Mara Cairo is obsessed with utilizing AI for good. She has a Bachelor of Science in Electrical Engineering from the College of Alberta and holds her P.Eng. and PMP designations. Earlier than becoming a member of Amii, she labored within the {hardware} improvement area, the place she helped purchasers take their merchandise to market, with a concentrate on micro and nano-fabrication.
As Product Proprietor of Superior Expertise at Amii, Mara leads a technical group that helps {industry} companions construct machine studying capability inside their group by offering steering and experience to develop predictive fashions. Her group works with purchasers who’re dedicated to advancing alongside the AI adoption spectrum by making use of machine studying to their most difficult enterprise issues.
Amii (Alberta Machine Intelligence Institute) is one in all Canada’s preeminent facilities for AI, they companion with firms of all sizes, throughout industries, to drive innovation technique and supply sensible steering and recommendation, company coaching and expertise recruitment companies.
We sat down for an interview on the annual 2023 Higher Certain convention on AI that’s held in Edmonton, AB and hosted by Amii.
What initially attracted you to electrical engineering?
As a child, I simply actually favored constructing issues. My mother would carry residence a fan when it was sizzling in summer season, and I might wish to construct it. I keep in mind rising up as a youngster, I had a cellular phone, a kind of Nokia’s that you can take aside and I might take it aside and put bejewels throughout it on the within and the antenna. However after I opened it up, it was like, “Holy crap, what’s in right here? What is going on on?” It was actually attention-grabbing to me.
I all the time excelled in math. So, placing all of these collectively, my mother and father additionally pushed me within the engineering route as a result of I used to be good at math, I had only a common curiosity in electronics and needed to know extra about it, that is form of what drew me in to start with.
Additionally, in engineering, I simply actually favored the thought of making use of math to real-world issues. Yeah, okay, cool, math is nice and thrilling and enjoyable for me, however with engineering you possibly can apply it to unravel arduous issues. It appeared form of the proper mesh of issues that might result in an attention-grabbing profession.
Your mother and father sounded very proactive in supporting your pursuits.
Yeah. My dad particularly. He says he noticed it in me from a younger age and simply all the time pushed me in that route. I used to be at a Ladies in AI occasion final evening too and we talked about eradicating some boundaries and making it a extra approachable subject for ladies. And I did not actually see that as a barrier as a result of, once more, my mother and father had been like, “That is what you must do. It isn’t a query of your gender or something. It is simply it is a talent you might have. You must naturally form of comply with it and nurture it.” I by no means felt prefer it wasn’t for me, which helped clearly.
Earlier than becoming a member of Amii you labored within the {hardware} improvement area to concentrate on micro and nanofabrication. Might you outline these phrases?
Positively. So, in electrical engineering, I took the nanoengineering possibility. It was the specialty round designing and manufacturing on the micro and nanoscale. After we speak about a nanometer, we’re speaking a few millimeter divided in 1,000,000 is a nanometer. A really, very small scale. And that is cool. This stuff are so small you possibly can’t even see them with the bare eye. However I may take this specialization to learn to manufacture on that scale and design issues on that scale.
We stay in a really related world. There’s electronics throughout us and we’d like to have the ability to design electronics for the packaging and area constraints. We’re always attempting to make issues smaller and smaller. You are taking one thing cumbersome, a prototype, and also you want to have the ability to make it reproducible and scalable. Nanofabrication is admittedly in regards to the instruments and the strategies that you just use to design and manufacture on that form of degree.
That is from manufacturing microchips to taking these two totally different chips and connecting them electrically to the ultimate packaging. Doing all of that on the microscale requires a special method than constructing one thing on our human scale. The micro and nanofabrication are simply across the chemical processes that you just use and {the electrical} processes, the packaging that you want to be sure that these are hermetically sealed and shielded from their atmosphere.
Outdoors of microchips, what could be one other utility or use case?
We labored on a number of tasks like fiber optics. Once more, all of it finally should come to some form of processing unit that is taking in alerts or producing alerts. We did work within the telecom {industry}, optics, cameras, all of that stuff. However the brains of it are usually some form of microchip within the center. However there’s additionally the sensors which can be feeding their alerts into no matter processing unit you are utilizing. So various manufacturing strategies for constructing no matter kind of sensor or enter or output machine that we’d like.
What are a few of the challenges behind engaged on this sort of nanoscale?
One piece of mud can break your complete day. Stuff you’re engaged on are the identical dimension because the mud within the air. So, you fabricate in a clear room. The clear room is admittedly an atmosphere that is defending what you are engaged on from you as a human, as a result of we’re very soiled as people, we’re always form of spitting out particulates, our garments are particulating, the make-up that we’re carrying it is making the air soiled. We have to get rid of as a lot of that as potential in order that the issues that we’re constructing are clear and clear of that form of contaminant.
