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Meet Marcelo Noronha: The brain behind Mr. Turing’s AI business assistant

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Meet Marcelo Noronha: The brain behind Mr. Turing’s AI business assistant

Meet Marcelo Noronha, the unstoppable force and brain behind Mr. Turing, an AI (artificial intelligence) business assistant revolutionizing how companies work with their data. In an increasingly AI-driven world, Mr. Turing is a true game-changer, providing companies with a powerful tool to unlock the full potential of their internal data to save time, knowledge and money. 

Like Alan Turing, the trailblazing mathematician and computer scientist who laid the foundation for modern computing and artificial intelligence by cracking the German Enigma code during World War II, Noronha is pushing the boundaries of what’s possible with AI.

What sets Mr. Turing apart from the competition is its unique ability to manage all of a company’s information in one place. With its innovative Alan technology, Mr. Turing helps companies process, interpret, and manage the knowledge generated from their internal data more effectively than ever before.

So, who is the mastermind behind Mr. Turing, and what inspired him to create it? We sat down with Noronha to discover his inspiration, the unique benefits of their AI-powered business assistant, Alan, and the measures they have put in place to safeguard sensitive information. If you’re interested in the intersection of entrepreneurship and AI, read on to uncover Noronha’s insights and discover the next big thing in business technology. 


What inspired you to build Mr.Turing? 

As a tech entrepreneur for 20+ years, all the companies I worked for used image processing for document management. However, every company had a gap in delivering value to its customers; we would process the documents but only deliver 20% of the value from all the information contained within them. This always bothered me because it was a lot of work for very little delivery. At the time, the technologies weren’t ready to process, interpret, and generate knowledge. When I came across the AI technique of Language Processing, I realized that this was where I could change the game.”


Tell us how your AI-powered business assistant (Alan) works.

Imagine needing information across different types of media: documents, videos, audio, websites, meeting minutes, and other sources. Now, imagine all of this scattered across multiple platforms within a company. How would you access and leverage it to improve your business processes? It would be practically an endless search, wouldn’t you agree?

This is the challenge we addressed with Alan, a tool that can manage and generate knowledge for companies, integrate with any system and process any type of media. After processing, interpreting and integrating where the information is, Alan is ready to respond naturally to the needs of those looking for information. And the best part of all of this is that this knowledge is secure within the company, so they can make informed decisions on how to use it.


How does Alan differ from other data management solutions on the market?

Our differential is the ability to manage all knowledge produced by company teams in a single platform, Alan. We can make connections between meeting videos, emails, projects, dialogues, and communication platforms.


With the increasing focus on data privacy and security, how do you ensure that Alan adheres to data protection standards? What measures have you put in place to safeguard sensitive information?

At Mr. Turing, we place great emphasis on data privacy and security. To ensure that we comply with data protection standards, we have implemented a range of measures to safeguard sensitive information. These include encryption, regular security audits, access controls, and user authentication. We are committed to staying up-to-date with evolving data privacy regulations and continuously improving our security practices to protect our users’ data.


How have you leveraged natural language processing to develop Alan? Can you walk us through your approach to training?

We utilized natural language processing (NLP) techniques and cutting-edge AI models to create Alan. Our methodology for training and refining the model involves several stages:

  • Data collection: We obtain a diverse set of data from multiple sources, including text, audio, and video content, to ensure a comprehensive understanding of a company’s information;
  • Data preprocessing: The collected data is cleaned and preprocessed to eliminate irrelevant or redundant information; 
  • Model training: The preprocessed data is employed to train our NLP models, with a focus on comprehending context, semantics, and relationships between different pieces of information; 
  • Fine-tuning: The trained models are refined using reinforcement learning techniques, which enable Alan to enhance its performance by adapting to the specific needs and preferences of each client; 
  • Evaluation and feedback: Alan’s performance is continually assessed against predefined benchmarks, and any insights gleaned from user feedback are utilized to further improve the model.


With the recent advances in natural language processing and conversational AI, how do you see your assistant evolving? Are there any new features or functionalities you’re excited to roll out?

The recent advancements brought by OpenAI with ChatGPT have given Mr. Turing the missing piece of the puzzle. We expected this to come around mid-2025, and it has been accelerated, which is great news!

We believe that we operate at the process layer of companies, with the capability of integrating, processing, and interpreting all the information that flows within them. With this, we can more precisely control what the conversational part of GPT models can synthesize without attempting to fabricate any information from non-existent data.


How do you balance the need for automation and efficiency with the importance of maintaining human oversight and control over data management processes?

Finding a middle ground between the need for automation and efficiency and the importance of maintaining human oversight and control is crucial. 

This can entail utilizing automation technologies such as Artificial Intelligence to boost the efficiency of data management processes while also keeping a check on human oversight and control to ensure the accuracy and quality of the managed data. 

Furthermore, it is crucial to ensure that data management processes are well-documented and that policies and procedures are adhered to consistently to uphold data integrity and regulatory compliance.


Can you discuss future plans or goals, such as expanding into new industries or integrating new technologies?

We plan to expand into new industries such as healthcare, finance, law, and education. To remain at the forefront of AI and NLP technologies, we are enhancing collaboration features, developing advanced personalization features, and incorporating environmentally-friendly strategies into our operations and product offerings.


What advice would you give an aspiring entrepreneur in the AI space?

