welcome I'm your host Conrad Chua if you're new to the show you can put your questions in the comments field whether you're watching us on YouTube LinkedIn or Facebook you can start off by putting in the comments to tell us where in the world you're watching this from today now the big story in 2023 is already clear it's AI chat GPT has Unleashed all kinds of questions about the impact of generative AI whose jobs are on the line and how should we be working with AI or robots but chat GPT is just the most visible way that machine learning and AI are already being used today's guest has built a company that air on AI hardware and a business model to do robot grocery deliveries is co-founder and CTO of Starship Technologies the company that has grocery robot deliveries here in Cambridge elsewhere in the UK and in college campuses in the US so thank you so much for joining us today RT hello everybody and uh hi Conrad and thank you for inviting me here we're also joined by shinichi nikuni an MBA Alum from Cambridge who is a founding managing partner of Nordic ninja it's a VC fund that focuses on deep Tech in the Nordic regions and they are also an investor in Starship Technologies so welcome shin hi nice to meet you I'm very happy to join this one other campus judgment school and as I said I mean from Japan but I'm joining here from Helsinki Finland looking forward to this thank you great so Arty could you start by telling us what is Starship so Starship is a company that is developing and operating delivery robots delivery robots that go on the sidewalk like you see on this this video here right now this is replaying what our robots have been doing right now we have actually done done more than 4 million deliveries uh and uh our robots go on the sidewalk and they deliver groceries and food to your doorstep and we do typically about like 15 minute deliveries in UK we are live in about I think eight cities in in UK and tons of places in in the US and elsewhere as well so this is really happening uh we are We Are automating The Movement of things in the world and RT there's obviously been a lot of interest in autonomous robots driver driving Etc how did you you or Starship decide on using autonomous robots for specifically for deliveries right we started the company eight years ago and already at that time I think there was a lot of talk in the world that that robots are coming robots will be will be automating a lot of things and so forth and uh and we thought okay that is really true and you know what can we actually do with robotics and there are a lot of robots being built in the world not all of them I would say have actually a good scalable business models where where but really you know you know business can be can be made and we're actually thinking that what are the what are actually the large scale use cases for Robotics and come to this understanding that delivery is is one of them one of the few places where actually robotics can touch everybody's lives it's just a massive Market uh people still need things not everything not all goods are virtual uh people need things to be delivered most and most importantly food and groceries this is not going anywhere you know people need to eat also in the 21st century or 22nd as well and we can automate the movement of things in in the world it's just a big Market that's why we selected that hmm and is you know your robots zip around the streets do they is the learning that they get from being deployed in one city transferable to let's say a new city that that you start up operations or do they have to learn everything all over again it's actually a lot a lot of that is transferable there are some differences between various cities and countries that we have also learned over time like you know like most maybe a most trivial example like the if you look at the traffic lights the traffic signals you know Walk Don't Walk signals for example they are different in UK versus us for example which is the colors are different the language how they how they laid out is different so if if you're using machine learning and AI to for example detect the state of the signal that is it walk or is it not work for example this needs to be trained separately for like UK and us for example right uh and there's some some other differences like that as well but by and large still the the all of the learning is most of the learning is transferable like if a robot is is driving on a sidewalk and there's a pedestrian approaching and the robot needs to select that okay do I pass over the left do I pass on the right or do I if slowed out or something like that all of that is the same so 95 is is the same and this is also a reason why this is a scalable technology why it is the case that we have been able to deploy right now in in 40 or more locations in the world it wouldn't be like that if you would need to develop new robots for every city that would be a lot more difficult does does this sort of delivery work for all kinds of cities though because uh I come from Singapore shins from Japan and over there it's much more heavily built up very urbanized lots more skyscrapers and people live in flats for example is this is Starship the kind of thing where it will struggle in those kind of environments definitely different sort of automation is useful in different environments all robots for example are not designed to enter buildings or you know write up elevators climb stairs that's not what they are doing uh our the current robots that we that we have are most suited for this sort of you know European or or U.S Suburban uh or like mid-tented Urban type of environments this is this is where our robots really shine um they work in a way that the the that you know in the environments where people live in in housing which is like individual for one family or maybe for a couple of couple of families then the robot pulls up on your doorstep essentially and you go out you as a customer you go out you open the front door and you take the things out from from the robot and the robot says you know thank you for your delivery it's a really nice experience for people to actually receive a delivery from from from our from our robots in different sort of environments like for example high-rise buildings different sort of robots you know might be might be might be useful so it's not going to be just one size fits all but the our size or our model that we have is actually applicable for a lot of us in Europe at least