Today’s guest speaker is a social entrepreneur building digital workforces in developing nations. He has helped over 10,000 individuals rise out of poverty into the new digital economy through his venture CloudFactory.
Listen in as Mark Sears and I discuss about how connecting people to meaningful work is the solution to enabling work 2.0, why people play a critical role in driving AI forward and what Kenya is doing to pioneer digital skills learning in the 21st Century. This is HumAIn.
Welcome to HumAIn. My name is David Yakobovitch, and I will be your host throughout this series. Together, we will explore AI through fireside conversations with industry experts. From business executives and AI researchers, to leaders who advance AI for all. HumAIn is the channel to release new AI products, to learn about industry trends and to bridge the gap between humans and machines in the fourth Industrial Revolution.
If you like this episode, remember to subscribe and leave a review.
Welcome back to HumAIn. My name is David Yakobovitch and on today’s episode, we have the founder and CEO of CloudFactory. Mark Sears is a computer scientist by trade and has been working for the last nine plus years on a venture powering AI for over 150 Fortune 500 companies around the world, helping them make better and smarter decisions with their data. Mark, Thanks for being with us today.
My pleasure, David. Looking forward to it.
Absolutely as someone who works in the future of work and work 2.0, I myself do a lot of reskilling and upskilling of employees all the time. And I love what your company is doing. Why don’t you share with our audience, how CloudFactory is training the future workforce?
Certainly. We are very passionate about seeing people grow and be prepared for the future, for no question. I mean, really, CloudFactory, We love our clients. We get to work with some of the most amazing tech and AI companies out there. I gotta admit when it comes to seeing our Cloud workers grow and just continue to be promoted and learn and personally, professionally grow, it’s certainly the thing that gets us going as a company. We’re super excited. So for us, we operate in emerging economies and specifically Nepal and Kenya, and we have over 5,000 very talented people, mostly 18 to 30 years old.
Many of them were college students, recent graduates. They are talent that is really not well-connected in the global economy. And so, that’s really the thing that started this whole thing of CloudFactory was saying, how do we build a technology platform and coordinate these really talented young people to connect them to the global economy? Because there’s so many people that need data work done. And we did this even before the need for training data and everything related to AI really boosted this need for data work.
So it has been a phenomenal journey just to see the opportunity to take somebody. They come in. They start with maybe a little bit easier task. They go through unlocking new skills and just get access to more and more work, working on different, We call them work streams. And so our clients are constantly streaming work and we have Cloud workers who are resource pooled across different work streams.
And so, they get to work on a lot of very cool autonomous vehicle stuff in the afternoon. And then maybe they’re doing some fashion tagging for an e-commerce startup, and then there may be processing some insurance documents or on and on and on. So they get the opportunity to get exposure to a lot of different types of work. They didn’t work as well as working with some really cool companies.
Now, traditionally, when someone thinks of AI, we think magic. We think a closed loop. It just happens. You snap your fingers, you wave your wand and the system has this beautiful result. But the truth couldn’t be farther from that. And it sounds like a lot of your Cloud workers, they start with simple data tasks. It could be such as, this is an image of a cat and a dog. And then they get to more advanced tasks such as ‘here is a Tesla vehicle and it’s moving. Is there a pedestrian in this photo? Is there a box falling off on 18 Wheeler in this photo?’ And so, the complexity starts simple and scales quite quickly. What are some of the ways that you help your cloud workers become attuned to being efficient, effective at processing data?
There’s a lot of different aspects. Certainly, the first and foremost is training. Becoming really efficient and effective with training. There’s some art to that and there’s a lot of science. So some of that, we do really the blended learning model. Both online as well as in-person. It’s probably a very unique aspect to how CloudFactory manages our workforce.
We have a hybrid workforce. Some of our workforces are working distributed. Some of them are working in one of our managed offices, but even those that are distributed are coming in regularly for training sessions.
