Speaker 1: Get in touch with technology with tech Stuff from how
Speaker 1: stuff works dot com. Hey there, everyone, and welcome to
Speaker 1: tech Stuff. I'm your host, Jonathan Strickland. I'm an executive
Speaker 1: producer with How Stuff Works, and I heart radio and
Speaker 1: I love all things tech. And I'm still in San
Speaker 1: Francisco at the two thousand nineteen IBM THINK Conference. IBM
Speaker 1: was kind enough to invite me out here to dive
Speaker 1: into their world and see what sort of technologies, products
Speaker 1: and services the company has on offer to help push
Speaker 1: the stuff that makes your stuff work into the future.
Speaker 1: And so this is my perspective on the things that
Speaker 1: I encountered here at the conference, and there were a
Speaker 1: lot of really interesting elements here. And in a previous episode,
Speaker 1: I talked about the struggle between taking an open source
Speaker 1: approach and a proprietary approach in developing technology. So in
Speaker 1: this episode, I'm really going to focus more on some
Speaker 1: of these sessions and stories about open source and the
Speaker 1: benefits of going with that approach that I saw here
Speaker 1: at IBM THINK two thousand nineteen, and some of these
Speaker 1: stories are really impactful, I think. Now a quick refresher,
Speaker 1: the open source approach is one in which the development
Speaker 1: process for a technology is open for a community to
Speaker 1: work on. Often, it also allows for people in the
Speaker 1: general public, or at least the developers and engineers out there,
Speaker 1: to actively tweak, adapt, modify, or upgrade that technology in
Speaker 1: their own way. One of the results of this approach
Speaker 1: is that you have this enormous community that can help
Speaker 1: make the technology better. In software and means that developers
Speaker 1: can identify and patch vulnerabilities, they can extend features, they
Speaker 1: can improve the way software works by applying their own
Speaker 1: ideas and expertise to the overall project. It's kind of
Speaker 1: like having a development team made up of millions of people. Now,
Speaker 1: in theory, the good ideas stick around, the okay I
Speaker 1: ideas can be massaged and tweaked to become good ideas,
Speaker 1: and the bad ideas end up being abandoned. It all
Speaker 1: happens really quickly, with potential iterations arriving much faster than
Speaker 1: you would see with a proprietary closed approach. With the
Speaker 1: proprietary approach, any changes to code rely upon a dedicated
Speaker 1: and thus, by its very nature, a limited team of developers. Now,
Speaker 1: on the positive side, with proprietary you can work to
Speaker 1: create the experience you want people to have when they
Speaker 1: use your software. You can have a very defined vision,
Speaker 1: but on the flip side, the path of development is
Speaker 1: completely dependent upon one group or one company's vision, and
Speaker 1: there may not be room to incorporate valid ideas that
Speaker 1: originate from outside that entity. One of the other big
Speaker 1: differentiators between open source and proprietary approaches has to do
Speaker 1: with adaptability. Sometimes markets change in ways that companies didn't anticipate,
Speaker 1: and if you're running a really big company that has
Speaker 1: tech processes that depend upon proprietary software and then the
Speaker 1: market changes, you're stuck waiting on your provider to recognize
Speaker 1: that change to the market and then to respond to it,
Speaker 1: and you can't really do much in the meantime, and
Speaker 1: if things are getting worse, you're kind of stuck. The
Speaker 1: open source community can continuously work on software, changing it
Speaker 1: as the market itself changes, in fact, anticipating changes and
Speaker 1: building in new features to help mitigate any negative effects
Speaker 1: of that change. So in an ideal case, you get
Speaker 1: changes in the market and changes in software going hand
Speaker 1: in hand with all everything else, and that leads to
Speaker 1: a minimum of a gap between what the market is
Speaker 1: doing and how businesses can respond to it. And then
Speaker 1: There's a related problem with going with proprietary approaches. That's
Speaker 1: the companies that do so limit the talent they can
Speaker 1: rely upon to run that part of the business. Open
Speaker 1: source software creates a lot of opportunities to find and
Speaker 1: bring on new talent. This is particularly important for companies
Speaker 1: located in places that don't have a really deep tech
Speaker 1: talent population. So if you run a tech company in
Speaker 1: San Francisco or maybe New York, you probably don't have
Speaker 1: a shortage of talent to draw upon. There's probably plenty
Speaker 1: of people who are qualified and you would want them
Speaker 1: on your team. But maybe you're someplace else like Omaha, Nebraska,
Speaker 1: and no shakes on Omaha. It's a great city, but
Speaker 1: you may not have quite as large a talent pool
Speaker 1: to pull from. You might have to try and give
Speaker 1: incentives for people to move there instead. So open source
Speaker 1: opens up a lot more opportunities. Otherwise, you have to
Speaker 1: look for people who specialize in that proprietary software. It
Speaker 1: might at first be surprising to hear that an organization
Speaker 1: like IBM, which is an enormous multibillion dollar company it
Speaker 1: does busy us all around the world, that such an
Speaker 1: entity embraces open source but in truth, it's a strategy
Speaker 1: that best serves the company's interests. Open source isn't just
Speaker 1: about rapid evolution. It's also about establishing what the standards
Speaker 1: are for a given process or approach. A developer might
Speaker 1: have one idea for those standards, and then the community
Speaker 1: might have a slightly different idea, but over time it
Speaker 1: tends to shake out, and because of the open nature
Speaker 1: of the code, it can find its way into many
Speaker 1: different products, services and companies and other implementations, and it
Speaker 1: helps cut down on the proprietary approach that by necessity
Speaker 1: limits what the end user can do with the technology.
