David Kim

Partner & CEO

Massive Insights

The year is 2012 and big data is all the buzz. For many companies though, it is just that, a buzz word. Everyone has figured out that their data is an asset, and terms like data lake and cloud are being thrown around freely, but few have yet figured out how to actually navigate that landscape and unearth the value. The maps are still being drawn, and the early movers are operating out at the edges where the cartographer has penned: “here be dragons.” And David Kim has caught the explorer’s bug.

In 2012, Kim had already built himself a successful and stable career in direct and digital marketing. But he wanted to be on the frontier, writing the future of data. And so, with his business partner, Clarence Chow, and a shared dream, they took the leap and Massive Insights was born. “We started with clearing out the proverbial garage office,” says Kim. “We were coming from really comfy, cushy, steady jobs, where we were well paid and had some great clients. But we had this dream of creating a culture that truly provided real value back to clients. Ultimately, our hearts are in helping others create their own success stories for us to be a part of.”

Relationships matter, even in this highly technical world of ones and zeros, and bits and bytes. We always focus on the quality of work, but we never lose sight of the relationships we’re building along the way.

In those early days, when there was some uncertainty about the future of the data sector, a guide with the right instincts and sense of direction was of inestimable value. With a prescient understanding of the power of analytics and data visualizations, Massive Insights soon secured a reputation as one of the few trusted navigators in the wilds of big data analytics. And in a frontier environment, reputation is everything. “Looking back over the last 10 years, how we’ve grown and how fortunate we’ve been, a lot of that was based on relationships, networks, the referrals from client endorsements,” says Kim. “Our very first client continues to be one of our clients today. Relationships matter, even in this highly technical world of ones and zeros, and bits and bytes. We always focus on the quality of work, but we never lose sight of the relationships we’re building along the way.”

Today, there are a lot fewer blank spots on the map, and Massive Insights has been instrumental in filling it. They have chosen to draw roads to a better world for their clients, and for Canada as a whole. Kim understands that data touches everything. For some companies, data is primarily a marketing asset; for others, it is a tool to reshape and improve not only how a product is delivered, but also to enhance the product itself. And sometimes that product is a healthier future for a sick child.

“We’re currently working the number one children’s hospital in the world, SickKids Foundation. Our objective is to help them understand their ability to uncover opportunities with donors, and how they can optimize and maximize their activities to generate the most value back to the hospital. It’s these types of meaningful applications of data that really connect us back to things that matter to us. And we’d always like to use any of our superpowers for good.”

In 2021, looking forward to their next decade, Massive Insights is retaining their explorer’s spirit, with their eyes set on new horizons beyond the map’s edge. And the network they have built and nurtured will continue to grow and expand with them as they uncover ways to build value and use data for the betterment of all.

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Paul McKenzie

CEO, NexOptic Technology

Bill Cawker

Corporate & Shareholder Relations, NexOptic Technology

In the world of artificial intelligence (AI) startups, when you’ve managed to secure partnerships with three of the world’s largest and most innovative semiconductor titans in a little under five months, well — it might just mean that you’re onto something. And that’s exactly what NexOptic Technology Corp. has managed to do.

Beginning this summer, the publicly-traded Canadian AI innovator NexOptic Technology Corp. caught the attention of Qualcomm, NVIDIA, and Arm, and by late November it had secured esteemed partnerships with all three. With partner support, NexOptic’s disruptive imaging AI is OEM-ready on NVIDIA’s Jetson and Qualcomm’s Snapdragon platforms. Snapdragon is the dominant semiconductor choice worldwide for smartphones.

Leveraging the power of vision

For the world’s largest businesses, staying relevant in the world of AI is critical for survival. Industries impacted by AI include automotive, smartphones, Internet of Things (IoT), manufacturing, and logistics. “When it comes to imaging and the future of big business, what their devices can’t see could hurt their bottom line,” says Paul McKenzie, NexOptic’s CEO.