So, as much as we love online training, and it’s a big part of it bringing a group of people into a room for a three hour session, and the format that we’ve developed to really make that session effective is super important. Because as much as, like you said, some of the examples of the work of a bounding box around cars in this photo sounds really easy, the nuances, the exception cases, quarters, cases, all of that.
And really, that’s where you get down to the important difference of every percent of accuracy really can make a huge difference. And so, how we train is certainly a big part of it. And the fact that some of that is actually face-to-face, throughput and productivity. Everyone’s trying to say, you know what? Yes, we need high quality, but we also need a lot of data. And so, how can we make sure that our budget for training data can go as far as possible?
And so, things like productivity. We love creating an environment of bursts and breaks and the Pomodoro technique of having our workers work hard for 25 to 40 minutes, and then taking a complete break. So, even in some of our delivery hubs, when that timer goes off, literally, people jump up and someone will lead them in some fun exercises and other things that happen so that we have a real culture around again, that bursts and breaks of working hard and taking breaks.
And that’s a really important part too, about staying focused. We don’t like having people work for too long, typically, though work for maybe four hours on one particular work stream to keep really focused. We’d like to have them switch it up and do different things, learn new skills and just really stay fresh with the work that they’re doing as well. So there’s a ton of things that we try to do to make this work very effective for our clients, but also enjoyable for our Cloud workers as well.
Just to hearing from you right now, I’m feeling so excited because bursts and breaks are so fun. One of my first jobs when I was in college was a financial transcriptionist. Before you had products like Amazon Polly inside we’d actually be listening to lawyers and doctors and different professionals and be typing with all these shortcuts and phrases to turn the audio into text. And we see how that has evolved as an industry.
What I love about hearing about the culture reminds me very much of Salesforce and Marc Benioff, like really empowering your teams there. And this is at such a polar opposite of what we see in the industry today. There’s been news reports from The Verge and other outlets that companies like Megvii and SenseTime with Face++, and these products have these data factories in China where it’s almost like Foxconn all over again. But I’m hearing exactly the opposite here. How did you establish this culture where it led for leadership and the growth of your employees so that they became valuable people in the new knowledge economy?
That’s exactly it. It’s a tough world where everyone’s worrying more and more about who was making my data. Who’s touching my data is really important. And where it started for us, again, was literally 10 years ago.
Me and my wife took a two-week trip, a vacation to Nepal, and we ended up meeting some developers there and ended up staying for three weeks to help train them up on Ruby on Rails. And then we stayed for a three-month project. We literally stayed for six years and lived in Nepal. We had our two kids there.
And so, CloudFactory, we exist to connect a million people to online work and we exist believing that talent is equally distributed around the world, but opportunity is not. So it starts and it ends with making sure that we are trying to create good opportunities. So, it’s from that starting point, really, the DNA and the origin of our business, that this happens. But there’s a second part to it somewhere along the way. Pretty early on, I realized I’m a techie. I’m a developer. We looked at every problem and said we’ve got 55 developers that are working on software to make this all work better.
But as much as I love technology, I realized when it comes down to someone sitting and working on a lot of this data work, we call it the zoom effect. And just really taking the opportunity to zoom in one or two more times to get that one pixel accuracy around that bounty box or to zoom in on that document to say, is that a six or an eight? Really that comes down to how engaged our people are. Do they really care about the work? Do they understand the context of the data they’re working on? Or is this just some micro task work? And they have no idea the value of it. And we’re just trying to beat an algorithm to make some extra money.
So for us, we make sure that people understand what the company is trying to accomplish in a big picture and how the importance of them performing accurate data really can make a big difference in their mission as an organization. So all of those things and how we set things up, is why we exist as a company. Also, why we’re winning in the market is because to get that extra percentage better quality data really comes down to sitting there for a one minute or 10 minute task and just having a different attitude over what you’re doing.
That’s fantastic. And I can see how that makes sense. When I used to get started that transcription space is all about attitude and is all about the long term, those goals that you’re establishing. And a lot of that is knowledge. A lot of your Cloudworkers could be the new startup leaders and the new founders who are going to work on projects in the future.
