thank you for joining the Deloitte AI Institute Canada's webcast today for our discussion on the gravity challenge my name is Audrey audreyancian and I'm the AI Institute leader for Deloitte Canada while this event is a webcast I would like to begin by acknowledging the indigenous people's lands that we are on today Deloitte Canada has offices with representation across most of the country we acknowledge that our office reside on traditional treaty and unseated territories as part of the Turtle Island which is still home to many First Nations metis and Inuit peoples innovation in isolation can be difficult on the other hand creativity when supported by a collaborative environment which inspires ideas to be shared and challenged and refined they it can generate opportunities for novel approaches to be pursued in a research conducted by Gartner it showed that crowdsourcing ideas had been used by 25 of Fortune 500 companies in shifting towards a more outsiding approach to problem solving and Innovation many businesses and public sector organizations have used competitions hackathons and challenges like the gravity challenge to innovate and create value partnering with ecosystem Partners provides several advantages including greater access access across the world to knowledge and subject matter expertise decreased time to create a viable proof of concept and diversity of thought today as part of today's discussion we will hear and discuss how space capabilities and data can be used to solve high value business problems more specifically as part of gravity challenge fourth edition we will discuss how Innovation ecosystems uh composed of Corporations entrepreneurs universities can be brought together to design and build solutions that help solve real industry social and environmental problems before we kick off this session and before I introduce our esteem panelists to you I'd love to quick I would love to run a quick poll a poll focused on the application of satellite satellite imagery I'd love to hear from you what you believe are a concrete applications are of satellite imagery today we're going to take a few minutes for you to complete our slider poll and please do let us know what applications of satellite imagery do you believe are impacting our world today let's review some of your responses and we'll give you another minute already have one response around defense Wildlife Management exploring materials or minerals inside the soil unfortunately another uh reminder of the the war in Ukraine and the defense related applications of satellite imagery wildfires yes detection and my management of wildfires pollution floods infrastructure resource allocations indeed food yes I was hoping to see something Precision agriculture Precision farming absolutely we can we can use it uh from a crop yield perspective Arctic Ice movement um population density weather development fantastic great thanks for sharing um so today basically we are going to explore uh how satellite imagery can be used to inform um policy development in in our Public Service organization here in in Canada I have the pleasure today of being joined by a few panelists um starting with uh Nicholas Nicholas Martinez from a static statistics Canada Nicholas is a project manager with statscan he's based in Ottawa he's led a number of projects over the last five years in I.T system development economic model modeling survey development and the use of Earth observation also known as known as EO in official statistics Nicholas has a breadth of experience touching sectors in resource development energy and construction he is passionate about team building and collaborating with industry stakeholders and governments while delivering value and insights to to us Canadians through the continuous Improvement of statistical program Nicholas we are thrilled to have you today with us thanks for being here it's glad to be here thank you Audrey next we have Mr gaitano gaitano Volpe Guyton who is the founder and CEO of latitude of 40 a startup in the downstream Earth observation or EO sector he's also the founder and CFO of esperatros a luxembourg-based startup focused on a new satellite carrier for small sets with more than 20 years of experience in space and Telecommunications gaitano is a business coach with extensive experience in strategy development business design and business applied to coaching activities for companies startups and smes a guy to know has Consolidated experience in business development Technology Innovation r d and designing growth for guides I know space is not just a job it is a passion he has cultivated since he was a child and dreamed of becoming an astronaut guy to know we are thrilled to have you on our panel today yes good morning happy for me to be here and thank you for the invitation and and thank you gaitano for joining us from Napoli in in Italy at this time of the day really appreciate it um we are our third panel is this Ali Ali elawad he is a senior manager within our Omnia AI practice Ali has a strong passion for bringing Bridging the Gap between traditional Industries and AI practices Ali has expertise in designing and developing computer vision AI solutions that accelerate the Journey of aiu's utilization with successful accomplishments which include amplifying the status of the Deloitte acquired data performance um welcome Ali Welcome to our panel it's my pleasure to be here thank you fantastic great um so let me share with you um dear listeners what are questions what questions we're going to use for our panel this will give you a chance to think about additional questions you might want to submit through our q a or our chat function so the four questions that we're going to ask our panelists are in front of you right now and we're going to start with the first one we're going to start with a basic question what is the gravity Challenge and I would love to start by asking new Nicholas as the organization that brought together the business problem