Daily Archives: May 6, 2017

You can pick your Kentucky Derby horses based on names or jockey uniform colors, but you might want to listen to this for some betting advice.

Last year, a startup called Unanimous A.I.used a platform to predict the exact top four finishers the superfecta at the 2016 Derby. And this year, Unanimous A.I.s UNU platform has made its picks.

First, heres how it works, via Newsweek:

UNU uses a unique form of artificial intelligence called swarm intelligence that aims to amplify rather than replace human intelligence.

It works like this: a group of people login to an UNU online forum through their smartphones or computers. At the start of each session, all participants are simultaneously presented with a question and a set of possible answers.

Each participant has control of a graphical magnet that they can move around the screen to drag a puck to the answer they think is correct. The puck can only fall on one answer, and the group has 60 seconds to collectively agree on a decision that best suits them all.

The result for this year, from some thoroughbred experts using the system?

1. Classic Empire

2. McCraken

3. Irish War Cry

4. Always Dreaming

A $20 bet on last years A.I. picks would have won you $10,842, so you might want to listen to them again.

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This artificial intelligence platform's picks could win you so much money at the Kentucky Derby - For The Win

May 5, 2017 Microscopic landscape of various types of cellsincluding tumour cells (in red). Credit: University of Warwick

Cancer cells are to be detected and classified more efficiently and accurately, using ground-breaking artificial intelligence thanks to a new collaboration between the University of Warwick, Intel Corporation, the Alan Turing Institute and University Hospitals Coventry & Warwickshire NHS Trust (UHCW).

Scientists at the University of Warwick's Tissue Image Analytics (TIA) Laboratoryled by Professor Nasir Rajpoot from the Department of Computer Scienceare creating a large, digital repository of a variety of tumour and immune cells found in thousands of human tissue samples, and are developing algorithms to recognize these cells automatically.

"We are very excited about working with Intel under the auspices of the strategic relationship between Intel and the Alan Turing Institute," said Professor Rajpoot, who is also an Honorary Scientist at University Hospitals Coventry & Warwickshire NHS Trust (UHCW).

"The collaboration will enable us to benefit from world-class computer science expertise at Intel with the aim of optimising our digital pathology image analysis software pipeline and deploying some of the latest cutting-edge technologies developed in our lab for computer-assisted diagnosis and grading of cancer."

The digital pathology imaging solution aims to enable pathologists to increase their accuracy and reliability in analysing cancerous tissue specimens over what can be achieved with existing methods.

"We have long known that important aspects of cellular pathology can be done faster with computers than by humans," said Professor David Snead, clinical lead for cellular pathology and director of the UHCW Centre of Excellence.

"With this collaboration, we finally see a pathway toward bringing this science into practice. The successful adoption of these tools will stimulate better organisation of services, gains in efficiency, and above all, better care for patients, especially those with cancer."

The initial work focuses on lung cancer. The University of Warwick and Intel are collaborating to improve a model for computers to recognize cellular distinctions associated with various grades and types of lung cancer by using artificial intelligence frameworks such as TensorFlow running on Intel Xeon processors.

UHCW is annotating the digital pathology images to help inform the model. The aim is to create a model that will eventually be useful in many types of cancercreating more objective results, lowering the risk of human errors, and aiding oncologists and patients in their selection of treatments.

The TIA lab at Warwick and the Pathology Department at the UHCW have established the UHCW Centre of Excellence for Digital Pathology and begun digitising their histopathology service.

This digital pathology imaging solution will be the next step in revolutionising traditional healthcare with computerised systems and could be placed in any pathology department, in any hospital.

The project has been launched in collaboration with Intel and the Alan Turing Institutethe latter being the UK's national centre for data science, founded in 2015 in a joint venture between the University of Warwick and other top UK universities.

"This project is an excellent example of data science's potential to underpin critical improvements in health and well-being, an area of great importance to the Alan Turing Institute," said Dr. Anthony Lee, the Strategic Programme Director at the Alan Turing Institute for the collaboration between the Institute and Intel.

Rick Cnossen, general manager of HIT-Imaging Analytics in Intel's Data Center Group, commented, "This project has massive potential benefit for cellular pathology, and Intel technologies are the foundation for enabling this transformation.

"We've seen what has happened over recent years with the digitisation of X-rays (PACS). The opportunity to transform the way pathology images are handled and analysed, building on experience with PACS and combining data with other sources, could be truly ground-breaking.

