Archive for the ‘IBM’ Category

Cognitive Computing Helps Vision Impaired

Tuesday, August 9th, 2016

Data analytics, a force for change in nearly every business, is now being leveraged to make lives easier for the vision impaired by increasing the graduation rate for guide dogs.

According to Guiding Eyes for the Blind, a nonprofit that breeds and trains service guide dogs, a mix of genetic and temperament data combined with natural language processing will bump the graduation rate to 59 percent from fewer than half. The initiative is also expected to lower the $50,000 cost to train each dog.

Guiding Eyes is using a combination of IBM Bluemix and Watson to analyze the organization’s structured and unstructured data. By moving half a million medical and genetic records and more than 65,000 temperament records to the cloud, Guiding Eyes uncovered insights into genetic, health, behavioral, and environmental factors that correlate to successful guide dog behavior and performance.

The organization is also applying natural language processing to trainer and foster family questionnaire answers to uncover insights into personalities and temperaments. This information is expected to improve the process of breeding, raising, and matching service dogs to owner.  

Cognitive Potential

Cognitive computing simulates human thought processes in a computerized model. According to author Bernard Marr, who has written several books about big data in business, the intent of cognitive technology is not to replace humans, but to expand on our capabilities and allow us to better process and understand the world around us.

IBM executives recently told Fortune that cognitive computing or machine learning is expected to become a $2 trillion USD market in the next 10 years, in addition to the $3 trillion opportunity in more traditional IT gear like servers, software, storage boxes. For startups, it presents a lucrative opportunity that can help deliver more innovative solutions and enhanced customer experiences across every industry.

For a free trial of IBM Watson Analytics click here.

For a free trial of IBM Bluemix click here.

Law Firm Uses Data Analytics to Give Clients Cost Certainty

Thursday, August 4th, 2016

International law firm McMillan LLP will begin using predictive analytics to create pricing models for its legal services to provide more cost certainty for clients.

By leveraging IBM’s comprehensive predictive analytics system, SPSS, and running the system on IBM Cloud, McMillan aims to remove subjectivity from the pricing process, according to announcement from McMillan and IBM. By analysing and interpreting McMillan’s internal data, the cloud-based solution will also help identify case issues most likely to affect price.

“We’ve seen how cloud and big data can transform business,” McMillan CEO Teresa Dufort, said in the statement. “We’ve chosen to be at the forefront of the legal industry using advanced analytics to service our clients. By partnering with IBM, we are looking to provide clients with greater transparency on the timing and cost of transactions.”

Dufort adds that the extra data and intelligence will allow the firm to better manage change and improve staffing, and provide clients with alternative fee options. The firm also plans to use IBM’s Bluemix platform to develop new app services, which will be exclusively available to McMillan’s clients.

“Analytics can be a catalyst for innovation to help organizations uncover data insights to solve business problems and yield real-time results,” says Tim White, Vice President, Software, at IBM Canada. “Data is the world’s new natural resource.”

McMillan has several practice areas including antitrust, commercial real estate, M&A and natural resources.

For a free trial of IBM Bluemix click here.

The Open Community Behind the Bluemix Cloud

Wednesday, August 3rd, 2016

The promise of cloud computing is scalability, collaboration, and dependability. But unless developers have access to a platform built around their needs and their preferences, the cloud remains limited in its ability to support enterprise solutions, a market worth upwards of $38 billion.

Until recently, using the cloud meant having the advantages of scalable power while relinquishing the control of an on-premise environment. IBM saw this gap as an opportunity and it became the basis for a new breed of Platform as a Service (PaaS), known as Bluemix.

The PaaS part of the cloud market is worth $12 billion, and is expected to be worth $55 billion by 2026.

Adam Gunther, Program Director, Bluemix Offering Management says that IBM started developing Bluemix from a user-based focus. “The next billion dollar idea always starts with a developer, alone in a coffee shop – that’s no different if you’re a startup or an enterprise.”

But the path from billion dollar idea to billion dollar app can be a messy one, full of obstacles like buying and configuring servers, creating application environments, and a hundred other tasks that prevent a developer from actually developing. Public cloud platforms were alleviating this, but as Gunther points out, there was still room for improvement.

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“What used to take 18 months, we can now do in a month,” Gunther says. “But that still isn’t fast enough. How does an enterprise, or just one developer, keep up with Silicon Valley?”

Speed and agility are important to developers, as BuildFax Founder and CTO Joe Emison told TechTarget. “Anything developers pick that they say allows them to deliver better software more quickly is going to win.”

Bluemix came out of this mission to create a cloud platform that could significantly speed up the process of developing scalable, enterprise-class apps, with the developer designed to be at the centre.

IBM was already in possession of a powerful Infrastructure as a Solution (IaaS) platform after acquiring SoftLayer, so the design team looked at the emerging PaaS market and came up with a product that not only differentiated IBM from other vendors, but provided IBM’s clients with a way to differentiate themselves from their competition.

Bluemix was built on Cloud Foundry, with support for open standards an integral ingredient in its architecture.

“What’s cool about Bluemix is that it gives devs in large organizations a secure sandbox to play in,” says Bryan Smith, CEO and co-founder of Toronto-based ThinkData Works, which is focused on providing APIs to standardized and normalized data from public sources.