to this challenge I would love for you to discuss or and Define what the gravity challenge meant for you and meant for statistics Canada yeah so thanks Audrey and um it's a lot of pressure to be the first to speak so uh I'll try and be relatively brief but you know for me the gravity challenge was um it was a game changer and I don't think I can I can under sell that point uh for me and for my project um we we've been in development for a number of years and uh we had you know we knew what we knew um but we also didn't know what we didn't know and um through participation in the gravity challenge uh we were able to leverage uh some of the best and brightest Minds uh in the world and of course you know at latitude of 40. um and uh and Deloitte really helped put us all together so uh for me um this was uh it was it was a major opportunity and um as I said it was a game changer for my project and bringing a sport I don't want to spoil it too much because I know we have to talk in the other questions too so um I I like that you're pacing yourself Nicholas well done so um for these kind of challenges right we need an organization that brings a real industry business problem and that was stats Canada then we need people who are bringing their expertise uh that come in and and compete and um guy to know with latitude 40 you were one of those quote-unquote competitors um uh team member to this Innovation program so talk to us about how you define the gravity challenge how you approached it yeah yeah I might be to share my experience this was for us a very big opportunity opportunity for growth because we are a small startup with low opportunity to enter in contact with large organizations to enter in contact with the champion digital Champions and to deal with real Market problem for the startup the problem is always the market probably Market fee to the validation of the idea and using the this challenge the the challenge description provided by The Challenge owners uh statcon we um the downstream the Earth observation solution can be can really solve a real problem a real business problem and gave us the possibility to uh think a new solution a new application for our technology for our business and for the output of our RND activities thanks guys and uh last but not least Ali what's what's your take on on the challenge and what was deloitte's role in it yeah actually um that that's a very good question I think uh Deloitte it started as you know Deloitte getting interest in the in the space sector in general as one of those technologies that uh exponentially uh improve um you know I would say humanity and the world in general but the idea is uh gravity challenge came out of that need to develop a global initiative that Bridges the gap between government corporations and startups right uh and knowing that for a fact uh the new um wave of this space technology and space startups are changing drastically how uh the space sector is approached um and the aim here is to to speed up the adoption process of space technology across the board and also when I speak specifically about this round of gravity challenge which is gravity challenge four uh previously there was a couple of um gravity challenges for for the past five years and they've always been focused around um Earth observation it's been the theme around it but there's quite a lot of other application in the future perhaps in space exploration and the role for Deloitte has been uh continuously to to really bring those to the innovators and the challenges together and and trying to help them from business perspective uh from the market fit as well to come up with viable solutions to the problems that the challenges are having that are financially um viable that are Innovative and you know um show a higher return of Investments and also in its nature it's Global you can see here um Canadian Challengers that can benefiting from a European Italian uh innovator firm so that's where you can you can go out of the box and see who could provide you know the best solution out there partner with them and really catapult your your development effort thanks Ali let's move on to our second question um so Nicholas as the Challenger like Ali called you um how did you frame the business problem we we often say when we think about AI or machine learning the first crucial important step is framing the framing reframing iterating on your business problem how did you approach that um sure yeah so uh for me as I was kind of touching on earlier we'd been at the project for for some time and um we knew that the the technology using remote sensing for change detection uh for construction starts um was viable uh we were able to to make it work with a very high resolution uh satellite imagery that being said we also had come to the realization um that the the mechanism through which we were acquiring data as the government of Canada rendered our project you know technically feasible but economically uh unviable um and this is why I said you know it was a game changer when I when I presented my challenge to um the gravity challenge cycle four uh what I had done and I mean I'm coming at this as somebody who had no prior experience in uh EO or managing an EO project right so um my thinking was I had a data cost problem I wanted to more efficiently buy my data um I just assumed that the price was the price and I couldn't get around it so um I had framed my problem as one of uh needing to very quickly um develop a mode for smart tasking satellites so that I was only buying data for areas where construction activity was ongoing or we anticipated it to to begin um so this was the challenge I presented um and uh you know so uh let me just see here back to the question uh how to pop up here um so anyway so that's that's how I presented the problem and I was just really happy and excited when uh um Gaetano and latitudinal 40 and some of the other innovators as well they all presented solutions that um didn't respond exactly