No matter the industry, the first step is to assemble a strong team with a common purpose. Then, it’s important to understand that building AI applications requires time, effort, and a great deal of persistence. Success cannot be guaranteed simply by utilizing AI technology, and it’s crucial to be ready to adjust and improve your ideas as you progress, given the rapidly evolving nature of the field.

Ready to save your business time and money with Mr. Turing? Click here to discover more >

International founders dish their first impressions of Toronto’s tech ecosystem

Last month, 4 rising tech startups from Lithuania embarked on a one-week soft landing program to Toronto called the Canadian Connection Program. In partnership with Pace Global Advantage and the DMZ, the program supported entrepreneurs and business leaders interested in exploring the North American market and gave participants the opportunity to tap into a wider network of investors, customers, corporates, founders and talent.

The Lithuanian visit to DMZ’s headquarters was productive for the startups – participants took advantage of various workshops and curated one-on-ones with DMZ’s Program Leads, Experts-in-Residence (EiRs) and Alumni-in-Residence (AiRs). The Lithuanian entrepreneurs walked out of the experience with a greater understanding of the North American ecosystem and its players.

Lithuania blog - DMZ team and visitors mingling

On their final day of the program, we had a chance to sit down with the founders and ask them about their thoughts on the program and first impressions of Toronto’s startup ecosystem. Here’s what they had to say.

1. Toronto is very well-positioned in the North American market.

“I have learned a lot about the close connections between the EU and this city’s ecosystem, especially for medical startups. Toronto is well-positioned in the North American market, which is important because we need to reach the largest user base possible. There’s a great support system here for startups and there are great connections to cities like Boston and New York, which are just a short hop away.” – Urte Steikuniene, Feetsee

“The ecosystem here is booming and attracts people from all around the world to relocate their businesses from other continents.” – Simonas Stankus, Unbalanced

“We are considering North America as our primary market. Through the program, we have realized how little we actually knew about Canada. By being here, we see the ecosystem in Toronto is really vibrant, and a lot of professionals and potential employers are living here. The access to the talent, capital and markets is much higher than you’d expect. It changed my concerns about Canada being the same as the U.S. in terms of work-life balance. It’s much more convenient for entrepreneurs considering relocation here compared to the United States. Being in Toronto was a perception-changing experience because we were too trusting of the assumptions we had developed.” – Vytenis Pakènas, IsLucid

2. There is value in the city’s multiculturalism

“I am very impressed with the diversity and openness that I see in Toronto. I’ve only been here for one week, but I feel like you’re at home almost everywhere you go. The diversity is very inspiring and all-encompassing.” – Urte Steikuniene, Feetsee

“I was especially taken aback by the fact that I have met other medical doctors like myself who have made successful startups here in Toronto. I’ve met other professionals as well who turned to entrepreneurship. That’s not something you see often. My favourite thing about Canada is that everyone is from everywhere. There’s this feeling of being away from home but also at home at the same time. A real melting pot of people and cultures, which is something that contributes to its unique atmosphere.” – Justinas Balčiūnas

3. The DMZ community provides startups with everything they need to grow.

“I thoroughly enjoyed my time here at the DMZ. I got in touch with healthcare providers, venture capital funds, and angel investors, and got to know the entrepreneurial ecosystem here in Toronto which is booming, energetic and inspiring. Not only am I leaving this program with an excellent portfolio of contacts, but I also leave enriched by hearing other success stories of startups that have entered this environment and have done well. I feel like I’ve learned a lot.” – Urte Steikuniene, Feetsee

“My experience in this program has been great! I partook in incredibly useful workshops and met such great people. Now, I have a much better understanding of what Canada is and what ecosystem it has.” – Simonas Stankus, Unbalanced

“When you enter a new market, it’s important to have the right support system of people who can tell you the truth. We received the right recommendations and connections within the context we needed to make the experience meaningful and actionable. I was touched because the team wasn’t too focused on revenue and speed, but more on care and guidance/growth. When you’re coming in from overseas, you’re being brought into a desert with people you don’t know. But the DMZ is helping turn that desert into a sweet forest with the right connections and resources needed to succeed.” – Vytenis Pakènas, IsLucid

Lithuania Blog - Founder Simonas Stankus pitching

The cohort of participating companies included:

Lithuania blog - isLucid logo
IsLucid is a productivity hack that specializes in machine learning through transcription. The service transcribes verbal communication in meetings and automatically assigns tasks to employees, eliminating the need to take meeting minutes and ultimately saving time.

Lithuania blog - Feetsee logo
Feetsee is a FDA-registered product that uses its advanced algorithmic technology, with 95% accuracy, to monitor and measure changes in diabetes patients’ feet. It stores this information in its mobile and desktop software that relays messages to the patient’s care team and physician via alerts.

Lithuania blog - InBalance logo
InBalance produces electric vehicle charging stations. Their product focuses on energy efficiency and helps fulfill the increased demand for electric vehicle charging without requiring any changes to the current power grid infrastructure, ensuring the sustainable growth of a community-based public charging network.

Lithuania blog - Ligence logo
Ligence employs machine learning algorithms and deep-learning technology to determine functional and structural aspects of a person’s heart through ultrasound images. Their current focus is reducing human error in detection and diagnosis and improving their measurement accuracy.

Want to act on the Toronto FOMO and get involved? Founders looking for international expansion support can learn more about DMZ’s global offices at dmz.to/global, and partners interested in developing a soft-landing program in Toronto at the DMZ can reach out at dmz@torontomu.ca.