Smith and his co-founder chose IBM Bluemix as their PaaS because of their commitment to providing developers with great tools. “They have a really similar mandate to ThinkData,” Smith says. “We look at it from a data perspective while IBM looks at it from a developer’s perspective.”

The Bluemix team opted for an open community model, combining the one million-strong developer membership of IBM DeveloperWorks with millions more on Stack Overflow. The benefit to this approach is, once again, speed for the developer. “Devs don’t want to call up tech support and ask for help,” Gunther says. “They want to Google the problem and come up with an answer quickly on a forum. The larger the community, the faster people can move.”

Open source technology

OpenWhisk, like Amazon Lambda and Google Cloud Functions, was released earlier this year. It is an event-driven “serverless” execution environment (sometimes referred to as a compute platform) and offers significant reductions in complexity and cost for developers who want to take advantage of microservices – small and light functions that do not require massive computing overheads. Instead of paying for the continuous up-time of a server, devs need only pay on a per-call basis.

Unlike Lambda and Cloud Functions, however, OpenWhisk is entirely open source. Not only can developers get under the hood and look at its inner workings, they can run the source code (and modify it) on their own, private machines.

As important as open technology and community support are, they aren’t enough to propel a PaaS product to be the preferred choice of developers and enterprise. For that, you need to offer users a large choice of software and services that can be quickly and cost-effectively integrated. This is one of Bluemix’s key selling points – a model that Forbes’ Greg Satell called “an app store for the cloud at enterprise scale.”

There are two major elements to this model. The first is the ability for Bluemix developers to choose from four application environments in which their code can be executed: OpenWhisk, Instant Runtimes (Cloud Foundry), IBM Containers (Docker), and IBM Virtual Servers (OpenStack).

Being able to choose an environment based on the design of your code without the need for multiple vendors or infrastructures is a huge advantage. If developing from scratch, devs can use OpenWhisk, an ideal environment for cloud-first projects, due to its cost-effective event-driven architecture described above. Meanwhile, given the increasing drive to move IT resources from legacy on-premises environments to the cloud, the option to create Docker-based IBM Containers or set up OpenStack deployments on IBM Virtual Servers means there’s no need to re-write for the cloud.

The second element, known as the Bluemix Catalog, is populated by a vast and growing array of services created by both IBM and third parties, across 13 categories including Data & Analytics, the cognitive technology of IBM Watson, Security, and Internet of Things, just to name four. Being able to bring these services to bear on a project allows apps to possess capabilities that simply couldn’t exist anywhere else.

Avoiding lock-in, reducing cost

Gunther points to Bluemix client GameStop, who came to IBM with a problem: daily inventory of their used game sales across their hundreds of locations consumed too much time and money. Employees had to manually identify every game box so that they could reconcile them with the game discs – every night.

GameStop was able to leverage IBM Watson’s neural net processing within a Bluemix app to process image captures of store shelves. Watson was able to return accurate counts for the video game boxes – sorted by title – even when the boxes were partially obscured or tilted on their sides.

Having access to IBM technologies such as Watson is a huge benefit to developers, but historically IBM hasn’t been an easy choice for them. “Over the last 20 years or so, we developed a reputation of being great and powerful, but really hard to use,” Gunther says. To counteract that perception, Bluemix was built to address two major considerations: lock-in and cost.

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A lot of companies do worry about lock-in,” Dave Hrycyszyn, Director of Strategy & Technology at Head, told TechRadar in 2015. Bluemix avoids this concern. “We go in assuming that multi-cloud and portability are must-haves,” Gunther says, pointing out that any company which makes this difficult for clients won’t see adoption of its platform.

Bluemix’s commitment to open standards helps with this greatly, as does its policy of not forking these open technologies.

“You could run a CloudFoundry app on Bluemix one day, and HP the day after that,” Gunther says. IBM has also taken the position that its Bluemix services should be portable too. If you developed an app on Bluemix with calls into the Watson service for example, you could move that app to another cloud provider or even take it in house. As long as the Watson API key remains the same, you’ll still be able to access that service from your app.

As far as cost goes, Bluemix has a free 30-day trial with 2GB of runtime and container memory to run apps – no credit card needed. There are free service and app tiers designed to let anyone experiment at no cost. Once you’re feeling comfortable, there’s a “down-to-the-penny” pricing calculator which gives precise numbers for every component of the Bluemix platform.

A strategy that focuses on the user, instead of the technology for its own sake, means that developers can concentrate on getting their work done. “Community and open technology are the underpinnings of our entire technical strategy,” explains Gunther.

For a free trial of IBM Bluemix click here.

AI and Big Data: The Next Frontier of Fintech

Wednesday, July 27th, 2016

Data analytics is becoming a cornerstone of the financial industry, with startups and established financial service firms looking to give investors clearer guidance with information collected and captured from multiple sources.

Advances in machine learning and artificial intelligence (AI) in particular are providing greater insights and better customer experiences.

AI-powered data analytics not only captures vast amounts of data in real-time, but also helps users understand how different data points relate to each other, providing insights that might otherwise be lost. Faced with a breakdown in brand loyalty as younger customers prioritize user experience, financial services are now racing to leverage data-driven cognitive technologies.

