Food contamination leads to deaths and illness all over the world, even in more industrialized nations. In lost food alone, such outbreaks cost companies hundreds of millions of dollars a year. A particularly aggressive case of Porcine Reproductive and Respiratory Syndrome Virus (PRRSV aka Blue-Ear Disease) struck China in 2007 and may have befouled 25 million of the nation’s ~660 million pigs. A lack of comprehensive tracking and pig-health monitoring meant that tons of healthy meat had to be wasted to protect consumers, even while recalls and warnings devastated consumer morale. As IBM points out in their Smarter Planet campaign, supply chain tracking could drastically reduce the impact of food contamination in meat, produce, or any product.

The trial in Shangdong Province is relatively small now, and won’t be fully deployed until 2013. However, at that point, the project will be ready to expand and it’s hoped that early success will encourage IBM and its partner, the Lushang Group, to bring this level of food tracking to China’s entire pork industry. Considering that China is the world’s leading pork producer (larger than dozens of the trailing nations combined), the possible size of this project is immense and globally impacting.

Greater gains, however, may be had not by the expansion of the number of pigs tracked, but in the data gathered. Most of the focus is simply on knowing with which pig a package of pork originated, and using that trail to quickly solve contamination issues. Yet the infrastructure put in place, centered on cloud based data storage, is ready to become so much more. Farms could upload data from pig health monitors (body temp, weight, sleep cycles, etc). On the production side of the equation Lushang and IBM are installing cameras, temperature gauges, and humidity sensors to record the processing and storage conditions of every piece of pork. They’ve also enabled retailers to track sales. Eventually data could also be used to help sell their pork (this meat got here in just 24 hours!), or even correlate consumer habits with trends further back in the production line. All that data is stored and associated with the same barcode, giving every piece of bacon or sausage a personal history enhanced by data and GPS location. Imagine a world where you could use your smart phone to read a code on a meat package and instantly see every detail about the pig it came from, the route it took to get to you, and all possible health risks.

That’s part of the dream behind IBM’s Food Technology portion of their Smarter Planet initiative. From pigs to tomatoes, comprehensive tracking could help guarantee freshness, improve production standards, and even automatically route food shipments based on consumer trends. There are some serious dollars to be saved by upgrading to these kind of supply chain logistics.

As the above video mentions, the trial with pork on Shangdong Province isn’t the only such project currently underway. Similar efforts are being made with other food products in Vietnam, Thailand, Norway and Canada. IBM even has an unnamed partner in the US working with fresh produce.

Cheap sensors, cloud computing, and nigh-ubiquitous GPS tracking are all coming together to enable the next generation of data gathering. IBM is already leveraging this evolved form of data collection for prescription medicine, various food products around the world, and now pork in China. Such supply chain logistics are just one of the earliest innovations from the Internet of Things – the growing network of smart objects that produce and interact with digital information. With the millions (or billions) of dollars these programs will save, IBM and its partners should continue to march towards a future where every consumer good comes accompanied by a digital history. Learning more about what we buy, and especially what we eat, is one of the closest and most empowering promises in our future. Get ready to know your food.

[video credit: IBM Smarter Planet]
[source: IBM Smarter Planet, IBM Press Release]

Hi, I'm Watson. Let's talk about your latest medical claim, shall we?

Ever feel like the people reviewing your claims at the insurance company are a bunch of faceless, mindless drones? Well it turns out your paranoid cynicism is coming true – congratulations! In a historic step towards modernizing healthcare, insurance giant WellPoint is teaming up with IBM so that the Watson AI can help their staff make informed decisions. The amount of medical literature is staggering – doubling in size about every five years. No human can possibly hope to keep up. Watson, however, is able to process 200 million pages of content in just three seconds. In early 2012, some WellPoint nurses will be able to access Watson to assist them in reviewing patient cases and treatment requests. Later, WellPoint expects to roll out the service to a few oncology practices and eventually this technology could be helping medical professionals all over the world. Taste a bit of this AI-fueled medical utopia in the video from IBM below. While many will undoubtedly lament the “dehumanizing” nature of AI in healthcare, Watson represents one of the great hopes in this field. With unparalleled abilities to understand human writing in huge amounts at high speeds, Watson can place the entire global history of medical literature in the hands of your doctor. Faceless and cold? Perhaps. But better and smarter as well.

As we discussed when Watson was poised to take on Jeopardy! champions earlier this year, the IBM system is a wonder when it comes to understanding natural human language. That’s not an easy skill for a computer, yet Watson is able to process billions of documents to find correlations between key words and concepts. This allowed the AI to win at Jeopardy! and it also allows it to recommend the best solutions to medical problems by searching through records and finding the most likely causes for ailments. Early tests with Watson have shown it to process complex symptoms, recognize possible causes with uncanny range and accuracy, and suggest treatments that impress the doctors working with the AI. The big goal of Watson in medicine is to give every medical professional access to the system, not to replace human decision making but to improve upon it by keeping humans informed. Here’s a brief video from IBM that highlights that vision:

WellPoint is one of the largest insurance groups in the US (the largest by some counts) with one in nine Americans participating. They have 34 million+ members and 70+ million when counting subsidiaries. Their agreement with IBM is historic not because it’s the first time AI is being applied to medical databases (it’s not, this has been done before) but because of the scale of the company and Watson’s superior understanding of human language. Early next year when Watson is made available to WellPoint personnel it will be used to sort through patient charts, medical records, WellPoint’s history of treatments, and IBM’s library of medical textbooks and journals so that the computer can synthesize treatment recommendations using all of these sources. We’re talking about millions upon millions of documents reviewed in just seconds. Nurses will take Watson’s recommendations as guidance, but conflicts in claims (your doctor wants to give you Drug X but Watson recommends Drug Y) will still be settled by human reviewers.

From there, WellPoint expects to roll out the medical version of Watson to oncology practices to assist in complex treatment plans. No word yet on the time it will take for that application to come online, nor how long WellPoint and IBM will stay at that level before moving on towards more general uses of the technology.

Eventually, however, I think we’ll see Watson, or its successor, commonly used in all areas of the medical industry from patient interviews to ER visits to insurance claim lawsuits. WellPoint expects the nurses in the opening trial will be able to access Watson from desktop computers or even mobile devices, and I foresee a future where tablet computers (or smart phones) serve as easy to use portals to Watson medical solutions calculated in the cloud. That means that not only will Watson-like technology be available to all levels of medical professionals but it will be available almost anywhere.

Consider that possibility for a moment. Every doctor (or nurse, or claim adjuster, etc) would have access to the world’s collection of medical expertise at their fingertips. And, because Watson not only makes recommendations but also cites the sources it used to make its decisions, your medical provider could quickly perform their own research to verify or expand upon Watson’s suggestions. This technology may turn every doctor into a super doctor. If we could make it freely accessible via smart phones it could also turn even untrained humans into passable medical assistants. These are world-changing possibilities.

And they come with world-sized risks. While I’m not a pessimist, there are clear avenues for abuse or failure. What if insurance companies (or governments, or whoever) got to decide that some treatments were too costly, and kept Watson from suggesting them? What if medical professionals became so trusting of Watson that an error in the AI would be accepted as medical fact and cause misdiagnoses of patients? What if Watson (or its successor) had no real competition, making an entire industry reliant upon a single system, and again allowing an error to be propagated to millions across the world?

WellPoint (and IBM) have assured the public (1,2) that they only intend Watson to be an objective assistant, and that it won’t take financial cost-benefit into account. Likewise, they have openly stated that Watson is here to augment human judgement, not replace it. Yet the fact that these companies must come out and assuage our fears about these risks reinforces the fact that such possibilities do exist.

That doesn’t mean we should let our fears keep us from adopting Watson on a large scale in the medical industry, but we should go into this with open eyes. AI could be one of the most powerful and transformative tools in world healthcare.  It is overwhelming a positive trend, and we need to support it and grow it as much possible. But, while this technology is still young, we should be very vocal about how we, as patients and human medical professionals, want it to be developed. One way or another medical AIs are going to revolutionize the industry. If WellPoint, IBM, and the public work together we can ensure that the revolution leaves us with a much healthier world.