and we're definitely also looking at at Asia as well there are I think a lot of environments in Asia where our delivery robots as they are right now would be perfectly applicable Arty um why do supermarkets or grocery you know supermarkets want to use Starship robots because quite a number of them already have uh big fleets of deliveries that vans that are operated by humans they have they have that and this Services obviously exist you know Grocery and food delivery services do exist on the other hand it's not an easy business it's not an easy business for them in particular it's very hard for them to make any money on this it's very hard to make the ends meet and the reason being is essentially that it um it works as a subsidized business it works well as a subsidized business if you look at you know for what for example what is the minimum wage or what is the living wage that people you know want to earn and and then you you calculate in the fact that you know in one hour one delivery person can do maybe two deliveries on an average and then you divide your your desired hourly wage you know by two and think that our customer is willing to pay that much and they are not they're often they are not so the unit economics wise uh the delivery even though it exists right now the companies that are operating this are struggling and uh our robots offer a better unit economic solution for some part of the market we cannot be not be taking all of the deliveries obviously our robots are not you know large enough to deliver some huge large packages for example they just don't fit into robots also distances are robots are not really designed to transport something from one in one end of the city to another you know it's more like this you know one or a couple of miles you know radius uh so so our robots are not taking all of the deliveries but our robots offer a solution to the Grocers and to the delivery companies how they can automate and and make the deliveries work in a more economical way and also more sustainable way sustainability of the deliveries is actually super important if you think about you know how much the CO2 emissions are caused by not the people doing deliveries it's not the people that they that is important there but the cars that they are driving or whatever vehicle that that they're riding our robots is so lightweight that it uses so little energy it uses as much much energy as you know like boiling a cup of coffee to do to do a delivery so it's actually the most environmentally friendly way to get your deliveries um it's it's much much better in terms of the emissions than than any vehicle um there's a couple of comments and questions coming in but I'll hold on to that I wanted to ask Shin first you know you invested in Starship what was it about the business model or the industry or the company that really Drew you to invest in in the company yep thanks and okay already touched some important Point their sustainability it's about also energy but it's also it's also about the people we see it's the chef after Kobe everyone started using like a home delivery delivery service apps it's about most mostly I think especially in nordics a lot of the actual tasks of Affairs by like immigrants and maybe they are they are paid they are paid some but not fully and it is hard to maybe this is not kind of sustainable job we thought and of course there's inflation in the wages will be increased so we are seeing uh uh by evaluating the Starship in the DD process that there will be in some years there's a moment that actually a robot DeBary course could be lower than the human body because in some years then we thought then this on top as as he mentioned sustainability this is also good for the people because people people don't need to need to do this kind of like a kind of repetitive not creative tasks anymore which robot can do easier robots are good at so that's why okay in some future in quite near future there's a moment that this kind of robot could be filling up more like a delivery tasks and also this is also good for the Suburban areas of course we admit I fully agree with acti that maybe this is not replacing all the table is but still if you go to Savannah areas still the nearby options can be limited even like a Tokyo around Tokyo you have a different options but actually it's just like a convenience store like already you can buy a lot of things but if you've got a bit still you don't have much options even for the delivery so that's why we thought that robot could feel a lot of larger areas and by using the autonomous driving autonomous assistance great and I think it's good now to move into some of the comments and questions so the first one actually is more of a comment and it's from Carrie who lives well here in Cambridge and her kids love the robots they've nicknamed them Kevin my 11 year old daughter calls them badges I think that's what they're called but I wanted to turn this into a question to you Artie which is at least when I walk around Cambridge I see these your robots and I see the reaction that children adults all have they all love it it's so cute and sometimes they treat them almost like a pet or a young child especially at a road crossing and they're like thinking should I help this robot get across the road was this part of the design or the technical process when you built this to make them look more cute and think of how they would in a way how humans would react to them right great great question and uh especially you know at the start of uh our company when we founded the company uh definitely there was a lot of thought process on how would people react to robots on the sidewalk we didn't have any you know data any experience you know in in this you know you know because you know robots have just not been used in public spaces or or sidewalks before uh but we definitely put a lot of thought into this uh and uh and and and and basically thought that you know do we want to make the robots look like really cute like you know let's say Disney like do we want them to look look Industrial uh maybe like Boston Dynamics uh or or do we do we want the the robots to look like neutral which was which was was actually what we settled on uh or maybe another alternative would be you know very futuristic you know like a spaceship or you know it's like you know some buzzing sounds and you know something you know cool like that right and we actually decided on this sort of sort of a more of a neutral