Cambridge, MA-based Kensho, which recently received $58 million in funding from Goldman Sachs, San Francisco-based Alphasense, backed by Tribeca Venture Partners, and Toronto-based Bigterminal are some of the fintech players leveraging AI.

It’s a lucrative market. Equity deals for AI startups, including fintechs, has increased nearly six times to nearly 400 in 2015, up from from 70 in 2011. As of June 15th, more than 200 AI-focused startups raised nearly $1.5 billion (U.S.) in funding this year alone.

 

TechPortfolio-Quote about Watson

“Data is the lifeblood of AI,” Falguni Desai of Future Asia Ventures wrote in Forbes recently. Desai quotes Adrian Lawrence, partner at Baker & McKenzie, in saying: “data and the various rules and processes which both enable and regulate access to and use of that data, stand at the heart of disruptive fintech businesses.”

The market is also “evolving from a descriptive analytics model (rear view mirror view) to a predictive analytics model (insight GPS view),” says Jim Marous, co-publisher of  Financial Brand.

“With predictive analytics, we are in a better position to ‘know the consumer,’ ‘look out for the consumer’ and ‘reward the consumer,’” he writes, “learning from previous experiences and predicting future behaviour.”

Bigterminal CEO Adam Rabie says advances in machine learning are allowing fintech platforms like his to do more for their customers.

Powered by IBM Watson, Bigterminal’s solution curates, consolidates, and analyzes financial data from markets, social media, and other sources. The company’s target market includes researchers, analysts, and traders as well as big banks and insurance companies. Bigterminal’s app can be used to conduct research, generate hypotheses, and make decisions based on significantly more data than what financial analysts traditionally use.

“Previously unthinkable”

Leveraging IBM Watson’s cognitive technology has allowed Bigterminal to do what was previously unthinkable, Rabie says.

“Our machines are computing hundreds of thousands of stories a day, millions of tweets, and trillions of financial data points,” he says. “If it can be smart at finding the anomalies and the connections between them, it can deliver a lot of explanations that are outside of human capacity.”

Developer FYI

Other notable financing in the space includes a $325 million Series E round last year for Avant, a personal-loan startup that leverages machine learning. Seattle-based fintech Kavout also recently launched a new investment platform that finds trading opportunities using tools powered by machine learning and big data.

Improvements in cognitive technology, such as relationship analysis and language comprehension, will expand the possibilities for data analytics in finance and banking. As fintechs bring this functionality into their services, they will continue driving disruption in the financial world.

For a free trial of IBM Watson Analytics click here.

VIDEO: Share Your Startup’s IP with a Resource, Not a Rival

Monday, July 18th, 2016

Partnerships between enterprise and startups can help tech ecosystems grow. One place where this kind of cooperation happens is IBM’s Bluemix Garage.

Pat HorganAccording to Patrick Horgan, VP, Manufacturing, Development & Operations at IBM Canada, Bluemix Garage operates on an open model that allows university researchers and startups to safeguard their IP while benefiting from the knowledge and resources of a large enterprise.

“We have a history of getting through [growth] cycles and to the world market,” says Horgan. That experience is critical to helping startups achieve success.

For more information on this open IP model, private partnerships, and the Bluemix Garage, watch this video:

https://www.youtube.com/watch?v=6csf9-k8npM

For a free trial of IBM Bluemix click here.

Insights on Demand: Capturing Streaming Data

Friday, July 8th, 2016

Saying your business is driven by data analytics is one thing. Using it to your advantage is quite another.

Brands often expect immediate benefits from data analytics, without using insights to help steer their marketing efforts.

About three quarters (74 per cent) of enterprise architects aspire to be data-driven, yet less than a third (29 per cent) say their companies are using it to generate measurable business outcomes, according to a report from Forrester. The report says data insight will be a “key competitive weapon” for companies this year.

This performance gap is driving an increase in demand for streaming analytics and what Forrester calls “systems of insight.” For most organizations, the best approach is a solution that captures customer insight and engagement in real time.

An example is the integration of IBM Cloud and Bluemix, which can deploy cognitive APIs to analyze a high volume of social media data in seconds using streaming analytics.

When combined with Watson’s Personality Insights, 40 calculated personality traits can show you if the people viewing your ads match the profiles of your target customers.

Analyzing continuous, incoming data and stitching that data together over time can also create something special: moving pictures of data that tell a powerful story. The bonus: It’s something companies can immediately act on.

For a free trial of IBM Bluemix click here.

Women in Tech on Twitter: Fear, Loathing, and Support

Thursday, June 30th, 2016

Women in the technology sector are using Twitter to share fear and vent, according to analysis by the TechPORTFOLIO team with the IBM Watson Tone Analyzer.

As part of our month-long series highlighting women in tech and their unique experiences and challenges, we looked at a list of prominent women in the sector who were active on Twitter and used cognitive analysis to determine the tone of the tweets sent to them in public. We wanted to find out whether there was a difference in the way that people in public and their community spoke to them on Twitter, compared with the technology sector at large.