to the question that I asked um but they all understood by business need and I'm gonna say that you know as somebody who came from a non-eo background um I think that left me open to solutions that were being presented because as I sort of said at the beginning I I knew that I didn't know what I didn't know um and so if if there were um a lot of people saying well hey here's the solution that maybe you hadn't thought of um that might work for you you know are you willing to give that a try um I had to take it love it Nicholas and I I love that you're you're calling your own known incompetence uh that's a great one to um to to share in role model um so guys I know you received the challenge and so as the innovator how did you approach uh how did you approach the challenge yeah the for us the the challenge was a was an opportunity to give value to our platform we created the workflow an automatic workflow that simplified the complexity because Earth observation is a very established technology uh more than 30 years uh that this technology is on the market but never moved from Niche to mainstream because the technology is complex so the first topic of Latino Fortis to simplify this access to create and access very similar to Google Maps or other solution for us the satellite in our platform satellite image are like raw materials and we created a digital factor to transform these raw materials in product in the meantime we started to work in the period on super resolution so how to use free of charge images provided by European Space Agency with the San continuous acquisition so there is no all in the acquisition but the satellite acquired constantly uh around the around the the our globe and our idea is how to improve these images because a 10 meter of resolution there is not so uh image to information to use so we applied Ai and some deep learning activity to transform this image from 10 meter to one one meter so to compare this image with a commercial image acquired by planet or maxer so this is the the challenge bro of presented by statcon was for us the opportunity to verify if this technology can be applied in a real business case we tested in the previously the technology to detect uh Farm boundaries but this this application was really new the change detection the building detection so we try to to do this with a lateral approach so we say okay we imagine they told the company uh can offer a standard approach we have these value proposition this secret sauce and so we tried to apply the secret source to these uh to this Challenge and we we received the success so uh is a a challenge also for us to go uh uh beyond the state of the art this is the the challenge for my team for my AI team development team uh and we uh refined the the solution meeting by meeting in constant interaction this is another fantastic thing to think that is not possible in normal commercial uh activity with a customer because Nicolas dedicated a lot of time Nicholas and his team dedicated a lot of time uh to us we tested several aspects uh lean approach to the challenge and then we are at the end of the period of Cooperative period we reached a result so a fantastic experience uh motivation to do uh everyday better than the previous day and so this is evolution this is innovation this is open Innovation that connect company with startups fantastic thanks for sharing guy to know and I think um we're now sharing the pictures maybe you can comment on um the results of your approach and what it looks like yeah on the first image that you see on the on the right on the right part of the on the left part of the slide you see the original image acquired by the satellite this in my image is not so defined you cannot analyze details and with these images not possible to solve the problem uh that Nicolas put in the challenge in the second in my image and the right part of the slide you can see the results the elaboration after the approach of the AI and deep learning methodology you can see that these are completely different image is an image where the details are clear and you can do some you can apply change detection so you can see the change between one and major and other also because this level of Zoom is very high but if you go uh in low level Zoom the the first image is not understandable are very big squares on the other side you see the details and so also Nicolas and all other customers that we are working with are impressioned by by these results and the we are now working out to create a patent around these in Europe it's very complex to pattern soft but we are working on it and now we are applying this technology also another case for example we are helping another startup in ukrainia uh with this technology we are identifying applying that algorithm that can identify the damage of buildings we are counting how many buildings are destroyed by the war to create a map that can be used for the Reconstruction so the use of the technology is very very huge and we are very proud that we are here and we can present our solution sounds good thanks Katana for sharing your work in it visually but also sharing with us a practical uh unfortunately very real application of your work uh for a good cause in in Ukraine Ali as someone who is completely passionate about computer vision um you observing the the competition at play uh what were your takeaways as a as a Deloitte professional uh I was actually blown away with the possibilities of what you can use um super resolution for and this this techniques I mean I read quite a lot about the in papers you know what they could be used for I've seen a lot of um let's call it artistic application of super super resolution but to see it in action and the possibility what you can do with it and directly tying it to the the uh Financial aspect to it of what it could save in terms of cost and allow a a huge Suite of application um it's uh it's stunning um previously I have used this technology before it was an incremental