Hello, and welcome to Catapult Network's Supercharging Innovation podcast. My name is Jeremy Silver, chair for this year of the Catapult Network. In this series, I'm talking with some of the UK's top industry and academic leaders, business people, and parliamentarians to get their views on the future of innovation. On today's episode, I'm delighted to welcome Maya Pindeos. Maya is a human experience designer, architect, and an engineer with a deep passion for human machine interaction.
Jeremy Silver:Working at the intersection of engineering, robotics, and user experience, her work has been widely recognized across the industry with multiple awards and publications in Forbes, Fast Company, the European Commission Starts Prize, and others, as well as top rankings as leading female founder in the AI and technology industries. Maier holds degrees from both Imperial College London and the Royal College of Art, and led commercial strategy and user experience at a number of companies before ultimately starting her own business, Humanizing Autonomy. As CEO, she leads Humanizing Autonomy's company strategy and oversees a world class team commercial and technical and product talent. Maja, welcome, and thank you for joining us today.
Maya Pindeus:Thanks a lot for having me.
Jeremy Silver:So I'm gonna plunge straight in because I'm sure that everyone is always intrigued by the name of your company. To ask you just to give us a few minutes on, what what does your company do?
Maya Pindeus:Happily. Well, humanizing autonomy. You know, we chose a explicit name, I'd like to say. It's really around improving human machine interactions, making sure that any machine is able to interact around people as automation really reaches full adoption as we see more artificial intelligence, more automation really being introduced into our daily lives, into our everyday lives. When we started humanizing autonomy, this is all about creating what we call a global standard for human machine interactions.
Maya Pindeus:We're a computer vision company. We built behavior AI, behavior AI that is able to understand and infer human behavior and how people relate with the environments from any video, any image really will do. And with that help machines, help, AI systems, help automation, interact better with people, making them safer, more productive, more reliable, more trustworthy, and more ethical, really. So it's really all you need as a camera. We feed into any camera, whether it's your consumer device, whether it's in a car, on a CCTV, very focused on the urban environment today.
Maya Pindeus:We can really feed into any camera in any city to make cities safer and, you know, more enjoyable.
Jeremy Silver:Give us an example of of, 1 of your customers and how they've used your technology.
Maya Pindeus:So we heavily moved in a essentially shaping the urban environment. So for example, we work with, virus, transport networks, feed operators and device manufacturers. For instance, Transfer for London is a partner of ours, where we feed into video telematics, dash cams or driver assistance systems. That means that our camera based system plugged into a truck, into a bus, into a car, for instance, is able to really anticipate what any pedestrian cyclist is on road use is likely to do. And if there's risk associated with that, We then help understand, is there likelihood of an accident?
Maya Pindeus:For instance, is there something dangerous likely to happen if someone distracted in the road, environment? And with that, the our customers can take action. We can prevent accidents. We can help really anticipate what is likely to happen. So that's a really, you know, focus use case on really bringing accidents rates down, really helping promote vision 0 in urban environments, in moving vehicles, for instance.
Maya Pindeus:And the same applies to roadside infrastructure where we're active in CCTV and smart infrastructure cameras.
Jeremy Silver:So you're you're providing predictive analytics in real time
Maya Pindeus:Yes.
Jeremy Silver:To operators. Amazing. How how fascinating is that? How big is the business today?
Maya Pindeus:We're about 30 people, now entering a new growth base. We're really excited about hiring at all levels. Today, we're about 30 people, you know, very focused around strong IP creation, a lean commercial team, and it's been a really, really fun journey so far.
Jeremy Silver:Excellent. And are you so you're seeking investment at the moment, are you?
Maya Pindeus:We are entering a growth phase which is really interesting.
Jeremy Silver:Excellent. That's that's super exciting. So let me take you back to the beginning though and ask you how did you get started with with humanizing autonomy? And I mentioned that that you'd been in some other companies and looking at things from another point of view, but what drew you to to starting your own business?
Maya Pindeus:I met my 2 cofounders, Ronig and Leslie, who was lead product and technology at Imperial College, who were, studying really, really exciting milestone called innovation design engineering, and it really led us to look at the interaction between people and the road environment, people and and machines, really, assuming that everything with a camera and wheels is a machine, in a lot of detail. We were puzzled that no 1 was talking about people. Everyone was talking about artificial intelligence. Everyone is talking about autonomous cars, automation essentially being solved. We didn't believe that's true, and it turned out not to be true.