Women on Twitter

Tone Analyzer Women

Control Group

Tone Analyzer Control

The figures above seem to indicate that there is much more anger and fear present in conversation aimed at women in technology, and marginally more emotional range and openness.

A large number of the tweets with a degree of fear or anger were people seeking or offering mutual emotional support, for matters large and small.

The tech community in the control group had more conversations, but they were more one-sided. There were a far higher level of “drive by” tweets without any real attempt to engage in conversation; such as requests to retweet, or feature suggestions.

In our analysis, we didn’t see that many examples of outright abuse directed at our women in tech list. The control group — which was filled with several high-tier individuals such as Apple CEO Tim Cook, philanthropist Melinda Gates, and “inventor of the web” Tim Berners-Lee — had several tweets that been marked as deleted. It’s possible that any retroactive reporting on Twitter’s language and possible tendency towards abuse might be affected by reporting of offensive content and moderation.

This shows that despite Twitter’s ongoing issues with harassment against women, the platform is still a valuable community space. Settings that allow for trusted conversation, like these from UX researcher Caroline Sinders, would support this while allowing for some protection against drive-by abuse.

https://twitter.com/dinosaurrparty/status/740227885772898308

Try the Tone Analyzer now. If you want to incorporate IBM’s Watson into your own application hosted in the cloud, click here.

Method

For our group, we selected the Anita Borg institute’s Twitter list of 500 most important women to follow on Twitter. Of those, we found the 50 most active, and took one week of tweets: June 8 to June 15, with a maximum of two @-replies each day.

There are no “men in tech” Twitter lists, of course, at least ones that are from comparatively reliable sources. Our control group, therefore, was Robert Scoble’s popular list of most influential people in technology. Several of the people on the list are, of course, women; a straight comparison with the online population at large works better for our purposes, anyway. Once again, we took the fifty most recently active users.

The control group contained several high-tier individuals on Twitter, making the volume of @-replies incredibly high. The TechPORTFOLIO team had to cut the time period down to 24 hours only, for June 8–and even then, we had to remove an unusually high spike of tweets aimed at @davidplouffe, an Uber board member and Barack Obama election campaign strategist. (Sorry, Mr. Plouffe, you were already having a bad day.)

For a free trial of IBM Watson Analytics click here.

Wimbledon and Data Analytics a Perfect Match

Tuesday, June 28th, 2016

The 2015 Wimbledon Championships were a battle for hearts and minds. While players were on the courts, the team behind one of world’s highest-profile sporting events fought to “host the best tennis championships in the world – in every way, and by every metric.”

To provide players, journalists and spectators with the best experience possible, Wimbledon partnered with IBM Bluemix to turn insights into powerful narratives.

During the two week period, 48 courtside experts captured approximately 3.4 million real-time data-points on every move and outcome. When Sam Groth hit the second-fastest serve in Wimbledon history, the information was shared with a digital audience instantly. IBM’s Sam Seddon told the BBC that “during last year’s final we were analyzing about 400 tweets a second.”

The data-driven approach served up big results: the partnership achieved 71 million visits and 542 million page views from 21.1 million unique devices.

As the 2016 Championships get underway, Wimbledon and IBM will aim to up their game and deliver an even better experience.

For a free trial of IBM Bluemix click here.

For a free trial of IBM Watson Analytics click here.

Land, Sea and Air: When IBM Bluemix Goes On The Move

Wednesday, June 22nd, 2016

Whether it’s in a tiny Swedish development drone no bigger than a slice of toast, or a lumbering garbage truck in the streets of Nairobi, Bluemix technology can be found on the move across the world. Check out these case studies:

Crazyflie Drones

https://www.youtube.com/watch?v=-rjpwJaDhz4

Malmö, Sweden-based Bitcraze has created a handheld drone called Crazyflie, which weighs 27 grams and is equipped with long-range radio. It’s open sourced and expandable – almost like an airborne Raspberry Pi.

The Bluemix cloud is used as part of the mechanism to pilot the drone, either through an app or a gaming controller, significantly reducing development time. “It really saved us a lot of work when we got started,” says Bitcraze co-founder and developer Marcus Eliasson.

Fixing Nairobi’s Roads

To monitor the Kenyan capital’s traffic and construction needs, city officials fitted their fleet of garbage trucks with specially adapted mobile devices that used acceleration, gyroscopic and location data. As the trucks make their rounds, the devices upload their data to the cloud.

Bluemix is then used to deliver the results of the analysis to officials, accessible on mobile and desktop. “For the first time, city officials have a clear understanding of where potholes and speed bumps are,” says Dr. Aisha Walcott-Bryant of IBM Research Africa.

Speedboat Racing

https://www.youtube.com/watch?v=FHGTmHEwr14

SilverHook designs high-speed racing watercraft reaching speeds of up to 200 mph. Pilots have access to real-time feedback about the race through IBM Watson Analytics and Bluemix was used to rapidly develop and deploy this infrastructure, cutting development time by 40 per cent.

Ian Taylor, CEO of Animation Research, which works with SilverHook, says that the speed boat’s pilot receives data in real time helping drivers make decisions on the fly.

For a free trial of IBM Bluemix click here.