value in terms of model Improvement so I remember it was I think a model performing at a knife 94 detection rate I think we we brought it up to 97 3 Emir three percent Improvement but here what you're looking at is it's a light and day difference right you can it goes from not being able to detect a feature to to all the way to detect a feature a change and in some cases counting right and and that that's the type of um transformative AI technologies that that we we're hoping to to work with in the coming years thanks for that Ali let's come back to you Nicholas and uh go into third gear think about the impact of the challenge so in terms of the tangible outputs coming out of the challenge what was the impact for you and for stats can can you comment on that absolutely so and you know I'm gonna I'm gonna take a this back a little bit just because um I don't think I really introduced my my use case very well at the beginning so um for those who don't know me who don't know my project the geospatial construction starts project uh is is looking to detect the beginning part of construction for all residential and non-residential projects uh in Canada um this this project came out of my redesign of our investment in building construction model um this uh this program the IBC program um estimates uh the value of construction put in place for Canada which represents approximately 7.6 of the Canadian economy so construction is not uh an insignificant part of GDP um and we had as one of our key inputs into that program uh the starts completion survey it's it's conducted by Canada mortgage housing Corporation um now they they do this the old-fashioned way boots on the ground you know they go out and validate based on you know issued building permits and this kind of thing um new projects that are starting um unfortunately because it's it's being done the old-fashioned way coverage is is limited they can't get everywhere uh every time and sometimes by the time they do arrive at a construction project maybe it started a while ago um but they they give us their best estimate on when it started um of course Canada mortgage housing Corporation isn't only interested really in the residential side and whereas for myself and the statistics Canada side I'm also trying to estimate for the non-non-residential sector um or fast forwarding a little bit here so when we initiated this project we were looking at um you know Blue Sky Thinking what could we do uh to improve our data inputs to produce better outputs this is the IBC data gets used by our national accounts and downstream by the Bank of Canada finance Canada um you know provincial uh Finance departments and of course um they're using all of this to to help set interest rates something that affects all of us and of course we're more acutely aware of this right now in Canada as inflation has been going up and the Bank of Canada um you know just yesterday raising interest rates again another 50 basis points um so this data matters it matters uh in our in our day-to-day lives and um it's more than just tracking what's going on uh you know this construction project or that construction project um it's the big picture so um the outputs for the GCS uh geospatial construction starts project uh and you know the the outputs by latitude of 40 um enabling uh the geospatial construction starts project it would have a huge value to our our business operations and being able to produce better data for policy making workers in a timely fashion because you know through kovid that was another another key thing that kind of came out um was uh we received a lot of pressure from policy makers to provide Now cast data what's happening with the economy now they really needed to know so they could put the appropriate measures in place to support the economy and to support Canadians so um you know all of that really comes together to to define the value of what this potentially could bring uh to us and um you know there are also a lot of potential snowball impacts of this so uh you know I talked a little bit earlier about the data cost and uh how this was an impediment to us well the The Snowball Effect of these kinds of challenges is um and and the solution that was brought by lab 240 like I said it was a game changer in that it it will enable us to move forward um with a pilot project and hopefully develop this into a program that we can apply at a national scale um and and and and and that will you know have all other kinds of knock-on effects because in addition to um providing data for our program uh you know the data could also be used for other things and I think I've I've touched on a couple of these uh not here but elsewhere um you know there are a lot of use cases that that could help us Monitor and and uh report on land available for development for example so one of the key components that we're looking at using is uh parcel data um that that's uh and monitoring those parcels and you know when we're looking at the housing Supply uh issue uh and and the different policies that are being implemented around housing Supply and land Supply you know Green belts in Toronto um this kind of thing if we're looking at it from a big picture perspective we can say okay well do we have enough land already allocated is it that Builders just aren't building or is it that we need different types of zoning in certain areas and um you know that kind of information which isn't presently produced at a national level you know could really help people get a get a handle on the issues um and and produce better policies that that could impact you know housing affordability housing Supply um and that kind of thing thanks Nicholas for uh situating the problem in its context quantifying the importance but also uh sharing some concrete applications of of the challenge um guys I know I believe that through this competition you were able to solve a certain Cloud problem which will help or coverage problem I should say which should