In fact, these Cloud workers play critical roles for driving AI forward. Some of your clients include Drive.ai and Microsoft and NuTonomy. And a lot of these companies are amazing. Even Pilot AI. I followed a few of these and they’re doing cutting edge things in AI, but the truth still is it’s so human-powered. And why is it human-powered? Do you see that changing anytime soon?
It is very human powered and to be honest, we’re still sometimes surprised.
So, it’s not only really CloudFactory world with AI companies. It comes down to two things. One is to help train and sometimes validate as well on the backend those models to see how well they’re performing. But the other side is to really augment them and fill in the gaps.
So, we say train and sustain. Really. It’s that human the loop that has both sides of training and augmenting that you see a huge amount of need for scalable people, people who can really do high quality work. And it’s all within a very tech forward friendly way.
We believe that the market’s learning two things. One is on the training side. The performance of models is very connected to the quality of data, the amount of data and the refresh data, but especially, the quality of data to make a really big difference. So everyone’s trying to win. Everyone wants to have the most data and the best data because they want to win the market. It’s still very early. That’s an arms race. That’s happening with a lot of different industries that our clients are working in. So that certainly is a part of it. We want a lot of data.
The other thing that’s really happened with layering of neural networks and deep learning is that people are realizing more data. It used to be that topped out a little bit. The curve on performance started to flatten out a little bit at some point where adding another hundred million data points wasn’t going to help.
People are seeing that, actually, no. With more data and more compute, you actually are gaining advantages. That requires more people. And the other side of sustaining or augmenting these algorithms is filling the gap. And really that gets more into the customer experience.
So our clients, their customers so much depend on the quality of that experience. And oftentimes, it’s related to data which is being touched by humans in the loop. So really, on both sides, both to get the best models in production and to fill those gaps in a way that creates the best user experience is critical. And when you do that at scale, because you’re a tech company, you need access to a large, scalable high quality workforce.
And with a large scalable high-quality workforce, we’re seeing products today, especially in the computer vision space, coming to life very quickly. I know you’ve mentioned a few times about the one pixel and the bounding boxes and image annotation. And for the layperson, it’s often incredible to even think how computer vision could be possible with autonomous vehicles. And we’re so close, but we’re so far.
I know Elon Musk gave a talk earlier in April 2019 about one of two directions to get to autonomous driving. It’s either going to be with LIDAR or without LIDAR. When you’ve been having your Cloud workers working on computer vision for autonomous driving, what are some of the big challenges you’re seeing in variance as they’re trying to solve this problem?
Yes. Good question. It is interesting. We work with currently about 11 of the top autonomous vehicle companies out there. So, we get to see people at different stages or using obviously different sensors and different approaches to gather data. One thing that we are seeing is certainly the variety of approaches. So variety of maturity within programs. The amount of data and detail it gets. Actually, I would say I’m quite shocked at that variation, which is really interesting because what that points to me is that there’s going to be some winners and losers.
This is not as simple as investing 1 to 3 billion dollars and you’re guaranteed to come out with the same level of technology. So that’s one thing that I can very generically share is that people are running really high quality programs and people are very early and almost much more experimental than one would guess.
Now, I say that. And some of the other challenges though, that we have from an AB perspective is that the programs are so much agility that’s required because everyone’s testing back and forth. So the feature engineering of ‘let’s try doing it this way. Let’s try tagging this’. Now we want to try doing that. And they have new data sets. And, and so that it has really helped us to grow as a company overall, to just have our work streams, extremely agile, and to really be a close partner to our clients, which is very different to be honest.
And even five years ago where a lot of the work was coming to us by API and it was micro tasks and pretty routine. And now there’s a lot of collaboration, a lot of communication, a lot of retraining and adjustments. And again, maybe you could look at that as being a hassle, but we actually love it. It’s great for us. It actually helps our model, and how we do things really stand out in the market.