look uh and we definitely wanted to avoid obviously that people would have a negative reaction to to the robots that obviously we did we did not want to have um uh but we we didn't actually predict how well people treat robots how much they are actually in love with our robots and and how much yes they they treat robots kind of kind of as bet and uh in particularly awesome also mentions that you know you know hey can I help the robot this is also a really interesting phenomenon around robots actually do not really need help from pedestrians right but people are so eager to actually you know see that I is this robot stuck you know can I actually get it healthy to get unstuck can I push the road a little bit and and then then actually you know we have actually programmed our robots you know to between in these cases actually when they when somebody helps the robot and actually the robot says thank you so you look at you know this is actually this is a human it's actually a great experience you see a robot on the street and you help the robot and the robot says thank you and it's an experience right you know I mean 10 years ago you could never have an experience like that this is like something new in the world that you can experience with you which you couldn't couldn't have before well and I think Kerry later on said that uh she called the family now calls the guy who collects them at night the modern Shepherd um so a couple more questions here I think there's one we'll do this very quickly Richard is asking about how do in a way how do you compete with let's say these very fast deliveries there was quite popular at the time during the pandemic uh I'm thinking like gorillas and get here do you feel find yourself competing on the time yes and no so definitely yes people prefer getting things you know kind of instantly and this is also a reason why we developed the developed this service because for for a delivery that is you get something next day just Logistics wise you can plan this as a milk run you can plan this in a way that that as an operator you load a bunch of these you know shipments into a van and and the person you know drives this band and you know stops every every five minutes essentially and you know drop something off this actually can be economical uh the Euro economics with this human delivery become really tough when things when the expectation is the sort of instant delivery or 15 minutes 30 minutes 45 minutes five minutes delivery and this is the this is the the thing that we developed our robots for so we we our robots robots driving time typically from the store to the you know to the customer in UK is 15 minutes uh so so we are we are doing these these sorts of deliveries uh the uh we are actually specifically delivering from typically from the nearest uh grocery store uh or or of some of the nearest grocery stores to enable the quicker delivery times absolutely the world is is is is moving towards that but that actually makes it the the more quick it is the harder it is to make the unit Economics work with the human couriers and as a customer of one of these um 15-minute delivery ones uh I I can totally see that given how much uh vouchers they were giving me to entice me to pay to use their service and I think the company that used to service me um they ran they closed their operations in like three months and I think we've got someone here on LinkedIn who basically thinks that this agrees with you that these 15-minute deliveries it's it was never sustainable and it was really something that came up when interest rates were low I I would call it I think it is actually sustainable with robots oh okay yeah but then the model of having a guy cycle to my house in 15 minutes was not sustainable yeah we have this other question which is Artie how do you approach government or public Regulators when it comes to expanding um do you have to speak with each City the the city mayor or the city public office as you expand right we always make sure that our operation is legal and is in line with the with the expectations of the of this of the cities and communities where we deliver we are not the company operating in such a way that we just drop our robots uh without asking permission or or anything and then pick up Species later that's not how we how how we operate uh and uh and uh we we have relations with all of the Cities we are right now operational in eight cities in in the UK all of these cities have expressly allowed uh us to us to operate and obviously we are talking to to many more cities as well they have there are also uh a lot of the regions and countries in the world that have actually changed a national law uh in order to allow cybercrombers to operate uh like in in that has been the case in in Estonia for example and in a couple of other countries as well I think in Japan also the the recently the laws for us to to to to allow operation of sidewalk robots in the U.S about half of the states in U.S have actually passed laws to specifically allow cyborg robots to operate you know essentially you know inspiration from Starship essentially they're actually not operating in all of these states uh but they're operating in many of them uh so The Regulators uh have definitely decided that this is a this is a good thing to do this is a worthwhile thing to do and uh generally uh obviously Regulators want to offer new uh services to to to to to the community cities generally generally love it and uh and some time ago uh like four years ago five years ago where we were just doing our first deliveries and we were just starting out our operation we were defining inventing a new category then for a lot of The Regulators there were two questions that okay what about safety have you proven that this is safe how safe this is right now now when you have done more than 4 million deliveries and the we have a good safety record you know people see that that this is an inherently safe technology and especially the robots on this on the sidewalk this is not like like a self-driving car like everybody knows that you know you know the cars I mean accidents could happen in theory obviously the technology is built to be safer than humans but still could happen uh but with a sidewalk robot like ours it's just you you can you can see inherent to that it's fairly safe technology even if the robot collides into Collide to the person the person doesn't really get hurt or this is it's not uh it's not a of course you know with