"This collaboration could not only improve service efficiency, but also open up new and exciting analytical techniques for more personalised precision care."

Explore further: New advances in cancer diagnosis

A University of Warwick computer scientist is working with technology that could revolutionise how some cancers are diagnosed.

US-based Intel announced a deal to buy an artificial intelligence startup as the computer chip colossus looks to broaden its role in data centers and the expanding internet of things.

Research by the University of Warwick, the University Hospital Coventry and Warwickshire NHS Trust (UHCW), and Tangent Reprofiling Limited, has discovered that statin drugs interact with a gap junction protein called GJC3 ...

New research from the University of Warwick and University Hospitals Coventry and Warwickshire (UHCW) NHS Trust could transform treatments and diagnosis for a common digestive condition which affects thousands of patients.

A serious problem in the Turing test for computer intelligence is exposed in a study published in the Journal of Experimental and Theoretical Artificial Intelligence.

Technology fan will.i.am, the frontman of The Black Eyed Peas, is teaming up with US computer chip giant Intel.

Burger King pulled a pretty juicy marketing stunt last month that drew plenty of attentionnot just to the Whopper, but also to the intrinsic vulnerabilities of a new type of voice-activated gadget.

There is something spooky about being able to see and talk to the pirate Blackbeard while one walks down a dark alley and then stepping right through him as he disappears into thin air. Such entertainment experiences are ...

The first solar plane aimed at reaching the stratosphere made an initial low-altitude test flight over Switzerland Friday.

More than 3 million people (three times previous estimates) are estimated to be actively using cryptocurrencies like bitcoin, finds the first global cryptocurrency benchmarking study by the Cambridge Centre for Alternative ...

A young man in a white t-shirt pulls on a dark blue denim trucker jacket, tucks his smartphone in an inside pocket and puts in-ear headphones in his right ear.

Community detection is an important tool for scientists studying networks. It provides descriptions of the large-scale network by dividing its nodes into related communities. To test community detection algorithms, researchers ...

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Cancer cells detected more accurately in hospital with artificial ... - Phys.Org

We don't have enough people to keep up."

"We have to go through miles of case law on this one."

"The paperwork is killing our productivity."

"We don't know because we can't track events like that."

Spend enough time in or around government agencies, and these are the kinds of pressures you're likely to hear about. How can governments overcome challenges like these that are both detail-oriented and labor-intensive? Increasingly, they could be turning to artificial intelligence (AI).

You might think of AI as futuristic, but it's already having a profound impact on government. Cognitive technologies can't replace the complex strategic planning and management required of public administrators. But we're entering an era of automated intelligence -- the computerization of tasks previously thought to require human judgment.

Here, as explored in a new Deloitte study, are five ways AI can help government agencies cut costs, free workers for critical tasks, and deliver better, faster services.

1: Overcoming resource constraints: From Facebook posts to sensor readings, we generate far too much data for humans to make sense of without help. Cognitive technologies can help to sift that data. Electronic document discovery, for example, can locate 95 percent of relevant documents in the discovery phase of legal cases, compared to about 50 percent for humans, and in a fraction of the time. And then there's NASA's Volcano Sensorweb, a network of space, terrestrial and airborne sensors that can trigger closer observation by human experts who can pinpoint and record just-in-time imagery of volcanoes and other cryospheric events. This is a major promise of AI: humans and computers combining their strengths.

2: Dramatically cutting paperwork: By pointing the way to new opportunities for automation, AI can help to significantly reduce administrative tasks, maximizing time for mission-focused work. One Colorado survey, for example, found child-welfare caseworkers spending 37.5 percent of their time on documentation and administration, versus just 9 percent on actual contact with children and their families. And at the federal level, our research indicates that simply documenting and recording information consumes a half-billion staff hours each year. "Bots" can automate all kinds of activities like these, from invoice processing to filling in forms, from data entry to writing budget-reporting documents. By freeing up all that time, we can create a more effective government, empowering employees to do the work that really matters: serving citizens in need.

3: Reducing backlogs: Backlogs and long wait times can be hugely frustrating to both citizens and government employees. At the U.S. Patent and Trademark Office, the backlog of patent applications topped half a million in 2015. Cognitive technologies can sift through data backlogs and perform end-to-end business processes on a massive scale while leaving difficult cases to human experts.