For a free trial of IBM Watson Analytics click here.

Pizza Menus, Rebounds, and Blood Sugar: 3 Watson Use Cases

Tuesday, June 14th, 2016

We’ve been told countless times, what you get out of a computer is only as good as what you put in. But what happens if you’re feeding a computer that learns and reasons?

According to Caroline Ong, Business Analytics Leader at IBM Global Business Services Canada, cognitive computing is not necessarily programmed, but designed to understand context, reason (and provide that reasoning). Moreover, cognitive technology means the machine learns from feedback.

And because there are so many applications for this kind of technology, the system becomes specialized according to what it’s used for.

“It’s not one giant machine that takes knowledge from person 1, client X and system Y,” explains Ong. “Watson is a solution tailored to specific industries and specific client use cases.”

Here are three real-life cases from the IBM Watson team and their collaborators that use real life data in surprising ways.

Rebounds

https://www.youtube.com/watch?v=7zKLEyLTqNU

The Toronto Raptors’ system can call up and interpret game statistics from every member of the team – and perhaps more importantly, their prospective opponents, so that the team can be as prepared as possible.

“We’re working with the Raptors to reimagine their data instead of using pen and paper, to pick out who we should be drafting next, or what are some of the tradeoffs we need to make,” says Ong.

Data is an important aspect of this with a feature called “Tradeoff Analytics,” where the user can tweak various statistics and see possible results. But basketball isn’t just a numbers game – personality analytics of players and opponents can also provide some valuable intelligence.

Quote

Blood Sugar Levels

Medtronic, which makes devices that measure blood sugar levels in diabetes patients, are exploring how to incorporate IBM Watson technology to ease the pressure on caregivers.

Ong said that the aim was to improve “quality of life for the patient and for the caregivers of the folks who are dealing with diabetes. The two teams in IBM and Medtronic worked together to see how we predict hypoglycemic levels and events, up to three hours in advance – as opposed to waiting for things to happen before we act on them.”

The aim is to get peace of mind for the caregivers without having them constantly monitor physically every single time.

Other health uses of Watson include Under Armour, data from wearable technology that can be used to make fitness recommendations, and a partnership with the BC Cancer Agency that uses patient data, a genetic profile and medical literature to make personalized treatment plans.

Pizza Menus

https://www.youtube.com/watch?v=jC0I08qt5VU

A robot concierge being piloted by Hilton hotels uses IBM Watson cognitive analysis to give guests advice, for instance, on what nearby Italian restaurants have kid-friendly cuisine.

Connie, the collaboration between IBM and Hilton, takes and interprets local information such as restaurant and tourist information using speech to text, dialog and natural language APIs, and ingests information from IBM travel advice too WayBlazer.

Ong says that the project behaves like a virtual assistant, “but this time the communication is done through talking to a robot in the lobby of the hotel.”

The more questions the robot is asked, the smarter it gets – and the robot keeps a log of questions that people pose it, which is helpful for the hotel itself.

“The good news is, you don’t have to tip the robot,” says Ong.

For a free trial of IBM Watson Analytics click here

Analytics4Life Takes The Stress Out Of Coronary Artery Disease Tests

Wednesday, June 8th, 2016

For a disease recognized as the most common global cause of death – 8.14 million worldwide in 2013 – coronary artery disease is extremely laborious to diagnose. A Canadian firm, Analytics4Life, is looking to cut out a large part of the labor involved – and the danger posed to patients – by leveraging data in new ways.

In a nuclear stress test, patients must exercise on a treadmill to measure blood flow after radioactive dye is injected. Physicians and hospital workers need to spend resources on managing radioactive nuclei. The test can take up to five hours and is only 75% accurate.

Analytics4Life, a startup based in Kingston, Ontario, is attempting to develop a much more straightforward method, using machine learning through neural networks and genetic analysis, with physiological information conventionally considered valueless.

“We’ve been able to demonstrate a very simple test that takes about three minutes to do where you don’t have to stress the patients,” says Shyam Ramchandani, co-founder and Director of Marketing and Business Development at A4L. “It’s just surface electrodes that go on patches on the body: seven of them. Three minutes later, they’re done, and then by the time their patches are off and their shirt’s on the result is on the doctor’s portal.”

Tech Portfolio Fact

This month, A4L is running its first machine learning tests with recruited patients already diagnosed with coronary artery disease, a condition where the vessels that supply oxygenated blood to the heart are obstructed by plaque; if the plaque builds up excessively and hardens, the condition leads to blood clots, angina and cardiac arrest.

After crunching what A4L calls “phase energy” data – which draws on a wide array of physiological signals – from the electrodes, and generating a formula based on the results, the company will then test blind on another selection of patients to see if their formula is an effective predictor.

“‘Phase energy’ is purely a mathematical concept,” explains Ramchandani. “There is no current physiological description of this. We will be the first to demonstrate this.”

The test itself can be administered from a “phase energy signal recorder”, an iPad Mini adapted with proprietary technology to connect to the electrode input. The recorder transfers the data to the cloud. The front-end software and the data processing lives on IBM Cloud, and important code infrastructure is hosted on IBM’s Bluemix platform.