One other problem, there’s nice methods to construct these clear rooms and there is a complete form of research and science behind that, however the different problem is taking it out of the lab as a result of finally these items are going for use in our very soiled world. That is when the packaging turns into necessary. We nonetheless want to have the ability to entry these gadgets, however we have to do it in such a manner that we’re not contaminating the atmosphere, the packaging. So hermetically sealing issues, ensuring it is fully sealed, nothing’s getting in or out. That is one other set of challenges that I noticed. We’d have one thing that works nice on a lab bench in a managed setting, however usually a lot of the issues that we’re constructing are supposed to be introduced out into our soiled world. That was difficult as effectively.
Once more, from manufacturing all the way in which to taking it to its ultimate vacation spot, it is simply very particular form of concerns and environmental considerations if you’re coping with issues that small. Additionally, issues do not all the time behave as anticipated on that small of a scale. In our bodily world, we anticipate issues to work a sure manner, however if you get all the way down to the micro and nanoscale, the bodily world turns into a bit bit totally different, and you may’t all the time anticipate the outcomes. That is a complete different subject of research.
What could be some examples of being totally different than the common bodily world?
Passing present via a wire. Now we have our chargers and our telephones and we’re passing present via it. Once you’re passing present via a wire that is sized like a strand of hair, there’s clearly warmth concerns and issues will simply begin behaving in another way as a result of, once more, the area and the scale constraints.
What’s your present function at Amii, and the way does your group assist {industry} companions?
My present function at Amii is vastly totally different from the world of micro and nanotechnology.
I am Product Proprietor of the Superior Expertise Crew at Amii. I lead a group of largely machine studying scientists and mission managers who’re all working with our totally different {industry} companions to unravel their enterprise issues via the appliance of machine studying.
We’re very industry-focused, all about bridging the hole between what’s taking place in academia, the entire actually nice breakthroughs with machine studying and AI however making use of them to our {industry} companions largest wants. We reply to these wants by primarily serving to our purchasers discover the talents and the experience that they want to have the ability to transfer the work ahead.
We run our internships and residencies program via the superior expertise group. So, I am hiring quite a bit. Recruitment just isn’t my background, but it surely’s one thing I do quite a bit now. And it is all about form of matchmaking, discovering the fitting ML expertise to put on our consumer’s mission. We rent these of us as Amii staff for a set time period and provides them a number of assist and mentorship, however actually, they’re devoted to work on the consumer’s mission and transfer that ahead. It is a manner for our purchasers to get entry to expertise with out having to do the recruitment themselves. Amii has some fairly good model recognition, we’re capable of carry actually nice expertise in after which place them on these {industry} tasks.
A possible good thing about the system is the consumer having the chance to rent these of us after the time period with us is finished. We wish this expertise to remain right here. We do not need mind drain. We’re giving the consumer a little bit of a leg up in order that they’ll strive the expertise out, check out the mission, get a really feel for what machine studying really is, what do we have to make it profitable, after which ideally putting the expertise inside these firms in a long term in order that these firms actually turn out to be AI firms and are capable of transfer their very own initiatives ahead sooner or later.
How lengthy is the time period that they join usually?
Typically, 4 to 12 months.
It’s one thing we work out initially, relying on the complexity of the mission and what number of issues we’re attempting to unravel. We discover the longer, the higher. Machine studying tasks to do in 4 months will be difficult. There’s much more to it than simply constructing ML fashions. Closely reliant on the info that is collected from the consumer that is handed over to us, that helps us construct the fashions. The longer we’ve, the higher it’s to iterate and cycle via the entire alternatives.
The work is experimental and exploratory in nature. Amii is a analysis institute; we will not all the time assure the result. An extended runway simply provides us extra time to do this analysis and guarantee that we have exhausted our choices and pursued as many issues as potential as a result of it is arduous for us to say, “That is the strategy that is going to work finest.” It’s a must to strive it and see.
What are some examples of difficult enterprise issues that your group has labored on with these firms?
I alluded to it, positively information preparedness is an enormous problem. Ongoing {industry} notion of information preparedness is totally different than what a machine studying scientist would assume is prepared for a machine studying mannequin. And entry. How simple is it for the consumer at hand over the info to us in a manner that’s consumable for our ML fashions. That is why we do like longer tasks as a result of it provides our group time to work with our purchasers via these kinds of information preparedness challenges and set them up for fulfillment.
Rubbish in is rubbish out, in case you hand us rubbish information, we’ll create a rubbish mannequin. We actually want high quality information. And there is a little little bit of a studying curve for purchasers. Business notion, once more, of what high quality information is, what are the examples that we have to see to have the ability to predict issues sooner or later. It is only a literacy factor, ensuring that we’re talking the identical language, they perceive the restrictions based mostly off of no matter information they’ve entry to once they perceive what is going on to set us up for fulfillment.
You want examples of what you are attempting to foretell in your dataset. If an occasion is admittedly uncommon, it is going to be arduous for us to ever anticipate it taking place. We may construct a extremely correct mannequin of one thing that simply say 99% of the time correct as a result of it is by no means predicting the 1% time that one thing does happen. Once more, simply ensuring that the consumer understands what we have to construct correct fashions.