help with further um uh use cases in the future can you talk to us about the The Snowball Effect of these kinds of challenges yeah we have several Snowball Effect the first one is uh that we sold the chicken and egg problem to start up the traction so with the confirmation that of the value of our Solution by a big organization it's clear that we can demonstrate that there is attraction for our idea so we can continue to investment we can commit resources on this project and in the in the interaction with the static we we identified another problem that Canada has a very huge cloud coverage and so the optical image cannot pass through the the code the the cloud so we need to solve another problem we solved the first problem now we have another problem and so for this my team started to work on another project that is a derivation of this uh that is how to have an optical image uh use that can be super resoluted and so we had an idea to use the SAR so the rather image because the radar is a an active sensor that can pass through them through the cloud but the image is not so under understandable and so we are applying now new up the new algorithm that's transform as a different uh as a chain of processing so the first aspect is is to transform a sar rather image in an optical image with the time meter resolution and then after this we apply the super resolution in this in this way we have the possibility to to solve also the problem of the of the of the cloud the cloud cover um so this is the idea how the challenge is the spark for us is the spark for new idea and also with this traction with this demonstration that the technology can solve a problem we acquired another customer in Italy with the same problem of how to transform the field survey how to accelerate the field survey this is a Motorway they need to the model has is as around 7 000 Lots along this Motorway and they need to decide where to put solar panels and so we we use the same technology to analyze these 7000 Lots uh reducing the time from seven days to two weeks for the analysis of the entire network and we identify if in this lot there is a small object a small construction that could be a problem for the installation of the new panels so just to to conclude that this is a typical application now the downstream section is Downstream sector is fundamental for the space industry because a lot of investors are putting money in the Upstream in creating new constellation new new satellite new tech new payload we use the uh very well established because uh Sentinel 2 was launched in 2014 so it's a very old-fashioned satellite but with the technology with dii with the everyday work and with the transmission chain that transformed the image inside useful in a business process we bring the technology to the customer this is the big problem now in the space industry how to take the image and distribute it to a very fragmented market and so the during the challenge we had the opportunity to found the new ideas and to improve this with a real interaction with the real customer so we are very happy of this this is a fantastic experience for us in this period for sure thanks thanks for sharing gaitano ali um up front the audience share with us lots of application of satellite imagery obviously we've been talking policy development right here uh in the context of Urban Development or or reconstruction um like gaitano was speaking uh what what's what's your take on the snowball effects of you know the democratization of basically satellite imagery how do you see this uh playing out uh for some of the people that are in in the audience right now that are you know part of public administrations or or Enterprises how how should this potentially affect us in the future potentially affect them in the future that is definitely a very good question I would say that there's maybe three folds that this could be making a big difference uh we can start also with the First with the Innovation angle of this right um traditionally you would have to do quite a lot of investment try to understand how you could you could play in the space sector or how it could benefit your organization but with things like you know the gravity challenge um it's it's creating in a easy way to get into this area and try to explore what what could be done for the organization so all the Innovation angle of it uh trying to discover um oh I have a problem I am not so sure if space is a good fit with something like the gravity challenge you can put a you can put a a challenge and see if someone could solve it with with the with the Earth observation uh or or satellite data and that's where that that gap between you know commitment to such a such a large um pursuit of trying to use uh uh space technology I mean in in any of its shapes or forms to actually concretely being able to have a use case you know developed within few months and that's where the biggest benefit too the second point is this type of challenge for example as you see the the super resolution concept is democratizing access to the data right because that was the second bucket of challenge when it comes to using space Technologies it was traditionally expensive and that barrier is becoming Democrat that that barrier is breaking right now and it's becoming much more democratized uh there's a suite um of satellites right now that are being put into orbit that have a lower cost of of imagery they're cheaper there's also AI technology like what latitude of 40 with guitar are doing they're democratizing the cost of the data and the the last piece here right um there is more and more applications beyond the standard for example the defense application or the standard pure research uh use of Earth observation data and that is uh making organization realize that well this technology is not for the original intended use only uh those uh satellites right now are using uh the latest kind of off-the-shelf type of electronics to to provide even higher quality imagery