But it also is great for our Cloud workers because they’re having to raise their game as well. And that’s just more opportunity for learning. And it’s a higher level job. Many of them are actually IT students. We have a ton of IT students. So there’s no question. Recent grads are trying to start their own company on the side. And so, we would love for them to get this sort of exposure and hopefully part of CloudFactory success is you’ve got thousands of young, talented people who are going off to start their own AI companies, that would be phenomenal.
And then much of that will be happening over the next few years. There’s so much democratization of learning AI happening now. And particularly at CloudFactory. You’ve had the chance to look under the hood that over 150 companies, as you mentioned, 10 or more in the autonomous vehicle space on building AI.
And everyone’s trying to collect and gather the data and prepare the data, but maybe it wasn’t always this way for you and the company. And you’ve had a lot of trying gains. You’ve learned a lot over the years. And as you mentioned, you’re a partner now for a lot of companies, but you may have been a provider before. So love to hear how you pivoted or found new success for your company over the last few years.
Yes, David, There was actually a moment. We have an internal name for it, which I’ve ever shared externally, but I’ll go ahead and call it the Nivasha moment. So Naivasha is a beautiful place just outside of Nairobi. And we had our leadership team meeting there, probably it was three or four years ago. And I remember sitting around that table and this was shortly after, this was just a few months after we lost the biggest deal that we’d ever lost before.
And so I personally was running that deal. And so it hurt because we went in and we had one of the biggest tech brands in the world that was really excited about working with us and was thrilled with how CloudFactory thinks about impact and that the talented workforce that we have and the results that they were seeing from sort of a referenceable clients.
But when it came down to actually doing work, they didn’t want to send the work to us and to do work using our tools, even though we built such amazing tools. They just said, ‘Hey, we actually have our own tools, our own platform to get this work done. So we need you to come have your Cloud workforce work on our stuff.’
And we honestly just couldn’t scramble enough to come up with the pricing and packaging and the tech and everything to do that. So I walked out of there knowing that we lost the deal that day. And we started to realize that there was a bit of a trend where a lot of our clients felt that it was important for them to have control or developing the tools to tag the data, annotate the data categories, whatever they were doing. The data work tools, they wanted to own them.
Even if they weren’t fantastic. They knew some of them actually believed the way that they built those tools could lead to competitive advantages in the tech they were developing. Some of them wanted to have control just to, again, for a lot of agility to be able to iterate really quickly for their data scientists.
But we saw that trend. And so we actually made a pretty big shift in our business to say, how do we take our Cloud workforce and adjust our tech stack to get performance management and visibility into the workforce? And how do we change everything so that we can become tool agnostic and allow our workers to work on the tools of our clients or the tool of their choice? Because we started to see there’s other startups.
There’s a little industry that was emerging, where people were building some of these connotation and NLP tagging tools, et cetera. So, that was a big shift for us three or four years ago. And that my Nivasha moment was that we had been experimenting in the market with this very early test. The product was very early, but there was enough data where we put that up and looked at it as a leadership team and said, Let’s do it. Let’s go after that. And so as a company it’s just been continued, huge growth. 20 consecutive growth, quarters of growth, and just a huge demand out there for what we do and how we do it. So that definitely looked at that moment as a big learning and glad that we made that shift.
The consistent theme I’m hearing is that you’re focusing on impact and by focusing on impact you’re changing lives. And recently, I know you’ve expanded your mission with new opportunities. One in Kenya, you’ve partnered with Safaricom Foundation, launching a new digital skills learning initiative.
I love everything with digital skills. And in fact, I’ve been most recently working with the Simons Foundation on a lot of their open source tools. So it’s very exciting to see how you can decentralize learning. Love to hear more about this initiative that you’re working on.
Yes, we’ve always been looking for the time and the partner to get started. I would almost say above the funnel. So we have such talented people that are coming to CloudFactory and applying online every day in Nepal and Kenya. And yet, we knew there was an opportunity to help people before they may get into our queue and began working and above the funnel.
Digital skills training was something we’ve been looking at for a long time. Safaricom Foundation came to us and I will remember that first phone call we had with the head over there. And I was so impressed with their attitude and real understanding of the need and the market for this.
