Daily Archives: March 5, 2020

Cloud platforms, managed service providers and organizations undertaking digital transformations are beginning to reap the benefits of an emerging IT trend: the use of AI-powered IT operations technology to monitor and manage the IT portfolio automatically.

This emerging practice, known as AIOps, is helping enterprises head off potential outages and performance issues before they negatively impact operations, customers, and the bottom line. But the more advanced deployments are beginning to use AI systems not just to identify issues, or to predict issues before they happen, but to react to events with intelligent, automated mitigation.

But what exactly is AIOps and how are organizations putting it to use today? Here we take a deeper look at the technologies, strategies, and challenges of AI-assisted IT operations.

AIOps is an emerging IT practice that applies artificial intelligence to IT operations to help organizations intelligently manage infrastructure, networks, and applications for performance, resilience, capacity, uptime, and, in some cases, security. By shifting traditional, threshold-based alerts and manual processes to systems that take advantage of AI and machine learning, AIOps enables organizations to better monitor IT assets and anticipate negative incidents and impacts before they take hold.

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What is AIOps? Injecting intelligence into IT operations - CIO

Dr Daniel Susskind, author of the bestseller A World Without Work, thinks that CTOs need to think of their roles in terms of tasks and which ones could be done by AI

How will AI impact job functions?

Will AI replace my job as a CTO? is one of the most pressing questions any senior technology leader must be asking themselves.

The answer is both yes and no, according to Dr Daniel Susskind, Oxford University economics fellow and author of bestseller A World Without Work, a study of how artificial intelligence is going to displace many white-collar jobs in professions such as law, accounting, education and HR.

What Susskind calls the AI fallacy is projecting onto computers the same kind of human skills that are valued so highly in the professions empathy, judgement, creativity and therefore deciding computers fall short.

This misunderstands AI capability, says Susskind, as its pattern recognition and data storage capabilities far outstrip anything humans can do.

Susskind was speaking at the Advanced World conference in Birmingham on March 5th 2020.

Instead of thinking AI is going to completely take over the professions something we are already seeing in IT departments with AI chatbots handling lower-level tickets it would be better to think of any job as a collection of tasks, some of which are better suited for automation than others.

Andrew Zitney explores his role as SVP, CTO of McKesson Technology with Information Age: how its changing and how to free up the IT department and developer teams. Read here

Susskind said: Any job can broken down into tasks that are relatively routine and process based. Weve got to think from the bottom up in terms of individual tasks. A lot of these tasks turn out to be relatively routine.

And according to a McKinsey survey of 820 occupations in the US, only 5% of occupations consist of activities that are 100% automatable.

The survey also found that 60% of all jobs involved repetitive tasks that could be automated to an extent given current AI.

And in an example of how automation can change the lives of all CTOs and CIOs for the better, a recent Asana survey of over 10,000 workers found they spent only 27% of their time doing what they were supposed to be doing in their job the rest of their time was spent doing robotic and automatable tasks.

Susskind said that the key to unlocking the AI challenge is education, the format of which has not changed for hundreds of years and trains people to do those activities that are going to be displaced. In future, education should focus on two areas said Susskind: either the kind of roles that machines cannot yet do or helping to design and build AI machines and putting them to use.

He foresees everybody being in a state of continual education, rather than people mostly cutting off at school-leaving age.

Susskind said: We dont face mass unemployment. Were going to see more demand for the people who can perform the types of tasks that cant be automated. The challenge as I see it is how do we prepare people for the change in work thats going to come?

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Will AI replace my job as a CTO? yes and no - Information Age

Artificial intelligence (AI) is a major influence on the state of education today, and the implications are huge. AI has the potential to transform how our education system operates, heighten the competitiveness of institutions, and empower teachers and learners of all abilities.

Dan Ayoub is general manager of education at Microsoft.

The opportunities for AI to support education are so broad that recently Microsoft commissioned research on this topic from IDCto understand where the company can help. The findings illustrate the strategic nature of AI in education and highlight the need for technologies and skills to make the promise of AI a reality.

The results showed almost universal acceptance among educators that AI is important for their future99.4% said AI would be instrumental to their institutions competitiveness within the next three years, with 15% calling it a game-changer. Nearly all are trying to work with it too92% said they have started to experiment with the technology.