This setup makes it all portable. “You technically can take our test anywhere you have a 3G signal,” says Ramchandani. “You wouldn’t have to fly people in from remote areas to a place that has a special camera.”

According to Ramchandani, IBM infrastructure is ideal for handling healthcare data. “We have an almost off-the-shelf HIPAA compliant tool. When you’re collecting medical information, you have to either de-identify it in a way that it can’t connect it back to the patient, or it needs to be hosted on and transmitted on infrastructure that’s been validated for security purposes.”

A4L completed series A funding last August for CA$10 million, and is hoping to complete series B at the beginning of 2017 to help it fund commercialization activity and a pivotal clinical trial.

Tech Portfolio Fact

That pivotal clinical trial will support their next key step: the FDA approval process. “If you can’t get through regulatory affairs in an efficient manner and get the kind of reimbursement you need, it’s not going to be a business,” Ramchandani says. The company has made senior level hires in order to facilitate interaction with the FDA.

Another option for A4L is expanding in Europe. (They will not start with Canada initially, because the market is too small.)

Although a price for the test hasn’t been set, A4L says that the overheads for its new system, once approved and functioning, are going to be astronomically less than the status quo. “We have no regulated nuclei that needs to be injected, purchased, or handled,” says Ramchandani. “You don’t need a specialized technician, or a specialized camera.”

And no more running on a treadmill, either.

For a free trial of IBM Bluemix click here.

VIDEO: Cognitive Technology Needs the Cloud

Sunday, June 5th, 2016

Cognitive solutions have developed beyond traditional AI capabilities into machine thinking, and startups can now leverage cognitive technologies like IBM Watson through the cloud to offer better solutions to their customers.

IBM’s Watson can digest and reason through information, and come up with solutions. This allows startups to offer their customers APIs like natural language processing without the obstacles that prevent easy, robust and responsive user experiences.

Placing this advanced technology in the cloud provides the resources that cognitive needs to function smoothly, and for it to be accessible through platforms including IBM Bluemix.

For more on this, here’s part of our recent interview with IBM’s Nevil Knupp, Vice President of Cloud, IBM Canada.

https://www.youtube.com/watch?v=24fSC8L3i5Y

For a free trial of IBM Bluemix click here.

For a free trial of IBM Watson Analytics click here.

VIDEO: Expertise and Mentorship Help Startups Exit the ‘Valley of Death’

Wednesday, June 1st, 2016

Transitioning to a scale-up is proving difficult for startups within Canada’s tech ecosystem. There are many questions about how to better support startups in order to maintain competitiveness and longevity. The transition can be so difficult that Patrick Horgan, VP, Manufacturing, Development & Operations at IBM Canada refers to it as the ‘Valley of Death’.

Bridges are being built over the Valley, though. Initiatives like IBM’s Bluemix Garage – which provides technology support, shares growth experience, and offers mentorship – aims to foster scale up success in the long-run.

To learn more about the challenges startups face in scaling up, and about initiatives that offer support, watch this video:

https://www.youtube.com/watch?v=gGVlvcO3pn0

VIDEO: IBM’s Watson Offers Cognitive Technology Out of the Box

Saturday, May 28th, 2016

Not all startups can afford artificial intelligence and the associated infrastructure, but thanks to IBM’s Bluemix platform, the cognitive capabilities of IBM Watson can be a ‘call’ away. Apps developed on the platform will be able to make requests from Watson.

This will give startups access to functions that analyze data streams or translate text into language that either a machine or another person can understand.

For more on this, here’s part of our recent interview with IBM’s Nevil Knupp, Vice President of Cloud, IBM Canada.

https://www.youtube.com/watch?v=HmqmBcJM0AE

VIDEO: IBM’s Ontario Research Consortium Partnership

Tuesday, May 24th, 2016

IBM provided a $200+ million “sandbox” and access to the country’s biggest supercomputer, along with an abundance of analytical tools as the company’s contribution to Southern Ontario Smart Computing Innovation Platform (SOSCIP), a research and development consortium that now includes 14 universities and 2 colleges.

The result? The partnership has generated $2 billion in pipeline revenue by helping university researchers and startups get to market.

This innovation model, facilitating collaboration between IBM, academic institutions, Ontario Centre of Excellence, and SMEs aims to help establish Ontario as a leading global centre for driving innovation in information technology, health, and urban infrastructure (water, energy, transportation).

By partnering with private enterprise, academic institutions can leverage cutting-edge technology and experience.

What IBM’s Watson Thinks of HBO’s Game of Thrones Characters

Friday, May 20th, 2016

When we found out we could access IBM’s Watson to analyze conversation tone, obviously our first idea was to apply it to HBO’s Game of Thrones.

So we coded a scraper and extracted the dialogue on Wikiquote of all the main characters. We then unleashed Watson’s Tone Analyzer — a tool for understanding the emotional impact of text — to assess five core emotions, as well as overall emotional stability, confidence, and agreeableness.

The Tone Analyzer is part of IBM’s Watson suite that includes several tools for textual analysis, such as concept search and linking, visual comprehension, and language translation. It’s accessible through an API on the IBM Bluemix cloud platform.