Speaker 1: IBM really showed how interested it was in the open
Speaker 1: source philosophy in when it announced plans to acquire the
Speaker 1: company red Hat. So let's have a quick rundown on
Speaker 1: what red Hat is. It's a company that began in
Speaker 1: its earliest phases you could argue around, and it was
Speaker 1: around the concept of a version of the Linux operating
Speaker 1: system tweaked by a hacker named Mark Ewing. Now, there
Speaker 1: are a lot of different versions of Linux, or maybe
Speaker 1: I should say that there are a lot of distributions
Speaker 1: or distros of Linux. That's the proper way to refer
Speaker 1: to it. At the heart of any Linux distro is
Speaker 1: the Linux kernel itself, and it's an example of free
Speaker 1: and open software. And while Lena's Torvald's created and released
Speaker 1: the first version of the Linux kernel way back in
Speaker 1: thousands of programmers have made additions, improvements, and tweaks to
Speaker 1: that kernel in the nearly three decades that followed. Linux
Speaker 1: distro typically includes several other elements in addition to the
Speaker 1: kernel in order to create a fully fleshed out operating system.
Speaker 1: That operating system might be for a personal computer, it
Speaker 1: could be for a mobile device, it might be for
Speaker 1: a web server or even a supercomputer. And you can
Speaker 1: also find it on stuff like set top boxes and routers.
Speaker 1: It is an incredibly versatile operating system all right back
Speaker 1: to the founding of Red Hat, Ewing used to wear
Speaker 1: a red Cornell lacrosse hat that his grandfather had owned,
Speaker 1: and he had become known as the guy in the
Speaker 1: red hat while he was working in a computer lab
Speaker 1: at Carnegie Melon, So he decided to use Red Hat
Speaker 1: as the name of his Linux distro, and later on
Speaker 1: Ewing with joint forces with a businessman named Bob Young.
Speaker 1: Bob Young had been buying copies of red Hat from
Speaker 1: Ewing and then selling them, and he had been selling
Speaker 1: them about as fast as he could get them. So
Speaker 1: they decided this was a very valuable product and they
Speaker 1: formed red Hat Software in n Now, this is not
Speaker 1: an episode about red Hat, so we're gonna skip ahead
Speaker 1: to the company was successful at turning a profit despite
Speaker 1: being centered on an open source and effectively free software package.
Speaker 1: So if you're making something and offering it up for free,
Speaker 1: how do you make money from that? How did red
Speaker 1: Hat generate revenue? Well, the company sells professional services and
Speaker 1: has maintenance and support plans that customers can use to
Speaker 1: get tech support for their products. Red Hat developers still
Speaker 1: make major contributions to the software, which is largely shaped
Speaker 1: by the red Hat community of users and developers, but
Speaker 1: the revenue comes from providing the supporting services around the product,
Speaker 1: rather than from the product directly. In October, IBM announced
Speaker 1: that it was making a move to acquire red Hat.
Speaker 1: The deal would involve IBM buying all red Hat shares
Speaker 1: for one dollars per share, which means this is a
Speaker 1: thirty four billion dollar deal. Red Hat investors approved the
Speaker 1: deal in January nineteen. Now, at the time of think
Speaker 1: twenty nineteen when I'm recording this episode, that deal is
Speaker 1: still going through the regulatory entities of the government for approval.