Yet on the other hand, most institutions still lack a formal data strategy or practical measures in place to advance AI capabilities, which remains a key inhibitor. The finding indicates that although the vast majority of leaders understand the need for an AI strategy, they may lack clarity on how to implement one. And it could be that they just dont know where to start.

David Kellermann has become a pioneer in how to use AI in the classroom. At the University of New South Wales in Sydney, Australia, Kellermann has built a question bot capable of answering questions on its own or delivering video of past lectures. The bot can also flag student questions for teaching assistants (TAs) to follow up. Whats more, it keeps getting better at its job as its exposed to more and different questions over time.

Kellermann began his classrooms transformation with a single Surface laptop. Hes also employed out-of-the-box systems like Microsoft Teams to foster collaboration among his students. Kellermann used the Microsoft Power Platform to build the question bot, and hes also built a dashboard using Power BI that plots the classs exam scores and builds personalized study packs based on students past performance.

Educators see AI as instrumental to their institutions competitiveness, yet most institutions still lack a formal data strategy to advance AI.

Kellermanns project illustrates a key principle for organizations in nearly every industry when it comes to working with AI and machine learningknowing where to start, starting small, and adding to your capabilities over time. The potential applications of AI are so vast, even the most sophisticated organizations can become bogged down trying to do too much, too soon. Often, it comes down to simply having a small goal and building from there.

As an AI initiative gradually grows and becomes more sophisticated, its also important to have access to experts who can navigate technology and put the right systems in place. To gain a foothold with AI, institutions need tools, technologies, and skills.

This is a big focus for our work at Microsoftto support educational institutions and classrooms. Weve seen the strides some institutions have already taken to bring the potential of AI technologies into the classroom. But we also know there is much more work to do. Over the next few years, AIs impact will be felt in several waysmanaging operations and processes, data-driven programs to increase effectiveness, saving energy with smart buildings, creating a modern campus with a secure and safe learning environment.

But its most important and far-reaching impact may lie in AIs potential to change the way teachers teach and students learn, helping maximize student success and prepare them for the future.

Collective intelligence tools will be available to save teachers time with tasks like grading papers so teachers and TAs can spend more time with students. AI can help identify struggling students through behavioral cues and give them a nudge in the right direction.

AI can also help educators foster greater inclusivityAI-based language translation, for example, can enable more students with diverse backgrounds to participate in a class or listen to a lecture. Syracuse Universitys School of Information Studies is working to drive experiential learning for students while also helping solve real-world problems, such as Our Ability, a website that helps people with disabilities get jobs.

AI has the power to become an equalizer in education and a key differentiator for institutions that embrace it.

Schools can even use AI to offer a truly personalized learning experienceovercoming one of the biggest limitations of our modern, one-to-many education model. Kellermanns personalized learning system in Sydney shows that the technology is here today.

AI has the power to become a great equalizer in education and a key differentiator for institutions that embrace it. Schools that adopt AI in clever ways are going to show better student success and empower their learners to enter the work force of tomorrow.

Given its importance, institutions among that 92% should start thinking about the impact they can achieve with AI technologies now. Do you want to more quickly grade papers? Empower teachers to spend more time with students? Whatever it is, its important to have that goal in mind, and then maybe dream a little.

This is a movement still in its early days, and there is an opportunity for institutions to learn from one another. As our customers build out increasingly sophisticated systems, Microsoft is learning and innovating along with them, helping build out the tools, technologies, and services to turn the vision for AI into reality.

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Unleashing the power of AI for education - MIT Technology Review

While self-driving cars have hogged the headlinesfor the past few years, other forms of autonomous transport are gaining steam.

This month, IBM and Promare a U.K.-based marine research and exploration charity will trial a prototype of an artificial intelligence (AI)-powered maritime navigation system ahead of a September 6th venture to send a crewless ship across the Atlantic Ocean on the very same route the original Mayflower traversed 400 years ago.

The original Mayflower ship, which in 1620 carried the first English settlers to the U.S., traveled from Plymouth in the U.K. to what is today known as Plymouth, Massachusetts. Mayflower version 1.0 was a square-rigged sail ship, like many merchant vessels of the era, and relied purely on wind and human navigation techniques to find its way to the New World. The Mayflower Autonomous Ship (MAS), on the other hand, will be propelled by a combination of solar- and wind-generated power, with a diesel generator on board as backup.