It’s no surprise no one in Westeros turned out to be especially emotionally stable (we’re looking at you Ramsay Bolton). In fact, the majority of characters we tested, from the Khaleesi herself to Jon Snow and even jolly old Tyrion Lannister, turned out to be mainly very angry and not at all joyful.

But the results we did find – some expected, some not – reveal a bit more about a few of the players.

Here’s our (spoiler free of season six, we promise) analysis.

CHARACTER: Joffrey Baratheon

RESULT: ANGER

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Rage is the overriding emotion for Joffrey the False. Interestingly, though, no one particular line in our textual analysis stands out as being obviously furious or malicious. This, of course, is worse because it just shows the continual burning rage inside the boy king.

CHARACTER: Sansa Stark

RESULT: Even ANGRIER than Joffrey

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Sansa’s incandescent fury is clear at several points – and the Tone Analyzer has picked up on this. Her reputation among fans as a passive flower is completely undeserved. There’s not a great deal going on with conscientiousness, which could suggest machinations to come.

Combine this with her sky-high confidence and it seems we have identified that Sansa is a rising power player in the battle for the Iron Throne.

CHARACTER: Arya Stark

RESULT: Low confidence

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A girl has no name…or confidence. Arya rates very low on the confidence scale for a Game of Thrones character. In fact, there are only four lines in her entire script that rate as confident. The rest don’t score anything at all. It looks like the first step of Faceless Man assassin training is breaking the spirit.

Still angrier than a burning nest of wasps, though. Just ask Meryn Trant.

CHARACTER: Varys, Master of Whispers

RESULT: Calm and in control

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Varys once said: “The storms come and go, the waves crash overhead, the big fish eat the little fish, and I keep on paddling.” With lines like this, we’re not shocked to see the tone analysis of his language shows he rarely raises his voice. He’s unique in Westeros in being able to regulate his emotions and keep his cards close to his chest. Clearly, he’s perfectly suited to his role as spymaster regardless of who he serves.

Is there a character you want to analyze? Try the Tone Analyzer now.

If you want to incorporate IBM’s Watson into your own application hosted in the cloud, click here.

Agriculture. Healthcare. Real Estate: Three IBM Bluemix Use Cases

Thursday, May 19th, 2016

We spoke to a sample of Canadian startup entrepreneurs using IBM Bluemix to support their apps, and found a key theme was the amount of time and resources saved by leveraging Bluemix technology.

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Agriculture

The PlantID3 mobile app is used by agricultural professionals to monitor crop health. The service is in beta testing with 2,000 trial users and a soft launch is planned later this year in Australia.

Dylan Lidster, founder and CEO of PlantID3, says in agricultural tech, startup organizations clear a path for the larger corporations because they can pivot quickly and spend less money getting to market.

“The aging demographic of agriculture is quickly rolling over as a new tech sophisticated producer enters the market, open to change and moving swiftly,” he says.

In the app a farmer might take a picture of an apple tree with a disease. The app then searches through the database for pattern recognition and tags. The image is tagged and stored, and then feeds into recommendations for remedial practice, such as pruning techniques, fertilization or spray application. The database of image storage and tagging and the recommendation tree run off IBM’s BlueMix infrastructure.

Lidster is making sure that the customer base is involved at the early stages of development of the PlantID3 app, to ensure product fit with the interface. Being cheap and quick to scale is key.

“[BlueMix] saves many hours of labour and provides us with advanced services such as use of Watson that we could not achieve without the support of IBM,” says Lidster.

Healthcare

Speed and scalability are also paramount when you’re building an app that transmits health data. With SwiftPad, when patients take a photo of their prescription and send it to their pharmacy of choice, they can get real-time feedback on when their medication is ready and can opt to have it delivered.

Saif Abid, CTO of SwiftPad, says: “Currently, we have around 12 services running on IBM’s Bluemix network. To put this in a financial perspective, we’re spending around 75% less than we would with other competitors.” Among the services used are CloudFoundry, push notifications, and Watson.

“With Bluemix, we’re able to focus on engineering the best solution possible for our users without having to compromise the quality of tools and services we use,” says SwiftPad CEO and co-founder Amir Motahari.

Real Estate

Gregory Melchior, CEO of real estate software startup 4D Virtual Space, is using social media marketing as a key part of his growth strategy. His organization aims to replace floor plans for real estate developers. Instead of constructing a sales centre, realtors would use the app to show customers through a space, allowing prospective buyers to walk through and even visualize how their own furniture might look.

Feedback from users is vital, and quickly accessed. “With IBM Watson we’re able to get, per month, 500,000 documents analysed in social media immediately,” says Melchior. “We hit the ground running.”

Click here for a free IBM Bluemix trial.

 

 

 

Under Armour Leverages IBM’s Watson to Challenge Fitbit

Thursday, May 12th, 2016

One of the biggest brands in athletic wear is charging into wearable tech with a pack of products and a pair of tech industry partnerships. Under Armour is leveraging artificial intelligence to give its offering an edge over competing products from Nike and Fitbit. 

Retailing for $400, HealthBox is a trio consisting of a Fitbit-like band, a digital scale and a heart-rate monitor. And UA isn’t starting from zero in its effort to tap demand for wearables.