4: Improving prediction: Machine learning and natural-language processing can reveal patterns, enabling better predictive capabilities. By trial and error, computers learn how to learn, mining information to discover patterns in data that can help predict future events. When your email program flags a message as spam, or your credit card company warns you of a potentially fraudulent use of your card, machine learning is probably involved. In government, the Army is developing wearable monitors that use a machine-learning algorithm to determine wound seriousness, helping medics prioritize treatment. Meanwhile, the Department of Energy's self-learning weather and renewable forecasting technology uses machine learning, sensor information, cloud-motion physics derived from sky cameras, and satellite observations to improve solar forecasting accuracy by 30 percent.

5: Answering citizen queries: Giving citizens quick answers to important questions improves service while reducing costs and backlog. "Chatbots" can handle tasks such as password resets (which one North Carolina agency's IT help desk found made up more than 80 percent of its tickets), freeing staff for more complex tasks. On the U.S. Army website, an interactive virtual assistant does the work of 55 recruiters: It answers questions, checks qualifications and refers prospective recruits to human recruiters. The system uses machine learning to improve recognition and helpful responses, with an accuracy rate of over 94 percent.

As these examples illustrate, cognitive technologies eventually will fundamentally change how government works, and the changes will likely come much sooner than many think. Some traditional models assume limits on the tasks that information technology can execute. Increasingly, however, such assumptions will no longer apply. As cognitive technologies advance in power, government agencies will need to bring more creativity to workforce planning and work design. The most forward-leaning jurisdictions will see cognitive technologies as an opportunity to reimagine the nature of government work itself -- to make the most of complementary human and machine skills.

This article was originally published on Governing.

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5 Ways Artificial Intelligence Is Already Changing Government - Government Technology

By Swapnil Bhartiya, star Thought Leader, InfoWorld | May 5, 2017

Opinions expressed by ICN authors are their own.

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I am a heavy user of Raspberry Pis. Every year I build a massive musical lighting setup for Christmas using couple of Pis. During Halloween, I build Pi-poweredtalking skeletons, spooky pumpkins, and scary lights. Raspberry Pi powers the wireless controller for my open source 3D printer and my water foundation in the garden. I am using Pi to run a Retro gaming rig, and my next project includes a remote controlled car and a possible drone.

You get the point, I am a heavy user of Raspberry Pi and IoT.

There is one thing that I miss in all of these projects. I wish I was able to not only control them with voice, but also give them some intelligence so that they can make some logical decision. And when it comes to AI and machine learning, no other platform beats Googles machine learning and Google Assistant. Now I am closer to bringing those capabilities to my Pi devices.

Google has started a project called AIY Project, do-it-yourself artificial intelligence for Maker, to bring Google Assistant to Raspberry Pi powered projects. Google says that along with everything the Google Assistant already does, you can add your own question and answer pairs. Google has teamed up with the Raspberry Pi foundation to create a new hardware add-on for Raspberry Pi called the Voice Kit.

Voice Kit is a fully open source reference project that includes Voice Hardware Accessory on Top (HAT) which contains electronics components for audio capture and playback, connectors for the dual mic daughter board and speaker, GPIO pins to connect low-voltage components like micro-servos and sensors, and an optional barrel connector for dedicated power supply.

The kit is designed and tested with the Raspberry Pi 3 Model B. Just like Google Cardboard, Voice Kit comes with a neat cardboard case.

Those who are more ambitious can also run Android Things on the Voice Kit, turning it into a fully functional prototype to build their own commercial IoT products.

Its amazing to see that people can now take advantage of Googles massive machine learning capabilities in their own home brew projects. I cant wait to get my hands on the kit so I can talk to my 3D printer and add smart features to my drone and RC cars.

It will be so incredible to say "printer, change filament," or "water the marigold pot" or "turn the Christmas lights on" and have these commands obeyed! I am overwhelmed with the possibilities because these are the devices that I built.

If you want the kit, Google is giving it away with the latest issues of MagPi magazine. If you dont want to subscribe to the magazine, you can sign-up for the waiting list to just get the hardware unit from Google. Barnes & Noble is also selling the kit in its stores.

This is the first kit from Google, and the company is working on many more such kits. I think a real IoT revolution is ahead of us. I am going to build some neat projects, are you building something?

This article is published as part of the IDG Contributor Network. Want to Join?

Swapnil Bhartiya is a journalist and writer who has been covering Linux & Open Source for 10 years.