[image and video credit: IBM]
[sources: WellPoint press release, IBM]

— Mark Dean CTO of IBM Middle East and Africa, 2011

Here’s a classy move for you: sell your company to someone else, watch them reach new levels of success, then announce that your former product (and all others like it) is obsolete. Oh, IBM, you really are quite the dashing gentleman. In a recent blog post, IBM CTO Mark Dean opined that personal computers are “going the way of the vacuum tube, typewriter, vinyl records, CRT and incandescent light bulbs.” In other words, PCs are dead.

Someone forgot to tell China.

Beijing-based Lenovo bought IBM’s PC business back in 2005 and has been selling them like gangbusters since then. In fact, all of China is going PC crazy. As of the second quarter of 2011, China surpassed the US as the biggest market for personal computers (22% market share vs. 21%). The Wall Street Journal has more on China’s silicon hunger in the video below. Is China gobbling up sales of a product that’s on its way out? Are we in the post-PC era? Who’s got it right IBM or Lenovo? Maybe, yes, and both. The world of computing is surely evolving, but don’t get concerned about which slice of technological progress is being replaced and which isn’t. Keep your eye on the forces behind those changes, that’s where the real action is.

International Data Corp recently published their evaluation of the personal computer industry and found that China had taken the largest market share for Q2 2011 with 18.5 million units valued at $11.9 billion. The United States came in second with $11.7 billion. Now, IDC still predicts the US to come ahead for the year due to seasonal variations in sales, but 2012 will undoubtedly be China’s year to rule the PC with projections of beating the US by millions of units. The Wall Street Journal summarizes this up nicely in the following video and gives their own conjecture as to why this is so (lower Chinese saturation, and US market interest in tablets/mobile):

You’ll notice that the reasons WSJ gives for China’s rise in PC consumption jive on a fundamental level with what Dean pointed out at IBM. We’re in a post-PC era. And by “we”, I mean the US. American interest in personal computers is now augmented by interest in tablets, mobile devices, and other form factors. That’s not stopping us from buying computers, it’s just changing what we’re asking computers to do, and buying our hardware accordingly. As Dean puts it:

“PCs are being replaced at the center of computing not by another type of device—though there’s plenty of excitement about smart phones and tablets—but by new ideas about the role that computing can play in progress. These days, it’s becoming clear that innovation flourishes best not on devices but in the social spaces between them, where people and ideas meet and interact. It is there that computing can have the most powerful impact on economy, society and people’s lives.”

What Dean says rings true for me. The most exciting developments in computing are the person to person applications. Most obviously I mean social networks, internet services, and the transformation file sharing has on intellectual property. On a deeper level though I’m talking about how computer-enabled applications fuel crowd-powered changes. Mobile phones are becoming one of the default platforms in Africa, with cheap smart phones giving hundreds of thousands of users access to the Android app market. On that platform we see innovators looking to effect health, education, and entrepreneurial endeavors. Similar scenarios are being played out all across the world and at every socio-economic level. Powered by (relatively) cheap digital technology, humanity is thinking up millions of new ideas for prosperity and profit. Computing in the 21st century is all about enabling people to enact change.

But that doesn’t mean the PC is dead. It just means that the ecology of computing is going to have more than one level. China is now (or soon will be) the world’s largest market for PCs. Guess what, it’s also the fastest growing market for iPhones. That just makes sense – they have low saturation for many advanced technologies and they have a national interest in launching themselves into the forefront over every major industry. They’re run by a group of scientists, for goodness sakes. China is going to gobble up computer power in all its incarnations, from desktops to server farms to smart phones.

So is every other developing nation.

We are in the post-PC era, but that era isn’t about ditching one hunk of plastic wrapped silicon for the newest gadget, it’s about what happens when we don’t have personal computing but global computing. When most of us have access to a computer on a regular basis, the world will do different things with computers. We aren’t there yet, but we’re getting closer. IBM is hinting at what that world may look like: companies pushing the boundaries of technology to find the next level of application space. IBM invests $6 billion per year in R&D, with projects like Watson, which could evolve into a virtual doctor, or any number of other possibilities. Why develop a program that can talk like a human, and make decisions like a medical professional? Because post-PC computing will eventually allow anyone with a mobile phone access to it through the cloud. That’s just one example. There will be millions more.

IBM declaring the PC dead and China buying record numbers of them are really the same story: “Computers are becoming democratized so it’s time to see what they can really do.” Just as some companies, like Lenovo, are having success bringing one tier of computing (PC) to new markets, other companies, like IBM, will need to expand what all forms of computing can do. And this won’t be divided along West-East lines either. China’s going to be right up there at the highest levels of computing looking to challenge IBM and all the other established names. The world is getting smaller and everyone willing to look a few years ahead will be scrambling to stay at the top of the technology pile. Ultimately I think that means humanity will have wider, cheaper access to all manner of devices running next generation applications that can have profound impacts on the fundamental challenges we face.

The era of global computing is near. The change that it brings is going to be unbelievable.

[image credit: Manuel Flores V via Flickr]
[video credit: WSJ]
[sources: International Data Corporation, A Smarter Planet Blog (IBM)]

It may be a while before nanotechnology improves human memory, but IBM's new phase-change memory could revolutionize how data is stored in computers and smart devices.

Scientists at IBM Research have created a relatively new type of memory that’s so fast and stable it may allow computers and servers to boot instantaneously, improve the overall performance of IT systems and make them more reliable. I say “relatively” because they didn’t build it from the ground up but rather made much needed improvements to what’s called phase-change memory (PCM). Just as printed circuit boards revolutionized computing, a practical PCM could usher in the next paradigm shift in data storage.

PCM is a type of non-volatile memory, meaning it doesn’t need power to store information. In this way it differs from RAM–if you shut down, whatever information is stored in RAM is lost. Right now the most ubiquitous type of non-volatile memory is Flash memory that’s found in thumb drives, digital cameras, and smart phones, among other devices. For a while now scientists have been searching for a universal, non-volatile memory technology that’s superior to Flash. The fact that their new PCM is much faster than Flash means Flash’s–and RAM’s–days might be numbered.

Phase-change memory earns its name from the special properties of its memory cells. They’re made of a versatile kind of glass that can be induced into different phases, the same way water can transition between liquid and ice. The bit data of PCM is actually stored as these different phases: one phase represents a binary 0, the other, 1. Conversely, RAM cells are stable and bits are stored in the form of electric charge: charged = 1, uncharged = 0.

Up to this point, however, those PCM cells had given scientists a headache. A major reason why PCM isn’t widely used today is the instability of its memory cells. After a time the cells would become unstable, drifting from their binary 0 or 1 phases, and cause read errors. Those ingenious IBM scientists used this drift ‘defect’ to their advantage. Rather than nail the PCM cells to one phase or the other they were able to attain two distinct phase states intermediate to 0 and 1, allowing them to store four bit combinations in all: 00, 01, 10, and 11. The multi-bit cells made for faster computation. PCM can store and retrieve data 100 times faster than Flash. To stabilize these four phase states they implement a nifty new “modulating coding technique.” Their demonstration last month was the first time PCM had been shown to reliably store multiple data bits over an extended period of time. To date, the chip has retained its data for five and a half months.

Revolutionary technology–now that's how you celebrate a centennial!

IBM has a long history of pioneering computer memory technologies. Invented by IBM’s Dr. Robert Dennard back in 1966, DRAM remain the world’s most ubiquitous memory today, loaded into our PCs, notebooks, and game consoles. As IBM celebrates its 100th birthday it’s poetic that they stand poised once again to lead a computer revolution. As they proudly write in their report: “With a combination of speed, endurance, non-volatility and density, PCM can enable a paradigm shift for enterprise IT and storage systems within the next five years.” Obviously PCM is ideal to replace flash memory in our thumb drives and our smart phones, as well as large scale enterprise storage systems used by businesses. What makes PCM’s timing all the more serendipitous is the increased use of cloud computing. “As organizations and consumers increasingly embrace cloud-computing models and services, whereby most of the data is stored and processed in the cloud, ever more powerful and efficient, yet affordable storage technologies are needed,” says Dr. Haris Pozidis, Manager of Memory and Probe Technologies at IBM Research, Zurich. “By demonstrating a multi-bit phase-change memory technology which achieves for the first time reliability levels akin to those required for enterprise applications, we made a big step towards enabling practical memory devices based on multi-bit PCM.”