Speaker 1: But the Red Hat acquisition plays a crucial role in
Speaker 1: ibm strategy to lead in the cloud computing space in particular. Now,
Speaker 1: as I mentioned in my earlier episode, one of the
Speaker 1: big barriers of entry to cloud computing is a fear
Speaker 1: of lock in going with a proprietary approach with a
Speaker 1: specific vendor, and that means you've hitched your wagon to
Speaker 1: that provider's proverbial horse. And if that horse would I
Speaker 1: don't know. I gotta stick with this metaphor, I would
Speaker 1: say it throws a shoe or something. You're stuck. The
Speaker 1: open source approach allows for more options, and options sound
Speaker 1: a whole lot better than only having a single choice.
Speaker 1: But while all these are the business arguments for open source,
Speaker 1: IBM has also pulled another lever. This one has to
Speaker 1: do with the power of the open source approach to
Speaker 1: do good in the world by engaging programmers and hackers
Speaker 1: to build code to meet specific challenges and help people
Speaker 1: who are most in need. I'll explain more in just
Speaker 1: a moment, but first let's take a quick break. In eighteen,
Speaker 1: the David Clark Cause proposed an initiative called Call for Code,
Speaker 1: which would establish a particular challenge each year for coders
Speaker 1: to tackle, and it would be a challenge that would
Speaker 1: have a real world impact and could help people who
Speaker 1: need it most. IBM joined on as a founding partner,
Speaker 1: committing millions of dollars and making available much of the
Speaker 1: company's technology and resources that it had developed for its clients,
Speaker 1: so participants got access to these incredibly powerful tools for
Speaker 1: their projects. The theme for the first Call for Code
Speaker 1: was natural disasters, so they decided to go big really
Speaker 1: early on. And natural disasters are an enormous threat to
Speaker 1: millions of people around the world. Flooding, fires, hurricanes, earthquakes, tornadoes,
Speaker 1: blizzards and more are all potential threats. They can wreak
Speaker 1: havoc on massive scale seals and mounting an effective response
Speaker 1: or mitigating the effects of the disasters that are hitting
Speaker 1: different areas, those are those are types of businesses. We
Speaker 1: just haven't seen much innovation around. We haven't seen a
Speaker 1: lot of movement there. We've definitely had advancements in tech
Speaker 1: and technique for dealing with disasters, but it's not the
Speaker 1: sort of traditional problem that attracts programmers or companies. The
Speaker 1: Call for Code was designed to be an incentive to
Speaker 1: help change this, and to use the open source approach
Speaker 1: to speed up the process. In the United States, the
Speaker 1: need for solutions to create more effective disaster response efforts
Speaker 1: was evident and keenly felt by eighteen. Puerto Rico, as
Speaker 1: well as many islands in the Caribbean, had been hit
Speaker 1: by a Hurricane Maria in September. The effects were absolutely devastating,
Speaker 1: and the recovery has been slow, to say the least.
Speaker 1: In fact, it's still going on in twenty nineteen. By
Speaker 1: January of twenty eighteen, months after the hurricane had hit,
Speaker 1: nearly half a million people on Puerto Rico were still
Speaker 1: without electricity, and power outages due to failures in the
Speaker 1: infrastructure exacerbated the problem. Hundreds of thousands more would find
Speaker 1: themselves without power, at least on a temporary basis, and
Speaker 1: by temporary I mean it would last days. The lack
Speaker 1: of electricity obviously creates additional dangers. People can't use modern
Speaker 1: communications to alert others to their needs, and first responders
Speaker 1: have trouble knowing where they are needed. The Call for
Speaker 1: Code initiative ended up getting a lot of momentum really quickly.
Speaker 1: The announcement came out in May eighteen, and within six months,
Speaker 1: thousands of coders from a hundred fifty six countries had
Speaker 1: been hard at work and a community had formed around
Speaker 1: this challenge. There were online discussions using tools like Slack
Speaker 1: to facilitate communication. Some teams even found their fellow team
Speaker 1: members through these channels, which connected people who were otherwise
Speaker 1: living so far apart from one another that they probably
Speaker 1: never would have had any connection otherwise. There were more
Speaker 1: than three hundred Call for Code City challenges that took
Speaker 1: place in cities all over the world to prepare the
Speaker 1: coders for the grand challenge itself, and the prize was
Speaker 1: a prestigious one. The winning team would take home two
Speaker 1: thousand dollars, but more importantly, they would also get the
Speaker 1: opportunity to actually deploy their solution with IBM S support.