We have seen even seemingly easy issues will be extremely advanced relying on their dataset. On the outset, having an preliminary discovery name with a consumer, we do should anticipate the size of time that we’ll want. However generally after we begin peeling again the layers of the onion, we notice, no, that is way more advanced than we thought due to these information complexities.
Different challenges, lack of dedication from material specialists wanted. After we companion with our {industry} companions, we actually want them to proceed to return to the desk as a result of they’re the area specialists and often the info specialists too. We’re not like a dev store the place we are able to simply take the info, construct the mannequin, and hand it over to them ultimately. It’s extremely, very collaborative. And the extra that our {industry} companions put in, the extra that they will get out as a result of they’re going to be capable of information us in the fitting route, guarantee that the predictions that we’re making make sense to them from a enterprise perspective, that we’re focusing on the fitting metrics, we perceive what success is for them.
We do want a multidisciplinary group round us to assist the tasks and it takes greater than only one machine studying scientist to construct a profitable mannequin that is going to affect a enterprise positively. There’s plenty of challenges. These are those that got here to thoughts.
You personally imagine that AI must be a power for good. What are some ways in which you assume AI can positively change the long run?
The factor I like most about my job is we work with purchasers from throughout all industries, fixing very totally different issues, however all of them are actually getting used for some form of optimistic change. And Amii has our principled AI framework that ensures that we’re doing simply that. From the contracting stage, we’re ensuring that the tasks that we’re engaged on with our {industry} companions are getting used for that optimistic change in an moral manner. All of the tasks I get to see are getting used for good and positively altering the long run.
One factor that involves thoughts, in Alberta most of the time now we’re coping with wildfire conditions in the summertime. This 12 months particularly, even in April, it was dangerous. We lately partnered with Canada Wildfire. It is a analysis group out of the College of Alberta. 40 years of climate information tied to extreme wildfire occasions. Working with them to raised predict these occasions sooner or later so we are able to higher put together the sources that may be wanted, have the groups go in and mood the environments earlier than it will get to a stage the place the wildfires are raging. I believe that is simply being in Edmonton, I do not know in case you had been right here final week, but it surely was very smoky.
After I arrived Sunday evening (Could 21, 2023) it was fairly smoky.
It is devastating. It ruins communities. It takes individuals’s houses away. Having to breathe particulate within the air is not nice, however the devastation could be very immense. That is one attention-grabbing (mission) that is near all of our hearts.
One other space we’re working in is the agriculture area. How are we going to feed our rising inhabitants? We’re working with the Nationwide Analysis Council on a protein abundance drawback. Attempting to ensure the crops that we’re rising have larger protein content material to feed our rising inhabitants and utilizing machine studying to have the ability to make these predictions.
Decreasing emissions is one other very talked-about one. Working with firms within the oil and fuel sector to guarantee that the processes and methods and instruments which can be used are as environment friendly as potential. We’re working with a water therapy plant out of Drayton Valley, which is a small city in Alberta, ensuring that that water therapy plant is working as effectively as potential and that we’re creating as a lot clear water for the group as potential. Precision medication as effectively.
The record goes on. Actually, each firm we work on its these kinds of tasks, these kinds of causes. It is arduous for me to choose a favourite as a result of when you consider it, all of them have the chance to have a extremely optimistic affect on the long run.
What’s your imaginative and prescient for the way forward for AI or robotics?
My publicity to robotics has actually been within the provide chain. It is the place robotics are already getting used, but it surely’s additionally how will we improve them with AI to construct on current methods and automation, once more, via extra environment friendly processes? The availability chain is clearly eager about growing throughput, fulfilling extra orders extra shortly, and extra environment friendly decision-making. On the robotics facet of issues, once more, my publicity has been constructing on high of current robots to make them smarter and higher.
I believe extra usually, the long run from what I see {industry} doing remains to be very human-centric. Robotics are used as a device, as an augmentation to people. Possibly robotics being deployed in circumstances which can be harmful to people the place we should not be uncovered to the environments. Robotics are a terrific substitute for us in that case to maintain us safer. There’s additionally actually cool analysis being executed by our fellows and bionic limbs, so simpler management and motion of people that do want that assist. All very a lot nonetheless tied to people and their use of those instruments however making it simpler for them to make use of and making their lives simpler via these new methods.
When it comes to the way forward for AI usually, that is simply such an attention-grabbing time to be on this area. Business is lastly getting it that AI is right here and it’ll change all the things and you may both lead or be led. I believe one in all Amii’s visions is to have each firm comfy with the expertise, conscious of what it might probably and can’t do, and actually keen to experiment and iterate on implementing it of their enterprise to unravel a few of their hardest issues.
Up till now, I believe perhaps there was a notion that it was simply tech firms that had been AI and ML customers, however now it is turning into extra obvious that ML will be deployed in primarily each group. It isn’t all the time the fitting reply, however there’s often a use case for it. I am hopeful that the long run is firms turning into pure AI firms themselves by getting extra literate and conversant in the expertise and conscious of how they’ll use it for his or her enterprise.
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