The future of forecasting: How Granularity uses AI and big data to bridge the industry’s supply and demand gap

To celebrate our women-identifying founders, we’ve put together ‘On Wednesdays, we startup,’ a blog series dedicated to positioning women founders centre stage to acknowledge their work, complexities and wins!

We hope to push women-founder stories forward and share lessons learned and insights for other aspiring women entrepreneurs.

This week, we had the pleasure of chatting Tali Remennik, the Founder of Granularity, to learn more about her startup and how she’s infusing demand forecasting with AI and big data to bridge the supply and demand gap in the sector.

Can you tell us a little about yourself and why you founded Granularity?

“As a data scientist and ex-management consultant, I’ve witnessed first-hand how helpful data science and machine learning can be in solving large-scale problems. I have personally used these methods to help major retailers combat fraud, help governments reduce the risk of traffic accidents and help uncover the underlying barriers to women gaining leadership positions.

Demand forecasting is an issue that consistently resurfaces due to its challenges – and being the engine of every retail business – it can affect a company’s ability to compete in the market. The sector is too often overlooked and issues are starting to trickle out, making consumers take notice. Last year when TikTok had the feta cheese pasta craze we saw a nationwide shortage in feta cheese. The need for demand forecasting is increasing while the sector remains stagnant in producing any new solutions.

This is exactly why Granularity was founded and we are excited to be able to drive progress and remedy this critical issue.”

Laptop screen with forecasting metrics - Granularity blog

What exactly is Granularity’s mission?

“In five years, I can’t imagine a world where retailers aren’t using near real-time consumer data to make decisions about what inventory to order. Consumers are actively communicating their excitement for products on social media and expect their favourite retailers to stock them. Retailers want to listen, and business leaders in the planning sector are eager to bring this data to the forefront of their decision making.

That being said, I know that it’s not easy to decipher the thousands of signals that are being sent daily – from TikTok to Instagram.

And that’s what we’re here to do – help retailers understand how trends can impact their sales. We provide their teams with the actionable consumer insight they need to make decisions.”

Tali, you’ve spent a majority of your career working in AI consulting. What made you decide to make the leap to leave the corporate world and found your own startup?

“When I was younger, I used to imagine being a positive leader – inspiring people to live their passion and purpose. The vision of being a leader has stuck with me and is something that I continue to aspire to do daily. Having my dad, who runs a franchise, only added to this vision and gave me an entrepreneur to look up to. Once that entrepreneurial seed was planted in my brain, I knew I needed to dive in head first.

My time at Accenture is what really gave me the building blocks I needed to start my business. The clients I worked with and the network I was able to create through my experience working in consulting were the key to unlocking curated resources that I could use to position myself as an entrepreneur. This is what allowed me to build a strong foundation and be comfortable embarking on my own entrepreneurial venture. Now that I have been working on growing the company, I am realizing there is truly no other experience that can substitute building a business from the ground up.”

The supply chain industry has been largely dominated by giants for decades. However, over the last 5 years, there has been a significant spike of supply chain management and logistics related startups entering the market. What do you think is the biggest misconception of the space and the influx of new startups?

“Everyone outside of the industry assumes that there is already technology for demand planning and that the market’s problems have been solved. It’s only the parties in the space that understand the lack thereof.

Through working with a few seasoned executives, it was expressed to us that retail and point of sale technologies were largely ignored until the mid-90s, where there was a huge spur of new technology. That was over 20 years ago. It has been almost three decades since the last wave of innovation in supply chain – and more specifically, demand planning. The market was in need of this technology years ago, companies could’ve gotten ahead of the curve.

This is exactly what Granularity is doing for our partners – helping them get ahead of their competitors by predicting and acting on early signs of demand in the market.”

Shipping containers - Granularity blog

The amount of women in the supply chain workforce jumped to 41% in 2021 up from 39% in 2020. However, every leadership level saw an increase in representation except the executive level where there has been a slight decline. Have you had a chance to work with leading women in the space?

“There is always a need to encourage more women to enter the space – there is so much to do and having diverse perspectives will undoubtedly get us there faster.

Granularity is honoured to be partnering with incredible female leaders in the industry. They have a vision of what needs to get done and understand that they need a unique take of the external market to get there. Ultimately, although we are the ones building the solution, I feel like a lot of the visionary ideas come from them.”

What’s next in store for Granularity?

“We are building partnerships with retailers across Canada and the United States to test our minimum viable product. These partnerships are an exciting opportunity for companies to receive actionable consumer insights for their product lines.”

If you work for a retailer, either as a demand planner or merchandise buyer, and want to contribute your ideas to the future of forecasting; please sign-up to provide feedback on Granularity’s product here.

 

If you are a leader at a retail organization and have been continuously talking about improving your demand forecasting, Granularity is actively seeking partnerships. Please reach out here!

Tackling Canada’s supply chain challenges head-on

Learn how these DMZ startups are harnessing AI to build world-leading supply chain solutions


It’s no secret the world is grappling with some serious global supply chain issues. Since the onset of the pandemic, supply chains everywhere have been impacted – leading to product shortages and jacked up prices. 

You’ve probably noticed there are a few things on your holiday shopping list that are out of stock. Retailers and businesses everywhere are feeling the squeeze, and it’s only going to get worse if we don’t look to innovative tech-powered solutions. 