Speaker 1: Now that meant the submission wasn't just an interesting idea
Speaker 1: that would win a prize. It would be put into
Speaker 1: practice in the real world and real people could stand
Speaker 1: to benefit from it. The winning team would also get
Speaker 1: long term support from the Linux Foundation and an opportunity
Speaker 1: to pitch their project to a venture capital firm. Now
Speaker 1: teams really did embrace the open source philosophy. They also
Speaker 1: were able to make use of many of the IBM
Speaker 1: technologies that likewise depend on open source, such as the
Speaker 1: company's cloud services. They got to work designing software and hardware,
Speaker 1: and collectively the competitors built more than two thousand five
Speaker 1: applications and there were more than one hundred thousand developers participating.
Speaker 1: The finalists all had intriguing ideas, and I'm gonna run
Speaker 1: down some of the finalists. I'll talk about the winner
Speaker 1: in just a moment, but here are just some of
Speaker 1: the ideas that made it to the final rounds. One
Speaker 1: team proposed a system called the Post Disaster Rapid Response
Speaker 1: retro Fit or p D three R. Their approach realized
Speaker 1: on using artificial intelligence to assess damage done to houses
Speaker 1: in the wake of a disaster like an earthquake, to
Speaker 1: determine if and how the structures can be repaired effectively,
Speaker 1: with designs meant to better withstand future earthquakes. So the
Speaker 1: team used IBM s Watson platform in its design, both
Speaker 1: to train computer models and to help recognize the extent
Speaker 1: of damage in homes. So you're using computer vision, you're
Speaker 1: using artificial intelligence to make design decisions. It was a
Speaker 1: really inventive approach to this and to try and improve
Speaker 1: communities in the future so that they could better withstand
Speaker 1: these disasters that might hit at perhaps not regular intervals,
Speaker 1: but often enough for it to be a concern. Another
Speaker 1: team created what was called the Lolly Wildfire Detection System.
Speaker 1: Their methodology was to deploy heat sensors over a wide
Speaker 1: area that would be able to update the overall system
Speaker 1: on the back end with real time analytics. So the
Speaker 1: back end of the system used Watson to look at
Speaker 1: changes and identify any markers that would indicate that a
Speaker 1: fire might be moving into the area. Further, they used
Speaker 1: artificial intelligence that would help figure out the features of
Speaker 1: the fire. It could determine what the intensity of the
Speaker 1: fire was, what the shape of it was, and it
Speaker 1: could pair this with other information such as weather information
Speaker 1: find out what the likely direction the fire might move
Speaker 1: in would be. And this system could help responders plan
Speaker 1: where they should dedicate firefighting resources. It could give residents
Speaker 1: and early warning to evacuate before it becomes a life
Speaker 1: threatening endeavor in the United States. The wildfires that happened
Speaker 1: in the western part of the country in ten were
Speaker 1: still very fresh in the minds of people, which I'm
Speaker 1: sure made this particular pitch really compelling. United Aid Net,
Speaker 1: which was another finalist, wanting to create a way for
Speaker 1: those affected by natural disasters to get funds quickly. The
Speaker 1: premise behind you a N is that you might have
Speaker 1: family members who live in areas that are vulnerable to
Speaker 1: natural disasters, and they might need access to money immediately
Speaker 1: following a natural disaster, and it can be hard to
Speaker 1: get money to people who need it. So you a
Speaker 1: N has two interconnected networks. One is with various financial
Speaker 1: institutions and the other is a network for family members.
Speaker 1: So you can sign up those family members to be
Speaker 1: part of this system and they can become beneficiaries so
Speaker 1: that they can, in the wake of a disaster, draw
Speaker 1: funds from an account you've set up and shared with them.
Speaker 1: In some parts of the world, money transfers can take
Speaker 1: as long as a few days, and according to U
Speaker 1: a N, their approach decreases this to a couple of hours.
Speaker 1: They proposed using blockchain to track the transactions, and they
Speaker 1: relied upon facial recognition technology and again machine vision to
Speaker 1: authorize withdrawals, leaning heavily on Watson for the horsepower to
Speaker 1: do so. IBM had some internal teams that competed in
Speaker 1: this as well. One of them freed to created a
Speaker 1: sort of Internet connected earthquake sensor and a back end
Speaker 1: to send alerts to mobile phones. So their focus was
Speaker 1: primarily on schools, using some low cost hardware which they
Speaker 1: actually housed in cardboard cases, so that really kept the
Speaker 1: cost slow. They could put those sensors into schools and
Speaker 1: monitor the schools for signs of earthquakes, you know, looking
Speaker 1: for any sort of vibrations that would indicate an earthquake.