And we can expect more great innovations from IBM. This past May they opened their Binnig and Rohrer Nanotechnology Center at the IBM Research–Zurich campus. The center was established with ETH Zurich, IBM’s partner for ten years. Both applied and basic science will be pursued to create new nanoscale devices as well as push scientific understanding of nanoscale physics. The center includes a “cleanroom” in which to build their nanodevices as well as “noise-free labs” that shield the equipment from surrounding electrical disturbances.

Along with genetics and robotics, nanotechnology is one of the three technological revolutions Kurzweil expects to usher in the beginning of the Singularity. With top-notch scientists, equipment, and funding that IBM and ETH Zurich bring to the table we’re sure to see more paradigm-shifting technologies such as multi-bit PCM, bringing the Singularity that much closer.

[image credits: They Might Be Timelords and Digg Hut Club]
image 1: Emmitt Brown
image 2: Jappinistic

Thanks to technology, the South can get mad all over again.

I opened up the newspaper this morning to find out that the president was in D.C. to witness a demonstration of the latest artillery. The new arms included a highly-accurate rifle invented by Mr. Wilson Ager and an automatic rapid-fire gun that is operated by a hand crank. Upon seeing the gun in action, President Lincoln likened it to a coffee mill.

The article’s date, June 24, 1861, is exactly 150 years ago. At this point in history America is at war with itself. A new App called The Civil War Today, created by A & E’s History Channel, brings daily news stories for the entire four years of the war. I got the App and have been enjoying it immensely these past couple days. You can go back and read the news from days past (the first shot was fired on Fort Sumter April 12), but it doesn’t let you scroll ahead, making the immersion seem all the more lifelike. It’s an enhanced experience. The “A Day In The Life” feature includes letters and diary entries from the prominent, like Abraham Lincoln, to the common like Confederate private Charles H. Lynch. Each day includes a new “Photo of the Day,” a “Quote of the Day,” and a running tally of North and South casualties. There’s also a daily quiz, a daily photo gallery, and updated battle maps. There’s also a game feature through which the user can earn medals for answering quiz questions correctly or, for example, sending “messages in morse code.” A “Feature Story” also brings a broader picture to the daily events. The current story summarizes the role the Dred Scott decision played in the lead-up to the war. Made by Bottle Rocket Apps, The Civil War Today has a nice, old newspaper feel combined with enough quick-and-easy features to keep the user entertained for more than a few minutes each day without feeling like they’re taking on a chapter from a history textbook. Here’s a short video from Apple ‘N’ Apps that runs through nearly all of the features.

Was this the App that the pundits of yesteryear were thinking of when they predicted that the internet would revolutionize education? Probably not. But I remember how tedious it was to memorize names, dates, locations when I was learning about history. Despite my primary education’s best efforts to make me despise history, I’ve grown to crave books on history, documentaries, Steven Spielberg HBO creations. But The Civil War Today would most certainly have captured my fertile but fickle young imagination. It’s a fantastic opportunity for history teachers to put technology to use and tap their students’ enthusiasm. Given the increased use of iPads in classrooms, The Civil War Today and like Apps should become a regular part of today’s curriculum. This App could serve as a template to learn about all sorts of history. What about an App for WWI and II? We could follow the daily events of the Boston Tea Party, the French Revolution(s), or, if it’s your thing, the O.J. Simpson trial. The possibilities are endless. Having history at our fingertips that’s interesting and fun could do wonders to improve historical literacy around the world.

At $8, the price tag is a bit more than we’re used to paying for Apps. But for four years of content it sounds like a bargain to me. If you’re a history buff you’re going to want this. If you’re even remotely interested in the Civil War this App is a necessity. Whoever faithfully follows the news and diaries over those four years will be rewarded with intimate details appreciated over the war’s true timeline. I’m going to keep up on events, not only because it’s a lot of fun, but also because I can’t wait to see who wins it all in the end.

[image credit: ipadvideoapps.net]
[video credit: AppleNApps via YouTube]
image: Civil War Today
video: AppleNApps

Try to make him feel welcomed. Reigning Jeopardy! champion and IBM robot, Watson, is devouring the material in medical textbooks and journal articles in hopes of landing a job as a physician's assistant.

The trainee was sequentially presented the details of a fictitious patient: there’s an eye problem; vision is blurred; the family, living in Connecticut, has a history of arthritis. The trainee’s initial response was uveitis. More clues and the diagnosis was changed to Behcet’s disease until finally the trainee settled on Lyme disease. How sure was this seemingly hasty student of medicine? Seventy-three percent sure.

Medical trainees and doctors are not typically in the habit of quantifying their assessments with such Commander Data-like precision, but this trainee happens to share more qualities with the Star Trek android than the rest of the medical staff. Following its resounding victory on Jeopardy!, IBM’s Watson has been working hard to learn as much about medicine as it can with a steady diet of medical textbooks and healthcare journals. The mock case described above was part of a recent demonstration to the Associated Press showing just how much Watson has learned. The robot’s diagnosis was correct and it identified a link between symptom and cause that was “not common,” as one participating physician called it. After being told the patient was pregnant and allergic to penicillin, Watson suggested treating her with cefuroxine. Its human colleagues agreed. The demonstration was a success, and it is the hope of IBM and many medical professionals that Watson will one day soon lend doctors a helping hand as they perform their daily rounds.

The need for efficient use of medical information becomes more pressing as the amount of information amasses at an exponential rate. Dr. Herbert Chase, a Columbia University medical school professor, tells the Associated Press that it has been 30 years since doctors were last able to keep pace with the growing body of medical knowledge. With only so many hours in an often overwhelming day, doctors are hopeless to keep up with a body of knowledge that doubles every five to seven years. In addition to the struggles of keeping pace, the sheer volume of information presents a separate challenge to share that information effectively. Michael Yuan, a scientist that has worked with IBM, cites a 1999 study that found doctors field more than 1,100 questions a day and fail to answer 64 percent of them. The inefficient exchange of information leads to mistakes in any field. In the medical field, those mistakes could cost lives. A widely-noted–and hotly debated–report published in 2000 estimated that as many as 98,000 people die in a given year from medical errors occurring in hospitals. As the report notes, “that’s more than die from motor vehicle accidents, breast cancer, or AIDS.”

Now imagine Watson on the job. Never one to nap in the library, Watson’s database would be updated daily with the latest in research from potentially all online journals. The director of Health Informatics Center at the University of Southern California, Carl Kesselman, points out the need to track advances in genomics, specialized drugs, off-label uses, and the increasingly finer-grained classifications of diseases. Of course the physicians themselves can find the information, but the online searches would be labor-intensive and time-consuming. A physician’s assistant like Watson with realtime updates could simply be asked Jeopardy!-style questions to find answers or get second opinions. To make the interactions Jeopardy!-style, speech solutions developer Nuance is currently working with IBM to provide Watson speech recognition software customized with medical jargon. Doctors could query Watson’s database on the go by speaking into a handheld device.

Not to be confused with Sherlock Holmes' sidekick, Watson is named after IBM founder Tom Watson.

At this early stage in its medical education Watson understandably, still makes mistakes. A team of medical students are working with Watson to catch mistakes and try to identify what causes them.

Its knowledge is not limited to science. Watson can also keep an eye on complex treatment guidelines that are often updated so the physician doesn’t have to. It can access medical records as well. However, for access to be completely streamlined they need to be digitized. Unfortunately the medical record digitization seems to be a change hospitals are thus far slow to adopt. Progress is being made, however, by companies like Practice Fusion, a maker of electronic health records (EHR) systems. Combining the latest medical knowledge with the patient’s medical history would give Watson the best chance to catch those rare cases that doctors might be slow to diagnose or miss altogether.

A major break from previous practice is IBM’s plan to include patient blogs among Watson’s data set. Much as they do now on websites such as carepages.com, patients can share symptoms, drug efficacy, drug side effects, relevant family histories, etc. Like a medical wikipedia, the data cloud that amasses could be mined by Watson to pull out obscure relationships that would normally pass under the radar of doctors concerned only with their patients. For example, cross-reactivity between two types of drugs that aren’t taken together very often. In essence, Watson would be conducting its own studies without a priori goals or limitations.