Moreover, while the first Mayflower traveled at a maximum speed of around 2.5 knots and took some two months to reach its destination, the upgraded version moves at a giddy 20 knots and should arrive in less than two weeks.

The mission, first announced back in October, aims to tackle all the usual obstacles that come with navigating a ship through treacherous waters, except without human intervention.

The onboard AI Captain, as its called, cant always rely on GPS and satellite connectivity, and speed is integral to processing real-time data. This is why all the AI and navigational smarts must be available locally, making edge computing pivotal to the ventures success.

Edge computing is critical to making an autonomous ship like the Mayflower possible, noted Rob High, IBMs CTO for edge computing. The ship needs to sense its environment, make smart decisions about the situation, and then act on these insights in the minimum amount of time even in the presence of intermittent connectivity, and all while keeping data secure from cyberthreats.

The team behind the new Mayflower has been training the ships AI models for the past few years, using millions of maritime images collected from cameras in the Plymouth Sound, in addition to other open source data sets.

For machine learning prowess, the ship is using an IBM Power AC922 system, which is used in some of the worlds biggest AI supercomputers. Alongside IBMs PowerAI Vision, the Mayflowers AI Captain is built to detect and identify ships and buoys as well as other hazards, including debris and to make decisions about what to do next.

For example, if the MAS encounters a cargo ship that has shed some of its load after colliding with another vessel, the AI Captain will be called into action and can use any combination of onboard sensors and software to circumvent the obstacles. The radar can detect hazards in the water ahead, with cameras providing additional visual data on objects in the water.

Moreover, an automatic identification system (AIS) can tap into specific information about any vessels ahead, including their class, weight, speed, cargo type, and so on. Radio broadcast warnings from the cargo ship can also be accepted and interpreted, with the AI Captain ready to decide on a change of course.

Other data the AI Captain can tap into includes the navigation system and nautical chart server, which provide the current location, speed, course, and route of the ship, as well as attitude sensors for monitoring the state of the sea and a fathometer for water depth.

The onboard vehicle management system also provides crucial data, such as the battery charge level and power consumption, that can be used to determine the best route around a hazardous patch of ocean, with weather forecasts informing the final decision.

Crucially, the AI Captain can communicate vocally with other ships in the vicinity to convey any change in plans.

The MAS ship itself is still being constructed in Gdansk, Poland, and the AI Captain will be tested this month in a manned research ship called the Plymouth Quest, which is owned by the U.K.s Plymouth Marine Laboratory. The test will essentially determine how the AI Captain performs in real-world scenarios, and feedback will be used to refine the main vessels machine learning smarts before the September launch.

Maritime transport constitutes around 90% of global trade, as its the most cost-effective way of transporting goods in bulk. But shipping is widely regarded as a major source of pollution for the planet. Like self-driving cars, a major benefit of electrified autonomous ships is that they reduce emissions while also promising fewer accidents at least three quarters of maritime accidents are thought to be caused by human error.

Moreover, crewless ships open the doors to longer research missions, as food, well-being, and salaries are no longer logistical or budgetary considerations.

There has been a push toward fully automating sea-faring transport in recent years. Back in 2016, news emerged that an unmanned warship called Sea Hunter was being developed by research agency DARPA, which passed the Sea Hunter prototype on to the Office of Naval Research two years later for further iteration. In Norway, a crewless cargo ship called the Yara Birkeland has also been in development for the past few years and is expected to go into commercial operation later in 2020. And the Norwegian University of Science and Technology (NNTU) has carried out trialsof atiny electric driverless passenger ferry.

Elsewhere,Rolls-Royce previously demonstrated a fully autonomous passenger ferry in Finland and announced a partnership with Intel as part of a grand plan to bring self-guided cargo ships to the worlds seas by 2025.

So plenty is happening in the self-navigating ship sphere a recent report from Allied Research pegged the industry at $88 billion today, and it could hit $130 billion within a decade. But while others seek to automate various aspects of a ships journey, the new Mayflower is designed to be completely self-sufficient and operate without any direct human intervention.

Many of todays autonomous ships are really just automated robots [that] do not dynamically adapt to new situations and rely heavily on operator override, said Don Scott, CTO of the Mayflower Autonomous Ship. Using an integrated suite of IBMs AI, cloud, and edge technologies, we are aiming to give the Mayflower full autonomy and are pushing the boundaries of whats currently possible.