Speaker 1: Is they're sort of like a seismograph, and it can
Speaker 1: also estimate the magnitude of an earthquake once as detected.
Speaker 1: It so not just that there is an earthquake, but
Speaker 1: how wrong is it? You know, how how serious is
Speaker 1: this problem? And it can send out alerts to mobile
Speaker 1: phones that belong to students, parents, and teachers, as well
Speaker 1: as first responders and other members of the community, bringing
Speaker 1: the sensors to potentially vulnerable sites, as opposed to relying
Speaker 1: on a sensing station that could potentially be a thousand
Speaker 1: miles away means that you can get hyperlocal results and
Speaker 1: that you can mobilize a response very quickly. And I'm
Speaker 1: not just talking about a physical response about you know,
Speaker 1: rescue workers going to the site, but kick starting the
Speaker 1: bureaucratic response, the government response needed to h to supply
Speaker 1: aid and other services to the area after the disaster.
Speaker 1: It can get that started earlier so that you don't
Speaker 1: have this long gap of time between when people need
Speaker 1: services and when they can actually get them. Another IBM
Speaker 1: project was help Chain, which took aim to address one
Speaker 1: of the most challenging aspects of disaster relief, which is
Speaker 1: making a case for donations. It can be a key
Speaker 1: to ask people to donate money. The team cited a
Speaker 1: figure about Puerto Rico and Hurricane Maria that is heartbreaking
Speaker 1: and infuriating. Around ten thousand shipping containers full of food
Speaker 1: and water never reached the point of distribution to the
Speaker 1: people of Puerto Rico. That was reported by NPR. Now,
Speaker 1: when you hear stories like that, you start to believe
Speaker 1: that any donation you make would just be a waste
Speaker 1: of money. Maybe you feel that the charities are taking
Speaker 1: too much money for administrative costs and very little if
Speaker 1: any of that money makes its way to the people
Speaker 1: who actually need it. Or maybe you hear stories of
Speaker 1: mismanagement and figure that any donation you make would be
Speaker 1: like throwing money out the window. The help Chain team
Speaker 1: used blockchain technology to help donators track a donation throughout
Speaker 1: its life cycle so that they could see exactly how
Speaker 1: much of their donation actually made it to the people
Speaker 1: who needed it. They could see each stage of that
Speaker 1: that transaction, and the transparency puts pressure on organizations to
Speaker 1: deliver upon the promise they made to help those in need.
Speaker 1: When everyone can see clearly how much money is going
Speaker 1: toward administrative overhead, you can't expect to be extravagant with
Speaker 1: those costs and still have people donate to your your cause. Now,
Speaker 1: when we come back, I'll tell you about the winning
Speaker 1: team of the team Call for Code and the follow
Speaker 1: up effort called Code and Response. But first let's take
Speaker 1: another quick break. The winning team for the two thousand
Speaker 1: eight teen Call for Code was Project OWL O w L,
Speaker 1: and that stands for Organization, Whereabouts and Logistics. I had
Speaker 1: a chance to sit down with Brian Canals, one of
Speaker 1: the members of the Project Owl team to talk about
Speaker 1: this at the IBM think table, and here's what he
Speaker 1: had to say. I'm here with Brian Canals of Project Owl,
Speaker 1: which is a phenomenal project that marries hardware and software
Speaker 1: for disaster relief in an application that I think is
Speaker 1: absolutely fascinating. Please, Brian, can you give us kind of
Speaker 1: the the big picture look at what Project Owl is
Speaker 1: all about? Thank you. So. Project Owl, as you mentioned,
Speaker 1: is a combination of two key ideas um and during
Speaker 1: the Call for Code competition, we i a dated this
Speaker 1: technology to help prepare for and recover from natural disasters
Speaker 1: through an application of a lot of the technology that
Speaker 1: IBM supports our our solution with. So we built two things.
Speaker 1: The first is a software incident management system that's a
Speaker 1: lot of buzzwords. It's really just dots on a map,
Speaker 1: a way to see, uh, what things and resources and
Speaker 1: people are where at what time to get a really
Speaker 1: clear operating picture of an incident, which in some scenarios
Speaker 1: if we're talking about a hurricane, chaos and misinformation is pervasive.