So, what is going on and what are we doing to help Canada ease some of its supply chain chaos? We’re glad you asked. 

Since March 2020, the world has experienced multiple waves of lockdowns, meaning factories everywhere have had to shut down for weeks or even months at a time. This has led to massive bottlenecks in our supply chains, with manufacturing disruptions and shipping delays. 

To say our supply chains are in utter havoc would be a gross understatement, but if there’s anything we have learned about our DMZ startups, it’s that they love a good challenge. 

We sat down with startups from our Supply AI Program to get their take on what’s going on and to learn more about their AI-powered solutions that are working to help.

A high-tech and low-cost provider of industrial and infrastructure construction materials, Material Supply leverages technology to make it effortless for buyers to get the best prices. 

Headshot of Andrew Allen, the Founder and CEO of Material Supply
Andrew Allen, Founder and CEO of Material Supply

Andrew Allen, Founder and CEO of Material Supply, points to the slow rate of technological adoption as one of the biggest challenges in supply chain management today. 

“The rate of adoption to more efficient technologies and antiquated business models is too slow today.” 

By offering a complete and easy-to-use procurement solution that creates efficiencies from manufacturer to end user, Material Supply is working to pioneer how we tackle global supply chain challenges.

“The rate of adoption to more efficient technologies and antiquated business models is too slow today.”

The first automated consulting management system uniting consultants and clients, Indie Tech gives procurement teams the tools to monitor, manage and mitigate supplier risk by tracking the performance of their suppliers in real-time.

Sophia Stone, Founder and CEO of Indie Tech, attributes a lot of today’s supply chain management issues to data and transparency. 

Headshot of Sophia Stone, the Founder and CEO of Indie Tech
Sophia Stone, Founder and CEO of Indie Tech

“The keys to the future of the industry rely on better and more transparent ways of viewing data and managing suppliers across tiers with greater insights.”

Sophia highlights that the tools and quantitative framework Indie Tech provides for risk managers is working to solve supply chain issues by empowering users to act proactively. “We help suppliers better manage their risk, before they see disruptions.”

“The keys to the future of the industry rely on better and more transparent ways of viewing data and managing suppliers across tiers with greater insights.”

 

Netwila is an integrated freight application platform and service that leverages AI for forecasting, operations, and asset deployment.

Headshot of Bob Vuppal, the Co-Founder and VP of Products and Technology of Netwila
Bob Vuppal, the Co-Founder and VP of Products and Technology of Netwila

Co-Founder and VP of Products and Technology, Bob Vuppal, highlights the global pandemic has not only put stress on our supply chain networks but has exacerbated existing problems.

“There’s no real easy way for companies to manage their operations across transportation forms and geographies, primarily due to fragmented networks and legacy systems. We save our companies money, increase data management across nodes and modes, support operational management of data, contracts and shipping, and manage out-of-stock.

“There’s no real easy way for companies to manage their operations across transportation forms and geographies, primarily due to fragmented networks and legacy systems.”

While the world’s global supply chain crisis is a result of pandemic lockdowns, now is the time to take action to not only resolve existing issues in the network, but embrace new AI-powered solutions to ensure its resiliency to future disruptions.

 

If you are a Canadian AI venture creating world-leading supply chain technology and are interested in joining the DMZ’s Supply AI program, check out eligibility requirements and program information here.

Our next cohort starts in February 2022. Applications are open until January 23rd at 11:59p.m. EDT. 

4 ways you can take your website copy from good to great

DMZ guest blog by: Karina Barker, DMZ EiR


As one of the DMZ’s tactical EiRs, I get the incredible job of working with founders to help them amp up their copywriting. Not only do I offer strategic advice around brand positioning, voice, content, etc., I also get to roll up my sleeves and do the writing alongside the founders.

Over my time in this capacity, I’ve noticed several common questions emerge as startups work to articulate their value proposition. While their vision might be clear in their minds, crafting website copy that has customers sitting up and taking action can be more of a challenge.

With more than 16 years under my belt as a copywriter and communications specialist, I’ve written for every kind of organization, from government, to startups, to Fortune 500 companies. I’ve seen firsthand how small mistakes can limit your copy’s impact—and how some simple tweaks can make all the difference. Seriously!

Here are 4 tips you can use to take your website from good to great:

 

1. Nail your homepage headline and sub-headline

According to the Nielsen-Norman Group, users leave websites on average after about 10-20 seconds. That means you’ve got less than 10 seconds to make your value proposition clear and convince visitors to stay. 

Your homepage headline and sub-headline are the first things visitors will see when they land on your page. That means these are your best shot to convince a visitor to stay (and hopefully convert). 

One of the most common mistakes I see companies make is focusing their website on them. 

A common format you’ll see is: We offer [this service] by doing [this thing]. Or, similarly: At [company], we help [this type of person] do [this thing].

But the goal of your website isn’t to share information about you. The goal of your website is to attract and convert customers. And that means you need to turn the spotlight on your customer —and talk about them.

Take a look at this homepage headline from Wealthsimple. 


Image: Wealthsimple

They don’t say “We help you do money right.” 

Instead the headline is direct and it implies “I’m going to do money right (with Wealthsimple’s help).” That subtle shift makes the reader see themselves in the headline.

The subheading then goes on to clearly articulate the actual “thing” that Wealthsimple offers (“powerful financial tools”) and the action-packed benefits that the customer can expect to derive (“grow and manage your money”).