Over the last few years, the company has snagged three massive online fitness communities: Endomondo, MapMyFitness and MyFitnessPal. They now control the largest online wellness-focused ecosystem, at 165 million users. And it’s what HealthBox can do with all that data that makes this a compelling package.

Under Armour partnered with HTC to develop the hardware and a smartphone app called UA Record, which ties all the products together. The UA fitness tracker is cleanly designed, made of a rubber-like material with a LED display. The heart rate monitor is constructed of durable band and the monitor glows when it detects a heartbeat. The scale measures weight and BMI. All the data from the three devices talk to each other and transfer data via Bluetooth to UA Record.

Cognitive Coaching

Under Armour’s partnership with IBM and the “cognitive coaching” potential of Watson differentiates HealthBox from the competition. By feeding nutrition, training, and sleep information into Watson, it’s “able to understand data in large volumes, make recommendations, and continuously learn,” says Chris Glodé, Under Armour’s VP digital, connected fitness. “The more data UA Record inputs, the smarter Watson becomes.”

UA has experimented with Internet of Things in the past. They built a sensor-laden compression T-shirt back in 2011 for the NFL Combine, where college stars worked out for prospective pro teams. The shirt provided raw data on acceleration, speed and heart rate for scouts to pour over. HealthBox and the partnership with IBM means that the Record app will be able to send the data to Watson to disambiguate.

Watson’s Cognitive Coaching uses a comparative model, grouping users based on criteria like age, gender and activity level in order to provide training and recovery recommendations.

And the experience will get richer over time.

“As you record more data and as more data is recorded across the community, the smarter the insights will become,”  Glodé says.

How Much is Cognitive Technology Helping the Raptors?

Tuesday, May 10th, 2016

A year ago the Raptors were victims of an unexpected 4-0 sweep in the first round of the NBA playoffs at the hands of the lower-ranked Washington Wizards. They’re now tied with the Miami Heat 2-2 in a grueling best-of-seven series, which will see the eventual winners play LeBron James and the Cleveland Cavaliers in the Eastern Conference finals.

Maple Leaf Sports & Entertainment, which owns the Raptors, announced in February that it would use cognitive analysis provided by IBM’s Watson technology platform, noting that Watson would be used mostly for talent acquisition.

Is cognitive technology one of the factors behind the improved performance?

It’s difficult to answer that question because the Raptors consider the IBM agreement to be a competitive advantage, and are therefore mum on this subject. With a head coach as tight lipped as Dwane Casey, this is hardly surprising.

There’s only been one addition to the team since IBM and the Raptors announced the use of Watson, so the application of cognitive technology might not be a factor unless they’re using Watson’s analysis for more than recruitment.

Unstructured Data

Traditional analytics-based approaches require data to be tightly structured and presented in a predictable format. Watson is different in that it makes sense of large volumes of unstructured data — video footage, news articles, scientific journals, social media, as examples —  which a few years ago would have required a human to interpret.

And the machine learns. The more data it’s fed, the better its predictions become. Each suggestion is even accompanied by a confidence level rating.

In professional sports, Watson can be used to determine, based on any number of parameters, if a player will be a good fit for a team’s social dynamics. Artificial intelligence can quickly identify, for example, a player who will fill the needs for a particular position, work within salary restrictions, and play well with teammates.

With two crucial contracts — Bismack Biyombo and DeMar DeRozan — on the table at the end of this season, a salary cap to manage and four first-round draft picks over the next two years, the next incarnation of the Raptors lineup is far from clear.

While it’s tough to gauge Watson’s impact on the current season, the platform is likely learning much as it analyzes players on and off the court. Whatever the case, fans should expect the big data addition to play a bigger role in the Raptors’ strategy going forward.

Fans Getting Closer Than Ever to Tour Action Thanks to the IoT

Wednesday, April 27th, 2016

As the official technology partner for the Tour de France, Dimension Data is changing the spectator experience of the world’s most prestigious cycling race with the IoT. Using IBM’s InfoSphere Streams analytics platform, Dimension Data monitored the real-time geolocational data of almost 200 riders over 21 days.

Every bicycle in the race was equipped with GPS sensors and a sophisticated relay system that transmitted data to apps, websites and broadcasters, giving fans and media the ability to track a rider’s progress throughout the race. The experience was no longer limited to a manual process that involved radios, stopwatches, and chasing riders on motorcycles to read the numbers on their shirts.

Dimension Data’s IoT solution provided a “positional fix every second, the latitude and longitude and the speed of every single rider,” IBM Asia Pacific’s Big Data Technical Leader Chris Howard told ReadWrite. “And from that raw data, we then did lots of things to determine their journey so far, how far they’d progressed, the ranking of the riders, the distance and times between all of the riders.”

In the future, a related IBM technology known as Quarks will provide cycling fans, broadcasters and team strategists deeper insights during the Tour. Quarks is an open source platform that lets developers create IoT applications to analyze data on the edge of their networks.

Howard believes that sensitive information such as “power output data, cycling cadence, pedalling cadence, respiration, [and] heart rate” could be gathered and used in a competitive nature.

To read more about how IoT is disrupting the Tour de France, please click here.