Speaker 1: But there's still a problem in the worst disasters where
Speaker 1: this type of data analytics capability would be really useful
Speaker 1: to really large chaotic disasters, these are the ones where
Speaker 1: infrastructure connectivity electricity is most likely to be offline. So
Speaker 1: we built a a network of IoT devices we call
Speaker 1: duck links, and these duck links generate a WiFi network
Speaker 1: that anyone can connect to with their cell phone or
Speaker 1: their laptop, and we can drop these duck links really
Speaker 1: quickly through commercial drones and a cluster that we call
Speaker 1: a cluster duck. And by dropping these cluster duck networks
Speaker 1: were able to distribute OWL incident management software two locations
Speaker 1: that may have no electricity or communications in a cost effective,
Speaker 1: fast manner. So from what I understand, you only need
Speaker 1: five of these ducks to cover a square mile, so
Speaker 1: just a broad deployment can restore connectivity to a pretty
Speaker 1: massive area in a short amount of time. And on
Speaker 1: the software, I would imagine that having all that information
Speaker 1: at your fingertips, you know important details such as what's
Speaker 1: the weather going to do next, which obviously is going
Speaker 1: to affect any kind of recovery efforts, and also who
Speaker 1: is where so that you're not duplicating efforts, that you're
Speaker 1: making the best use of your resources. Is that an
Speaker 1: accurate assessment? Yeah, and you touched on one other aspect
Speaker 1: that I didn't mention, we leveraged multiple APIs from the
Speaker 1: Weather Company, so we're able to get real time local
Speaker 1: climates in an area, which is really useful for first
Speaker 1: responders operating during a disaster. UM but in conjunction with
Speaker 1: that and using all the Watson APIs, we can get
Speaker 1: a really crisp clear look on the ground. And as
Speaker 1: you said, deploying these ducks UM is a unique way
Speaker 1: to bring coms in an area that traditionally this is
Speaker 1: a really complicated, expensive thing to do. And on top
Speaker 1: of that, not everyone can carry a VSAT in their backpack.
Speaker 1: These are hard that they require training, they're complicated and
Speaker 1: time consuming to set up, not to mention expense, and
Speaker 1: you have to align them to a particular geostationary satellite
Speaker 1: in the sky that's at a very particular coordinate and
Speaker 1: latitude and longitude. It's very hard to use. So our
Speaker 1: ducks were designed to be almost, you know, idiot proof
Speaker 1: in the sense that you just kind of throw a
Speaker 1: bunch of these out and they just kind of turn
Speaker 1: on an Internet in a place that doesn't have anything.
Speaker 1: And I understand they even can float, so if you're
Speaker 1: in a situation like a flooded area in the wake
Speaker 1: of a hurricane. They still work there too. Yeah, especially
Speaker 1: calling them ducks. It was imperative that they could float,
Speaker 1: they could sit on the ground, and that we're thinking
Speaker 1: about ways that maybe we'll make them fly to Oh fascinating.
Speaker 1: So I'm curious. I I read a little bit about
Speaker 1: the the actual genesis of the group. Can you talk
Speaker 1: a little bit about how you all came together? So, yeah,
Speaker 1: our team is just made up of technologists who and
Speaker 1: I be personally here. I just love building things and
Speaker 1: that has led me to some interesting communities and especially
Speaker 1: software and technology competitions. I've been doing this for a while,
Speaker 1: um and I think that's a great environment to find
Speaker 1: people who are really passionate about building technology. Um So,
Speaker 1: a couple of the guys on our team I had
Speaker 1: met through previous competitions and then we've you know, worked
Speaker 1: together on other projects. One gentleman in particular, Mangus Pereira
Speaker 1: on our team from Greenville, North Carolina. We met each
Speaker 1: other very early on in the competition through Slack, and
Speaker 1: I distinctly remember we had one conversation one phone call
Speaker 1: after that, and his passion and interest and creativity. And
Speaker 1: he comes from the background of being self taught that
Speaker 1: his desire to just be there doing things was self
Speaker 1: evident from the very beginning. These are the people I
Speaker 1: want to work with. These are the passionate minds I
Speaker 1: want to be around. So through kind of these different communities,
Speaker 1: through the Call for Code Slack, we're able to in
Speaker 1: this team of people who just want to be they're
Speaker 1: doing good things. And clearly you have impressed a lot
Speaker 1: of people for you one call for code, So what
Speaker 1: is next? What do you plan to do next after
Speaker 1: after winning that prestigious or yeah, thank you? Um. So
Speaker 1: when we won the Call for Code that was October Halloween,
Speaker 1: I believe, and basically the next day we had set
Speaker 1: a goal post in the ground that you know, this
Speaker 1: wasn't just about winning a competition or building technology, as
Speaker 1: fun as that is. This is about making a positive impact,
Speaker 1: making tech for good. And we set a goal post
Speaker 1: that we're gonna go to Puerto Rico and do a
Speaker 1: stress test before a hurricane hits, and we're gonna deploy
Speaker 1: a bunch of these and really see what can our
Speaker 1: technology actually do. That test is happening in two weeks
Speaker 1: in Puerto Rico. We're gonna go to three different regions,
Speaker 1: an urban region in San Juan, a mountainous region, and
Speaker 1: a coastal region, and we're basically going to start a
Speaker 1: stop watch, deploy a hundred ducks, cover about twenty square
Speaker 1: miles and see how quickly, how effectively, and how much
Speaker 1: does it cost for a few people with a bunch
Speaker 1: of ducks to get an Internet and Comm's network up
Speaker 1: and running. And you know, can we do this in
Speaker 1: a couple hours? Fascinating? Well, I have to say that
Speaker 1: your story is absolutely inspiring on multiple fronts, from just
Speaker 1: being passionate about tech and building things and this area
Speaker 1: of experimentation that I find fascinating, to the desire to
Speaker 1: actually make a positive impact and to help people who
Speaker 1: are at the most vulnerable who need that help at
Speaker 1: a critical time through an easy user interface where they
Speaker 1: can connect, they can find out how everyone is doing,
Speaker 1: they know what to do next. This is a wonderful story.
