Ryerson University’s startup incubator DMZ has launched an advisory council to support the Canadian startup and entrepreneurial ecosystem.
The 18-person council was handpicked from over 500 applicants and includes: Kirstine Stewart, former Head of Media at Twitter Canada, Yung Wu, Managing Director of NFQ Ventures, and Dino Trevisani, President, IBM Canada
The goal of the council is to “increase visibility for Canadian entrepreneurs, and to develop new approaches to fuel the success of Canadian innovators,” according to a DMZ press release about the initiative.
“The DMZ’s advisory council will play an important role in finding strategic and innovative approaches that will strengthen the DMZ’s position as a hub in the innovation economy,” says Mohamed Lachemi, president and vice-chancellor at Ryerson University.
“The council will also better forecast the needs of the startup community and find solutions that will be supported by some of the leading minds in business and technology,” he says.
The first order of business for the advisory council is to create a bootcamp-style program to help new startup owners learn hard and soft skills needed to accelerate their success or failure in the first six months.
Beyond that, the advisory council will develop a collaboration agenda for Canada’s startups to bring together technology hubs nationwide and align with Canada’s innovation agenda.
The Advisory Council members are:
Nadir Mohamed, (DMZ Advisory Council Chairman), Chairman, ScaleUP Ventures
IBM has a plan to keep companies in Canada, help them grow and commercialize internationally. A major component of that plan is the company’s Innovation Space announced today in Toronto.
“I want these companies to stay in Canada. I want jobs. I want to create businesses,” Dino Trevisani, President of IBM Canada, told TechPORTFOLIO in an interview at the company’s launch. “Companies don’t have to go to Silicon Valley. They don’t have to sell themselves. IBM as a multinational corporation can give them access to markets.”
Companies in IBM’s Innovation Space will be offered advice, mentoring, support services, education, and legal counsel, as well as technical capacity and infrastructure.
“The government is doing their job – they’re investing,” said Trevisani. “Academia is doing their job. Now, private sector multinationals that can give access for commercialization for these startups is what it’s all about. If we’re going to grow, we need companies to grow here. We don’t need them to develop great technologies and leave.”
IBM’s Innovation Space was set up with $24.75 million of investment by IBM Canada and $22.75 million investment by Ontario’s Jobs and Prosperity Fund.
“We’re putting our technologies in at universities and the government is helping,” said Trevisani. “It’s great innovation but we need to give them a reason to stay [in Canada].”
Toronto was picked as a location for the innovation hub because of its infrastructure and established talent. “Tech companies want to be close to transit,” said Trevisani. “Close to universities where there are sources of skilled workers.”
But Toronto is not the only focus for IBM, as Trevisani pointed out initiatives underway in throughout Ontario and other provinces.
“We’re not branding this so we can get some kind of value for IBM,” said Trevisani. “We’re partnering with MaRS, with OCE and all other incubators. We want to be an impetus for growth and support for that marketplace and for that incubator innovation market.”
More info about the IBM Innovation Space can be found in our coverage of today’s launch.
Toronto has a new startup hub, and it’s right in the downtown core on Spadina Ave.
This morning, IBM in partnership with Ontario Centres of Excellence (OCE) and the Government of Ontario launched the IBM Innovation Space that aims to help businesses propel into the global marketplace.
The IBM Innovation Space is part of the IBM Innovation Incubator Project, a $54-million initiative funded IBM and the Government of Ontario’s Jobs and Prosperity Fund. Other partners include the SOSCIP Research Consortium and members of the Ontario Network of Entrepreneurs (ONE).
The IBM Innovation Space houses startups and technology companies that use IBM Watson and cloud technologies. The diverse group of tenants include LifeLearn, whose Sofie veterinary software uses IBM Watson to search through diagnoses and literature, and BigTerminal, a personalized financial information aggregator.
“Access to the latest technology, including cognitive and cloud, as well as these kinds of resources and support, are so often out of the reach of start-ups – that’s why we created this space,” said Dino Trevisani, President of IBM Canada. “We want to help them innovate, get to market and expand more quickly to ultimately become the disruptors of tomorrow.”
The IBM Innovation Space will provide companies with capacity, networking and infrastructure along with new IBM cloud and cognitive business technologies. In addition, experts will offer mentoring, support services, education, and legal counsel to assist in companies’ growth.