And they’d heard a lot about CloudFactory in Nairobi and just the growth that we’ve had there. But specifically they talked about this idea that there’s some people who just aren’t getting the same access to the online tests and they aren’t maybe in the right circles or they’ve been maybe out of the workforce for a few years, or there’s different reasons that were, actually. There were barriers to finding and being successful, to pass our assessments and join the workforce, but they were pretty small barriers.
And so the idea was, could we, even in two weeks with a really well-designed program, could we get people over the hump? And so we did a pilot with them and it’s been going very well. So that’s what we’re doing.
We’re trying to say, can we actually above the funnel start to have more people gain the digital basics, real practical stuff? It’s even things like, ‘great, you use Microsoft office’ a few years ago and you were really good and effective, maybe you’ve been out. Let’s get you super efficient on G-Suite on Google tools. Can you use Google sheets and other things? Because a lot of our clients is what they use.
And so just starting to get into really practical, tangible skills to contribute to the knowledge economy today. And so we’re thrilled even seeing, I don’t know the exact stats, but I remember seeing that our first three cohorts continued to get better and better where we saw people, it was like up to 30% or more people were passing our tests, and therefore, getting access to employment that wouldn’t have otherwise.
So, really honored to be working with Safaricom Foundations. Safaricom is obviously a huge name in East Africa and, really, globally. Just for their innovation and to see them now really giving back by trying to help alongside us to give these skills to the growing youth of Kenya makes us really excited and happy to partner with them.
Absolutely. And one of the most exciting things about running digital training and the future of work is going through the assessment process, the constantly tuning, the learnings and tuning the skills that you’re teaching, so that everyone’s having those relevant skills. What are some of the takeaways you’ve had just in these first few cohorts of what’s working with skills training online, or how you’ve made some adjustments that have continued to increase that impact?
The biggest thing that our team has been working on is trying to really make sure that our criteria for even accepting people is really clear because certain people that we’ve found have been very effective. Their learning curve has just gone so far up in just two weeks and there’s others that weren’t.
And so it was that, again, that idea of we’ve got limited capacity here. How do we really focus on bringing people in that really have some barriers that can be overcome quickly? We don’t want to mismanage expectations thinking people are gonna come in and they really don’t have high
knowledge of computers in general. So finding that sweet spot of who are the people who just need that boost to get across the finish line.
So that’s a big part of it, obviously the effectiveness of the curriculum and all of that, just iterations that we just all do is the standard stuff. But especially in saying, okay, let’s make sure that we set people up for success and select the right profiles and personas of people that can really get over the hump and join the digital economy.
Now looking at countries that you’re working in like Nepal and Kenya, they’re both very rapidly growing countries that are becoming digital and are emerging markets for people who haven’t been to these countries before. Can you paint a picture of what is the new Nepal? What is the new Kenya?
Yes, that’s really, it’s a great question, Dave, because you’re right. It’s hard to know. Maybe people haven’t had the chance to go, first of all, start with that, get on a plane and go. My goodness, Nepal, Kenya are beautiful and yes, there’s Katmandu and Nairobi is capital cities.
The real fun happens when you get outside and see the real Nepal and the real Kenya. So these are beautiful emerging economies. Unemployment, though, is just really hard to even measure. So, 40% to 60% employment are easy stats to throw out, but when you start looking at the amount of informal and underemployment, that’s there, and then you start looking specifically at people who are more 18 to 30. Then those numbers go way higher.
And you look at the number of college graduates that are happening in both Kathmandu and Nairobi. And so this problem is not getting better. It’s actually getting worse. And so you have people who have high English proficiency. They’re connected online and their whole social lives. So they’re taking MIT courses online and living, breathing WhatsApp, Facebook, you name it. So they are fully digital and English proficient and they are hungry to really join and yes, they want to earn, everyone wants to earn money, but more than that, they’re looking for opportunities to really grow. And also to connect.
