analysis. For example, the following DATA step reads the Sashelp.Zipcode data, but excludes zip codes for the states of Alaska ("AK"), Hawaii ("HI"), and US territories such as Puerto Rico ("PR"), Guam ("GU"), and so on: In my previous article about how to use the WHERE clause in SAS/IML, my examples used scalar comparisons such as where(sex "F") to select only females in the data. The SAS/IML language does not support the IN operator, but there is another compact way to include or exclude multiple values. Because SAS/IML is a matrix-vector language, many operations support vector arguments.

The startup-within-a-big-company is a narrative that's becoming increasingly popular, but Sohel I S, CEO of the property portal HDFC RED, feels that six years on, the mindset genuinely applies to his organisation, where the average age of the team is still 28. "We're able to make decisions quickly and don't have to go through so much hierarchy and we've had to be very fiscally responsible," Sohel tells Gadgets 360. This also helped the company have a relatively narrow focus from the beginning, something he says helped a lot. While many of the best known companies in the property space in India got their start in the rental market, HDFC RED stayed out of that segment, focused instead on the buying and selling of private homes from the beginning. Last year, Housing.com announced layoffs and shut down its rentals; visit most of the other popular sites and the first option you now see is "Buy".

The focus here is on data: from R tips to desktop tools to taking a hard look at data claims. R users can now use the popular dplyr package to tap into Apache Spark big data. The new sparklyr package is a native dplyr interface to Spark, according to RStudio. After installing the package, users can "interactively manipulate Spark data using both dplyr and SQL (via DBI), according to an RStudio blog post, as well as "filter and aggregate Spark data sets then bring them into R for analysis and visualization." There is also access to Spark distributed machine-learning algorithms.

From Apple s Siri to Google Allo, we are in the age of artificial intelligence, and it is getting integrated into our daily routines. Similar trends can be seen in the way we do our sales. Yes, you heard it right -- artificial intelligence is shaping our sales strategy. Right from sales prospecting to closing deals automatically, it has brought about a transformation. There is no need to fear for your jobs, however; artificial intelligence is only going to help those in sales focus on chasing the right customers and closing deals faster.

SAN FRANCISCO: Major technology firms are racing to infuse smartphones and other internet-linked devices with software smarts that help them think like people. The effort is seen as an evolution in computing that allows users to interact with machines in natural conversation style, telling devices to tend to tasks such as ordering goods, checking traffic, making restaurant reservations or searching for information. The artificial intelligence (AI) component in these programmes aims to make create a world in which everyone can have a virtual aide that gets to know them better with each interaction. Google is making a high-profile push into AI, with the internet titan's chief referring to it as a force for change as powerful as powerful as smartphones. Google Assistant software is being built into new Pixel handsets - aiming to outdo Apple's Siri - enabling users to organise and use information on the devices and in the cloud - to check emails, stay up to date on calendar appointments, news or ask for traffic and weather data.

I really enjoy my TurtleBot. I haven't programmed it to do anything very useful, like bringing me coffee, but it's still a lot of fun: It lets even a n00b like me explore and learn a bit about ROS, or Robot Operating System, the influential software platform used by a growing number of robotics researchers and companies around the world. My kids seem to like the TurtleBot, too. It's now decorated with "Frozen" stickers and a drawing of what I assume is Elsa's face. Now, after nearly three years, ElsaBot needs an upgrade.

Video Friday is your weekly selection of awesome robotics videos, collected by your Automaton bloggers. We'll also be posting a weekly calendar of upcoming robotics events for the next two months; here's what we have so far (send us your events!): Let us know if you have suggestions for next week, and enjoy today's videos. "Current and previous single-legged hopping robots are energetically tethered and lack portability. Here, we present the design and control of an untethered, energetically autonomous single-legged hopping robot. The thrust-producing mechanism of the robot's leg is an actuated prismatic joint, called a linear elastic actuator in parallel (LEAP). The LEAP mechanism comprises a voice coil actuator in parallel with two compression springs, which gives our robot passive compliance. An actuated gimbal hip joint is realized by two standard servomotors. To control the robot, we adapt Raibert's hopping controller, and find we can maintain balance roughly in-place for up to approx. If you have a robot that runs ROS and makes maps, you've likely been using GMapping, which gives you very GMapping-y results. Google has just released its own open source ROS-based real-time 2D/3D SLAM library called Cartographer, and it already has support for PR2, TurtleBot, Revo LDS (aka Neato's lidar), and even TRI's HSR: POW! For more details, read this 2016 ICRA paper. "Toyota Motor Corporation plans to launch sales of its compact and cuddlesome'Kirobo Mini' communication partner through Toyota vehicle dealers across Japan in 2017.

Enterprise applications trending to adopt Machine Learning as their strategic implementation and performing machine learning deep analytics across multiple problem statements is becoming a common trend. There are variety of machine learning solutions / packages / platform that exist in market. One of the main challenges that the teams initially trying to resolve is to choose the correct platform / package for their solution. Based on my limited experience with different machine learning solutions I thought to write this blog to list out the points (features in machine learning term) to consider while choosing a specific ML platform and list pros and cons of each of the solutions in market. Let's look at feature set to be weighted before deciding a ML solution Now let's look at the different machine learning solutions / platforms available in the market and where they stand with respect address the feature requirements.