Maya Pindeus:It turned out to be the people, the human element be crucial for any level of adoption. So that drew us to starting our own business. In terms of our personal backgrounds and my personal background, I had a journey from architect. I'm an architect turned into action designer, design engineer. And we know it's looking at people's interaction with urban environments from different levels, 1 of the macro scales looking and understanding how complex and fragile cities really are, but then also the smaller scale, looking at the ambiguity at the complexity of interactions when we look at a person and their environment, how to interact.
Maya Pindeus:This is what led me to move into humanizing autonomy.
Jeremy Silver:It's so interesting that the sense that you could equip computers and machines with a sufficient intelligence to be able to predict behaviors. We usually find it quite difficult to predict 1 another's behaviors, let alone to expect a computer to do that. What do you think the the sort of limits at the moment to this are and where do you think goes?
Maya Pindeus:Well, from a vision perspective, we see humanizing autonomy, powering the interactions behind the scenes. You know? A few years from now, not being able to walk through any city construction site, manufacturing place, more retail space without seeing or experiencing our technology behind the scenes, enabling the interaction. So that's the scale. The scale is any camera.
Maya Pindeus:When it comes to the limits of this, what is, what is really enables, what we really specialize in is understanding and inferring complex behaviors from video. As human beings, yes, it's difficult to understand 1 another's behavior, but we're really good at computing and and inferring what is likely to happen for what we see. So there's this statistical calculations going on in our head, and this really helps us to do a pretty good job. For a machine, here you can extract what is happening, but it's really complex to infer. And we've really focused on the journey from extracting, understanding, observing to inferring what is happening behind the scenes and what is likely to happen next.
Maya Pindeus:And the applications for that really are, you know, wherever there's automation, this is required.
Jeremy Silver:So you really are at the very leading edge of of innovation and and creating extraordinary new approaches to to quite familiar problems in a way. You talk about hiring. Where do you draw your talent from?
Maya Pindeus:1 of the first things with them when we started the company is really also start focusing communicating on on the employer branding on a piece, you know, communicating to potential team members, help understand the problem, help communicate the problem. So today we have a really, really good pool of of inbound candidates where we publish a new role. It's usually very, very good talent, good pool to draw from. In the early days, of course, it was our networks that helped us promote it. You know, we're very focused on on promoting diversity and and technology, making sure that the teams are diverse, not just gender and nationality, it's also age diversity and so on.
Maya Pindeus:And I think that really making sure that there's genuine focus around that really helped us position ourselves from a from also from an employer perspective.
Jeremy Silver:And where do you draw the talent from though? Is it from other businesses? Is it from academia? Or is it from other parts of the economy or the world?
Maya Pindeus:It's a combination of on 1 hand, we are a deep tech business, so that means that having really, really strong IP generating stuff, people that are the leading edge of computer vision of artificial intelligence super important to our business. So these colleges join us from a variety of sources, whether it's from academia or other businesses, really. What they all have in common on the technical side is a very, very strong in in shaping the future of AI. And we're really happy we're able to communicate it to a lot of prospective team members.
Jeremy Silver:It's interesting that the the UK has an amazing reputation for its academic AI work. According to some indexes, rates only after the US and China for its academic publications in AI, but we haven't quite seen that level of success, in the development of businesses. I mean, there are some great celebrated businesses like DeepMind, of course, but not very many of them compared with how successful we are in academic publication. Why do you think that is?
Maya Pindeus:I think to build, you know, large scale celebrated business, you need somehow a boost sky approach. You need to look at innovation, not at a short return on investment time frame, but really in a longer time frame because ultimately scale comes with time, and it also comes with jumping on on on on daring opportunities and really, really focusing on them. The US has been great at this. China is being very, very good at this. UK and Europe, tend to have a legacy of a slightly conservative look at companies, and that may be good at a at a at a smaller scale, but if it's really around creating leadership and worldwide leadership or competitiveness when it comes to company building and and promoting.
Maya Pindeus:That is, I believe, not the most sustainable approach.
