10.13.2014

The possibilities of Project Lucy


The TED Institute micro-documentary on Project SyNAPSE gave us a look at the future of cognitive computing, with glimpses at some possible practical applications. Those exciting possibilities become positively exhilarating in the Project Lucy micro-documentary, which gives us an idea of the potential for cognitive computing to transform a continent.


The project is a collaboration between IBM researchers in Africa and the company’s business and academic partners to apply IBM Watson to the continent’s biggest challenges. The goal is to use Watson to discover insights from big data and develop commercially viable solutions in the areas of energy, healthcare, water and sanitation, agriculture, human mobility and education. 

It is this last area that is the particular focus of IBM researcher Dr. Charity Wayua. In the film, the Kenya-based Wayua lays out the ambitions for cognitive computing to give teachers greater ability to deal with crowded classrooms. Armed with data-based insights, teachers can address needs and situations on a student-by-student basis.

While Africa’s challenges are daunting, it is far from the only place where classrooms are overcrowded, teachers are overstretched, and children are underserved. The potential impact on Africa’s education systems is awesome to contemplate, and it’s easy to see how the benefits could be replicated around the globe. Add in the other challenges Project Lucy is tackling and the potential for cognitive computing to improve the lives of millions becomes even greater. 

“For the African continent,” said Wayua, “I think this is going to be our 'big bet' on transformation.” If that big bet pays off, it won’t just transform Africa, it will transform the world.

Editor's note: This article is by Jonathan Batty, external relations leader for IBM's global labs.

10.08.2014

Multilingual Watson

Learning to understand the human gift of language

DJ McCloskey, IBM Watson Group
Machines use programming languages to at least appear to understand our human languages. IBM Watson is one of the most sophisticated, helping everyone from healthcare providers to sous chefs by using several programming languages and algorithms to read and comprehend natural language. But the system could only answer questions posed in English – until now.

Natural Language Processing architect D.J. McCloskey leads a team “teaching” Watson the fundamental mechanisms to comprender español, entender português, 日本語を理解する(understand Japanese), and many other languages.

“Back in the late 1990s and early 2000s, the notion of a machine reading text was primarily defined by creating search indexes out of the words in text. We wanted to take it one step farther where ‘reading’ actually meant ‘understanding’ the text. So, we created LanguageWare in 2001, a technology that could automate fact extraction from the text,” D.J. said.

LanguageWare established a lightweight, optimized library of functions for processing natural language text, using a set of generalized structures and algorithms that captured the essence of language. Multilingual by design, this foundation gave LanguageWare a way to process text from any language so that a machine could understand the atomic sentence context, and build semantic understanding of that sentence in any language.

But D.J.’s team developed this sophisticated tooling with the mantra of “involve the humans” in mind. By letting humans teach the machines everything about language – from word morphology, to knowing the difference between “run” and “running” and “goose” and “geese,” and transcribing the knowledge of domain experts (learning from a subject’s human masters) – the system can then detect accurately worded facts in text, such as negative reactions to a drug, or an acquisition of one company by another. Today, Watson’s entire suite of cognitive capabilities uses and extends this tooling.

“And in Watson we have employed this capability to capture and apply precise knowledge from oncology experts, providing a way for human experts to teach the system at a deep level,” D.J. said.

Gluing it together with open architecture

These analytics and algorithms work together on top of Apache’s Unstructured Information Management Architecture, or UIMA (“you-ee-mah”). Its open architecture gave LanguageWare back in 2001, and Watson today, a way to combine their analytics with other complementary analytics to rapidly collaborate and prototype new ideas – a way to end up with a whole much greater than the sum of its parts, like the ideas from the Watson Mobile Challenge.

“I remember trying to convince people of the viability of machines understanding unstructured data, pre-Watson,” said D.J. “And then Watson (and UIMA) happened, and now people believe it can cure cancer, and make our tea!

“Amazingly enough, the power of this technology actually has potential to help do both – and more. Watson can’t cure cancer but we have real solutions where Watson Oncology Advisor helps consultant oncologists improve treatment of cancer patients. And a member of our team recently made Chef Watson’s Korean BBQ lemon cupcakes and they were awesome (with my tea)!”