NexOptic’s imaging AI, ALIIS, transforms and enhances images using the latest breakthroughs in machine learning. Not only will you be able to take better selfies, but ALIIS is also perfectly tailored to meet the demands of the fastest-growing segments of the imaging industry: machines that capture and process images that no human will ever see. These machines are increasingly leveraging the power of vision to perceive and react to the world around them. Vision systems such as facial recognition, object detection, and classification — can all be paired with ALIIS to enhance their capabilities. This requires lightning-quick and sophisticated AI married with the world’s best semiconductors, all to create “a better view.”

Incredible picture quality — and opportunities

ALIIS works pixel by pixel, whereby every single part of an image is independently and uniquely perfected. The result? Images with superior resolution and sharpness, and dramatically-reduced image noise, glare, and motion blur. Additionally, it enhances long-range image stabilization by enabling faster shutter speeds (up to 600 times) while offering upwards of 10 times reduced file and bandwidth requirements for storage and streaming applications. What’s more is that ALIIS does all this in real time. As the next generation of AI-enabled cameras come to market, the opportunity could be enormous.

Headquartered in Vancouver and with recently-opened operations in Seoul, South Korea, NexOptic is a Preferred Partner in the NVIDIA Partner Network, a member of the Arm AI Partner Program, and a member of the Qualcomm Platform Solutions Ecosystem. 

For more information, visit NexOptic Technology Corp. or email [email protected].

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The detrimental and cascading impact of loneliness and isolation is being felt around the world. This is especially true for those managing complex conditions, today and every day. To help combat this lack of connectedness, patients are turning to digital social channels to fill the void.

Health care organizations have traditionally been very limited in how they participate in these channels due to regulatory and privacy concerns and other safeguards deemed essential in a health care setting. However, the growth and utilization of these platforms for health care related needs continues to organically grow.

At the same time, health care organizations are looking to deepen and extend the reach of their relationships with patients beyond one-dimensional treatments, the four walls of a clinic, or episodic touchpoints during medication refills.

How can health care organizations foster community and leverage another tool to support the patients they serve in a safe, intuitive, and effective way? The key is building dedicated patient communities that have been built from the ground up to address the unique needs of health care.

Engaged, informed, and activated patients

Every patient journey is unique and requires a personalized, dynamic approach to drive optimal healthy behaviours and outcomes. In order to truly empower individuals in their health journey, every touchpoint has to be relevant, timely, and personalized in order to make a meaningful difference.

Achieving this goal of personalization and empowerment at scale in a health care context has traditionally been a difficult task. However, using the power of artificial intelligence (AI), mass personalization is now a reality in helping patients manage their health challenges in a more intelligent and compelling way.

When managing a new health challenge for the first time, whether this be a new diagnosis, starting a new treatment, or making a proactive health change, entering a discovery phase is a common first step. Searching Google and sourcing insight from others in the community are two common actions that lay the foundation for all future actions.

The acute need for community

Social connectivity, or lack thereof, is a major variable that is often forgotten. When surrounded by a group of peers on the same journey, it empowers an individual to take control of their health, drives accountability, retention and adherence to therapy.

To enable authentic connections that provide support, a sophisticated AI model is applied to identify those in the community who are in the best position to support one another in their journey. This proprietary, multifactor approach to matching individuals takes into account condition and profile-specific variables. The individual is in full control through a double opt-in process that needs to be accepted on both sides, and also provides a configurable level of anonymity.

This same logic is applied to the personalization of interventions that meets every individual where they are in their journey. Behavioural change interventions are predicated on understanding the current state of a patient, behavioural models that take into account a wide array of attributes to predict the best way to nudge and a method to predict interaction outputs.

The next frontier in patient support is going to take into account the entire patient and social connectivity. Tailored behavioural nudges will unlock the full potential in driving informed, empowered, and engaged patients.  

Consistent, long-tail engagement drives healthy behaviours

Curatio builds regulatory and privacy compliant peer-to-peer communities in partnership with health care organizations. Visit Curatio to explore how dedicated digital patient communities are helping support, inform, and activate patients in over 100 countries and 15 languages during these challenging times. 