unfortunate circumstances potentially uh potential accidents can happen but uh you know but but people see that it's a safe technology a follow-up question um I think just zero in on demo would be you talk a lot about the safety aspects of Regulation has there been any um questions about privacy aspects because you've got sensors cameras on the robots definitely definitely the the uh also the gdpr definitely has been you know influencing our work and also the way how we have built the technology uh but but ultimately this is solvable ultimately it is it is possible to and we have done that to uh to build our technology in such a way that the that that that these concerns or this uh these questions are answered um and uh there's a lot to do with uh with the the with like retaining data where does the data get stored um and and where is the processing happening and so forth like for example our cameras are not actually high resolution cameras they they we don't actually need that we we don't need cameras that are are are are accurate enough to to like record people's faces for example our cameras are actually actually too blurry to do that uh they don't need that because they are designed to identify that hey there's a car coming on the left you don't actually need a high definition camera camera for that so these things we have all worked out uh uh I would say for for Regulators of all sorts of uh autonomous Technologies you know your safety has been probably the number one concern but this is also solved for us yeah I mean at one point uh from the investor side and it was very clear that from the beginning this is only for the lobot a delivery not for like a security robot like of course theoretically the robot can be used for security purpose then but you would lose the value proportion clearly so as an investor was good that the management is really committed also to make this data value automated but not for other things hmm we have a question from actually a faculty member here at Cambridge so Virginia she teaches a class about the future of work actually so I think this is why her question is for organizations interested in using Starship does the company Supply Technical and coordinating support or do you expect firms to hire and expand their own staff skill set to deploy this technology absolutely good question and and as we are signing up new partners a new new you know commercial customers you know for our service these are also the things that we are we are negotiating with them uh generally we are a turkey solution we we offer we offer for example things like you know if you deploy our robots the robots from time to time they do need maintenance for example anything that moves sometimes also breaks we need to lead to service the robots replace the parts uh and and so forth this is what Starship is doing so uh uh our our customers our business customers like the Grocers they do not need to do that um uh and and other things like things like like that as well there are there are actually a number of things in our service which require quite you know deep technology to operate like the mapping of the Cities analyzing you know where it is safe for the robots to drive um uh where is the most economical to drive uh setting all sorts of technical parameters in our robots you know this is all all that that our company is doing and the the uh our customers our partners like the Grocers they just want to get deliveries done they just want to get something delivered from A to B and that's the service that we are selling and now there are quite a number of questions about where where can you go right where do you see Starship scaling and what other application or problem areas do you think you'll be going towards next is it construction Health other Industries right now the most of our scaling is um I would say horizontal or it's essentially that you know we are we are covering eight cities in UK that's not all of the UK and even if you cover all of the UK that's not not the whole of the world so we are expanding in the number of cities that we cover in a number of sites we operate also in in U.S and and elsewhere
um uh Asia like we mentioned before uh we could we could definitely do completely different sorts of applications as well like uh you know we could go into construction for example that is that is theoretically possible but the robots are not specifically designed for that um and there's a lot of opportunity with just food and the grocery delivery that we are doing right now and another sort of more general question is where do you see this sort of AI machine learning in the next five to ten years in terms of businesses or in terms of individuals and Artie and shin both of you can can chip in on this yeah sure maybe with us everything this is basically obviously on the uh so we see that GPT generative AI things and this would be not depressing it will be helping a lot of the some creative works of the human beings that would be the one thing but for this physical world it was still just some like maybe we might still need some years about five to ten years is good timing for like because ultimate driving hype maybe it's gone already but still some companies get fully funded companies like Starship and others we are basically they are also shipping The Edge and try to achieve the Optimus driving and also my automation with those kind of deliveries and not necessary for groceries but other more other chemical tracks and buses so still in the business context of this would be individual would be I think that people have to adopt and I think people already young younger Generations are already adopting the new technology very quickly so I think how we work and how we even commute how we move everything will be of course climate affected but business has to be in a sense especially large organization has to be very agile but also the startup has to be much we match up with the new things right I think I think you know especially in in the recent months you know with uh with the popularity of chat GPT you know you know you know specifically I think I think a lot of people are also overestimating the short-term impact of that um I think some some people are more thinking that oh you know is Chachi PT going to take over my job I don't think that's going to happen like not immediately it's not just that we can just you know take chat GPT and replace you know any any person you know with uh with uh with with a robot