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 house, the place she helped purchasers take their merchandise to market, with a give attention to micro and nano-fabrication.
As Product Proprietor of Superior Know-how at Amii, Mara leads a technical crew that helps {industry} companions construct machine studying capability inside their group by offering steerage and experience to develop predictive fashions. Her crew 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 considered one of Canada’s preeminent facilities for AI, they companion with firms of all sizes, throughout industries, to drive innovation technique and supply sensible steerage 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 appreciated constructing issues. My mother would convey house a fan when it was sizzling in summer season, and I might wish to construct it. I keep in mind rising up as a teen, I had a cellphone, a type of Nokia’s that you would take aside and I might take it aside and put bejewels throughout it on the within and the antenna. However once I opened it up, it was like, “Holy crap, what’s in right here? What is going on on?” It was actually fascinating to me.
I at all times excelled in math. So, placing all of these collectively, my dad and mom additionally pushed me within the engineering route as a result of I used to be good at math, I had only a basic curiosity in electronics and wished to know extra about it, that is form of what drew me in to start with.
Additionally, in engineering, I simply actually appreciated 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 resolve exhausting issues. It appeared form of the right mesh of issues that might result in an fascinating profession.
Your dad and mom sounded very proactive in supporting your pursuits.
Yeah. My dad particularly. He says he noticed it in me from a younger age and simply at all times pushed me in that route. I used to be at a Girls in AI occasion final night time too and we talked about eradicating some obstacles and making it a extra approachable area for girls. And I did not actually see that as a barrier as a result of, once more, my dad and mom had been like, “That is what you must do. It isn’t a query of your gender or something. It is simply this can be a talent you’ve. You must naturally form of observe 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 house to give attention to micro and nanofabrication. May you outline these phrases?
Undoubtedly. So, in electrical engineering, I took the nanoengineering choice. It was the specialty round designing and manufacturing on the micro and nanoscale. Once we speak about a nanometer, we’re speaking a couple of millimeter divided in one million is a nanometer. A really, very small scale. And that is cool. These items 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 dwell in a really related world. There’s electronics throughout us and we want to have the ability to design electronics for the packaging and house constraints. We’re continuously attempting to make issues smaller and smaller. You’re taking one thing cumbersome, a prototype, and also you want to have the ability to make it reproducible and scalable. Nanofabrication is actually concerning the instruments and the strategies that you just use to design and manufacture on that form of stage.
That is from manufacturing microchips to taking these two completely different chips and connecting them electrically to the ultimate packaging. Doing all of that on the microscale requires a distinct approach 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 it’s essential to make sure that these are hermetically sealed and shielded from their setting.
Outdoors of microchips, what could be one other utility or use case?
We labored on a variety of tasks like fiber optics. Once more, all of it finally should come to some kind 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 typically some kind of microchip within the center. However there’s additionally the sensors which might 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 system that we want.
What are among the challenges behind engaged on any such nanoscale?
One piece of mud can smash your complete day. Belongings you’re engaged on are the identical measurement because the mud within the air. So, you fabricate in a clear room. The clear room is actually an setting 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 continuously 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 kind 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 this stuff are going for use in our very soiled world. That is when the packaging turns into vital. We nonetheless want to have the ability to entry these units, however we have to do it in such a method that we’re not contaminating the setting, 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 might have one thing that works nice on a lab bench in a managed setting, however typically a lot of the issues that we’re constructing are supposed to be introduced out into our soiled world. That was difficult as properly.
Once more, from manufacturing all the way in which to taking it to its closing vacation spot, it is simply very particular form of concerns and environmental issues once you’re coping with issues that small. Additionally, issues do not at all times behave as anticipated on that small of a scale. In our bodily world, we anticipate issues to work a sure method, however once you get right down to the micro and nanoscale, the bodily world turns into a bit bit completely different, and you’ll’t at all times anticipate the outcomes. That is an entire different area of research.
What could be some examples of being completely different than the common bodily world?
Passing present by a wire. We have now our chargers and our telephones and we’re passing present by it. Whenever you’re passing present by 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 house and the scale constraints.
What’s your present position at Amii, and the way does your crew assist {industry} companions?
My present position at Amii is vastly completely different from the world of micro and nanotechnology.
I am Product Proprietor of the Superior Know-how Crew at Amii. I lead a crew of largely machine studying scientists and challenge managers who’re all working with our completely different {industry} companions to resolve their enterprise issues by 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 basically 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 by the superior know-how crew. So, I am hiring loads. Recruitment will not be my background, nevertheless it’s one thing I do loads now. And it is all about form of matchmaking, discovering the precise ML expertise to position on our consumer’s challenge. We rent these of us as Amii staff for a set time period and provides them a variety of help and mentorship, however actually, they’re devoted to work on the consumer’s challenge and transfer that ahead. It is a method 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 convey actually nice expertise in after which place them on these {industry} tasks.
A possible advantage of the system is the consumer having the chance to rent these of us after the time period with us is completed. 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 will strive the expertise out, check out the challenge, get a really feel for what machine studying truly is, what do we have to make it profitable, after which ideally putting the expertise inside these firms in a long run in order that these firms actually turn into 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 determine initially, relying on the complexity of the challenge and what number of issues we’re attempting to resolve. We discover the longer, the higher. Machine studying tasks to do in 4 months might 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 have now, the higher it’s to iterate and cycle by the entire alternatives.