um that now we're enabling a new suite of applications uh monitoring emissions um as well as understanding the temperature of different buildings on the ground in a large scale all that is becoming possible because this new type of data and Technologies are going beyond the traditional use of Earth observation so by understanding that uh organization could slowly um uh kind of lean into some of those Earth observation applications uh and and dapple into it through through something like the gravity challenge thanks Sally um let's move to our fourth and last question for the panel this is an opportunity for me to remind our audience to kindly share your questions for our panelists in the chat or the Q a section so my last question for you is what advice can you share with others that are considering um an AI or ml open competition or hackathon or challenge or what are what are your advice for people who basically want to innovate and are looking for assistance or looking for that outside in approach and support from ecosystem Partners let's start with you Nicholas what's your advice for others given what you've gone through on this gravity challenge uh thanks Ed Audrey um so my my advice to anyone who's who's considering coming forward and putting a challenge uh in cycle five or cycle six um wherever you guys on your own uh development missions uh is is absolutely do it uh there's there's nothing to lose uh and everything to gain um you know my project was almost dead in the water uh a year ago like back in February this this spring um and because of our work together with latitudo we were able to prove the the financial viability of the project and you know Audrey I think we talked about this earlier um but it's it's a 98 reduction in data costs compared to what we were looking at before which is huge um and with that reduction in cost we were able to breathe viability back into this uh and really now it's it's a it's a nuts and bolts problem in terms of just putting things together um and being able to to build a new program um that will benefit policymakers and Canadians ultimately so um you know there's there's sometimes fear uh about getting off the fence and engaging um and working with you know uh the innovators through the gravity challenge is free so if you're a project manager like me on a budget um that was also a great experience because you're able to leverage the talent and the sweat of of the brightest Minds in the world um you know risk-free and and Deloitte is walking you through the process the whole way keeping you on task making the job easy um as a PM you know uh it was really helpful having um Ali and the Deloitte team uh walking me through this and uh you know sometimes organizations are afraid to get involved because they're worried about Market capture getting into a new fiscal Arrangement or with a new uh new seller of data or Services um but if you're worried about the potential future costs of having a wildly successful program or Innovative solution well you forgot the first part which is you've got a wildly successful and Innovative solution um so it's probably worth you know entering into that commercial Arrangement after the fact so um I think you know as long as you're open to those experiences and uh you know you can you can explore the possible in a I would absolutely recommend um getting involved thanks for sharing that Nicholas um guys I know your take and your encouragement I guess for innovators out there um startups entrepreneurs uh folks who are you know considering um putting out their their capabilities out there and joining such a competition or challenge what's your advice yeah Audrey thank you for this opportunity to share my vision with other startuper or other innovators this is a big opportunity now um the the the gravity is totally concentrated on the space Technologies probably are the only Global competition that focus on application of innovation in the space technology the technology is evolving extremely fast in the moment where are we Italian Canada are two space country because uh we have a constellation of satellite Canada launched the radar sat in 1995 so is another era at the moment now Italy invested just with the new plan to create a new constellation 1.2 billion
to create a new space ecosystem in Italy but it's complex it's complex to enter in this market to to gain traction to identify the user personas the typical aspect that you study on the book so the user Persona the UK cases to validate your your idea and so the gravity challenge is a competit the World Cup of the space competition probably I can Define is a competition where you have your competitor uh the top of the Innovation at worldwide level because the competition is open to company all over the world so you go in a very extensive competition is not a sales activity so it's an investment also for the company so the investment is on both part the company and the innovator and the the large company but it's a challenge not only for the company as organization it's a challenge for the team is an opportunity for the team to try to have this lateral approach this thing out of the build thing out of the box and to elevate the limit typically in the everyday everyday job you have the limit you you don't have these long-term Vision uh the the to reach this objective over over the the state of the art that we can see and so you can work to create new use cases you can work to improve the experience because also in the interaction with the Deloitte we had the opportunity uh to to interact with the methodology that Deloitte has with statcom so is also an improvement personal Improvement of the team on the approach to the work because it's very difficult for a startup to have a weekly meeting with a large organization large Consultants consultant consultancy firm like the Lord where you need to pay a lot of money if you need to have a consult a con a cons a coach by Deloitte in your company so we had the opportunity