Parsing languages (other than English)

Another ingredient in Watson’s NLP pantry is its parser. This set of code helps it analyze and understand the written English language down to the grammar and syntax level. For example, Watson’s parser lets the system know “who did what to whom,” as in “the boy kicked the ball.” So, a question about what was kicked will find “the ball” as the receiver of said action.

But not all sentences operate the same way or in the same order.

Say “Hola” to Watson, and find out more about its new capabilities, and its new home at Astor Place in New York City, here.
In English, the subjects, verbs, and objects follow a certain order: “John saw Mary.” John did the seeing, while Mary was seen in a subject-verb-object order. However, in Hindi it is “Jŏna mairī dēkhā,” or “John Mary saw,” so a subject-object-verb order. And in Ireland, where D.J. lives and works, verbs follow subjects, which follow objects for “Chonaic John Máire” which is “Saw John Mary.”

D.J.’s team chose Spanish first, a widely spoken representative of a romance language, as Watson’s next language to parse, but hopes to build a generic parser that, once plugged into UIMA, will allow Watson to understand any language.

“We are after the mechanics of language to get to a point where Watson works between languages in a pragmatic way, Watson going global!” D.J. said.

Now, with Watson’s capabilities on BlueMix available to developers all around the world, its ability to process local language just as well as English will be increasingly valuable. New mobile apps could exploit all of Watson’s natural language power on regionally relevant knowledge sources. Ultimately, Watson will be cross lingual, meaning questions in one language can find answers in another and be returned to the user, translated back into his or her native or preferred language – making the knowledge of to world available to all regardless of language.

More about IBM Watson

10.02.2014

Creativity the ingredient for ACM award recipe

ACM winner Jakub Ocwieja
Warsaw University's Jakub Ocwieja and Comenius University's Peter Fulla have a lot of things in common. Both are young university students, both like algorithms, and both were part of teams that took home medals at the Association of Computing Machinery's International Collegiate Programming Contest World Finals 2014 in Ekaterinburg, Russia.

When they visited IBM Research-Zurich in September to meet fellow computer scientists and to present the their winning projects, we spoke to them about competing in the oldest, and certainly one of the most prestigious, programming contests in the world -- where Jakub's "team Jagiellonian" earned a silver medal, and Peter's "team Docikáme ďalej" earned bronze.

IBM Research: How did you hear about the contest, and why did you decide to compete?

Jakub Ocwieja (JO): ACM is very well known at the Warsaw University and every year there are many students who compete. I wanted to participate and see if I could beat other students and I just like solving problems, especially in algorithms.

Peter Fulla (PF): It is a good feeling to end up amongst the 50 best college programmers in the world. I also like the t-shirt, which is a frequent prize in such competitions.

ACM winner Peter Fulla
Their interest in computer science and algorithms started at an early stage. Peter participated in various programming competitions during high school and decided to pursue a CS degree. And Jakub had access to a computer as a young boy, thanks to his elementary school and older brother. As a young student, he learned how to program turtle movements in LOGO. Shortly thereafter, his brother gave him a book about the programming, PASCAL, which helped him qualify for the final of the Polish Olympiad in Informatics during his first year of high-school.

PF: In high school, I just started participating in similar competitions, and the ACM challenge was just a natural thing to do.

IBM: As someone from the millennial generation, are organizations like the ACM and research awards still important?

PF: I think it drives a lot of young people towards computer science in general. Competing is an enjoyable way to learn how to program. You also meet people of similar minds. I think that programming competitions are very important and beneficial for the whole industry of computer science, and I hope organizations like the ACM continue to support these competitions.

IBM: The competition is based on creativity, team work and innovation. How important is creativity in Computer Science?

JO: Even though Computer Science is one of the youngest fields of science, it is a great challenge to invent algorithms. So creativity plays a significant role to progress the field.

Jakub and Peter are ambitious students with a strong focus on the future. While at the Comenius University in Bratislava, Slovakia, Peter created an artificial intelligence player that could play the game Dominion against humans. And the computer actually managed to win several games.