Four centuries after the Mayflower carried the Pilgrims across the Atlantic, we could be entering a whole new era of maritime adventures.

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AI, AI, Captain! How the Mayflower Autonomous Ship will cross the Atlantic - VentureBeat

Update: HIMSS20 has been cancelled due to the coronavirus. Read more here.

The rise of artificial intelligence into the mainstream of healthcare information technology is one of the biggest trends at HIMSS20, according to analytics vendor Health Catalyst, which will be in booth 2428.

Healthcare IT News asked Jason Jones, chief data scientist officer at Health Catalystand a speaker at HIMSS20, about a few overarching trends surrounding AI that are important to HIMSS20 attendees. He says that a lack of results from healthcare AI implementations, algorithmic bias and difficulty attracting and retaining data science professionals are some key areas to watch.

Jones said the industry is not seeing healthcare AI results in the timeframe and to the magnitude hoped for. On a related note, there is the question of how healthcare-provider organizations deal with the crush from AI-powered health IT vendors in the space.

"It is very easy for individuals or organizations to get excited about their first AI project,"Jones said. "It is new, exciting and a bit magical. Out of dreams of doing good or pressure to perform, people would like to believe there is a solution. What is the problem? Building predictive models is very quick and easy."

Jones said the problems here are in four areas.

"First, ironically, the biggest obstacle toward solving a problem via leveraging AI can be that the problem to be solved is defined poorly or differently by different people,"he explained. "Start with a great problem statement and common understanding of what 'awesome'looks like across stakeholders. Second, technically, the difficult part is getting high-quality data to train the model commonly 50-100x more time and effort than building a predictive model."

Jason Jones, Health Catalyst

Evaluate whether the organization has the high-quality data it needs before starting an AI project, he advised; if not, acquire or improve available data or choose a different project, he cautioned.

"Third, most improvements in healthcare require behavior change on the part of physicians, nurses, administrators, members, patients, etc.," he said. "We do not need AI to tell us to eat and exercise well, it's just that it can be hard to do. When human behavior change is needed for success, we need tools and resources for change management."

And fourth, few AI efforts are set up for optimization or formal evaluation, Jones explained.

"If you fear you are being left behind in the AI race, consider the last time you felt left behind by an infomercial," he offered. "The claims of success for AI may not be much better founded. Focus on fundamentals, ask challenging questions, realize that AI typically fits into a workflow that requires multiple changes, and plan to monitor and improve over time."

Then there is the artificial intelligence problem known as algorithmic bias. How do healthcare-provider organizations deploy AI in such a way that they do not exacerbate health disparities?

"There has been an increase in concern that the 'move fast and break things'approach may have done more harm than good in particular and in aggregate," Jones stated. "People are intolerant of breaking things in healthcare in ways they feel could have been anticipated. We are justifiably and particularly angry when the nature of the failure involves disparity based upon personal characteristics such as gender, ethnicity, geographic location and socioeconomic status."

But healthcare does want algorithms to discriminate between people at greater or lesser risk for readmission or ready or not ready to quit smoking, for example.

"Remembering this helps us to think differently about AI," Jones said. "For algorithms to succeed, we should retain the right and accountability to define what we want the algorithm to do and not do and then measure against these desires. With that in mind, it is possible to go beyond fear of algorithmic bias to algorithms helping assure equity."

On whiteboards, healthcare-organization staff can convert equity from a balancing measure (possible harm) to an outcome (desired benefit) and then design and measure for that, he explained.

And Jones third healthcare AI trend surrounding HIMSS20 is how healthcare provider organizations attract and retain data science talent.

"It can feel as though it is very difficult and expensive to attract a data scientist," he said. "In healthcare, it can feel impossible to compete with the tech sector. If you feel this way, pause and consider your needs and assets. First, in healthcare, most of the technical time and effort is in gathering and preparing data data engineering. You may not need as many data scientists as you think, or you may be able to 'rent'one when you have the need."

Second, think about what the organization needs a data scientist to do for example, ask and answer questions better with data, and in a way staff can understand, he added.

"Test and evaluate for people who can do that," he advised. "Usually this means not using the 'Kaggle'(data competition) approaches. These are the aspects of data science that are both most technical and most easily automated."

And third, if a healthcare organization has a noble purpose, point this out and explain how the data scientist contributes, Jones advised.