Jeremy Silver:Is your aspiration of your business to grow it to a significant size then, or are you looking to try and develop something, highly acquirable by a big tech company in the next?
Maya Pindeus:No. It is it really is around, you know, this global standard we're talking about. We want to see humanizing autonomy, AI powering any device, any camera. That's a really multi geogroup, multi industry approach. So really making sure that we reach scale is super important.
Jeremy Silver:Fantastic. So let me ask you. We first came across 1 another in the context of the digital catapults machine intelligence garage program, which is a a support programme and an acceleration programme for AI companies. Just tell me a bit about your the challenges that you've experienced in developing your ideas, you know, at the earliest stage from early concept through to commercialization, how much support is there, do you think? And is there enough?
Maya Pindeus:Support is is so important, particularly in the early days when you have an idea, maybe a prototype, and you try to understand what the right path on your journey would be for you. So my own experience, when we started humanizing autonomy was all around finding networks, talking to people, and I think talking to people is the most important thing. If if ideas happen in isolation, there's a lot to be lost. So in our case, server support structure, of course, the catapults, machine intelligence garage, particularly, was super helpful when it comes to, really tech development and support. There were institutions like capital enterprise, of course, the universities and pro college and so on.
Maya Pindeus:And I think we're in a good way. I would say the UK is in a good, in a good path when it comes to support structures for early stage funders. There's obviously always more that can be done, but it is most important to encourage everyone having an idea to really, really talk and reach out. I think this is how how they actually become more tangible.
Jeremy Silver:So do you think there are things we need to do to improve that, to really ensure that that kind of business mindset is enabled in in as many people as possible? I mean, what else should we be doing, do you think?
Maya Pindeus:Well, I think so. I mean, I started at a young age. There's a lot to be improved in education, secondary education, and as well to implant diversity in people. The other thing is, you know, I'm familiar with networks, founding networks when it comes to universities, Imperial, Oxford, Cambridge, UCL, and so on. And then there we always felt we were very well welcomed and very well taken care of.
Maya Pindeus:Probably democratizing it more and making it more accessible to a wider community of founders of of people that might not have access to, you know, decent university networks, for instance, I think would be very beneficial in terms of fostering more innovation.
Jeremy Silver:It's really interesting. The role of the university as as the creator of an ecosystem around itself is so interesting and yet at the same time, the numbers of universities that we've got that are actually really doing that very effectively could probably increase, I guess. Is is that what you're suggesting?
Maya Pindeus:I agree. I agree. Yeah. I mean and I think it's a innovation pools and founding networks. Few universities have done, but I always focus a selected few.
Maya Pindeus:If you are in these networks, great. You know, we were always lucky to be in this network. We started at Imperial. We had a great network. Team players from Cambridge and other universities.
Maya Pindeus:That's a great start point. But if you don't have that and you still have a great idea and you want people to listen to you and to, support you, I think there's more to be done.
Jeremy Silver:And what about the investment side of things? Do you think that the kind of the beginnings of that, so the earlier stages of funding that are coming through from both the private sector and the public sector. Are we in the right place with those, do you think? Do you think that the the kind of level of public funding is helping the private investment community? How do those things play together, do you think?
Maya Pindeus:I think that the level of public funding can really be increased. I think there's there's good things that happen, you know, with Innovate UK funding and so, but I think the barriers are high. There is a high, that applies to innovate UK funding to EU funding and so on, particularly in the early stages, we're really trying to navigate the landscape. I don't believe it's as accessible as it may seem or as it may want to be or intend to be. When it comes to private funding, we're seeing a lot of kind of precede seed investment in the UK.
Maya Pindeus:So I think that is really going into the right direction. I think from the time we were at this stage, you know, 3 years, 4 years ago to now, I think there has been quite a lot of increase. So that's that's great to see. In terms of public funding, public private partnerships, I think there's there's level 4. No.
Maya Pindeus:There's always more that can be done.
Jeremy Silver:And in terms of industry adoption and of companies themselves, getting their heads around the use of AI, finding the right starting point,
Maya Pindeus:Is that a challenge? I mean,
Jeremy Silver:when you're going out and presumably you're engaging all kinds of companies across a whole range of different sectors and transport and urban environments is obviously a key focus for you. But what's your experience in terms of how traditional industry is responding to the the opportunity of AI?