But the data is anecdotal, you say? Dr. Chase agrees, but argues that doctors are already using anecdotal data when they take medical histories. The patients’ descriptions are anecdotal, and the doctors don’t listen any less.

To me the patient blogosphere is the most exciting of Watson’s resources. What sort of insights into medicine and disease will we gain simply by blogging about our own experiences? As Wikipedia shows us, there’s truth in numbers. A major challenge to mining those insightful gems is blogs that are easily understandable to Watson. It’s one thing for a doctor to have a one-on-one conversation with Watson and refine his query when he inevitably runs up against misunderstandings. But it’s quite another thing to glean underlying facts from thousands of blogs from all over the world. A universal format for the patients would help, perhaps including a basic list of yes or no questions.

C'mon, admit it. You can hear the heart beat: "boomp...boomp...boomp..."

A know-it-all robotic physician’s assistant that you can talk to from anywhere with a handheld device. Reminds me, again, of Star Trek, “Computer, across how many worlds has the epidemic spread?” (Yes, that’s two Star Trek references in the same blog!). But one company would argue that it is years ahead of IBM in bringing AI to the forefront of medical diagnosis support–and her name is Isabel. Isabel Healthcare’s founder Jason Maude’s named the database program after his daughter who as a child was misdiagnosed with chicken pox (instead, she had two rare chickenpox-related complications). Created a decade ago, the company’s mission is to decrease misdiagnoses, and it performs essentially the same functions as Watson: symptoms are entered and the computer sifts the database to produce a list of the most likely causes. Isabel asks questions that the doctor might not think to ask, indicates the gold standard treatment, and lists relevant medical literature.

So, what do we need Watson for?

IBM executives point out that Watson is much faster than Isabel and much better at understanding terms that it hasn’t memorized from a textbook. Watson would know, for instance, that “difficulty swallowing” is “dysphagia.”

Watson has a ways to go before it makes the grade. IBM estimates that they are still a couple years away from making a marketable Watson. Doctors, IBM execs say, should not feel threatened by their fast learning student. The clinician’s role is to practice medicine and Watson’s role is to support the clinician, to act as a library. I have to admit, I’m skeptical. Medical students are a pretty ambitious lot. It may just be that beating two of the world’s best at Jeopardy! on primetime television isn’t enough for Watson. Maybe its done playing games and wants to contribute in a meaningful way to society.

Or, maybe Watson just wants to be called Doctor.

[image credits: modifed from Asset Protection Law Journal; Wikipedia; scoreforsale.com]
image 1: modified
image 2: Tom Watson
image 3: sickbay

Is there an AI doctor in the house?

Will you ever be treated by Dr. Watson? Not Sherlock Holmes’s right-hand man, but the AI Jeopardy! champion who’s poised to be a sidekick for future physicians. IBM and Nuance Healthcare have teamed up with Columbia University and the University of Maryland to build a medical Watson that’s fine-tuned to address the queries of doctors. The goal is to enhance decision-making and eventually put Watson on every medical center’s computational cloud. But is this the first sign of transitioning healthcare labor from humans to machines? Don’t hold your breath. Given the person-centered focus of treatment, we’re nowhere near having AI that can match the full capabilities of the human medical workforce. But don’t count Watson out either. As a physician’s assistant, AI could be a godsend to America’s healthcare system by facilitating accurate diagnosis.

The video above describes the natural limitations of doctors and how Watson’s powerful AI could supplement clinical cognition. Dr. Herbert Chase, a professor at Columbia University, says that diagnosis can be exceedingly complex (0:33), so pairing symptoms to a condition won’t always lead you to the right answer. Another limitation he points out is that physicians have been unable to keep up with the rapid growth of medical knowledge, which has been doubling every five to seven years (1:35). The ever-rising tide of biomedical literature is simply too much for the human brain to learn. Due to these limitations, Dr. Chase cites the high incidence of delayed diagnosis. As Watson demonstrated on Jeopardy!, the AI could be up to the task on all these fronts. In a fraction of a second, Watson can comb through terabytes of data and formulate an answer. When lives are at stake, the speed and accuracy of a medical Watson could be an invaluable addition to patient care.

Hypothetical model of a medical Watson. Nuance's medical language analysis will beef up Watson, and doctors at Columbia and the University of Maryland will see if the system is clinically relevant and user-friendly.

We won’t see a prototype for almost two years, but here’s how a medical Watson might work. Much like his strategy on Jeopardy!, Watson would masterfully dissect natural language. Unlike the game show, this would be handled by Nuance’s front-end speech recognition software, which is specifically tailored for medical jargon. Also, the question would be processed on the medical center’s computational cloud, so clinicians could pose questions remotely. With this approach, there’s no need to wait for laptops with the computing power of IBM’s Blue Gene.

As illustrated in the diagram to the right, an internist could ask, “My patient, Jane, has had digestive issues and has also lost interest in bowling, her favorite hobby. Could these be linked?” Using the Nuance software, IBM’s Blue Gene supercomputers would focus on the words “lost interest.” After a cursory search of the DSM, the computer would recognize this as a symptom of depression. Then Watson would scan hundreds of journals, looking for articles where “depression” and “digestive problems” co-occur. He would eventually come across articles like this one, suggesting that coincident depressive and digestive symptoms are associated with celiac disease, an under-diagnosed autoimmune disorder. Once Watson finds enough articles supporting this hypothesis, the answer would emerge from the cloud to be read by the physician, who would follow-up with lab tests for confirmation. After adopting a gluten-free diet to prevent a relapse, Jane could be back to bowling in no time, all thanks to her physician and the Watson computer. Without Watson, the doctor could have been dancing around the diagnosis for weeks before finally getting it right.

This sounds like an impressive system on its own, but I think IBM and Nuance could do even better. To accommodate the exponential growth of medical knowledge, Dr. Watson must be able to seamlessly integrate new information with existing data. Furthermore, thinking like a scientist and maintaining a computationally-based skepticism would optimize Watson’s accuracy. A medical Watson might adjust an article’s weight according to the number of citations or ignore outdated or unsubstantiated information. Also, the designers could improve Watson’s accuracy by considering epidemiology. For example, Watson could boost its confidence score if an infection was also found in surrounding clinics. If Watson adopts even one of these features, I will be even more impressed than I was during the Jeopardy! performance.

If IBM and Nuance successfully install a practical Watson, how might Watson stack up against other clinical decision support systems? The major competitor will be Qualibria, a joint venture by GE and Intermountain Healthcare. This clinical software is the final product of a prototype we’ve covered before. The purpose of Qualibria is to convert a hospital’s existing health information (i.e. electronic health records or EHRs) into an ongoing clinical trial. In a recent ComputerWorld article, the CIO of Intermountain Healthcare questioned the usefulness of Watson in the clinic. He suggested that Watson’s analytics could be incompatible with the unstructured health information found in EHRs and other hospital data sources. We’ll see if Watson proves him wrong.

Watson and Qualibria aren’t the only players in town. We saw an artificial neural network (ANN) for diagnosis, which is still in the experimental stages. The advantage of this method is that it can adapt to new problems based on trial and error, much like the brains of human doctors. Unfortunately, the system must be “trained” to optimize functioning, and ANN has only been tested on a handful of conditions, such as endocarditis and heart murmurs. There’s also SimulConsult, a system that can be updated by registered physicians, so it’s a bit like clinical crowdsourcing. However, it’s limited to only certain kinds of disorders. Among Qualibria and others players, Watson has his work cut out for him. See how Watson could match up to his competitors (and human doctors) in the table below.

Comparison table of decision support systems and physicians. Dr. House's accuracy takes the cake, but he lacks an empathy chip. Can't win 'em all, even for $480,000 an episode.

Even though Watson packs a computational punch, there’s no reason to suspect AI will replace doctors in the near term. And IBM agrees. In the video at the beginning of this article, the IBMers make it perfectly clear that Watson is intended to be only an assistant. However, that hasn’t stopped people from speculating. After his historical loss to Watson on Jeopardy!, Ken Jennings made a bold prediction about AI replacing human workers.

Just as factory jobs were eliminated in the 20th century by new assembly-line robots, Brad [Rutter] and I were the first knowledge-industry workers put out of work by the new generation of “thinking” machines. “Quiz show contestant” may be the first job made redundant by Watson, but I’m sure it won’t be the last.