As a member of the mathematical faculty at the Warsaw University, Jakub worked on an algorithm could find the distance between points on a map faster than had previously been done by a machine.

IBM: Have you participated in a more memorable programming competition?

PF: A few years ago, I attended the International Olympiad in Informatics held in Cairo, Egypt. At some point I stepped out of the conference to visit the pyramids. To my astonishment, a local salesman grabbed me and seated me on his camel. I was so shocked I didn't even resist. In the end I had to pay him over 50 dollars to finally get off that camel. I won’t make that mistake again!

IBM: What are your career aspirations?

JO: I am just finishing my Master Degree in Computer Science, so I am still considering several possibilities. I might work as a software developer or I might focus on some research in the same direction.

PF: I am just starting my PhD at the University of Oxford now, and after three years, I hope I'll be able to decide which path I want to take -- whether it will be in the academia or in some similar lab like this one. 

IBM: What’s your impression of the IBM Research - Zurich lab and of IBM in general?

JO: I didn’t have much opportunity to see the lab itself but I have heard about projects that IBM does here and I am very impressed by the scope of the projects and the topics of your research.

PF: My impression is that you do a lot of interesting things and I would be happy to do an internship in the same areas. What I particularly like is that you solve problems which have really interesting applications in real life. That practical application is one part which is truly interesting -- that it matters what you do here.

And those problems are in fact interesting from an algorithm point of view. It is often challenging to come up with the algorithm that solves the problem. I am more of a theoretical guy, so this is a nice change to have something which is also relevant to many people.


Interview conducted by Malena Sundstroem, IBM Research

9.29.2014

Microserver powered by the sun


IBM scientist Ronald Luijten has many hobbies, from gliding over the Swiss alps at 4,000 meters, to taking photos with his quadrocopter, or tinkering with technology -- particularly microservers, which he refers to as "data centers in a box."

By day, Ronald is working on a 64-bit microserver for the Square Kilometre Array (SKA), an international consortium to build the world’s largest and most sensitive radio telescope. He hopes that someday petabytes of Big Data from the Big Bang (13 billion years ago) will be crunched on the microserver, and uncover fundamental questions about the universe, including are we alone?

By night and on the weekends, Ronald has also built a microserver to host his website swissdutch.ch. The passionate environmentalist spent this past weekend "unplugging" his microserver from the electricity grid and and now powers it from solar panels backed-up with batteries.

"On September 27, 2014, I changed the energy source of the wandboard Quad to solar panels. I installed 40W of photo-voltaic panels feeding a lead acid battery of 18Ah (2x 9 Ah). The panels come in increments of 20W, and I did not think 20W was enough to make it through winter. Note that around this time of year (September), the sun is right between its minimum and maximum high point. So, I pointed the panels due south at an angle of 45 degrees," Ronald said.

To keep track of Ronald's progress visit his blog or follow him on Twitter @ronaldgadget





9.25.2014

The algorithms of show business

New IBMer begins work to make Watson work smarter, having made HBO’s Silicon Valley look smarter

Vinith Misra
“We need to talk.” Generally not something you want to hear from your PhD advisor. But when it was followed by, “Have you heard of HBO?”, then-Stanford student, now-IBM Watson engineer Vinith Misra was intrigued (and as a film enthusiast, a little amused). His advisor, Dr. Tsachy Weissman, had been contacted by the technical advisor for HBO’s Silicon Valley in 2013 to help the show’s creators develop fictionalized compression algorithms, and he wanted to bring Vinith on board.

The series, heading into its second season, follows the story of Richard Hendriks, a brilliant, young programmer and founder of Silicon Valley startup Pied Piper. He and his colleagues face a race against time – in the form of competition from a bigger tech company, reverse-engineering their work – to land funding from venture capitalists.

Favorite algorithm? 
“The most memorable algorithm I’ve heard has to be the solution to the countably-infinite prisoners-with-hats problem. You really have to admire the ludicrousness of it (and the insanity of its claim).” 