Maya Pindeus:Yeah. Well, everyone is always very interested in AI and knows they want to use it, but every startup is resource constraint. Every side is to find the right path as quickly as possible. And when it comes to customer acquisition, then it's around understanding who is waiting to see adoption happen and then essentially jump on the train, or who is actually proactive, who are the customers, who are the organizations are really proactive and want to feel competitive pressure, feel that they need to act now. And and you'll be surprised, you know, some of the very traditional seeming, industries or companies are often the ones that are moving really quickly, whereas it's surprising often where you find that match.
Jeremy Silver:Do you think that the level of interest from industry is balanced by the level of investment that industry is making? Or do you think that industry is still finding it challenging to make investments in this area?
Maya Pindeus:I think there has been a lot of investments in this area. So very often the way it works is that an industry, well, a corporate may have a separate fund that does, investments in the area and then aims to connect the company invested into the corporate, essentially. So I think a lot of investment have been done. But it's probably I mean, AI is definitely still on a watch list for a lot of these. When it comes to working with corporates, I think every start that goes through the pilots POC phase and so on.
Maya Pindeus:And then, it's really around making sure that you, again, understand who the right customer is for your solution at this time. So that you move on, to to kind of wider and bigger engagements. And that's something that obviously is true to us. That's even as you turn in pro to every AI starter, make sure that you really navigate that steps very, very consciously. Because not every corporate is ready.
Maya Pindeus:Yeah.
Jeremy Silver:I mean, everybody has a challenge in in selling a new product, obviously. But the flip side of that is, when I was asking about investment, I was also thinking about the sort of investment that the companies are making themselves into their own businesses in adopting the technology. And I'm just wondering, you know, it was really interesting to say to hear you talk about the the sort of the early adopters Mhmm. And the sort of the the skill of of identifying who they are and going for them. But do you think there's more that needs to be done to encourage more early adoption?
Maya Pindeus:Definitely. I mean, businesses need to understand, you know, the value that AI would bring. And very often, this is internal investment of which internal investment fluctuates. So things like COVID, things like, you know, external events that may move, you know, invest into different to different phases. The other thing that I believe helps are, again, there where the public can have or the public private partnerships can really have an impact in helping well, through projects, through innovation, helping businesses take their time to really understand how to use new technologies internally.
Maya Pindeus:Very often, they're ready to do so to explore, but some just need a bit of extra help. And I think public private partnerships are exactly the sweet spot.
Jeremy Silver:And do you and do you think that your business has been held back at times because the companies that you've been engaging with just haven't had that level of understanding and and haven't made enough internal investment themselves to be able to embrace what you're offering?
Maya Pindeus:Not necessarily. I think what we adopted very, very quickly is this level of, really making sure that we understand, you know, when in our pipeline and where to navigate first. There's a huge pool of companies that could use and will use that technology, but who will do it first? So I don't think it's holding back, but it's about on both sides, making sure that you're smart about how to approach it. I think that's the key part.
Maya Pindeus:Not everyone will be, particularly when it comes to really, you know, new technology that serves a really existing market, at the same time, creates a new 1. It is really important to be quite quick around, understanding who to go to first and who to work with first.
Jeremy Silver:Yes. Absolutely. Now I know that humanising autonomy strives very explicitly to be inclusive and to create equality as part of your core business values. Why is diversity so important? Why and why is this a priority for your business?
Maya Pindeus:If you want to build technology that changes society, the impact society, the people building it need to be representing societies. But it happens way too often, way too frequently, and it's quite quite prevalent that only a small part of society is is building technology, and then essentially mapping it onto everyone else. We believe this approach is from, particularly with humanizing autonomy is about helping machines understand people, all people. So that's essentially the first 1 was, by diversity and inclusion is incredibly important, but then it's also around team culture. It's around creating a creative environment where people learn from 1 another and learning from someone who's very like yourself, you know, you can learn something, but, of course, you will learn much more if you have people from different interdisciplinary backgrounds.
Maya Pindeus:It means different studies, different prior careers, different nationalities, different cultural backgrounds. We actually found that to be a huge enabler in their own company, and it just makes an environment as much more fun and inspiring to work in.