Speaker 1: I am very honored to have been able to talk
Speaker 1: with you about it. I greatly appreciate the opportunity and
Speaker 1: I wish you the best of success us in Project
Speaker 1: al in the in the years to come. Thank you,
Speaker 1: so much. Um, you know, but like I said, we
Speaker 1: just were really inspired to build things and do good.
Speaker 1: I think, um, one of the challenges. You're very familiar
Speaker 1: with technology and the landscape. I think there's been a
Speaker 1: challenge with technology and that we're not certain a lot
Speaker 1: of these things are actually helping us. Some people might
Speaker 1: be getting rich, but does this really help us with
Speaker 1: what's going on? So I think you know that the
Speaker 1: holy grail of what we're trying to do as a
Speaker 1: company is to marry the ability to build a business
Speaker 1: and build a company with the ability to do good
Speaker 1: and make a tangible, positive social impact. It really sounds
Speaker 1: to me like you've made great strides towards that goal.
Speaker 1: So I wish you the best. Thank you so much,
Speaker 1: thank you. I really like Project Owl's approach here. The
Speaker 1: hardware is both simple and innovative. Housing the mesh network
Speaker 1: nodes in rubberized buoyant cases and then using a drone
Speaker 1: delivery system makes deployment much less of a challenge than
Speaker 1: it would be if you were using cell phone towers
Speaker 1: or some other more traditional means of deployment, and using
Speaker 1: cloud services to pull together different pieces of data to
Speaker 1: provide to first responders and to help them plan effectively
Speaker 1: is really exciting as well. It could help responders focus
Speaker 1: specific efforts on particular regions rather than going in blind
Speaker 1: with a wide but shallow response. You know, if you
Speaker 1: have to prepare for anything, you probably don't have the
Speaker 1: capacity to have a very deep response to any one
Speaker 1: given need because you're trying to prepare to provide for
Speaker 1: any need. Well, this would give responders more tools to
Speaker 1: plan a specific approach and a more effective one. It
Speaker 1: also helps them not duplicate those responses. So the code
Speaker 1: in Response phase of this whole initiative is now ramping up.