While Wealthsimple makes it look easy, this kind of copy can take time and work (not to mention testing). If you don’t know where to start, a great first step is “voice of customer” research. Interview your customers, survey your product testers, read your online for views and search for the words your target audience uses to talk about benefits. This gives you a foundation to begin crafting and testing your headlines.

 

2. Don’t underestimate the power of social proof

Social proof is a powerful form of persuasion. When you include social proof in your webcopy, you tap into one of humanity’s deepest desires: to belong. 

We all put a lot of value on what we see people we trust doing and supporting. When we’re trying to decide between all the different options out there, we look to see what other people are doing. In fact, 91% of consumers read reviews before making a purchasing decision.  

If you’ve ever wondered why brands are willing to pay influencers big bucks for endorsements, this is it.

Here are some ideas for how to include social proof for businesses, even if you’re just getting started:

  • List any awards or prizes that your business has received
  • Share press/media/interviews covering your company
  • Run a social media campaign (and offer incentives) to encourage users to rate or review your product 
  • Request reviews or testimonials from existing customers
  • Create case studies based on real-life clients—or if you haven’t worked with any clients yet, craft use case studies that use a character that customers will identify with. (Note: always be clear if a study is based on a hypothetical rather than real world client.)
  • Share logos of high-profile clients that you’ve worked with
  • Share the number of users you’ve reached or clients you’ve served

Certain types of social proof will be worth more to certain audiences. Think about what can do to move the needle the most, and work towards collecting and presenting that type of social proof.

 

3. Keep your calls-to-action consistent

A call-to-action (CTA) is the moment when all of the work you’ve put into the rest of your copy gets put to the test. The CTA is where you encourage visitors to take your desired action. 

In order to craft a successful CTA you need to: 

  • Know what you want a visitor to do. Sign up for a free trial? Subscribe to your newsletter? Book a call with your sales team? 
  • Make it stand out. Pick the right spot, colour, visuals to draw visitor’s eyes to your CTA.
  • Be direct. CTAs are usually imperatives that begin with an action word. “Sign Up Now,” “Learn More,” “Start Your Free Trial.” Your CTA is not the place to get too wordy. 
  • Offer incentives. Make it easy for visitors to say yes by adding a line or two below your CTA: reassure visitors (e.g. cancel any time) or offer a desirable incentive (e.g. 10% of your first order)
  • Create urgency. Make visitors take action while they’re on your site. Use time words (e.g. sign up now, grab your instant download) to create a sense of urgency or signal time constraints (e.g. limited time offer)

But one of the most common mistakes I see is a lack of consistency in your CTA copy. If you want visitors to follow through, your CTA must be crystal clear–and repeated over and over. 

You can’t possibly miss Hubspot’s CTA. Not only is it in bright orange, it’s repeated word-for-word in their header and navigation bar. Even though their CTA is a little on the longer side, you know exactly what you’re supposed to do next (“Start free or get a demo”):


Image: Hubspot

In essence, when crafting your CTA, ask: What should the user do, and why? Your CTA should work in tandem with the rest of your webcopy to drive that message home. Inconsistent messaging (or multiple, competing CTAs in close proximity) can confuse your target audience or, worse, make them lose trust in your business. 


4. Boost interest with a unique brand voice

Once you’ve nailed the technical copywriting pieces, you can take your website (and your brand) to the next level by honing your brand voice. 

While it can seem daunting, developing your brand voice doesn’t have to be complicated. Here are some tips to get you started:

  • Reflect your audience. Go back to customer profiles and reflect on the voice used by your ideal clients. Is your target audience young and sassy or mature and sophisticated? 
  • Name three characteristics of your ideal brand voice. Authoritative? Trustworthy? Quirky? Cool? Passionate? Informative? Pick three attributes that capture the essence of your business. 
  • Define the dos and don’ts of your brand voice. Once you have your three characteristics, you can get more detailed on how this translates to your copy. For example, if you pick “trustworthy” as one of your attributes, your dos and don’ts may include: 
    • Do: use honesty, direct language, be transparent, share mistakes, follow-through
    • Don’t: push the hard sell, use jargon, over promise, trash talk competitors

As you grow, you can build out your brand voice into a document to share with anyone who is handling communications for your business. And remember, as you grow and change, your brand voice may develop too. 

If you need help with your copywriting, I’d love to chat! Learn more about how DMZ’s EiRs can support your business here. 

The future is female: How women are redefining A.I.

There’s no shortage of new stories about artificial intelligence (also known as A.I.) these days. The cutting-edge technology is driving billion-dollar investments, turning founders into millionaires overnight and increasing competition amongst the biggest businesses around the world.  

As the industry matures, A.I. will revolutionize how humans interact with the world. Interestingly, some of today’s new breakthroughs are fueled by women. It’s hopefully a telling sign of what’s to come when women are making important moves behind the scenes.  

The drivers of change

 
Despite significant gains made in the last decades, women still remain underrepresented in STEM, and the A.I. field is no different. Given the preponderance of men working in the industry, the achievements made by just a few women end up making their success all that more impressive.

“AI is a technology that gets so close to everything we care about. It’s going to carry the values that matter to our lives, be it the ethics, the bias, the justice, or the access…” @drfeifei

Megan Anderson, business development director at Integrate.ai, is one of a growing number of female leaders working in the industry. Her role, which focuses on driving and implementing new growth opportunities, has helped grow the company (more than $9 million raised in 2017 so far). That accomplishment, including being named to the Top 25 Women of Influence, has put her in the spotlight. It’s also highlighted the impact women like Anderson are having in A.I.