"Give him or her opportunities to see that contribution firsthand from call centers, to boardrooms, to nurses' stations,"he concluded. "Taking these steps not only helps you attract and retain talent, but also helps you get better output through the data scientist better understanding the real problems and what solutions might look like."

Jones will be at HIMSS20 on a panel entitled "Analytics to Algorithms: How to Maximize Impacts" on Monday March 9. He also will be presenting alongside Dr. Terri Steinberg during a presentation entitled "Machine Learning and Data Selection for Population Health"on Thursday, March 12.

Twitter:@SiwickiHealthITEmail the writer:bill.siwicki@himssmedia.comHealthcare IT News is a HIMSS Media publication.

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Health Catalyst points HIMSS20 attendees toward three AI trends - Healthcare IT News

Saadia Muzafarr founder of Tech Girls Canada

With her work focused on maximizing the public good and having built up Tech Girls Canada the hub for Canadian women in STEM Saadia Muzaffar is renowned for the vast amount of work that shes poured towards creating an environment in the AI industry that includes diversity.

Tech Girls Canada, a Canadian non-profit, is dedicated to conducting research and co-designing solutions that address barriers for diversity and equity in science and technology sectors by championing LGBTTQ+, women of colour, women of all abilities, refugee, immigrant, and indigenous women.

Muzaffar is a leading force in the tech scene of Canada, author, and passionate advocate of responsible innovation, decent work for everyone, and prosperity of immigrant talent in STEM. She is an advisor to the Government of Canadas Economic Strategy tables for the Access to Skilled Talent working group, and part of Canada Beyond 150: policy for a diverse and inclusive futures Feminist Government initiative.

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10 women advancing AI in Canada - IT World Canada

Vatican officials are calling for stricter ethical standards on the development of artificial intelligence, with tech giants IBM and Microsoft being the first companies to sign its new initiative.

The Rome Call for AI Ethics lays out six broad principles: transparency, inclusion, responsibility, impartiality, reliability, and security and privacy. These principles say that technology should protect people, particularly the weak and underprivileged. They also urge policymakers across the world to create new forms of regulation on advanced technologies that have a higher risk of impacting human rights, which includes facial recognition.

AI is incredibly promising technology that can help us make the world smarter, healthier, and more prosperous, IBM vice president John Kelly III said after the initiatives signing. But only if it is shaped at the outset by human interests and values.

The Vatican wants to ensure that companies are not using AI as a means to collect data without the consent of individuals and then using that data for commercial or political benefit. In one recent example, it was shown that thousands of federal government agencies and private companies were using software owned by face recognition company Clearview AI, which scraped facial data without peoples knowledge. The companys database, which features more than 3 billion images pulled from various online sites, is being used by law enforcement to catch persons of interest.

The document also says that a duty of explanation must be established and that AI-based algorithms should provide individuals with information on how these algorithms came to their decisions to ensure that there is no bias. Last year, US lawmakers introduced a bill that would do just that and allow the Federal Trade Commission to create rules that would force these companies to evaluate automated systems containing highly sensitive information.

Vatican officials hope to increase the number of signatories for its AI ethics initiative in the coming months. They also hope to collaborate with universities across the globe to promote more scientific research into ethical AI guidelines.

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The Catholic Church proposes AI regulations that protect people - The Verge

]]> Collaborating with QRI enables Emerson to enhance its capabilities in giving useful analytics to maximise production. Credit: Paul Lowry.

US-based companies Emerson and Quantum Reservoir Impact (QRI) have collaborated to develop applications for artificial intelligence (AI)-based analytics for oil and gas exploration and production (E&P).

The two companies will also develop and market decision-making tools for E&P analytics.

The collaboration aims to help oil and gas customers to harness data to optimise their reservoir management strategies.

It will also enable customers to enhance digital transformation technologies.

Emerson E&P software president Steve Santy said: Collaborating with QRI enhances our capabilities to give customers meaningful analytics to maximise production and capital efficiency and for better reserve assessment.

The partnership integrates Emersons E&P software portfolio with QRIs expertise in applying augmented AI, machine learning (ML) and advanced analytics for reservoir management.

Emerson and QRI will also apply advanced computational technologies to help geoscientists and engineers make actionable field development decisions to achieve higher productivity.

QRI chairman, CEO and co-founder Nansen Saleri said: People, process and data are as important as technology to the success of the solution. Our partnership with Emerson makes for a very powerful team to ensure that our offerings will become a prominent choice in the market.