Speaker 1: IBM calls it a twenty five million dollar four your
Speaker 1: initiative that will build, fortify, test, and laun open technology
Speaker 1: solutions that helped communities needing critical aid. So this is
Speaker 1: the opportunity to actually put into place the proposed solution
Speaker 1: and see if it works in the real world, to
Speaker 1: take it from the development team, from the code and
Speaker 1: the prototypes and actually put it out there for real
Speaker 1: zes well. In addition, collaboration is continuing beyond the call
Speaker 1: for code competition, carrying forward that open source philosophy beyond
Speaker 1: the event itself. Pedro Cruz who headed up another call
Speaker 1: for code project called Drone Aide, maybe working with Project
Speaker 1: Owl to combine his ideas with THEIRS into a new
Speaker 1: implementation that could really help people. Drone Aide grew out
Speaker 1: of a real world experience that Pedro Cruz had in
Speaker 1: the wake of Hurricane Maria and Puerto Rico. Because getting
Speaker 1: around the island was nearly impossible due to the massive
Speaker 1: destruction and because communication systems were down, Cruz wasn't sure
Speaker 1: how his family was doing, so he went and grabbed
Speaker 1: a drone that he owned as a camera on it,
Speaker 1: and he decided to fly his drone around to check
Speaker 1: on his family members make sure they were okay. And
Speaker 1: while he was doing that, he noticed that in some
Speaker 1: of the areas around Puerto Rico, some of the damaged
Speaker 1: areas that people had written messages on the ground, you know,
Speaker 1: using chalk on pavement, and some of them were messages
Speaker 1: to alert other people in the community about their family
Speaker 1: members and their status. Others were requests for help. There
Speaker 1: are a lot of requests for fresh water, for example,
Speaker 1: and CRUs thought that a solution using object character recognition
Speaker 1: could be paired with a drone to do scans of
Speaker 1: an area and search for these messages and then you
Speaker 1: could geo tag them so you know exactly where those
Speaker 1: messages are and you know where people are and what
Speaker 1: they need, and you can send that information to first
Speaker 1: responders so they know immediately who needs what and where
Speaker 1: they are. I think twenty nineteen I attended a session
Speaker 1: in which Canals and Crews spoke about this collaboration, combining
Speaker 1: the drone approach with the dashboard software that OWL built
Speaker 1: to add more information for first responders, giving them a
Speaker 1: much more complete picture of what's going on. And by
Speaker 1: using object character recognition and automated processes to identify places
Speaker 1: where people need help, you take the need for a
Speaker 1: human to review hours of footage, which is an enormous
Speaker 1: time constraint. These stories are really inspiring and I think
Speaker 1: it serves IBM well in many ways. It's not just
Speaker 1: good PR, although there's no denying it's good PR. It
Speaker 1: also is encouraging more people to get into coding. It's
Speaker 1: tapping into the desire to make a real positive difference,
Speaker 1: and a lot of people want to do that and
Speaker 1: aren't sure how so designing this program gives people an
Speaker 1: avenue to actually do that. So it's not just to
Speaker 1: build an app or a piece of software, but to
Speaker 1: actually improve or even save lives. That's going to lead
Speaker 1: to more people getting into the field, which will benefit
Speaker 1: tech companies like IBM when they're seeking out talent. And
Speaker 1: obviously the use of IBM S technologies raises awareness of
Speaker 1: what those technologies are and how they can make an impact.
Speaker 1: But throughout Think twenty nineteen, the message of using technology
Speaker 1: to make a positive change was repeated. Jenny Romedi's opening
Speaker 1: keynote even featured a video titled Dear Tech, and that
Speaker 1: was an open letter to technology and to developers about
Speaker 1: using these tools to transform the world in positive ways
Speaker 1: and making that positive impact. I'll be following up on
Speaker 1: Project al in the future. I want to speak to
Speaker 1: the team to find out how the deployment tests turn out.
Speaker 1: My hope is that they get the support to scale
Speaker 1: up their efforts so that they can actually put this
Speaker 1: into practice in the real world in in the wake
Speaker 1: of real world disasters. Now you never want to need
Speaker 1: a natural disaster response plan, but you absolutely should have one.
Speaker 1: But back to open source. Open source projects cover every
Speaker 1: area of coding. You can think of the community of
Speaker 1: developers that grows around. Open source tends to be passionate.
Speaker 1: Members can be really opinionated. People can disagree over implementations
Speaker 1: or changes. Ideally, through the process of contributing code, the
Speaker 1: best options survive and the others evolved or they fall
Speaker 1: to the side. And there are thousands of workshops, hackathons,
Speaker 1: meet ups, and seminars about coding. And from what I've seen,
Speaker 1: the community tends to be really eager to welcome new
Speaker 1: people into their world. After all, new people bring new ideas,
Speaker 1: new perspectives, and new solutions, and that's really what open
Speaker 1: source is all about. Well, that wraps up this episode
Speaker 1: from Think two thousand nineteen. I want to thank IBM
Speaker 1: again for the opportunity to kind of explore this world
Speaker 1: and to talk with so many people who are really
Speaker 1: passionate about open source. It was really a cool experience
Speaker 1: for me. If you guys have any suggestions for future
Speaker 1: episodes of tech Stuff, send me a note. The email
Speaker 1: addresses tech Stuff at how stuff works dot com, or
Speaker 1: you can visit our website that's tech Stuff podcast dot com.
Speaker 1: You can find links to our social media there. You
Speaker 1: can find links to our merchandise store. Check those out
Speaker 1: and I'll talk to you again really soon. For more
Speaker 1: on this and thousands of other topics. Is that how
Speaker 1: stuff works dot com