Favorite film? 
“I’m a big fan of the director Bong Joon-Ho, and his film Memories of Murder is probably my favorite. There is a new layer every time you watch it.”
For Vinith, who studied and now works in information theory and machine learning, the project held great promise. The challenge: create a lossless compression algorithm more powerful and efficient than anything that currently exists – or, rather, to make it look like they had created such an algorithm. They had to come up with something that isn’t currently possible, but isn’t immediately identifiable as such.

Vinith approached the challenge of writing the algorithm like he would any research problem. “You have a few things to keep in mind when formulating a problem. It needs to be impactful to people, it needs the potential to work, and the ideas should be elegant, compelling, and provocative,” he said.

With script in hand, Vinith knew that the algorithms were in essence their own character in the show, so he needed to make sure his work could play the part. He combined elements of lossy algorithms for their visual aesthetics on a whiteboard, with the lossless algorithms the show called for, and even created the Weissman Score — a fictitious compression benchmark that could fool even the biggest fanboys.

Vinith and Weissman think it’s reasonable to imagine radically innovative compression algorithms of this sort emerging in the future – which explains why these algorithms would also survive a cursory glance from highly trained engineers. “If you gave these ideas to a first-year grad student, they could run with them,” Vinith said. It would require a more detailed analysis to uncover the algorithms’ fundamental unfeasibility.

Hard at work finishing his doctoral studies in electrical engineering, Vinith didn’t spend much time on set during filming. Instead, he would conduct what he called “firefighting calls” with cast and crew, adjusting technical dialogue, finding material for the whiteboards and sets, and helping producers and actors deal with unexpected technical elements.

Spoiler alert!

Vinith knew that the finale to the first season would involve a drastic alteration to Pied Piper’s compression algorithm – an alteration that was the product of a mathematical joke from a pivotal scene. Developing and coding even as his team pitches the compression during the final episode, Richard comes up with a groundbreaking development after a humorous debate about how to influence the potential funders to choose their work. This breakthrough, which set the stage for the second season, stemmed from the phrase “middle out.” Vinith even published a 12-page analysis of the scenario that gives rise to the breakthrough, and while it is highly detailed and mathematically rigorous, it is explicit; reader discretion is advised.

Vinith will continue to work on the show, but this month he also began a new chapter with IBM’s Watson Group. “Watson is transitioning from the conceptual to working on real problems…and I’m glad to be a part of it,” he said.

Vinith will work on Watson out of the IBM Research – Almaden lab, where he will be developing algorithms to reason about concepts across a variety of domains, including subjects ranging from food to baseball cards — all in an effort to make Watson more agile.

Regarding the future of the show, Vinith can’t reveal much. He continues to work on Pied Piper’s breakthroughs and is looking forward to seeing the finished product of his work on screen. “I hope people treat the show like science fiction,” he said, “but the good kind.” He says it has been a fantastic and unique experience, and one from which he has gained a greater appreciation for the aesthetic side of what he does. “Algorithms and systems are designed to be used, but the ideas behind them can often be compelling, even to non-technical people.”

9.18.2014

IBMer earns "Genius Grant"

Craig Gentry's cryptography recognized by MacArthur Foundation

In 2009, computer scientist Craig Gentry solved a cryptography problem – one posed in 1978. The problem: can encrypted data be analyzed without being accessed? Thought impossible for more than 30 years, Craig’s “fully homomorphic encryption” technique did just that. And the John D. and Catherine T. MacArthur Foundation took notice. They recognized the impact this solution may have on cloud computing and how we protect information on the web by naming him a MacArthur Fellow.

“It has the potential to pave the way for more secure cloud computing services – without having to decrypt or reveal original data,”  said Craig. His team later earned a patent for the efficient implementation of fully homomorphic encryption.

He explained to the Foundation how homomorphic encryption works with a physical analogy of the fictitious “Alice’s Jewelry Store.

“Alice wants her workers to turn raw materials into rings and necklaces, but she doesn't trust her workers. So, she creates these glove boxes that have locks on them. She then puts the raw materials inside and locks the box. The workers can stick their hands into the box's gloves to manipulate the raw materials to create the jewelry. And then she can unlock the box to remove the finished piece.

“This is what I try to do with cryptography (and could apply to cloud computing).”