As our industry continues to transform, we share Emersons vision of applying state-of-the-art deep learning tools to automate next-generation workflows and offer our customers a rapid means of generating value.

In July, Emerson acquired Zedis software and automation businesses to help accelerate digital transformation in the oil and gas industry.

In March 2019, Emerson formed a strategic alliance with Repsol to provide advanced subsurface geophysical technologies to expedite production.

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QRI and Emerson partner on AI-based oil and gas E&P analytics - Hydrocarbons Technology

Athena Pathways Consortium will be training 500 B.C. women in AI, machine learning and data science for at least 18 months | Credit: Shutterstock

What happened: Industry group launching new program to expand artificial intelligence expertise for hundreds of B.C. women

Why it matters: Initiative will try to improve gender balance in male-dominated tech sector

B.C.s artificial intelligence community wants to get smarter about correcting its considerable gender imbalance.

The Athena Pathways Consortium officially launched Thursday (March 5) with the goal of training 500 B.C. women in AI, machine learning and data science over the next 18 months.

Its the almost hidden costs of not doing this that are particularly pernicious, said AInBC executive director Steve Lowry, whose industry association is spearheading the initiative backed by a mix of private sector and post-secondary players.

When you look at organizations that arent gender-balanced or diverse enough, they underperform.

Athena Pathways sees the University of B.C., Simon Fraser University, the B.C. Institute of Technology and Northeastern Universitys new Vancouver campus developing courses and workshops for women at high school and post-secondary levels as well as those already in the workforce.

While the initial phase of the program, budgeted at $682,000, will offer 300 scholarships and is set to run 18 months, Lowry said Athena Pathways could extend beyond that as it hunts for additional donors.

In addition to AInBC and the aforementioned post-secondary institutions, Athena Pathways is receiving support from Vancouver-based Canadas Digital Technology Supercluster, D-Wave Systems Inc., Metaoptima Technology Inc. and Tech Resources Inc. (TSX:TECK.B), among others.

B.C.s technology sector is among the most male-dominated in Canada.

Women account for 18.3% of Vancouvers tech workforce, according to a 2019 report from real estate services firm CBRE Group Inc.

Thats the second-largest gender disparity among Canadian cities, tied with Saskatoon.

The only Canadian city to fare worse in the rankings is Victoria, where women compose 15% of the technology workforce.

The B.C. Tech Association unveiled 15 recommendations for the tech sector in December 2019in a bid to create an ecosystem much better at recruiting and retaining women.

Among the recommendations curated from a series of workshops, panels and roundtables:

Set targets and publish the results. Ask if your employee diversity mirrors that of your customers.

Leverage your teams network: ask women in your organizations to identify people theyve worked with in the past and would like to work with again.

Ask yourself if talent is promotable before someone takes parental leave consider promoting before they take leave.

Put in place salary bands for each role, track and communicate pay vs. industry averages (compa ratios). Establish and enforce minimum salaries for each role.

Our objective is to make this easy for people by giving concrete, actionable suggestions, B.C. Tech Association CEO Jill Tipping told Business in Vancouver in December.

Were not trying to be one size fits all. Were trying to give you a menu of options and challenge you to find at least one that would work for your business.

torton@biv.com

@reporton

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B.C.'s Athena industry initiative aims to train 500 women in AI - Business in Vancouver

Nine days before the World Health Organization alerted the world to the threat posed by COVID-19, an artificial intelligence-powered startup led by the University of Torontos Kamran Khan had already spotted the first signs of an unusual outbreak.

In an interview with CNBC, Khan explained how his company, BlueDot, was able to scour big data and spot the emergence of the novel coronavirus before anyone else.

He said BlueDotuses machine learning and natural language processing to comb through masses of data, which are then reviewed by doctors and computer programmers who create threat reports.

We dont use artificial intelligence to replace human intelligence, we basically use it to find the needles in the haystack and present them to our team, said Khan, an associate professor at the Institute of Health Policy, Management and Evaluation at the Dalla Lana School of Public Health and an infectious disease physician at St. Michaels Hospital.

He said his experience treating patients during the SARS outbreak in 2003 inspired him to start BlueDot.

What I learned during SARS is, lets not get caught flatfooted, lets anticipate rather than react.

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T's Kamran Khan on how his startup used AI to spot the coronavirus before anyone else: CNBC - News@UofT