The  implications of this statement parallel issues we’ve covered before, like Martin Ford’s hypothesis that advanced AI will cause structural unemployment for even the most highly paid, cognitively demanding jobs. If machines have a better price-performance ratio than people, there’s nothing keeping the higher-ups from adopting automation. But actually building an autonomous AI physician responsible for human life? Easier said than done.

Let’s first identify hospital tasks that are within reach of state-of-the-art AI. Systems that automatically prioritize patients or robots that roam hospital hallways to collect vital signs seem attainable. Also, if Watson becomes a complex question generator (not just an answerer), machines could even perform the initial clinical interview for some patients. It would be relatively uncomplicated to generate standard questions about diet, family history, and health behaviors. With a little algorithmic ingenuity, AI workers may even pursue more in-depth lines of questioning if patients give particular answers or alert doctors or nurses when the patient requires human attention.

But let’s not get ahead of ourselves, techno-optimists. This is only a fraction of the physician’s skill set, and there are certain clinical competencies far beyond any current AI. Think of situations where a patient presents symptoms undocumented in the medical literature. Physicians  rely on intuition, experience, and imagination to guide them in these cases, and so far, fluid intelligence for AI is only theoretical.  Sorry Watson, but “What is Toronto?” is not an acceptable response when lives are at stake. Furthermore, good physicians also have a keen emotional intelligence. Imagine a robot performing the most challenging task in any doctor’s career, informing a patient they have a terminal illness. It’s not as simple as just saying the words. The exchange must sound sincere and sensitive to the emotional needs of the patient and family. If this emotionally intelligent human-machine dialogue ever passes a Turing Test, it will likely be the zenith of AI. I think that this achievement is so far off that the most common illnesses afflicting patients will be cured by the time it comes to pass. For the foreseeable future, people will be running the healthcare show.

At the dawn of my own medical career, I’m not worried about AI in the clinic at all. In fact, I find it to be a rather exciting prospect, and I hope most doctors will similarly view AI as a partner, not a competitor. I imagine pacing the halls of the hospital, stroking my chin with one arm behind my back, while a mobile AI unit follows closely behind. I’m working on a difficult case and bouncing ideas off Dr. Watson, much like Sherlock Holmes solving a mystery. But I’m jumping the gun. My very own Watson will have to wait. Eight years of medical training, here I come.

<Image credits:  IBM (modified), Nuance Communications, University of Maryland, Columbia University, Microsoft Clip Art>

<Video credits: IBM>

<Sources:  IBM, ComputerWorld>

Watson Prepares to Dominate Jeopardy!

Today, February 14, 2011, IBM’s Watson computer system is slated to take on the world’s best humans in a televised duel of the world famous game “Jeopardy!”.  Should Watson defeat its human competitors, it will herald perhaps the most significant achievement ever in the field of artificial intelligence and computer science.  For IBM the prestige and positive publicity stemming from Watson’s victory would be long lasting and the envy of the world.  For the rest of us, Watson’s victory would mark yet another of a long series of achievements where computers increasingly exhibit behavior that matches or exceeds human ability.

Perhaps most intriguing of all, however, is that Watson requires the computing power of a mere 90 computer servers (albeit very specialized ones!).  As computing power continues to get ever more powerful and ever more tiny, we all could have access to our own Watson within a decade, maybe much sooner.  Imagine having an assistant as powerful as Watson at your personal disposal – the implications are incredible.  As we all wait during these final hours for the televised match to begin, join me as we take a look at a fantastic trio of short videos that IBM has released to showcase the many facets of this truly historical event.

IBM Watson: Countdown to Jeopardy!

In the video above we are reminded that when the IBM engineers were just beginning to create Watson people thought they were crazy. Many of those Watson engineers themselves questioned quite strongly whether or not they were just wasting their time.  Yet the forces of both human determination and accelerating technology are a formidable combination.

Watson is not only a challenge in information retrieval, it is a challenge in interpreting, and then responding to human language.  Google founders Larry Page and Sergey Brin have often remarked that the ultimate search engine “would understand exactly what you mean and give back exactly what you want.”  Such a vision is a far cry from the Google of today, which simply returns a list of websites related to our questions.

IBM’s Watson does not have access to the entire internet like Google does, and even if Watson did have such access, it is doubtful that the system IBM has built would be able to scale to an internet sized pool of data without a complete rewrite.  Yet at least for the still quite large corpus of data required to compete in Jeopardy!, it would appear that IBM has mostly delivered on Larry and Sergey’s dream.  With the advent of Watson might the bar now be set for the creation of a search engine that can truly listen and respond to our questions verbally?  Whereas before the arrival of Watson an intelligent, verbal search engine seemed decades away, in today’s post Watson world such an engine seems much closer on the horizon.

Google already seems well positioned to make such a leap.  Google has until now been a world leader in language translation, whether it be the automatic generation of captions for videos or sleek new applications that bring Star Trek-like language translation to our phones.  Google aside, there are plenty of other talented companies and individuals out there.  Wolfram Alpha certainly comes to mind, as does a Vicarious Inc, whom we recently covered.

IBM Watson: The Face of Watson

The video above shows the great lengths IBM cleared to create a Watson that was pleasing to its human spectators.  It is fascinating to consider how important image is to the overall human perception of Watson.  Should Watson be male or female?  Should Watson speak with an accent?  Should Watson have a human face, with eyes, nose, mouth, and all the other fine qualities of human anatomy?  These questions and more needed to be considered with great care as IBM attempted to create an intelligent computer that humans would respect and perhaps even enjoy.  IBM had to make absolutely sure that Watson was not perceived as annoying, dorky, or worst of all – threatening.  The public relations and marketing component of the Watson project is a very big deal.

IBM Watson: Watson After Jeopardy!

As we see in the video above, IBM sees the creation of Watson as a watershed moment that will lead to the creation of countless Watson progeny in the future.  We can envision a single Watson that is trained to answer a wide range of general questions, but we can also envision Watsons that are trained to become absolute experts on a relatively narrow field of inquiry.  Whereas it may be difficult in the near term to create a single Watson that would know all of the world’s information, creating a Watson that is an expert in a single field such as American history or human anatomy and disease would be a much more tractable problem.

The negative crowd will always find a way to shoot down the beauty of a creation such as Watson.  They will say that Watson does not think like a human, that Watson does not truly understand language, or that Watson does not understand humor.  But such thinking, although grounded in truth, entirely misses the point.  Watson does not need to reproduce all facets of human behavior to achieve greatness.  Isn’t it enough for Watson to reproduce just one or more of the incredible abilities of humans?  Isn’t it enough, at least for today, to be impressed that a computer can defeat any one of us, perhaps even the great Kenneth Jennings and Brad Rutter, in a game of Jeopardy!?  Rest assured, in the decades ahead we will find less and less human abilities that computers cannot reproduce.

The very existence of Watson, whether he succeeds or not in his debut today, is a historical moment that completely changes the landscape of artificial intelligence for the entire world.  Before Watson it was nearly impossible to get people to invest money or their own talents into computer projects that could try to recreate human intelligence in the manner that Watson does.  Now that Watson exists, brilliant minds across the globe will be inspired with a new sense of what is possible.  Watson is a specialized system, created for a very specialized task.  IBM and the world at large won’t be able to re-create mini Watsons for our corporations and for our pockets overnight, but as of today the race is on to do just that.  Before Watson existed the challenge was to get people to even try.  Now that challenge is behind us.  People will try, and in great numbers.  People will believe that they can do it, and so they will!

(L to R): Ken Jennings, Watson, and Brad Rutter. Careful humans, your dominance is in jeopardy.

Today is the day computers took over…game shows. In a brief exhibition match in upstate New York, IBM’s pure language processing computer, Watson, faced the titans of Jeopardy: Ken Jennings and Brad Rutter. Watson won. Sure, it was a brief sparring session, and the real trials won’t air until February, but it looks like Watson has a good shot at becoming the world’s champion of trivia. Alex Trebek didn’t preside over this preliminary match, but he was on hand to watch Watson go toe to toe with some of the top human competitors from the history of Jeopardy. He joked that the computer would soon be on sale on eBay. Not quite, Trebek, but IBM engineers do think that Moore’s law will allow everyone to have their own Watson years from now. Considering how well the computer performed against Jennings and Rutter I’m sure the two of them will be among the first in line. Watch Watson’s stellar performance in the video below. I’ll take The “AIs” Have It for $2000, Alex.