to be coached by by Ali by other team other people in the in the Delight so this is another Advantage it's clear we invested the start can and every corporate invest time but the final is a win-win approach because if the the challenge as a success we have the we as a startup as innovator have the opportunity to enter in a new market and the the challenge owner has the opportunity to obtain a project give to to have a benefit a business benefit and to reduce the cost of scouting because probably uh Nicolas or any other company can find us browsing on the internet but probably how many time you need to spend to to search any innovator uh with this challenge you received probably different proposal and he choosed the best one the best that fit uh uh is is need so I invite every startup every innovator every team to try to to do this this job to this also if they will not be selective is not a failure is an experience it's an experience that give you the the chance next time to improve your proposal and to have a better result thanks for that guy to know um Ali I believe you have a certain perspective from a from a talent view right people who may want to test their capabilities or push their capabilities pick up a new skill um what's your call to action uh my my call to action is uh challenges like those are the fastest way to to reskill uh to learn a new uh set of tools and uh the the idea of a time frame the competition makes it more fun uh gamified in a way but um very tangible outcome and at the end of it you would be very content with the the development your personal development as well technical development that you will gain from such process and if you look across the the the the landscape competition right those competitions are really inspiring you can see in the space sector you have you know what Deloitte is doing here with the gravity challenge you have X price you know it's a standard Global challenge NASA challenges are a great way to um get Global competition learned from others learn how they do things um and and basically in a way increases collaboration in a way we've never seen before uh actually my I'll share a personal maybe a story here my interest in the space sector came from a challenge I was part of a challenge during school time and the in the aim of the challenge was how could we increase the uh the space talent pool in Canada at the time there was there was a shortage of of um uh individuals with space hardware and software knowledge so one of the the leaders in the in this sector kind of went around gathered some some funds from different companies and created a challenge for for people to build satellites and you know the winner get to have a launch to space um and and that just basically rallied hundreds of of students around this this calls and and build satellites across Canada and at the end of it fast forward five years you have more than a thousand graduate of these programs uh with skill in the space sector and all that done with the energy you could expect from from students learned a lot about the field became at least started to intermediate level in the field and he you can find that way of of Skilling people uh and having their the a drive and passion for what they're doing without something like a challenge love it thanks for sharing your personal story Ali and um and I think all of you um uh thank you for sharing your perspective on how you learned something right you you developed some skills through the process and uh enjoyed being exposed to a diversity of thought uh and expertise right uh each with your respective expertise uh really enjoy that um let me ask you uh Nicholas uh a question around um uh what other space applications would you like to pursue absolutely yeah and I think this is a this is a great question to ask uh it's timely for me I'm I'm a member of the government of Canada's Downstream working group I'm not sure if we've got other members here um in the audience perhaps um but one of the things that we're we're looking at is expanding uh the development of use cases in the I'm going to call it the gray economy so you know a lot of EO focuses on the blue side of things the maritime monitoring oceans um that kind of thing and then there's there's the green uh EO which covers you know land-based monitoring of uh forests and Agriculture and um biomass and other kinds of stuff like that um so the the gray um is is looking at infrastructure um and the human built environment and I'd like to continue to expand in this in this area um I'm hoping to build a a list of use cases that we can add and build off of um you know the data from latitudo uh I touched on one which is in addition to the geospatial construction starts project the monitoring of of parcels and the development of those Parcels so the growth in in the stock of those Parcels um so that we know that we have a good supply of land for people to build on um which is very important of course um uh another one that uh I've discussed with some other colleagues is improving our disaster management dashboard so there's there's a program in in Canada whereby the federal government and provinces you know together under right um disaster management uh sort of insurance for Canadians um and one of the things that kind of came up is well you know it would be great if we could um if there was an impact on a specific area we could draw a boundary file or like draw a boundary around the the impacted area and and produce a dashboard of all the information um sort of that it's that is affects the people who are there so either you know property values um languages of people who are spoken in the area that we might get from like State census um of course uh sensitized and anonymized so that uh there's there's no risk to uh to privacy issues there but um you know getting this information in the hands of those disaster management response uh responders uh so that they can better serve people who were there um and so governments can