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Ulrike Bahr-Gedalia

Senior Director, Digital Economy, Technology & Innovation, Canadian Chamber of Commerce

Mehdi Merai

CEO, Dataperformers

As the manufacturing sector is increasingly moving from blue collar to white collar and embracing the light blue realm, the wealth and magnitude of where the next generation of technology, transformation, people, and opportunities could take us is exponential.

In an interview with Ulrike Bahr-Gedalia, Senior Director, Digital Economy, Technology & Innovation at the Canadian Chamber of Commerce, Mehdi Merai, a member of the Chamber of Commerce and CEO of Dataperformers, explains what artificial intelligence (AI) contributes to manufacturing, what some of these opportunities might be, and how the future could look.

We keep hearing about Industry 4.0. What is it?

The Fourth Industrial Revolution, or Industry 4.0, is all these new technologies like the Internet of Things (IoT), AI, and 3D printing, that when combined can create new ways to do manufacturing, also known as smart manufacturing.

What’s big data and how can it influence smart manufacturing?

Every day, we generate data when performing tasks like searching the web, checking our Facebook, or using a GPS. This phenomenon of generating, in an exponential way, more and more data is what constitutes big data. Likewise, manufacturers are generating lots of data through the use of their equipment (IoT), quality control processes (images), or through their maintenance logs.

What are some smart manufacturing use cases? Increased technology adoption across Canada in all sectors and sizes of business is crucial, and we’d definitely like to see more of it!

We have to understand that AI has applications across the entire manufacturing value chain. Two of the most mature applications are on preventive maintenance and quality checks. Siemens is currently using sensors on old industrial motors to detect subtle changes in vibration or energy use to predict near failure — and so it triggers maintenance before such failures can occur.

At Dataperformers, we worked with Toyota Aisin Seiki to help them detect welding anomalies in real time. Molding defects are hard to catch as the discrepancies can be really fine and image quality and luminosity are often poor. Nevertheless, using techniques like deep learning, we developed an AI model that performed with high accuracy. Following that success, we developed a solution, Macula AI, which was a platform for any kind of defect detection using images or videos.

As often is the case with adoption and transformation, change doesn’t come without challenges. What are some issues that could arise?

This revolution presents challenges for different stakeholders:

Policymakers: The skills and competencies needed today in the manufacturing industry aren’t the ones that will be needed in the future. Jobs will disappear, new ones will be created, and others will evolve. To keep the manufacturing sector competitive in Canada, we need to attract and prepare youth today.

Society: Those technologies will bring new situations that will need new legislation, like the new law on data privacy in preparation. In manufacturing this will be the same, with new standards and regulations.

Manufacturers: This technology enables new opportunities. Manufacturer business models will have to evolve to stay competitive by taking the best of what those technologies enable and become more agile.

There always seems to be a storyline. What does the AI journey in manufacturing look like?

The prerequisite is to create a general database, with no specific purpose, that collects all the different data generated. We call it a “data lake.” Manufacturer AI journeys start by identifying problems easily solved by AI and that would have a high impact for the company. Because of the lack of AI specialists and the cost of their expertise, the manufacturer hires an AI company to undertake its pilot project. This pilot is generally the demonstration that convinces the chief experience officer to start a company transition to AI. Then the manufacturer generalizes the use of AI by rethinking their process, hiring an AI team, and helping employees adapt. While this is the final step for the initial journey, it means a future full of potential for the company at large.

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What initially drew you to working in cybersecurity?

In 2003, I founded Herjavec Group by selling the first commercial firewall in Canada. I had a vision of selling a handful to the right IT buyer. At that time, cybersecurity was an IT challenge and a security breach being featured in the news would have been absurd. Since then, we’ve seen a monumental shift towards what we refer to as a cybercrime epidemic. Herjavec Group has grown to be one of the world’s most innovative cybersecurity firms, excelling in large, complex, multi-vendor environments.

What about your work excites you the most right now?  

2020 has completely transformed the way businesses operate. Almost overnight, companies were forced to pivot and go completely virtual. Digital transformation is now a requirement for survival and protecting businesses in an ever-changing threat landscape is what motivates me day in and day out. 