Cognitive technologies and artificial intelligence are becoming increasingly attractive to investors, especially after social media startups have peaked. CB Insights predicts that funding of AI-enabled startups will reach $1.2 billion in 2016.
The Internet of Things leverages chip technology, data analytics, and the cloud to make machines that not only work for us, but know us. A toothbrush called Grush extends the inroads of IoT technology into our daily lives.
Grush makes a children’s toothbrush that connects to both a mobile game for kids and a dashboard for parents, in a bid to ensure youngsters learn the proper way to clean their teeth.
An embedded Intel chip in the toothbrush collects dates, times, accuracy, duration and other usage data. That information is relayed to IBM Bluemix via a JavaScript runtime, allowing the toothbrush, the mobile game app and the parental dashboard to work together in real time.
The Watson Analytics platform interprets the data and determines whether the user is about to stop brushing before all the teeth have been properly cleaned. If that’s the case, Grush will alert the kid (and his or her parents) that there’s more work to do.
Grush and IBM first connected in 2014 at Smart Camp, where the fledgling IoT startup impressed judges. Grush later joined IBM’s Global Entrepreneur program, where the startup has used Bluemix to develop and scale its cloud-based smart toothbrush and smartphone app.
Using the IBM Cloud Architecture Center allowed Grush to refer to IoT, data analytics and mobile material and expertise as it worked, skipping some of the trial-and-error process in developing its interactive device.
How quickly can an online enterprise go global? Just ask Pokémon Go developer Niantic.
While such immediate virality is rare, predicting user uptake is always a guessing game. Surprises on the upside can trigger an avalanche of negative reviews if the back-end infrastructure doesn’t support viral popularity in multiple markets.
Human resources and finance software company Workday recently cited global expansion as a reason for its decision to sign a seven-year contract with IBM to use the IBM Cloud platform for developing and testing new products.
Workday CEO Aneel Bhusri said IBM Cloud will enable his company to scale development and testing faster, and that they may use further services in the future. “Workday will use IBM Cloud to continue accelerating Workday’s internal development and testing efforts to support our ongoing global expansion,” Bhusri said.
IBM’s global cloud data infrastructure includes nearly 50 scalable and security-rich IBM Cloud data centers in 17 countries on six continents, according to a statement by Workday.
Fast Company notes, “The last thing you want is to start losing customers because your site crashes or some other part of your infrastructure isn’t up to the task.”
Learn more here about the Workday and IBM Cloud partnership.
How do you create a movie trailer about an artificially enhanced human?
You turn to the real thing – artificial intelligence.
20th Century Fox has partnered with IBM Research to develop the first-ever “cognitive movie trailer” for its upcoming suspense/horror film, “Morgan”.
Fox wanted to explore using artificial intelligence (AI) to create a horror movie trailer that would keep audiences on the edge of their seats.
Movies, especially horror movies, are incredibly subjective. Think about the scariest movie you know (for me, it’s the 1976 movie, “The Omen”). I can almost guarantee that if you ask the person next to you, they’ll have a different answer.
There are patterns and types of emotions in horror movies that resonate differently with each viewer, and the intricacies and interrelation of these are what an AI system would have to identify and understand in order to create a compelling movie trailer.
Our team was faced with the challenge of not only teaching a system to understand, “what is scary”, but then to create a trailer that would be considered “frightening and suspenseful” by a majority of viewers.
As with any AI system, the first step was training it to understand a subject area. Using machine learning techniques and experimental Watson APIs, our Research team trained a system on the trailers of 100 horror movies by segmenting out each scene from the trailers. Once each trailer was segmented into “moments”, the system completed the following;
A visual analysis and identification of the people, objects and scenery. Each scene was tagged with an emotion from a broad bank of 24 different emotions and labels from across 22,000 scene categories, such as eerie, frightening and loving;
An audio analysis of the ambient sounds (such as the character’s tone of voice and the musical score), to understand the sentiments associated with each of those scenes;
An analysis of each scene’s composition (such the location of the shot, the image framing and the lighting), to categorize the types of locations and shots that traditionally make up suspense/horror movie trailers.
The analysis was performed on each area separately and in combination with each other using statistical approaches. The system now “understands” the types of scenes that categorically fit into the structure of a suspense/horror movie trailer. Then, it was time for the real test.
We fed the system the full-length feature film, “Morgan”. After the system “watched” the movie, it identified 10 moments that would be the best candidates for a trailer. In this case, these happened to reflect tender or suspenseful moments.