After a brief opening session, the scores were Jennings $3400, Watson $4400, and Rutter $1200:

As mentioned in our previous discussion, Watson draws its information from a personal database, not the internet. It can answer most Jeopardy questions in about three seconds. To do so, Watson uses massive amounts of parallel computing power. Inside the large machine are racks of servers, over 2000 cores, with 15 terabytes of RAM, and about 80 teraflops of processing power. Yet all of this hardware is more or less “off the shelf”. What makes Watson really unique is the way it processes language. IBM developed the DeepQA project (of which Watson is a part) to be able to provide human-like answers to human-asked questions. That means it has to understand the ambiguities and intricacies of human speech – a medium of communication notorious for its acceptable mistakes and imprecision. Using its vast database of literature, scientific reports, and other documents, Watson develops ideas of how often words are associated with other words, and what meanings are extracted from those connections. Add in a few rules about how to best play Jeopardy, and you are most of the way towards building a computer that can defeat humans at their own game.

Here’s IBM engineer David Gondek, speaking with engadget’s Paul Miller, at the event to explain more:

As you saw in the first video above, there are areas in which Watson does better than others. Or rather, there are areas where humans still outperform Watson. First, it only speaks English (though it appears to have knowledge of words that have been anglicized). The computer may also be more conservative than its competitors in choosing to buzz in early, and perhaps more shy in deciding when it has the right answer. Word play and association categories, such as filling in the blanks in book titles, were still clearly won by Ken Jennings. Probably because humans are pretty good at not fixating on the things they don’t know.

Yet even if Watson is only a great Jeopardy player, and not a perfect one, that hardly matters in the greater plans for its use. IBM executives claim it could read all of the world’s medical files in a few seconds. Watson could likely handle similar stores of data with the same speed. Think of what it would mean to have a computer with such a complete knowledge in a field. Expert doesn’t even come close to describing it. In ten or twenty years, when there’s a Watson in every smart phone (and home), we will all have access to medical, engineering, or legal opinions that in scope (if not quality) exceed anything a human could hope to produce. Applications in intelligence, military applications, and general security are equally profound. If you can provide the database, a computer like Watson can provide the unparalleled expertise. It’s an amazing future.

In the next few days, Watson will take on many other former Jeopardy champions, playing in several rounds of competitions. The event will be aired in a special program in February. Win or lose in that eventual showdown, today’s scrimmage showed us that Watson has the right stuff. Good luck to all the human contestants…you’re going to need it.

The real test is still yet to come. Are you ready, Trebek?

[image credit: EnGadget, CrunchGear]
[video credit: EnGadget]
[source: CrunchGear, EnGadget]

Barcodes and data centers could curtail the global counterfeit drug market.

IBM may be a big scary corporation, but there are bigger and scarier worries out there. Among them is counterfeit prescription drugs. According to the computer giant, around 10% of the medication consumed globally is a forgery. Looks the same, tastes the same, but it could kill you. As more countries, like China and India and Brazil, get into the development and distribution of prescription drugs, the volume of international sales will increase. As will counterfeit production. Testing every pill before it is consumed is probably impractical, but tracking every pill may not be. IBM is developing the software that, in conjunction with barcodes, GPS sensors, and environmental controls, could help us ensure that every drug we take came from the manufacturers we trust and in the condition they required. It’s the Internet of Things for prescription drugs, and it could save lives and streamline inventory all over the world. Watch IBM’s executives explain their ideas in the video below. Universal tracking of medications, food, and more could be upon us very soon.

Think about this: there are probably around 1 billion people on the internet. Most are sending email, checking statuses on Facebook, and posting weird photos to /b/ on 4Chan. In the future billions of more people are going to come online, but they are likely to be dwarfed in number by an even larger group: smart objects. Tiny GPS sensors, QC barcodes, and environmental sensors are going to turn every shipment of goods (from apples to stereos) into a hive of digital information that is constantly uploaded to the net. Special software will be needed to track the trillions (yes, trillions) of objects that will compose this Internet of Things. IBM is looking to tackle that job head on, designing the systems that will organize data from objects and control things like temperature and humidity in shipping containers to optimize freshness. It’s a daunting task, but as IBM describes in the video below, the benefits are great. And the alternative is chaos.

With prescription medications, the cost-benefit of tracking is measured not just in dollar amounts, but in lives saved. This means that companies are more likely to invest in the technology to track drugs in the near future. The simplest tracking methods, like rigorous monitoring of barcodes, have been in use for several years in various stages. Next generation solutions will include tiny GPS sensors embedded in every drug container so that the history of their travels can be closely watched. If a shipment of drugs arrives that doesn’t have a complete verifiable history, chances are it’s counterfeit. Add in environmental sensors (either on small drug containers or larger shipping containers) and you can optimize the condition that the drugs arrive in.

These same solutions can be applied to another widely shipped good: food. Like prescription drugs, food has a cost-benefit analysis that includes lives saved. Salmonella outbreaks and E. coli contamination regularly make the news, and if we could track global food shipments better we may be able to stave off these outbreaks quickly and effectively. Again, some tracking methods are already deployed, IBM itself has been running a trial food tracing project out of Manitoba Canada for the last few years, but the level of sophistication can be raised considerably. According to IBM, less than 1% of food is actually inspected before it enters the United States. In the absence of complete inspection, complete tracking may help us improve quality of food. In fact, environmental controls tied into sensors attached to food containers would have even more important impacts on food delivery than they do with drug delivery. There are billions of dollars and millions of lives that could be saved by better food tracking every year. Improved supply chain efficiency could also reduce the carbon footprint for shipping food around the world. Of course, we probably could save nearly as much money, lives, and energy by buying food from local farmers…but I digress.

Tracking prescription drugs and food are just two of the dozens of the opportunities that IBM is pursuing in relation to the developing Internet of Things. Their ongoing Smarter Planet initiative is looking to revolutionize every major computerized field through the use of smart objects. With a powerhouse like IBM pursuing IOT solutions, you can be sure that we’ll see many of them deployed in the years ahead. Actually, IBM is pursuing many of them on a trial basis already. A global network of smart objects is coming, though, and with it will arrive a flood of data that will make our current online activity seem like little more than a trickle. It will take the might of corporations like IBM, or the innovative creativity of smaller competitors, to channel that flood into a resource that transforms our lives. Better medicines, healthier foods, and more could all be arriving soon. The Internet of Things is near…and get nearer everyday.

[image and video credits: IBM]
[sources: IBM Smarter Planet]

Are you ready to face a computer in Jeopardy?

Back in 1997, IBM made history when its computer Deep Blue defeated Grandmaster Garry Kasporov in a game of chess. Now their new questioning answering system, Watson, is looking to do the same with Jeopardy! Run on multimillion dollar super computers, Watson solves questions by analyzing their language and finding possible answers in millions of documents stored in its memory. It is not connected to the internet. IBM is looking to pit Watson against former Jeopardy! champions in a broadcast match sometime soon (perhaps this fall). Clive Thompson from The New York Times recently wrote an amazing article on Watson, and the Times has a special page where you can challenge the machine to a match. Good luck, you’ll need it. You can scout your competition by watching Watson in action against real human contestants in a video from IBM below.

Jeopardy! questions prove especially difficult for computers because they contain so much wordplay and twisted phrasing. Watson has advanced skills in natural language processing, and is able to parse the relevant portions of a question. IBM wants to create a computer that can understand the way humans talk. That will have big applications in the future, as we try to build virtual assistants (imagine super-smart versions of the Siri iPhone App). As we mentioned before, automation is going to leak into many fields you wouldn’t expect. A computer that can answer Jeopardy questions could cut through bureaucratic red tape, do research for lawyers, or answer questions for doctors. Watson may make its debut playing humans on Jeopardy! but no mistake – IBM is building a system with a far greater potential.

For now, however, that potential is still limited. Watson works by rapidly searching through its millions of stored documents and finding associations between words and phrases. ‘Shakespeare’ often appears with ‘Hamlet’ and ‘Midsummer Nights Dream’ but also with ‘William’ and ‘England’. Likewise, ‘pen’ is linked to ‘writing’ and ‘ink’. All these associations help Watson answer a Rhyme-Time clue like “Shakespeare’s writing instrument” as “What is Will’s quill?”