“I would love for more women to make the leap into careers in tech, even if they don’t have STEM backgrounds,” she says. My background is in management consulting, but I am an analytical person with intense curiosity so I took the leap into tech.”

While more women are needed, Anderson points to industry leaders —  like McGill University professor Joelle Pineau and Fast Forward Labs CEO Hilary Mason — who are showing a new path forward.

“AI companies need lots of skills and talents in addition to engineering, like sales, customer success, operations, etc. As long as you learn quickly, stay curious and leverage skills that you have built in other sectors, it is never too late to jump into tech.”

Education is key

 
Dr. Inmar Givoni, Autonomy Engineering Manager at Uber ATG (the company’s self-driving division), is also blazing a new trail. Her company is on the frontline of driverless car technology. Last year, the company famously launched a fleet of self-driving cars in San Francisco.

These days the technologist is used to being the only woman in the room. While she’s not surprised that women are now being recognized, more needs to be done. The key, she says, is to focus on introducing tech to the next generation as soon as possible.

“There’s no point in trying to get more women into A.I. specifically. I think the effort should be towards getting women into STEM,” she explains. “From my perspective, it basically starts as soon as the baby’s born. When a girl is given a shirt that reads ‘I’m a princess’ and the boy gets one that reads ‘I’m a hero’ it already sets a mindset of expectations for [the child] from society.”

Other leaders in the industry agree. Stanford professor and A.I. researcher Fei-Fei Li’s organization, AI4All, is partnering with universities to inject much-needed diversity into the field. “We need to get them young,” she shared with Wired magazine earlier this year.

Making a difference

 
Even though men right now outnumber women, there is hope at the end of the tunnel.

Influencers and stakeholders are now making a dedicated effort to improve those numbers. The Women in Machine Learning Conference, launched in 2006, is doing its part. Through it, entrepreneurs can network, find connections to mentors and learn more about the field.

A little closer to home, the Canadian Institute for Advanced Research (CIFAR) is helping in as well. The organization, probably best known these days for its role leading the $125 million Pan-Canadian A.I. strategy, is championing women at all levels.

Dr. Alan Bernstein, president and CEO of CIFAR, is keen to see change since diversity is crucial for innovation.

“Diversity is our strength. At CIFAR, we’ve known that since we started. We have a strong view that for the advancement of knowledge you need diversity,” Dr. Alan Bernstein, president of @CIFAR_News

As part of their efforts to increase opportunities for women, CIFAR is putting in place ways to increase diversity. “You don’t make as much progress having 10 of the same person in the same room. When you have people with different perspectives sitting around the table, you end up with different questions being asked, and better results.” While change takes time, Bernstein is optimistic. “We’re going to see a big difference in the coming future,” he explains.

 

Is artificial intelligence dangerous?

Elon Musk. Stephen Hawking. Bill Gates.

Some of the richest (and best known) names in science and technology are worried about the future survival of mankind. These innovators are sounding the alarm, not about North Korea, nuclear war or even global warming, but something much more sinister: artificial intelligence.

Hollywood has spent decades showcasing how dangerous artificially intelligent computers (think: Terminator, Ex Machina and more) can be. However some experts believe the bigger (and arguably more immediate) threat A.I. poses isn’t from killer robots, but something far less sexy: computer-generated bias. When computers make decisions based on data skewed by humans it can topple economies and disrupt communities.

Helpful or harmful?

 
One of the most pivotal moments in A.I. history took place in 1996 when IBM’s supercomputer, Deep Blue, beat chess champion, Garry Kasparov. For some, it signalled how far technology had come and how powerful the technology could soon become.

Since then, newspapers have produced countless stories about what an artificially intelligent future could look like. However, the reality is that A.I.is already here. In fact, machines lurk behind the millions of decisions that impact our every move, like what stories pop up in online newsfeeds and how much money banks lend its customers.

In a way, this makes the A.I. infinitely more dangerous. These algorithms shape public perception in ways that were once considered unimaginable.

“The idea of robots becoming smarter than humans and us losing our place in the totem pole is misplaced,” @HumeKathryn.

What people should worry about instead is how machines are making big decisions based on little information. “What I found the greatest hurdle has to do with machine learning systems. They make inferences based on data that carries with it traces of bias in society. The algorithms are picking up on that bias and perpetuating it,” explained Kathryn Hume, vice president of product and strategy for integrate.ai.

What comes next?

 

In theory, machines should offer up bias-free and objective decisions, but that’s often not the case. Computers learn by reviewing examples fed to it and then use that information as a basis for future decisions. In layman terms, it means if you train a computer using biased information, it will end up replicating it.

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One doesn’t have to look too far to find examples of this phenomenon. In 2016, Pro Publica found learning software COMPAS was more likely to rate black convicts higher for future recidivism than their white counterparts. Last year Google’s algorithm was likelier to show high-paying jobs to men than women, and online searches for CEOs regularly showed more white men than another other race or gender.

Breaking down bias in A.I.

 
Breaking down bias is possible. However, it takes work and a lot of it. Relying on more inclusive data can go a long way to fixing the problem.