If we were working with a different movie, perhaps “The Omen”, it might have selected different types of scenes. If we were working with a comedy, it would have a different set of parameters to select different types of moments.
It’s important to note that there is no “ground truth” with creative projects like this one. Neither our team, or the Fox team, knew exactly what we were looking for before we started the process.
Based on our training and testing of the system, we knew that tender and suspenseful scenes would be short-listed, but we didn’t know which ones the system would pick to create a complete trailer. As most creative projects go, we thought, “we’ll know it when we see it.”
Our system could select the moments, but it’s not an editor. We partnered with a resident IBM filmmaker to arrange and edit each of the moments together into a comprehensive trailer. You’ll see his expertise in the addition of black title cards, the musical overlay and the order of moments in the trailer.
Not surprisingly, our system chose some moments in the movie that were not included in other “Morgan” trailers. The system allowed us to look at moments in the movie in different ways – moments that might not have traditionally made the cut, were now short-listed as candidates. On the other hand, when we reviewed all the scenes that our system selected, one didn’t seem to fit with the bigger story we were trying to tell – so we decided not to use it. Even Watson sometimes ends up with footage on the cutting room floor!
Traditionally, creating a movie trailer is a labor-intensive, completely manual process. Teams have to sort through hours of footage and manually select each and every potential candidate moment. This process is expensive and time consuming – taking anywhere between 10 and 30 days to complete.
From a 90-minute movie, our system provided our filmmaker a total of six minutes of footage. From the moment our system watched “Morgan” for the first time, to the moment our filmmaker finished the final editing, the entire process took about 24 hours.
Reducing the time of a process from weeks to hours – that is the true power of AI.
The combination of machine intelligence and human expertise is a powerful one. This research investigation is simply the first of many into what we hope will be a promising area of machine and human creativity. We don’t have the only solution for this challenge, but we’re excited about pushing the possibilities of how AI can augment the expertise and creativity of individuals.
AI is being put to work across a variety of industries; helping scientists discover promising treatment pathways to fight diseases or helping law experts discover connections between cases. Filmmaking is just one more example of how cognitive computing systems can help people make new discoveries.
This story first appeared on the IBM THINK blog. John R. Smith is an IBM Fellow, Manager, Multimedia and Vision.
IBM is deepening its cooperation with Canadian fintech startups through Toronto-based MaRS, following up on pledges to help promising startups develop and commercialize their innovations.
The tech giant will join a network of corporate partners including CIBC, Manulife and payment processor Moneris in the MaRS C Suite, MaRS’ “corporate innovation district.” Partners provide startups with product feedback, advisory services and other forms of support.
“What we’re doing is saying: you have a great idea,” Patrick Horgan, VP, Manufacturing, Development & Operations at IBM Canada, said in an interview with TechPORTFOLIO in June. “You’re missing some ingredients to be successful. Let’s help you through that because we have some history of being able to get through all of those cycles and to the world market.”
As part of IBM’s partnership with MaRS, the company will provide technology and services, including access to IBM Cloud and cognitive computing (Bluemix and Watson), support for demonstration projects, data analytics internships, and “soft-landing export development opportunities.”
Fintech startups will also get assistance in opening new markets, completing international sales transactions, and connecting with new parties for collaboration.
“As IBM transitions into the physical building in the space, we’ll continue to expand the programming elements of the partnership,” Adam Nanjee, head of the MaRS fintech division, said in an emailed response to questions. “This type of collaboration tears down silos to accelerate the rate of innovation and leads to tangible, meaningful results.”
MaRS’ fintech hub aims to connect the financial services sector with startups developing next generation technology in emerging payments, financial services, peer-to-peer transactions, alternative lending and crypto-currencies.
Coworking shouldn’t be limited to former factories with exposed brick and chunky wooden beams. Shared resources should also be leveraged in the cloud, particularly for early-stage startups with limited access to funds.
Sometimes referred to as multi-tenancy, sharing space in the cloud can give startups more development flexibility, but users need to manage expectations around security, reliability, scalability and serviceability.
“Networks underpinning a cloud deployment need a higher degree of automation, programmability and multi-tenancy versus traditional non-cloud buildouts,” Andrew Lerner, Research Vice President at Gartner, said in a blog post last year. “Further, there are multiple paths to achieving automation, programmability and multi-tenancy … it’s not SDN or bust.”
