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

#Viral

Tag Archives: artificial intelligence

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 >

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.

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.

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.

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.

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.

dmzthereview-ai

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.”

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

Tag Archives: artificial intelligence