To determine the right associations, Watson makes evaluations. It finds all the possible connections between relevant words using several different algorithms and then weighs them according to how often they come up in its database. It prefers answers that are found by multiple algorithms and it double checks its answers by running them back through its system. The analysis of possibilities, probabilities, and double-checking lets Watson not only know what the answer might be, it let’s it evaluate how right it thinks it is. If it’s not confident, it doesn’t buzz in. That sort of decision making is a sign of a great Jeopardy! player and as you’ll see in the following clip, Watson has some serious trivia chops:

When you play against Watson on the New York Times site, you’re actually playing against pre-recorded guesses – so questions don’t change. That means if you lose the first time through you can go back and answer all the questions with the correct answers. While you don’t get a sense of Watson’s speed, you can get an idea of how it evaluates answers by looking at the probabilities (bar graph) it associates with each one. Pretty cool.

Of course, you’ll also notice that Watson makes some big mistakes as well. Tricks in semantics, and reasoning still trip up the machine. But that’s okay, it’s a work in progress. The DeepQA project was only begun in 2007, headed by David Ferrucci, and IBM only announced the Jeopardy! Challenge last year. Thompson does an amazing job describing the history of the project in greater detail in his NYT article. Watson still has several months, perhaps longer, before it must face a set of unknown Jeopardy! all-stars on television.

It will need the time to prepare. IBM categorizes what it takes to win at Jeopardy! into four basic skills: searching through a clue for the relevant portion, finding the correct answer in a vast realm of stored knowledge, evaluating the confidence in your answer, and quickly deciding whether or not to buzz in. Watson is good at all four skills sets, but humans excel at the later two skills. An all-star contestant will buzz-in before they are even sure of their answer, trusting in the five-second grace period to figure things out. Winners typically buzz in first for half or more of the questions, and get the answer right 85-95% of the time. Watson isn’t at that level yet.

The human trials you see in the video took place over several days. According to the NYT, Watson carried one day, able to win 4 out of 6 games against 7 human opponents. Yet the following day it lost just as many games, once with no points. It still loses to humans with rhyming clues, and wordplay, and can get distracted by word associations that appear often but are not relevant to the question. Watson will have to get better if it hopes to beat the likes of Ken Jennings.

Watson is powered by large and expensive servers...but costs and size are shrinking. Eventually everyone will have a system like this in their home.

Whether or not Watson finds success in its eventual Jeopardy! showdown, IBM plans on marketing similar systems to companies in the next few years. In the beginning, the list of those who could afford such a machine will be short, as Watson depends on Blue Gene servers, around $1 million each. IBM executives, however, hope that in the next ten to fifteen years price performance in computing will allow a DeepQA system to become much cheaper, eventually available on machines the size of a laptop. 2025 could be the year that everyone has a Watson in their home.

But we might be experiencing the benefits of question answering systems far sooner. We’ve already discussed how medical AI programs could help doctors in the near future (the Xprize is even aiming to put them on your smart phone). These systems won’t have Watson’s level of language analysis, but they’ll answer questions with quick (and hopefully accurate) results. One day, the techniques created for the DeepQA project will allow us to interact with such systems by talking just as we would with any human. Eventually we may not be able to tell the difference between the two experiences. Eventually we won’t might not even care if there is a difference.

[image credits: New York Times, IBM]
[video credit: IBM]
[source: IBM, New York Times]

Try on makeup before you buy.

Mega-corp IBM has teamed up with Israel-based EZface to create a “virtual mirror” that allows you to see what makeup looks like on your face without ever opening a compact. Inside your favorite retail store, the EZface kiosk will take your picture and display it on its screen. Simply scan in the bar codes from cosmetics and the virtual mirror will show you what they would look like on your skin. You can even share your results with friends via email or mobile phone to get their advice. Check out a cool demonstration of the technology from IBM courtesy of The Street. Augmented reality just got fabulous.

Though dubbed the ‘virtual mirror’, the EZface kiosk is an augmented reality system, blending live video images with virtual/digital elements on the same screen. This is just one of many uses of AR in marketing that we’ve seen recently. Not only that, but it has the potential to become one of the most widespread. EZface kiosks are already in stores in North and South America, Europe, and Asia, and are covering major brands like L’Oreal, Maybelline, Covergirl and Revlon. The adoption of the system has some distinct advantages. The kiosk allows customers to preview and personalize their purchases without actually applying and removing makeup, and it allows stores to track which products are being reviewed most often. The virtual mirror has the potential to help bring augmented reality firmly into the mainstream.

I am also moderately impressed by the facial and color recognition algorithms displayed by the kiosk in the video above. EZface software not only identifies where each type of makeup should be applied to the customer image, it can suggest the appropriate shades of cosmetic to match skin tone. Something which, if done right, would save customers loads of time and frustration.

Along with the in-store kiosks, EZface has an online portal that allows you to upload a photo and try out various cosmetics from major brands. I tried it out with a snapshot from a webcam. The interface was fairly easy to use, but I was disappointed to find that the facial recognition tech that was touted in the video didn’t seem to function completely on its own. I had to manually adjust the outlines of my features to get the computer to accurately recognize them. Maybe I just have one of those faces? One hopes that the kiosks are a little more user-friendly than the online version. In any case, once the photo is setup the ‘trying on makeup’ part of the virtual experience works just fine and seemed reasonably realistic. Try it out for yourself.

EZface’s isn’t the only virtual mirror you can use. There are many others you can find on the web, and Silhouette even has an iPhone App that will let you demo some of their sunglasses. I’m betting that the technology will catch on and expand. With online sales gaining a larger share of the market every year consumers are going to want a way to see how things will look on them before they buy. Webcams and virtual mirrors could make that happen. (In the process, they might be automating away some retail positions.) Eventually, augmented reality systems are going to not only shape the way we purchase goods, but what those goods are capable of. We’re approaching the day when your sunglasses will give you navigation instructions and your car windshield will highlight dangers. The potential for augmented reality is vast and EZface’s kiosk is just one of many uses we’ll see in the upcoming years. Word of advice though: be careful when using AR. When it works well it’s a great tool, but when it fails….things can get ugly…

EZface allows you to email your virtual mirror results to friends...though I think I'm going to skip that option.

[image credit: EZface]
[video credit: The Street]
[source: IBM, EZface]

IBM's newest nanoscale technique allowed them to create this 3D relief map of the world. It's the smallest one ever created - just 22 microns across.

Last year IBM revealed the first true images of a molecule using a special atomic force microscope (AFM) with a carbon monoxide tip. AFMs have been around for a while, but IBM continues to find interesting ways to innovate them. The nanoscale 3D map was created using an adapted AFM setup that allowed a very small (few nanometers) silicon tip on the end of a cantilever to be heated as it brushed against a special polymer surface (polyphthalaldehyde). Essentially the tip carved this polymer to create the relief map of the globe. IBM also created a replica of the Matterhorn on a molecular glass substrate using the same technique. In both cases, the AFM-like tip was used to not only create the image, but also to “view” the image when it was completed.

As the video mentions (vaguely), this isn’t the most precise nano-sized endeavor ever attempted. Scientists routinely work on submicron scales to create all manner of nanodevices, including lasers. Heck we’ve even seen a snowman that was similar in size to IBM’s nano-maps. Yet, as IBM points out in the Advanced Materials article, it isn’t enough to simply construct an interesting nanoscale creation. For a real-world application you need to handle a large volume of such microscopic tasks without having your microscopic equipment break down. That’s why IBM’s system represents a real break through. Their silicon tip is sturdy, and can handle a large workload. IBM’s essentially created a rapid nanometer scale lithography system. Their new AFM-like tip for scratching, and the use of polymer and glass surfaces as substrates, allows them to quickly construct nanometer paths. What others can do at the same scale, IBM is attempting to do faster, easier, and cheaper.

Those nanometer paths could allow all manner of new creations. They may be used to facilitate the assembly of nanomaterials by helping molecules move in the right directions. They could serve as a pattern for printing pathways on other surfaces. Or, if the substrates have the right properties, they may even be used to create actual electrical or opto-electrical devices. All of this and they should be able to be made quickly, reliably, and in manufacturing conditions.