“It’s important that we be transparent about the training data that we are using, and are looking for hidden biases in it, otherwise we are building biased systems,” said John Giannandrea, Google’s chief A.I. expert, earlier this year.

Education is also a crucial part of the equation. Organizations like the Algorithmic Justice League are helping on that front. Among many things, they’re educating the public about A.I. limitations and working to improve algorithmic bias.

“We in the data community need to get better at educating the public,” adds Hume. “The superficial level sounds really scary and they will stymie the use of it. The tech community can help people who aren’t technical community know what the stuff is and feel empowered to use it.”

Meet the future Einsteins: The kids taking over A.I.

It’s Saturday morning and Toronto-born Tommy Moffat is hunched over his computer. The award-winning programmer is fixated on getting the algorithm behind his A.I.-fuelled robot up and running.

Despite an impressive Rolodex that includes contact details for influencers at some of today’s hottest tech companies, Moffat isn’t an entrepreneur at some high-flying startup or engineer at a high-profile tech company. In fact, he’s just a teenager living in Burlington, Ontario. Although, you would be hardpressed to believe it by just looking at his resume.

At 16 years old, he’s accomplished what it takes some professionals a lifetime to achieve. Earlier this month he spoke at the 2017 Toronto Machine Learning conference, alongside industry heavyweights, like Ozge Yeloglu, chief data scientist at Microsoft Canada, and Google Brain’s Aidan Gomez.

He also recently placed in the top one percent for his age group at an international conference and is slated to join a new startup, called Gradient Ascent, where he’ll be the youngest member of staff.

But all that doesn’t really matter to him. “What I really want to do is change the world,” he says. His motivation isn’t fame or fortune but altruism, he confesses. “I want to use what I’ve learned to help other people. Using augmented reality and computer vision could help a lot of people with disabilities in the real world.”

Teen prodigies making a difference using A.I.

Artificial intelligence has transformed how people around the world access data. It’s  created a new way for everyday engineers to change lives by helping machines do what humans can’t: analyze data at lightning-fast speeds.

While it might be easy to view Moffat as an outlier, he’s quick to point out that he’s not. Other Generation Z-ers — those born mid-to-late nineties — feel the same way he does. “You can see the difference you can make in the world with [artificial intelligence]. It’s not only me.”

Moffat’s right. He’s not the only teenager focused on making the world a better place.

Meet Generation Z


Kavya Kopparapu, also 16, has created an application that A.I. app that can cheaply and quickly diagnose diabetic retinopathy. The eye disease, associated with diabetes, and can lead to blindness if not treated early.

“One of the most important applications of artificial intelligence is in medicine, in saving lives,” she explains in a recent TED Talk. “I envision … a future where a diagnosis is available to anyone, regardless of where they live, money or even electricity. I envision a future where we can save lives”.

Meanwhile, Canadian prodigy Tanmay Bakshi, 13, is working with IBM on a project designed to help a quadriplegic woman walk again. “We’re trying to give her artificial communication ability … through the power of artificial intelligence and systems like IBM Watson that allow you to essentially implement artificial intelligence.”

While he’s somewhat of a celebrity in the tech world — his YouTube channel has more than 20,000 subscribers  — he remains humble. “[I’m interested] in generally sharing my knowledge about these sorts of technologies with the rest of the community and of course through things like open-source technology and so much more.”

The kids are alright



Vik Pant isn’t surprised by today’s tech-leaning youth. Especially teens choosing to specialize in A.I.; a burgeoning new area in tech that’s expected to grow in the future.

“A.I. is the future. It’s not a trend. It’s on the ramp up, not down,” @vikpant, who works for Oracle’s competitive intelligence team. “Youth see that and want to harness that potential.”

The only challenge he can see is a discrepancy between those, like Moffat, who posses new-age tech skills and those that don’t. Primarily, youth from lower-income brackets who might have access to tools they require.

“Definitely in terms of artificial intelligence it’s a discipline and domain that doesn’t discriminate, he explains. “It’s socioeconomic factors that constrain or allow youth to be more involved. I’m encouraged, though. I’ve noticed that many private sector and corporations are helping underprivileged helping youth.”

Moffat agrees. Thankfully, the learning opportunities that exist today have grown beyond what was available as little as 10 years ago. Now people, at any age, can start learning online. It’s this type of thinking that drives Moffat’s to one day become an industry expert in A.I.

“Before I broke out of my old way of thinking, I never thought about becoming an ‘expert’ in anything. It takes years to go through school to get a degree. With the help of modern education programs like The Knowledge Society, it’s possible to go way deeper into a topic at a significantly earlier age than ever before.”

How Canada became a hotspot for artificial intelligence research

Canada’s dominance in the artificial intelligence space is drawing attention from techpreneurs around the world. The country, probably better known in recent years for its pop music exports and human rights record, has become a hotbed for the computer algorithm-powered technology over the last five years.

Toronto’s startups making waves

 
Last summer, Montreal’s Element AI raised an eye-watering $102 million from investors and earlier this year Toronto-based Integrate.ai secured a $5 million seed round. That’s on top of other notable moves being made by some of today’s more entrenched companies, like Royal Bank that will employ AI for its customer operations and DeepMind, a Google-acquired intelligence company, opened an office in Alberta last summer.

Not to be outdone, General Motors said it was going to launch one of its self-driving research hubs in Markham, Ontario. Thomson Reuters last year announced it would open a Toronto center for “cognitive computing” that would create 400 “high-quality” jobs.