What’s the biggest challenge for the cybersecurity sector in keeping up with the ever-increasing amount of data collected in our world?

Cybersecurity is complex. You can’t just focus on protecting small bits of data, you have to look at all the linked components. Ten years ago, a cybersecurity practitioner could focus on something targeted like credit card data, health care data, or sensitive intellectual property and successfully protect these individuals and their information. Today, the cybersecurity industry has to continue to protect these targeted pieces of information, but also focuses on how all of this data comes together and is linked. 

These small bits of data, when combined, now represent something much bigger: details like who someone is, what their preferences are, or where they’ve been. For instance, a person’s credit card information might be valuable, but information regarding intimate details about a person or a company are far more interesting to an attacker and also represent much more regulatory risk should that information be disclosed. As more data about everything comes into existence, the burden of protecting that information becomes more difficult and consequential.  

With more data being collected and stored than ever before, what protections do consumers have a right to when it comes to how companies safeguard their personal information?

That’s a great question and we’re seeing some of this being codified into laws such as the Personal Information Protection and Electronic Documents Act (PIPEDA) and EU General Data Protection Regulation (GDPR). In general, the world seems to be wrapping its head around the idea that if a company collects information about a person, that company must consider the risk of harm to that person when designing security controls. Security has to be considered from the beginning and reasonable security controls should be in place based on the sensitivity of the data that’s being collected.   

Businesses must also afford the person who’s the “data subject” some rights, such as the right to be forgotten, the right to ask the organization to correct inaccurate information, and perhaps most fundamentally, the right to know what data the company is collecting and what they intend to do with that information. Consumers expect transparency and they also expect companies to provide due care for their information. Privacy laws like PIPEDA and GDPR are really a way of codifying that expectation and providing appropriate consequences for companies that are negligent.

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How does the Government of Canada use AI?

Canada has emerged as a world leader in AI in recent years. As the Minister of Digital Government, I want to make sure that we harness these investments, and the power of AI, to provide better government services to Canadians. Citizen trust is central to this goal.

The Government of Canada uses AI to complement and support the efforts of people. Our approach is to keep humans in the loop when we’re using AI. Ultimately, AI in government is one tool we can use to reduce backlogs and processing times while offering convenient, client-centric service.

A great example is a chat bot. Many government websites use a chat bot to answer simple questions so that people don’t have to call 1-800-O-Canada. This frees up call centre agents to respond to more specific or complex questions, or to speak with folks who can’t use a computer. 

We currently don’t use the full range of AI technology but it’s important to introduce these capabilities now so they’re integrated as we accelerate our government-wide digital transformation.

What’s being done within the federal government to ensure the ethical development and use of AI tools?

Canada has advocated for a human-centric approach to the development and responsible use of AI, taking into consideration the ethical matters,  like openness, transparency, bias, equity of access, safety, and security principles, that are already central to decision-making in the Government of Canada, whether by human or machine.

Canada was the first government in the world to establish a policy on our internal use of AI that puts these guiding principles into practice. As AI becomes an increasing part of our everyday lives, I want Canadians to know that their government is carefully monitoring and evaluating both the benefits and the risks of the use of AI.

Our Directive on Automated Decision-Making helps to shine a light on where government departments are using AI that affects Canadians directly, and ensures that these tools are closely monitored and respects our democratic values including fostering diversity and inclusion.

We’re committed to good governance underpinning AI as we shift to a more digitally-enabled government.

How can government leverage big data for
the benefit of Canadians? 

As we consider post-COVID recovery, we see the opportunity for government to make big data a force multiplier for economic growth and for smart decisions to advancing environment, biodiversity, and climate goals. We recognize the challenges to get there. While Canada produces high-quality data sets, they’re not always easy to access in meaningful ways. Just as the U.S. Government’s release of topographical data was the foundation for Google Maps, the Government of Canada’s data is a potential resource for Canadian AI and intellectual property. We started this journey with open government initiatives and now we’re exploring solutions to some of the hurdles to the next step — bilingualism, accessibility, and usable formats. 

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