better plan uh for the liability um of those uh uh events so that's that's one um and I think you know there's there's other stuff to be done around the construction sector um you know maybe mapping uh traffic patterns you know maybe looking at Road Network development as an indicator of of future growth um because there are all kinds of ideas I could think of uh but of course if you have other ideas too if you remember the audience feel free to reach out to me you know either on LinkedIn um I'm not sure if Deloitte has all my information if they're going to share it but to feel free to touch base and um I'd love to hear the ideas because uh at some point we've got a we've got to build uh the world that we want to see and and these are the kinds of things that bring value to Canadians and I'm passionate about that so love that Nicholas and that you're uh you're so open to uh to ideas from our audience and others um let's let's go to you guys I know I'm wondering if you could um share with us your views on where satellite imagery is going and what we might expect you know five years from now yeah yeah fantastic question because as a you presented me I am like do you know sour of the space because I started uh more than 25 years ago and started like in the the last 20 years the satellite never changed it's a stupid object that is flying around our globe uh transmitting information so that in the last five years we entered in this space 2.0 and probably we evolved to Space 3 and 4.0 and first of all we will we will now have a huge number of satellite in space so we moved from large satellites to cubesat so now the satellite the cubesat is like uh 12 15 centimeter an object of 15 centimeter with a camera so more satellite this means that we can have more revisiting time so now for example with sentineland we haven't made two image per week now with planet we have one image per day but with new constellation of subtle logic that is a South American company we can have an image every 20 minutes in the next couple of years so probably in the future we can move from image to video also because the technology of the communication technology between satellite and ground is evolving now there are a lot of experimentation of laser communication that this means that is possible to transfer terabyte of data from space to the ground and this opened the logic for the the video in the from the space something that we saw in Minority Report or James Bond film where I can ask to follow the a criminal using the satellite probably in the not in the next probably the next five years will be a reality it's clear that Assad is there is also changing the technology uh just a couple of years a couple of days days ago uh Amazon AWS uh share the news that one of the uh AIML algorithm is not executed in the data center of the AWS bottom Board of a satellite the satellite of an Italian company that is the orbit this company is creating the space Cloud so the concept to move the elaboration from the ground to the space this means that more real-time in information the old elaboration the intelligence is on board of the satellite the satellite is not will not be more a stupid object but a smart object that can identify objects in the in the image share only the notification so the the market is evolving very very fast uh the new technology is just around the corner is the high perspectral so this means that each image is not eight band of Lights like now but is now there are tests from 120 to 160 different band of Lights this means that it's possible to identify this spectral signature of materials I can detect if there is a concrete or wood or any other asbestos for example from the space so the the market is evolving extremely fast a lot of investment in the in the market and so at the moment is very difficult to to give a precise answer to your question uh probably it's possible to see what will happen the next see in the next six months but it's very difficult to move to five years also because now we have the exploration of the Moon uh our time is with our time is we and Italy is a big part of Artemis one we will come back to the moon but the next step is the the exploration of other planets too because the mining one of the future deep space exploration is how to find uh valuable resource and this you can have from the satellite that can identify where there is gold platinum or other materials on asteroids or any other planets so this is a very evolving Market uh and we need to to monitor everyday this aspects to to have the the chance to take the the hype of this Market fantastic uh Nicholas Guy to know Ali thank you so much for joining me today uh to make you know space capabilities and data a bit more real for for folks on on on this uh this AI Institute webcast I really also appreciate it how you you helped us demystify whether a data or an ml competition or hackathon looks like I'd love to hear from you our audience um on how we did today how this was conducive to your learning I'll give you a minute to complete our polling questions foreign Deloitte for the uh Integrity of the survey uh I tried to vote 10 for myself on the quality of my panel discussion but but I couldn't so well done I like that you tried Nicholas that's great love it um as if I can ask you to move to our our next slide I wanted to just briefly say a few words about our next webcast in January we will look at Ai and life sciences and Healthcare so do register do tune in if you're interested in that topic or in any of the topic that we have lined up for 2023 if today we piqued your interest with computer vision do join us in February more to come on on the topic absolutely so once again um guides I know Nicholas Ali thank you so much for for being with us today and to our loyal audience thank you for your pieces of feedback we appreciate it um grazimile have a great afternoon thanks everybody merci beaucoup thank you thank you bye-bye thank you thank you Audrey thank you
2023-01-24