Jeremy Silver:And do you think that the the kind of values that you're bringing in that way, are they are they reflected
Maya Pindeus:definitely our intention. I would hope. I I definitely would hope so. Ultimately, it's That's definitely our intention. I would hope.
Maya Pindeus:I definitely would hope so. Ultimately, you you build a business, you build a team, and that team essentially builds the technology that is then being brought to customers and ultimately the end customers, everyone, you or I, then that sense is so important to be very, very conscious about how to build it. And there's a big responsibility in building a business, particularly these days. We're talking about AI. We're talking about ethics.
Maya Pindeus:We're talking about inclusive teams. Equal representation is a lot that needs to be done in our society. And if you like, when building a high growth business, there's a lot responsibility and opportunity here as well.
Jeremy Silver:It's fantastic to hear you say that. And III mean, it's so interesting, obviously, that AI has the ability to translate a set of values so rapidly into all aspects of a product. Do you think about that when you're designing algorithms and you're thinking about the way in which the software itself is making assessments? Yes. Absolutely.
Jeremy Silver:Where you have I mean, how do you address issues like unconscious bias and so on?
Maya Pindeus:Yeah. There's a few ways to address it. It's a really important part. On 1 hand, we're really focused on the ethical piece of AI. Ethics is a big word.
Maya Pindeus:Right? What does it mean with regards to algorithms? On 1 hand, it means that the data used is very diverse, is is robust, is big, represents different environments, different situations, and is constantly quality assessed. So that's just 1 big part in order to preventing a certain unconscious bias. The other 1 is that AI traditionally is what people may call a black box, like 1 big model not transparent, not really understandable.
Maya Pindeus:Again, we don't believe that's right, so we build a modular approach that is interpretable, where you can always understand the decision making system. So those are things that are all built into the technology, decision making, understanding interpretability, the data is being fed, and then, of course, pre proactively work with privacy and tracking, tracing, and so on. So that's all pieces that are part of the software architecture, ultimately, and that how we incorporate ethics in in how we build the technology.
Jeremy Silver:It's absolutely fascinating. You've you've obviously accumulated an incredible wealth of knowledge and experience both of how to build your own business but also the innovation ecosystem that you're working within. Just as we come towards the end of this, what what advice would you give to other early stage entrepreneurs who've got great ideas but don't necessarily know where to go for support?
Maya Pindeus:I like to say, you know, be be loud, and what I mean, but I don't shout around, but essentially, developing ideas and isolation just doesn't work. And what helped us so much, and we're still, you know, students with an idea considering, just thinking of starting a company, not really knowing how to do it. What we've done is we spoke to everyone. We reached out to potential customer, reached out to potential investors. We started finding networks, that would help us in this kind of early stages of the journey.
Maya Pindeus:So I think the kind of be loud and test your ideas, as early on as possible. Just don't be shy about it. That's what helped us a lot, and I hope it would help others too.
Jeremy Silver:That sounds like brilliant advice to me. I've got 1 last question for you, which I've always ask at the end of, this podcast to all of my guests which is we've been talking a lot about innovation, about the leading edge of creative thinking, What's your favorite innovation?
Maya Pindeus:What's my favorite innovation? That's a really, really good question. I may answer something very down to earth. For me, 1 of my favorite innovations in urban environments is public transportation. Something that helps connect people, connect communities, does not require a lot of machines, a lot of, pollution, a lot of space taking up in a city, but actually is efficient, is is affordable, and helps us get from a to b.
Maya Pindeus:So that's very, very done to earth. But I think that's something that's really on top of mind, particularly today. Right? We're talking about sustainability, about making fast, you know, growing cities, urbanized environments, just better. And I think that's an innovation is often forgotten.
Maya Pindeus:Really, really important.
Jeremy Silver:Brilliant response. Thank you so much. Well, thank you for joining us this week, and thank you to my guest, Maya Pindais, for telling us all about the future of AI technology and the challenges of growing your business.
Maya Pindeus:Thanks a lot, Jeremy, for having me.
Jeremy Silver:That's all for today's Supercharging Innovation podcast. Thanks for listening. Join us again for the next podcast episode, and make sure you subscribe to us on Itunes or Spotify. Other podcast distribution platforms are, of course, also available. Goodbye.