“Canada is home to some of the brightest minds in the field of artificial intelligence; it has been at the academic forefront of the broad field of AI for over 30 years,” Richard Zemel, a senior fellow at the Canadian Institute for Advanced Research, told R&D magazine. “Specifically in the areas of machine learning, reinforcement learning and deep learning, leading researchers and professors have been graduating some of the most promising talent out of cities like Toronto, Montreal and Edmonton.”

How did this happen?

 
So, how did we get here and why now?  It doesn’t hurt that Canada has become famous for its liberal immigration policy. Just recently it opened its doors to tech talent willing to relocate to Canada.

The fast-track visa program offers up permanent residency and is designed to woo talented innovators from around the world. The Canadian government has also committed about $125 million to A.I.

Officials at all three levels are also lending a helping hand. In late 2016, the federal, provincial and municipal governments joined forces to launch the new Toronto-based Vector Institute.

The non-profit is focused on A.I. research and helping startups get funding for ongoing work. It also has backing from tech giants like Google and Air Canada — making it a force to be reckoned with. Meanwhile Montreal is home to its own deep learning expertise thanks to Yoshua Bengio (one of the co-fathers of deep learning) and the Montreal Institute for Learning Algorithms.

Future outlook

 
But Canada faces a tough (and unpredictable) road as it battles for AI superiority. Compared to the U.S., Canadian startups receive a fraction of the investment dollars that their counterparts in the U.S. do.

For example, last year $69.1 billion was invested in America found the National Venture Capital Association, while Canadian companies received $3.2 billion. But, things are now on the rise. Last year represented the seventh straight year of growth for VC investment in Canada and the largest since 2001.

While only time will tell how far Canada’s A.I. scene will fare in the future. Although, its current booming outlook signifies that things for the country (and Toronto especially) look bright.

“Toronto’s tech industry is booming right now, so it’s no surprise that it’s also emerged as a hub for AI job opportunities.”

Daniel Culbertson, an economist at job-seeking website Indeed, shared with BetaKit.

From science fiction to science fact: Tech that actually exists

For many, it serves as an inspiration and more importantly a peek into what the near future might offer. Everything from smartwatches to relatable robots can arguably be traced back to a fictional piece of work.

Thankfully technology moves at breakneck speeds and what was once considered impossible has quickly become reality. If you’ve ever wanted your very own hoverboard or a robotic servant to call your own, you’re in luck. Here are some of the best fiction-influenced technologies that now exist.

Hoverboards

Fans of Marty McFly – the wonder kid from Back to the Future – can finally rejoice. The hoverboard that helped propel the smart-talking, wise-cracking teen to new heights is now a reality. In 2015, car company Lexus introduced its own version of the device that relies on “magnetic levitation” (read: magnets that repel gravity) to achieve lift-off.

Since then other companies have stepped up and created their own. U.S. startup Hendo Hoverboards introduced the world to its first levitating device on Kickstarter two years ago and since then has launched four different versions of the board that look and move like a traditional skateboard.

Embeddable microchips

In most dystopian movies, GPS-tracking microchips are tools oft used for nefarious reasons. Bad guys inject the tiny, plastic devices at underneath the skin of the heroic protagonist (or protagonists) in an attempt to track, manipulate and in some cases even kill. Thankfully, in real life, things aren’t so bad.

While tech startups (and a few forward-thinking innovators) have long flirted with the idea of embeddable tracking technology it’s only in recent years that it’s become a real possibility.

Wisconsin-based Three Square Market is one of the first in North America to provide its employees with tracking chips that allow them to enter and exit a building at will and make cashless purchases from company kiosks. The devices, the size of a single grain of rice, use radio-frequency identification (RFID) — the same technology found in key fobs and smart wristbands. While Three Square Market’s chips don’t include in-depth tracking by choice the Swedish company — called Biohax International — behind the device does include that feature in its other smart embeddable products.

The Jetson’s ‘Rosie the Robot’

Robots are all too often employed by Hollywood as a way to demonstrate just how modern and advanced a society is without being explicit. It’s a popular trope that can be found in Star Trek’s Data, Ava from Ex-Machina and even Arnold Schwarzenegger’s character in The Terminator. While the characters from our favourite science fiction novels aren’t feasible just yet, several companies have figured out a way to emulate some of their best features.

Sophia, a humanoid robot created by Hanson robotics, is as close as it gets to a Rosie from The Jetsons. She can converse in up to 20 languages, easily mimic human emotions, clean and respond to questions in real-time. Her skills have even garnered her a vocal and enthusiastic following online and since being launched last year has appeared at the UN, Jimmy Kimmel Live and CNBC.

Driverless cars

Hiring a human driver is so passé. If science-fiction movies are to be believed the best way to travel is with an artificially intelligent and self-aware driver behind the wheel. Knight Rider’s Michael Arthur Long and his trusty sidekick — the smooth-sounding Pontiac Firebird Trans Am — were for many the epitome for what a smart car should act like.

The growing roster of driverless cars on the market, unfortunately, lack the spunk found in KITT (the affectionate nickname for the car) but they do showcase some of the basics that consumers will likely want in a vehicle.

Google, one of the top companies in the AI driving market, has seen its cars rack up a total of three million self-driving miles so far. It’s autonomous fleet rely on sensors to differentiate between pedestrians, other cars and cyclists and can transport individuals to their chosen destination, just like KITT.