Craig Gentry on what it means to earn the “genius grant” (its unofficial title since the first Fellows were named in 1981).

The MacArthur Foundation extends each Fellow “a no-strings-attached stipend of $625,000, paid out over five years, with no stipulations or reporting requirements, and allows recipients maximum freedom to follow their own creative visions.” And while the Foundations does lay out its process for choosing the Fellows, the award has achieved near-mythic status as no one can apply, no one knows if they are being considered, and when they’re told, they’re sworn to secrecy until the official announcement.

9.11.2014

Growing single-crystalline materials on reusable graphene


Editor’s note: This article is by IBM Research Staff Member and Master Inventor Dr. Jeehwan Kim

Dr. Jeehwan Kim
Since the first demonstrations of removing graphene from graphite a decade ago, the size of a single-oriented piece has been limited to less than a millimeter – far too small for real-world application. Our team worked to break through the original millimeter barrier, and together we found success in producing wafer-scale, single-crystalline sheets of graphene 100 millimeters (four inches) in diameter. Having achieved scalability, we reported the possibility of replacing a thick, “single-crystalline” wafer with a single-atom-thick graphene layer for growing single-crystalline materials in the paper, “Principle of direct van der Waals epitaxy of single-crystalline films onepitaxial graphene” – published today with my chief collaborator Dr. Can Bayram in Nature Communications.

Graphene holds incredible promise as a linchpin material for breakthroughs in numerous technologies, and my team at IBM’s Thomas J. Watson Research Center is working to make its potential a reality. Due to its incredible strength and supreme electrical, optical and mechanical properties, graphene – pure carbon functional at the thickness of one atom – has been touted as the next big thing in everything from high-frequency transistors and photo-detectors, to flexible electronics and biosensors. IBM is investing $3B over the next five years towards initiatives such as this, which are building a bridge to a “post-silicon” era. 

Part of what makes the material so promising is its strength relative to thickness. At only .3 to .4 nanometers thick (that’s 60,000 times thinner than a sheet of plastic wrap, or 1,000,000 times thinner than a strand of human hair), graphene is an astonishing 200 times stronger than steel. It is also the world’s most conductive material yet discovered, extraordinarily flexible and – as a single layer of carbon atoms – the first two-dimensional material.

Our groundbreaking approach, known as “graphene-based growth/transfer,” allows single-crystalline semiconductor film growth on graphene – rather than on expensive, single-crystalline wafers. The graphene serves as a “seed” for single-crystalline film growth, and because this film can be separated precisely from the graphene surface, the graphene can be reused for further growth. In principle, graphene has therefore been demonstrated as an infinitive source for growing these semiconductor materials, making the work an enormously cost-effective and reliable production method for single-crystalline films. 

Graphene’s periodic hexagonal crystal structure then allowed us to experiment with growing other semiconductor materials that demonstrate similar structural properties. Previously, production of single-crystalline semiconductor films required the use of ~1 millimeter-thick, single-crystalline wafer templates that were not reusable and were very expensive. For example, growth of a 4-inch, wafer-scale GaN (gallium nitride, a direct bandgap semiconductor) film would require a 4-inch SiC wafer – at the cost of some $3000. Now, graphene can be produced in a lab to replace the expensive SiC wafer. 

Furthermore, the new growth technique is useful in that semiconductor devices can be deposited on graphene and released or transferred to a flexible substrate.

While we have demonstrated an important, present-day use for this material, the future of graphene as a standalone material is still bright. Uses for graphene are being developed for a number of electronics, and over the next five years, the material could be used as transparent electrodes for touch screen devices, rollable e-paper and foldable LEDs. In the near future, uses are being developed for large-area graphene in high-frequency transistors, logic transistors/thin-film transistors and beyond. Its high electronic mobility – the ability of charged particles to move through a medium in response to an electronic field – makes graphene a promising material. 

Read Principle of direct van der Waals epitaxy of single-crystalline films on epitaxial graphene by Jeehwan Kim, Can Bayram, Hongsik Park, Cheng-Wei Cheng, Christos Dimitrakopoulos, John A. Ott, Kathleen B. Reuter, Stephen W. Bedell and Devendra K. Sadana