Certainly part of the reason companies like IBM go to the trouble of creating stunning displays of their microscopic prowess is to demonstrate the efficacy of their new techniques. But just as importantly, it serves as a place holder in the public mind while the company works on developing real applications for that technique. It is likely to take many years for IBM to design some sort of product that is created using their newest AFM/silicon tip method. It will be years after that until they go ahead and produce such an item and we have a chance to buy it. In the meantime, the incredibly tiny map serves as a good indication of the remarkable potential for their technique.

[image credit: Advanced Materials]
[video credit: IBM]
[sources: IBM, Science, Advanced Materials]

Henry Markram's model of a brain is built one neuron at a time.

Once you start building a brain in a box you get two things: admission into the Mad Scientists’ Club, and a chance to speak at TED. Henry Markram is the director of the Blue Brain Project, a collaboration between European scientists and IBM that aims to construct a life-like simulation of a brain using a supercomputer. Earlier this year Markram spoke at TED Global discussing how most of human perception is based on decision making within the brain. BBP hopes it will only take another decade to create a fully functioning computer model of a human mind, and Markram will guide you through some of the most important concepts behind the simulated brain today. Check out the TED Global 2009 video after the break.

This is neither the first Blue Brain Project story, nor even the first video of Markram that we’ve discussed here at Singularity Hub. What keeps us coming back to the topic? The amazing possibilities created by the BBP research and the uncertainty as to whether it will ever succeed. While not aimed at creating an artificial intelligence, a fully functioning simulated brain would be hard to define as anything else. Even ignoring the AI applications, BBP could help neuroscientists learn what causes certain mental illnesses, or how to repair trauma to the brain, or how to improve the way the brain processes information. Right now, BBP is exploring different theories on how the mind works. Yet it’s still much too early to tell if Markram will ever be able to exploit those theories to create a full fledged simulation.

The BBP is focused on the neocortex and specifically the neocortical columns that provide the raw computational power that shapes our minds. These columns are where our higher reasoning and decision making abilities reside. Research into the neocortex not only informs Markram and his team in how to program their supercomputer, it also highlights the fundamental ways in which our minds interact with the universe. As Markram describes in the video, 99% of our perception is based on the decision making processes which analyze incoming sensory information. Our world is cognitively based on our choices. That’s powerful stuff.

Neuroscientists have spent the better part of the last 15 years learning how to build digital models of the branching and connectivity between neurons. In Markram’s discussion he mentions that there is a huge amount of neural diversity, that each cell in our brain is different in its orientation and connection from every other cell, and different from every other neuron in the brains of others. Yet despite this diversity, there are consistent patterns in how neocortical circuitry is wired. Hearing that, I wonder if the efforts to build devices to “read people’s minds” will be enhanced by BBP’s discoveries. Once we understand common patterns in neurons, couldn’t we look for those patterns and translate them as thoughts or emotions? What if those patterns are too complex, or if the diversity is too strong to create a general model of the brain? BBP has a long way to go in understanding the nature of neuron interactions.

Markram’s goals for modeling the electrical activity in the brain may lead to a better understanding of how real world objects are mapped into neuron connections and signals. Such “electrical objects” in the brain show us its perception of the outside world, and could also give us the key to programming the brain. Creating artificial electrical objects in the brain (however one might do that) could allow us to experience things without ever being near them. There are many possible applications of such a technique for virtual reality and accelerated learning. Those technologies would require a tremendous understanding of the brain, however, and it’s unclear how quickly Markram’s team will be able to define the way neurons map the real world.

It’s hard to know if the Blue Brain Project will achieve its goal of creating a life like simulation of a brain in just 10 years. The task is monumental, but if you listen to Markram you sort of believe that they are most of the way there already. Hopefully that confidence will be supported by many years of fruitful work in the near future, because his research is far from over. There are likely some functions of the brain than can ever be revealed by simulation. But as far as mad scientist projects go, this one makes me as hopeful as I am skeptical.

[photo credit: blue brain project]

[video credit TED Global 2009]

The IBM device would read single strands of DNA as they passed through layers of a microchip.

Sequencing your genome is going to be such big business that everyone wants to get in on it, even if they aren’t ready. In a recent press release, IBM announced that it is working to create a microchip that will sequence DNA by running it through tiny ‘nanopores’. The DNA Transistor will be able to sequence the entire genome rapidly and for less than $1000. While a working prototype of the chip won’t be created for three more years, IBM thinks that the theory and computation behind the concept is sound. If ultimately successful, the computer giant would launch itself to the forefront of the genome sequencing field. For now though, the company is just pushing an idea, not a product. I love it when companies compete in a field, but IBM’s got years of hard work before it could be a genome sequencing competitor. A fact that makes their press release seem premature at best. Still, you should check out the admittedly cool PR video after the break.

The first human genome cost around three billion dollars to sequence. Today, Illumina is offering to do the same for $50,000 and Complete Genomics is looking to a $5000 price tag under certain conditions by the end of next year. But the big hurdle is $1000. At that point, sequencing a genome will become accessible to almost anyone, and could see wide spread adoption in health and medicine. Using genetic information, doctors could provide personalized health care that would target illnesses and choose treatments which best suit your body. Knowing more, we could live much longer.


IBM’s proposed device would work by threading a single strand of DNA through a 3 nanometer diameter pore that is drilled through a silicon chip using an electron beam. As the press release admits, that idea is being explored by several companies around the world (including Agilent, Sequenom, NabSys, and Oxford Nanopore Technologies). The IBM innovation is to slow the progress of the DNA through the nanopore by using electric fields as gates. By controlling the speed at which the DNA moves, IBM hopes to read the strand. That reading would be accomplished by measuring the variation in electric potentials across the pore, which is uniquely different depending on if the base is A, C, T, or G.

Strands of DNA suspended in a solvent would be encouraged to pass through the nanopore due to an electric bias. Electric fields in the pore would control strand movement and read the DNA.

When I first looked at the IBM video describing the DNA Transistor, I thought, “I’ve seen this before.” I interviewed DNA Electronics CEO Christopher Toumazou about the combination of CMOS technology and genetics last month. The SNP Dr is a hand held silicon chip based device that reads DNA to find interesting genetic sequences. Unlike IBM’s device, it’s already been made and tested.

But there are big differences between the two devices besides the fact that IBM’s is still on the drawing board. First, the SNP Dr looks for single nucleotide polymorphisms, the single gene variations that have important impact on physical traits, drug reactions, etc. The SNP Dr does not sequence your entire genome as the DNA Transistor plans to do. If it helps to draw comparisons to companies, the SNP Dr is like 23andMe and the DNA Transistor is more like Illumina or Complete Genomics. Secondly, the SNP Dr works by using enzymes (polymerases) to cause protons to be released as a strand of DNA is read, and the silicon chip measures that current. The DNA Transistor would only use electric fields to read the strand as it passes through the nanopore.

So the DNA Transistor could be an important improvement over the existing SNP Dr technology, but not yet. In fact, IBM is looking to have a working prototype in three years. That seems like forever. Complete Genomics will have $5000 sequencing by the end of 2010 and it should only get cheaper thereafter. The same goes for Illumina and every other genome focused company. By 2013, the $1000 hurdle could have been jumped by one of these companies. Heck, by that time, we could see the price drop much lower. If the DNA transistor is to be competitive that far down the road it will have to be cheaper (IBM has tossed around the $100 mark as a possibility) or much much faster.

Luckily for IBM, silicon technology has speed down to a fine science. I don’t know if the DNA Transistor is going to be the device that defines the next generation of DNA sequencing, but I do know that the marriage of CMOS and genetics is powerful. That’s a sentiment shared by the researchers behind the IBM device, Stas Polonsky and Gustavo Stolovitzky, in the companion video embedded below.

Everything about this press release strikes me as hype. Good hype, sincere hype, but hype all the same. There’s no doubt that the combination of genome sequencing and microchip technology is a game changing idea, but IBM doesn’t have a monopoly on it. Obviously DNA Electronics has a somewhat related device already nearing market, and there are other companies also working towards using nanopores to sequence the whole genome. A lot can happen in three years. Hopefully someone will have a working prototype by that time. It could be IBM, but no matter who it is, their cheap and quick sequencing is going to change our lives.