A big part of cloud factor specifically is we put people in teams, so they actually come in, they join a team of 5 to 10. They are meeting regularly to do leadership development, go out to community service projects. We’ve done over 5,000 community service projects. And so there’s this earn, learn and belong thing that people are joining. And that’s really the next generation in general. It’s about more than just earning.
Sometimes that’s the mistake that we have in our mind. It’s like, Oh, well, these are relatively material or financial poor countries. So as long as we’re giving jobs and money and that’s actually not the case. Everyone there is actually very hungry, looking for a good place to work, a good opportunity to learn and grow.
So that’s one thing that sometimes people are surprised by. I know I was surprised by early on many years ago, and these are bustling cities that the growth and the opportunity is just, it’s huge. It’s phenomenal. It’s fun to see. And obviously the talent is just amazing.
So that’s super exciting how the impact is growing the new digital workforce, both in Kenya and in Nepal, but specifically for Africa. That is one of the most rapidly evolving continents, where there is such a digital workforce. I’ve had the opportunity to work with clients in South Africa and Tunisia, and just really start seeing digitalization and any other innovation efforts. You’re starting to see it happening in Africa.
We’re seeing a lot of great things. On the high-end, Microsoft just announced in the last week a hundred million dollar commitment over the next four years for a new African Development Center. That’s huge news and people have been building and investing, but it feels like that’s just really accelerating right now.
And so we see stuff like that happen. We see another partner of ours, Andela, who is doing very similar idea of saying, okay, how do we take talent? How do we use training and technology to really connect them? And so they’re doing it with software developers in Africa, trying to find that top 1 to 3%.
And so they’re also continuing to grow very effectively as well. So from the smaller startups to the biggest companies in the world, everyone’s recognizing that the world is more connected than ever, and talent is all over. How do we continue to get access to the best talent, to both grow our companies and also give opportunities to those people who really need and deserve them?
The other piece you just hit on is, right now, we’re doing a lot of the work with helping people get these opportunities and be re-skilled. But it’s also about the future of companies. And what are these new AI organizations that are going to be the new startups? The new Megvii, the new Face++, the new Microsoft. And if I wanted to launch an AI company today, I might say I’d like to partner with CloudFactory. And I know you’ve come with a lot of new solutions recently to help startups start to train their data, label their data. What are some of those solutions that you’ve been opening up to the world?
We just recently relaunched our products to be very matched to what our clients most need to get done. So we have been working with many clients for years now, and we realized that specifically, there’s those two buckets. One is when you’re trying to train up your AI and the other one is when you’re trying to fill the gaps of your AI and technology with inserting humans in the loop.
And so we came up with train.cv. So training computer vision is one product offering and then train.nlp. So for natural language processing, those are really the two use cases and focus areas that we’ve been investing a lot into and doing a lot of work for different companies. And so we wanted to really fine tune all of the different details around the workforce and everything to make sure that we could take all of those learnings and really help accelerate those that are developing computer vision and NLP applications.
On the other side for augmenting and the data processes that are ongoing, We wanted to really also continue to optimize around things like having enough capacity and agility whenever we need something done. So if you need to have enough capacity online to get a really quick turnaround, how do we make sure that you do that? So we’ve got one package that we designed around that.
So we are really just beginning to break down our product offering to say, we know after so many years of experience with other companies, what’s most important and let’s begin to pre-configure and pre-tune these managed workforces, so that out of the gate, people can benefit from all of that work that we’ve done over the years.
So it’s amazing how the work streams with your Cloud workers are working on such phenomenal AI applications. And having worked with over 150 major clients and even a lot of the small startups and companies, I’m sure you’re seeing a lot of the trends in AI, a lot of changes in development. Your core product workstreams are looking at computer vision and natural language processing.
One of my mentors, who I took her training fellowship in New York City last year, Amy Webb, she has her annual Future Trends Reports sent just this past year. So there’s over 44 sub fields of artificial intelligence that are emerging and getting out in the space. And they’ve highlighted computer vision and NLP. Are there any that, perhaps you’re thinking beyond these two, that could be the next fields that your clients are demanding or companies should start considering to work with as well?