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How to get Google's artificial intelligence on the Raspberry Pi - InfoWorld

I asked Huang to compare the GTC of eight years ago to the GTC of today, given how much of Nvidias focus has changed.

We invented a computing model called GPU accelerated computing and we introduced it almost slightly over 10 years ago, Huang said, noting that while AI is only recently dominating tech news headlines, the company was working on the foundation long before that. And so we started evangelizing all over the world. GTC is our developers conference for that. The first year, with just a few hundred people, we were mostly focused in two areas: They were focused in computer graphics, of course, and physics simulation, whether its finite element analysis or fluid simulations or molecular dynamics. Its basically Newtonian physics.

A lot can change in a decade, however, and Huang points to a few things that have changed in the past 10years that have shifted the landscape in which Nvidia operates.

The first thing is that Moores Law has really slowed, he said. So as a result GPU-accelerated computing gave us life after Moores Law, and it extended the capability of computing so that these applications that desperately need more computing can continue to advance. Meanwhile, the reach of GPUs hasgone far and wide, and its much more than computer graphics today. Weve reached out into all fields of course computer graphics, virtual reality, augmented reality to all kinds of interesting and challenging physics simulations.

But it doesnt end there. Nvidias tech now resides in many of the worlds most powerful supercomputers, and the applications include fields that were once considered beyond the realm of modern computing capabilities. However,the train that Nvidia has been riding to great success recently, AI, was a later development still.

"AI is just the modern way of doing software."

Almost every supercomputer in the world today has some form of acceleration, much of it from Nvidia, Huang told me. And then there was quantum mechanics. The field of quantum chemistry is going quite well and theres a great deal of research in quantum chemistry, in quantum mechanics. And then several years ago I would say about five years ago we saw an emergence of a new field in computer science called deep learning. And deep learning, combined with the rich amount of data thats available, and the processing capability came together to become what people call the Big Bang of modern AI.

This was a landscape shift that moved Nvidia from the periphery. Now, Nvidias graphics hardware occupies a more pivotal role, according to Huang and the companys long list of high-profile partners, including Microsoft, Facebook and others, bears him out.

GPUs really have become the center of the AI universe, though some alternatives like FPGAs are starting to appear, as well. At GTC, Nvidia has had many industry-leading partners onstage and off, and this year will be no exception: Microsoft, Facebook, Google and Amazon will all be present. Its also a hub for researchers, and representatives fromthe University of Toronto, Berkeley, Stanford, MIT, Tsinghua University, the Max Plank Institutes and many more will also be in attendance.

GTC, in other words, has evolved into arguably the biggest developer event focused on artificial intelligence in the world. Nowhere else can you find most of the major tech companies in the world, along with academic and research organizations under one roof. And Nvidia is also focusing on bringing a third group more into the mix: startups.

Nvidia has an accelerator program called Inception that Huang says is its AI platform for startups. About 2,000 startups participate,getting support from Nvidia in one form or another, includingfinancing, platform access, exposure to experts and more.

Huang also notes that GTC is an event for different industry partners, including GlaxoSmithKline, Procter &Gamble and GE Healthcare. Some of these industry-side partners would previously have been out of place even at very general computing events. Thats because, unlike with the onset of smartphones, AI isnt just changing how you present computing products to a user, but also what areas actually represent opportunities for computing innovation, according to Huang.

AI is eating software, Huang continued. The way to think about it is thatAI is just the modern way of doing software. In the future, were not going to see software that is not going to continue to learn over time, and be able to perceive and reason, and plan actions and that continues to improve as we use it. These machine-learning approaches, these artificial intelligence-based approaches, will define how software is developed in the future. Just about every startup company does software these days,and even non-startup companies do their own software. Similarly, every startup in the future will have AI.

Nor will this be limited to cloud-based intelligence, resident in powerful, gigantic data centers. Huang notes that were now able to apply computing to things where before it made no sense to do so, including to air conditioners and other relatively dumb objects.

Youve got cars, youve got drones, youve got microphones; in the future, almost every electronic device will have some form of deep learning inferencing within it.We call that AI at the edge, he said. And eventually therell be a trillion devices out there: Vending machines; every microphone; every camera; every house will have deep learning capability. And some of it needs a lot of performance; some of it doesnt need a lot of performance. Some of it needs a lot of flexibility because it continues to evolve and get smarter. Some of it doesnt have to get smarter.And well have custom solutions for it all.

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AI everywhere - TechCrunch