Mahinda Rajapaksa the best of the best: https://youtu.be/ge9GrDOjIfQ
Daily Archives: April 16, 2015
Quick – think of a robot, any robot.
If you’re into movies, you might imagine the android from the new movie Chappie, a machine with artificial intelligence that learns morally questionable behavior. If you think more about industry, you might imagine a mechanical arm programmed to install parts on a production line. If you have dirty floors, you might think of a Roomba.
What do these and other robots have in common? What is it about them that makes them a robot? Finding an all-encompassing definition of a robot is actually a difficult problem, even for world-class roboticists. Form-factors, intelligence, and the purpose of robots can all vary significantly. And yet many of us think we know a robot when we see one. How is this so?
For Westerners at least, our working cultural definition owes a lot to robots in stories and film, as well as real-life robots past and present. But it’s worth looking further for a more considered definition, starting with the origin of the word itself.
Before robot meant what it does today, the word meant “forced labor” or “hard work.” The robot was a central European system of serfdom – according to the Oxford English Dictionary – abolished in the Austrian Empire in 1848.
Then, in 1920, a Czech writer named Karel Čapek wrote a play called Rossum’s Universal Robots, coining a new meaning for the word. In R.U.R., as it’s known, Čapek’s robots were mass produced workers assembled from artificially synthesized organic material. The play featured the first robot uprising, and the genre of dystopian robot sci-fi was born. Descendants include Terminator and Battlestar Galactica, among others.
While some research groups are working hard to make highly intelligent humanoid robots as those depicted in R.U.R., most real-life robotics efforts are decidedly less dramatic. A good place to find the staid, real-life state of robots is the International Federation of Robotics, or IFR. Helpfully, the IFR categorizes today’s robots into two major categories: industrial robots and service robots.
The IFR defines an industrial robot as “an automatically controlled, reprogrammable, multipurpose manipulator programmable in three or more axes, which may be either fixed in place or mobile for use in industrial automation applications.” For years industrial robots were all that a real robot could be.
The first industrial robot was installed in a Swedish metalworks plant in 1959. It was a jointed, actuated arm that weighed two tons. Controlled by a program on a magnetic drum, the robot relied on hydraulic actuators to adjust its position over a set of pre-programmed joint angles. It was precise, but not necessarily elegant.
By 1973, there were 3,000 industrial robots in operation. By 2003, there were 800,000. Today, more than 1.3 million industrial robots are in use or available in various industries including automotive, electronics, rubber and plastics, cosmetics, pharmaceutical, and food and beverage. Their market value is $9.5 billion. (A more complete history can be found here.)
Industrial robots will always have a place in the economy, but the relative newcomers on the scene are service robots. This category, according to the IFR, is populated by autonomous machines that complete tasks outside industrial applications. This means service robots are found in personal and professional settings: a telepresence robot at work, a robot in the operating room, an educational robot helping students learn to write code, a research robot exploring the ocean, a robot in space helping astronauts make repairs, and so on.
The industrial vs. service distinction is helpful because it defines robots based on their relationship with people and work more than around any technical factor. Combining industrial and service robots, we can generalize to offer a basic definition of a robot as an artificially created system designed, built, and implemented to perform tasks or services for people.
There are echoes of the original meaning of the word robot here, as robots are doing labor and hard work. And while this labor has historically been physical, we might also consider that robots needn’t have actuating limbs.
Much of work today is knowledge work, therefore the definition of a robot should extend even to automated computer programs to include cognitive computing, which describes IT systems that can sense, comprehend, and act. This includes pre-programmed Twitterbots on the low end and IPSoft’s Amelia artificial intelligence system on the high-end. Across the spectrum, though, robots perform rule-based work, and tend to be configurable with basic features like authentication, security, auditing, logging, and exception handling.
But even this broad definition will have to evolve as robots progress. What should we expect from machines built to be stronger and smarter than the people who made them? Will they always be limited to doing work for people? It’s a question that conjures Čapek’s robot uprising, and has prompted many essays invoking Mary Shelley’s Frankenstein, among other texts of monsters and unintended technological consequences.
It’s with good reason engineers, scientists, writers, ethicists, and philosophers are considering the ramifications of advanced robotics and artificial intelligence. Even if real robots are unlikely to match their dystopian sci-fi counterparts anytime soon, they still disrupt economic sectors and directly affect the way people live and work.
Some clues to our robot future could come from an emerging field called “wise computing,” presented at the recent annual meeting for the American Association for the Advancement of Science (AAAS) in San Jose, Calif. Wise computing as a research field originated in Japan, where cultural attitudes toward robots are less fraught as in Western countries.
The movement’s aims are to investigate the ethical, legal, and social relationships between humans and machines, to develop machines that can make decisions with a kind of programmatic wisdom, and to help humans make wiser decisions themselves. At the AAAS panel, researchers from industry and universities in Japan and the UK discussed the possibilities and challenges of such an approach.
While it might not catch on in the western world anytime soon, wise computing offers an intriguing modification to the western cultural definition of robots. Imagine: Future robots could be built to include a kind of ethical clause that limits what they are allowed to do. As we progress with these technical, social, and ethical challenges, our definition of what a robot is will have to change too.
Mahinda Rajapaksa the best of the best: https://youtu.be/ge9GrDOjIfQ
IT majors are providing hyper-converged infrastructure appliances that help organisations streamline deployment and scale out of software-defined IT infrastructure
With increasing organisational complexity, companies are becoming more open to the value of seamless and transparent architecture and delivery platforms.
As such, several IT majors are entering this arena by providing hyper-converged infrastructure appliances that help organisations streamline deployment and scale out of software-defined IT infrastructure at the speed of business.
Take the case of VMWare. The company recently announced the availability of VMware EVO: RAI for the Indian market through its Qualified EVO: RAIL Partners.
The aim is to help midsize businesses that require flexible and open architecture to simplify IT operations and transform the speed and efficiency of application service delivery.
“With this, VMware and its Qualified EVO: RAIL Partners are bringing the simplicity of consumer appliances to the world of enterprise infrastructure. VMware EVO: RAIL is a new building block for software-defined data centre environments that take the guesswork out of building, deploying, scaling and managing software-defined infrastructure services,” said Arun Parameswaran, managing director, VMware India.
On similar lines, SAP delivered its new generation planning in cloud earlier this year. It’s called the SAP HANA Cloud Platform.
“The results of our recently published research on next-generation business planning underlined the importance of using a dedicated planning application with advanced analytics and collaboration-in-context capabilities,” said Robert Kugel, senior vice president and research director, Ventana Research.
“Data showed there is a correlation between the use of advanced analytics, more effective collaboration, gaining accuracy and agility in a company’s planning processes.”
The new solutions are centered on the user so as to enable a natural flow among analyses, planning, collaboration, consumption and impact delivery of information. And this is where skill requirements will have to change.
“Yes, we do need specialists (in IT) but we are also looking for people who can stitch together across platforms and offerings,” said Ganesan K, CEO, GA Software Technologies, at the TimesJobs.com Industry-Academia Connect 2015, a platform for HR professionals to synergise and exchange ideas.
“This is a critical success factor – whether in BI, innovation or design expertise,” said Puneet Aggarwal, HR head, eNT Data Management Solutions.
“Much more than technical issues, a lack of this alignment is the biggest reason for dissatisfaction with client servicing initiatives,” he said.