As regulations around data security evolve in an age of near-daily headlines about hacking, developers, founders, CTOs and CIOs need to know what the cloud coworking options are.
As hackathons proliferate, the value of winning one declines.
That is, unless you turn your winning hack into a startup that attracts $2.5 million in seed funding, as Kiwi Wearable Technologies co-founder and CTO John David Chibuk did. The first iteration of Kiwi’s technology, a heart rate sensor app, was the result of a victory at AngelHack Toronto 2013.
Kiwi produces intelligent motion capture technology that analyses speed, direction, angle, and torque. The company is targeting developers looking for an easier way to integrate these functions into a variety of products.
“We found there were a variety of different products on the market that all offered a form of step counting, or different types of motion classification,” Chibuk says. “However, the software was not available for other developers or people who actually wanted to make a product.”
The device accepts development on several platforms. SDKs are available for iOS and Android, as well as for open-source electronics platform Arduino and JavaScript.
Kiwi aims to form partnerships, completing pilots for consumer and industry applications with potential use cases in sports, healthcare, and in the industrial internet of things. Pilot projects so far include integration of sensors on forklifts at a car parts distribution center.
“The aim for this pilot was to determine down time optimization – when there is a piece of equipment not being utilized, and to improve the floor workers’ schedule,” Chibuk said.
To test in the sporting arena, Toronto-based Kiwi picked lacrosse, the national summer sport of Canada, and worked with Silicon Valley-based sports wearable technology startup Snypr to capture movement of lacrosse throws and see how players’ forms developed and improved over time.
“The purpose is player performance enhancement, to see the nuances in their movement,” says Chibuk. “They can undergo different training schedules and see when they’re performing best, or when they need to alter their routines to perform better.”
Kiwi Wearables was also part of the Cannes Lions Innovation Festival 2016. Soccer players wore wristbands that recorded each kick and touch of the ball. The data was processed by Watson, and donations to charity were made for each movement.
And Kiwi has strong support in other respects. FounderFuel is Kiwi’s main seed investor, and the company counts GoInstant’s Jevon MacDonald as an advisor. MacDonald gained prominence in Canada for selling Golnstant to Salesforce in 2012 for a reported $70 million.
IBM Bluemix is an integral connector in Kiwi’s technology. The cloud platform “allows for a lot of variety of APIs to be integrated quickly together,” Chibuk explains. “There’s a good methodology for distribution and hosting applications.” The device sends the recognition events to Bluemix, storing them and interfacing with an online presentation layer for clients.
One key aspect of Kiwi is the importance of accurate motion data at source. The more that data is converted and its format is changed, the more the quality degrades, particularly if the data is being captured in real time. Everything is classified on the device.
Developing for industry and the consumer market means different emphases. For the former, accuracy and high performance; the latter, keeping the cost of the parts down. “It’s the same mathematics, it’s just what’s computationally available in each of the use cases,” says Chibuk.
Kiwi aims to launch its first developer-focused product by the end of this month.
Even concierge apps need a little help themselves to get their jobs completed.
Some are turning to artificial intelligence, a sensible solution given that significant VC funding is moving away from social media and towards businesses that utilize cognitive technology. Magic+ and Operator, personal assistant and personal shopper messenger services, use IBM Watson as an integral part of their stack.
Magic+, which received $12.5M of Series A funding in 2015 from Sequoia Capital, is an on-demand, scalable high-end personal concierge that claims to be capable of handling any task, regardless of size or scope. Users can send text messages that will help users with tasks such as arranging mutual meeting times and finding personal trainers. You can even order helicopter transport.
Requests are fulfilled through a combination of humans working as executive assistants paired with intelligent software. According to Magic, their “unique combination of humans and software is what enables us to consistently deliver an unparalleled level of service.”
Operator, set up by Uber co-founder Garrett Camp, specializes in personal shopping. You can request items by text message in very specific detail from around the world. Among other things, it keeps records of your preferences. Operator was most recently funded by three investors in a $10 million Series A round.
The same machine learning and natural language processing technology that powers these startups via IBM Watson is available by signing up to IBM’s Global Entrepreneurship Program.
Through the Global Entrepreneurship Program, up to $120K of credits are available to spend on access to IBM services that these startups use, as well as go-to-market support, technical expertise, and business mentorship.
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