World of Watson – Talk on Data Science

Last week I had the opportunity to attend the annual IBM conference in Las Vegas. The World of Watson conference, formally known as Insight,  provided me with an opportunity to meet new interesting people, talk to colleagues and customers, learn new things and share some ideas with like-minded people. As you can imagine, with Watson being at the centre stage of the event, there were a large number of presentations, stands and marketing featuring Watson-related things: from cognitive chocolate and brews through to cognitive computing and beyond.

World of Watson Presentation
World of Watson Presentation

My session took place on Monday October 24th and I was very pleased to see a full room, and even later standing-room only just minuted before the start. We covered some of the fundamentals of data science and machine learning and took the pulse of their use in the insurance industry in particular. I then had the opportunity of sharing some of the results of the work we have been doing over the past 12 months at the Data Science Studio in London. The case studies showcased included examples in insurance, banking, wealth management and retail.

All in all, it was a very successful and enjoyable trip, in spite of the constant flashing lights of the slot machines around Las Vegas different venues.

Bluemix – a set of tools/tutorials for app development

IBM’s Bluemix provides access to a large set of API’s such as Watson services like AlchemyAPI, Natural Language Classifier, Visual Recognition, Personality Insights and more. I have recently started playing with it a bit more. You can set up a free account (free for 30 days) and see what you think.

Check it out:

 Here is what IBM has to say about it:

Bluemix is the latest cloud offering from IBM. It enables organizations and developers to quickly and easily create, deploy, and manage applications on the cloud. Bluemix is an implementation of IBM’s Open Cloud Architecture based on Cloud Foundry, an open source Platform as a Service (PaaS). Bluemix delivers enterprise-level services that can easily integrate with your cloud applications without you needing to know how to install or configure them.Bluemix

I will be happy to hear what you build and how you use bluemix. Keep in touch.

Quantum algorithms for topological and geometric analysis of data

Story Source:

The above post is reprinted from materials provided by Massachusetts Institute of Technology. The original item was written by David L. Chandler. Note: Materials may be edited for content and length.

Quantum Data Algos

From gene mapping to space exploration, humanity continues to generate ever-larger sets of data — far more information than people can actually process, manage, or understand.

Machine learning systems can help researchers deal with this ever-growing flood of information. Some of the most powerful of these analytical tools are based on a strange branch of geometry called topology, which deals with properties that stay the same even when something is bent and stretched every which way.

Such topological systems are especially useful for analyzing the connections in complex networks, such as the internal wiring of the brain, the U.S. power grid, or the global interconnections of the Internet. But even with the most powerful modern supercomputers, such problems remain daunting and impractical to solve. Now, a new approach that would use quantum computers to streamline these problems has been developed by researchers at MIT, the University of Waterloo, and the University of Southern California.

The team describes their theoretical proposal this week in the journal Nature Communications. Seth Lloyd, the paper’s lead author and the Nam P. Suh Professor of Mechanical Engineering, explains that algebraic topology is key to the new method. This approach, he says, helps to reduce the impact of the inevitable distortions that arise every time someone collects data about the real world.

In a topological description, basic features of the data (How many holes does it have? How are the different parts connected?) are considered the same no matter how much they are stretched, compressed, or distorted. Lloyd explains that it is often these fundamental topological attributes “that are important in trying to reconstruct the underlying patterns in the real world that the data are supposed to represent.”

It doesn’t matter what kind of dataset is being analyzed, he says. The topological approach to looking for connections and holes “works whether it’s an actual physical hole, or the data represents a logical argument and there’s a hole in the argument. This will find both kinds of holes.”

Using conventional computers, that approach is too demanding for all but the simplest situations. Topological analysis “represents a crucial way of getting at the significant features of the data, but it’s computationally very expensive,” Lloyd says. “This is where quantum mechanics kicks in.” The new quantum-based approach, he says, could exponentially speed up such calculations.

Lloyd offers an example to illustrate that potential speedup: If you have a dataset with 300 points, a conventional approach to analyzing all the topological features in that system would require “a computer the size of the universe,” he says. That is, it would take 2300 (two to the 300th power) processing units — approximately the number of all the particles in the universe. In other words, the problem is simply not solvable in that way.

“That’s where our algorithm kicks in,” he says. Solving the same problem with the new system, using a quantum computer, would require just 300 quantum bits — and a device this size may be achieved in the next few years, according to Lloyd.

“Our algorithm shows that you don’t need a big quantum computer to kick some serious topological butt,” he says.

There are many important kinds of huge datasets where the quantum-topological approach could be useful, Lloyd says, for example understanding interconnections in the brain. “By applying topological analysis to datasets gleaned by electroencephalography or functional MRI, you can reveal the complex connectivity and topology of the sequences of firing neurons that underlie our thought processes,” he says.

The same approach could be used for analyzing many other kinds of information. “You could apply it to the world’s economy, or to social networks, or almost any system that involves long-range transport of goods or information,” Lloyd says. But the limits of classical computation have prevented such approaches from being applied before.

While this work is theoretical, “experimentalists have already contacted us about trying prototypes,” he says. “You could find the topology of simple structures on a very simple quantum computer. People are trying proof-of-concept experiments.”

The team also included Silvano Garnerone of the University of Waterloo in Ontario, Canada, and Paolo Zanardi of the Center for Quantum Information Science and Technology at the University of Southern California.

Changing date/time in Ubuntu virtualbox

I was a bit puzzled by the fact I could not easily change the date/time in an instance of a virtualbox as used by the High Performance Scientific Computing Coursera course run by Dr. Randall J. LeVeque via Coursera.

I tried using the simple date command but I kept on being told that

date: cannot set date: Operation not permitted

I tried updating the Ubuntu distro, but no luck. Eventually I found a solution using a symlink to localtime:

$ cd /etc
$ mv localtime localtime_original
$ ln -s /usr/share/zoneinfo/Europe/London ./localtime

You will have to use the correct zone for your location. Et voilà!

Ubuntu-Desktop
Ubuntu-Desktop
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Happy birthday Turing

Today, a 100 years ago Alan Turing was born. As a form of celebration Google has put a functioning Turing machine as their latest doodle. A Turing machine is a device that uses a tape with symbols that are manipulated according to certain rules and as you can imagine it was proposed by Turing in 1936.

Turing machine

NASA Explores Semantic Search

I came across a news article about NASA using technology from Google and Smartlogic to perform semantic searches of its manned space-flight program.

Smartlogic is a UK based company and the software that NASA is using is called Semaphore which retrieves data semantically; the data is organised semantically and the search is done by parsing each sentence of the query to obtain its meaning.

The original article can be found here.