The work is experimental and exploratory in nature. Amii is a analysis institute; we will not at all times assure the end result. An extended runway simply provides us extra time to try this analysis and guarantee that we have exhausted our choices and pursued as many issues as potential as a result of it is exhausting for us to say, “That is the tactic 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 crew has labored on with these firms?
I alluded to it, undoubtedly knowledge preparedness is an enormous problem. Ongoing {industry} notion of knowledge preparedness is completely different than what a machine studying scientist would suppose 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 method that’s consumable for our ML fashions. That is why we do like longer tasks as a result of it provides our crew time to work with our purchasers by these types of knowledge preparedness challenges and set them up for fulfillment.
Rubbish in is rubbish out, in case you hand us rubbish knowledge, we’ll create a rubbish mannequin. We actually want high quality knowledge. And there is a little little bit of a studying curve for purchasers. Trade notion, once more, of what high quality knowledge 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 primarily based off of no matter knowledge 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 actually uncommon, it’ll be exhausting 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 might be extremely advanced relying on their dataset. On the outset, having an preliminary discovery name with a consumer, we do must anticipate the size of time that we are going to want. However typically after we begin peeling again the layers of the onion, we understand, no, that is way more advanced than we thought due to these knowledge complexities.
Different challenges, lack of dedication from subject material specialists wanted. Once 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 normally 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 in the long run. It’s totally, very collaborative. And the extra that our {industry} companions put in, the extra that they’re going to get out as a result of they will be capable to information us in the precise route, guarantee that the predictions that we’re making make sense to them from a enterprise perspective, that we’re concentrating on the precise metrics, we perceive what success is for them.
We do want a multidisciplinary crew round us to help 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 numerous challenges. These are those that got here to thoughts.
You personally consider that AI must be a drive for good. What are some ways in which you suppose 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 completely different issues, however all of them are actually getting used for some kind of constructive 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 constructive change in an moral method. 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 yr particularly, even in April, it was unhealthy. We just lately partnered with Canada Wildfire. It is a analysis group out of the College of Alberta. 40 years of climate knowledge tied to extreme wildfire occasions. Working with them to higher predict these occasions sooner or later so we are able to higher put together the sources that is likely to 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, nevertheless it was very smoky.
Once I arrived Sunday night time (Might 21, 2023) it was fairly smoky.
It is devastating. It ruins communities. It takes folks’s houses away. Having to breathe particulate within the air is not nice, however the devastation may be very immense. That is one fascinating (challenge) that is near all of our hearts.
One other space we’re working in is the agriculture house. How are we going to feed our rising inhabitants? We’re working with the Nationwide Analysis Council on a protein abundance downside. Making an attempt to verify the crops that we’re rising have greater protein content material to feed our rising inhabitants and utilizing machine studying to have the ability to make these predictions.
Lowering emissions is one other very talked-about one. Working with firms within the oil and fuel sector to guarantee that the processes and techniques and instruments which might be used are as environment friendly as potential. We’re working with a water remedy plant out of Drayton Valley, which is a small city in Alberta, ensuring that that water remedy plant is working as effectively as potential and that we’re creating as a lot clear water for the neighborhood as potential. Precision drugs as properly.
The checklist goes on. Actually, each firm we work on its these types of tasks, these types of causes. It is exhausting for me to select a favourite as a result of when you concentrate on it, all of them have the likelihood to have a extremely constructive 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, nevertheless it’s additionally how will we improve them with AI to construct on present techniques and automation, once more, by extra environment friendly processes? The availability chain is clearly thinking about growing throughput, fulfilling extra orders extra rapidly, and extra environment friendly decision-making. On the robotics facet of issues, once more, my publicity has been constructing on prime of present robots to make them smarter and higher.
I believe extra typically, the long run from what I see {industry} doing continues to be very human-centric. Robotics are used as a software, as an augmentation to people. Perhaps robotics being deployed in circumstances which might be harmful to people the place we should not be uncovered to the environments. Robotics are a terrific alternative for us in that case to maintain us safer. There’s additionally actually cool analysis being completed by our fellows and bionic limbs, so simpler management and motion of people that do want that help. 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 by these new techniques.
When it comes to the way forward for AI normally, that is simply such an fascinating time to be on this house. Trade is lastly getting it that AI is right here and it’s going to change all the pieces and you’ll both lead or be led. I believe considered one of Amii’s visions is to have each firm snug with the know-how, conscious of what it will probably and can’t do, and actually keen to experiment and iterate on implementing it of their enterprise to resolve a few of their hardest issues.
Up till now, I believe possibly there was a notion that it was simply tech firms that had been AI and ML customers, however now it is changing into extra obvious that ML might be deployed in basically each group. It isn’t at all times the precise reply, however there’s normally a use case for it. I am hopeful that the long run is firms changing into pure AI firms themselves by getting extra literate and acquainted with the know-how and conscious of how they will use it for his or her enterprise.
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