There’s no question that there is a lot of work on the taxonomy of trying to classify different AI work that’s coming up and we’re trying to do the same.
So we have a lot of clients who are doing things that don’t fit so neatly into computer vision and NLP, as you can imagine. So, I don’t know if there’s anything to call out necessarily right now, but we certainly are continuing to learn what are the common things around data and having a workforce fine tuned, as you apply it to some of these other fields. And so obviously, we anticipate continuing to release other things, other workforce product offerings that are fine tuned for others as well.
But there’s no question. I can’t keep track of the different use cases. I’m constantly surprised looking over the shoulder of our Cloud workers and seeing the things that we’re working on and some of them are not straightforward to classify for sure. And we love that. That’s really what it is in general. We are a custom partner and we are working on so many different applications and ideas. But that’s the only thing that we can expect is just more and more innovation as it’s applied to AI over the coming years. And we’re just excited to be a part of it.
Awesome. And with all the technology changing, what do you think about the future of the workforce with being decentralized in the sense of 5G coming around and internet coming from satellites, especially, working with countries like Nepal and Kenya, where there could be some remote regions. How has access to the internet empowering your future workforce to work on these AI solutions?
It’s certainly improving every single year. There’s no question about that. And we do believe, like I said, that we have both a distributed and in-house, and we’ll always have that. But more and more it’s becoming very effective and also more enjoyable for people to have that flexibility of being able to work from anywhere.
And so, there’s more coworking that’s opening up all over Nepal and Kenya. And so, making it effective for people to even find places like that to plug in is certainly something that we’re working in, experimenting on.
There’s also for us a big push to continue to get outside to more and more secondary cities as well. And so that’s a really fun thing for us to try and do because there’s better and better internet access. And there’s a lot of talent that actually has a lot of pressure to move into the capital cities, to try and find work. And so the opportunity for them to stay where they are, to stay with their families, to stay in their communities, to continue to become leaders that can help bring change where they are in Nepal, Kenya, and wherever we take CloudFactories model next. That’s really exciting for us.
So, there’s no question that is becoming easier and better and more effective. And for many people, enjoyable. I mean, traffic is rough. And so, if people can find effective ways to not just. We always think about what does the future of the best good job out there is really what we’re trying to design. And it’s not as simple as working at home alone.
And so that’s where some of the community team model aspects of what we do, gives that balance where people feel like they’re part of a smaller team. They get together. Even if they work from home, they get together regularly every week or every other week. So, that combination and the way we’re trying to experiment with it will continue to make it more effective and more common to have people working distributed.
That’s amazing. And that really hones a home for each and every person that the future of everything is human-powered AI. The future of everything is decentralized working and online experiences and the future of everything are AI powered companies and excited to see what’s next from CloudFactory and perhaps to bring my own venture up off the ground and see what that looks like as well.
Let’s talk, David. It sounds good. Sounds like a good plan. I couldn’t agree more. Everything you just said and all those statements are true and some people think they’re conflicting, but there’s no question that the future of work is human and machine intelligence finding the right mix of both. And we couldn’t be more excited about both. The opportunity over the coming years. There’s a lot of negativity and fear. And you know what, there’s no question there’s going to be some disruption, but I am one of those who’s in the techno optimist side where I believe that we’re going to navigate it well.
And that this idea of human flourishing is, we’re on a path to accelerate, seeing more of that when we do find the right balance and the right roles for human machine intelligence. And so it was fun to be at the center of it. And I’m sure you’re excited about being on that cutting edge as well.
Fantastic. Thanks for being with us today on HumAIn, Mark.
Thank you, David
Humans. Thanks for listening to this episode of HumAIn. My name is David Yakobovitch, and if you like HumAIn, remember to click subscribe on Apple podcasts, Spotify or Luminary. Thanks for tuning in and join us for our next episode. New releases are every Tuesday.