like that that doesn't work but longer term like let's say you know yes five to ten years or or even longer I'm sure AI will have a quite significant impact uh the you know specifically you know if you if you take out you know specifically these you know generative AI things essentially there there is there it automates certain kinds of things it does certain kinds of things really well but certain other kinds of things it doesn't do you know you know too too too well too well at all so uh I think also in uh we will need to figure out um how can we use this technology in such a way that people are doing the things that they're doing best and the AI is doing the things that AI does best I think you know chat CPT specifically is I think not well set up for that for that sort of Separation but but you know image generation AI actually might be it actually might be if if I'm doing a presentation and I need you know a backgrounds for my slides um but but if I have if I want to you know design a nice house a building for example and I have some specific requirements maybe that's not what you know what the AI right now would be doing but maybe in five years to do it yeah one other question about um Starship and the business model from Tien which is um obviously deliveries went through the roof during the pandemic so now that things are getting back to normal has that have you seen enough you know an impact on business for Starship so we we also saw I think what a lot of other companies companies that that were doing delivery you know you know saw during that time that uh that when the pandemic started then uh obviously the demand went up people people started started doing more more there was more interest in in getting in getting our deliveries and then when things are more back to normal then there was a bit of an opposite Trend but things didn't go go back this to the same level they went back only a little bit and also uh at Starship you know this is a technological business we are developing the technology further all the time at the start of the pandemic that was three years ago three years ago I think our technology was not performing as well as it is right now it wasn't 15-minute delivery then it was maybe 20 minute delivery okay now it is 15. and now everything works better in our service so people also see that so so we're seeing an increasing trend of increasing interest in our in in in our service not a decrease in one and um auntie I wanted to shift a bit to thinking about startups and deep Tech startups and you've been involved in well first Starship but you also in that early founding team of Skype if you look back is is there a Playbook or a pattern in terms of how these companies that Grew From a very strong technical background started to really flourish and become strong businesses right I think there are definitely some commonalities I was one was one of the founding Engineers of of Skype around the table when Skype was was founded I was the chief technical architect and built a lot of the early early software at that at Skype um as well uh and uh um I think you know with the there are some similarities you know between you know Skype and Starship in the way that we both we were both using technology to do something that wasn't kind of possible before uh and the just like with Skype we kind of we popularized the concept of people could use internet to do calls and also chatting as well uh we were one of the Skype was one of the first chat apps essentially um then then uh and this this was was kind of the world first at the time some of the base technology existed like voiceover variety existed also before just like robotics existed also before Starship right between the first company to popularize robotics in public spaces and that and Skype popularized Voiceover IP as a mass-market technology so we when when we found that both of these companies we were product Centric in the sense that the whole motivation as in like also my own entrepreneurial Journey why why haven't started companies is it that because I want to make huge amounts of money no not really I want to change the world and I'm thinking how can I use technology and my technological skills to change the world and offer the services that were not possible before I I am not really interested in seeing that you know hey there was there's this super successful startup in the U.S and I'm now you know copying this in Europe for example that's not my favorite butter that's not what I'm doing I'm trying to do something which is completely new and I'm trying to use the tech to to do that uh there there might be other kinds of there are other kinds of entrepreneurs who have whose driving force is different uh but this is my driving force and shin you obviously have seen a lot of deep Tech startups in the Nordic region do you see a certain pattern in terms of how these companies develop and scale the way that RT was talking about I think from my perspective for the Nordic baltics origin the Skype success the successful Skype was very important because maybe 100-ish people run the playbook for how to scale globally and how to get exit fully then I think that a lot of people like USD started a new company like that then there's some then also this is also adding the new Angel Investors like somebody who started a VC but who can understand the technology company deeply so this is this is very important step for the conference I will see similar not exactly same patterns but we see a lot of business Founders and the technology Founders are coming together to grow a deep company but still if I see the Nordic about Investors there's not many actually like a deep Tech investors who can put especially the hardware related Technologies but still maybe I don't see the majority but but I still have quite many this is still like to invest only in the software but it is changing especially if you consider the impact to the society impacted economy we have to to solve that not only the software related problems but also have to subnet something related to the hardware which is essential for our lives and human being as a human being and RT and Shane I wanted to ask another question which is in our business school we I see so many graduates who want to work for Tech startups what advice would you have for a business school graduate whether it's an MBA an Executive MBA who wants to make that kind of career transition maybe Shin if we start with you and then then go to RT yeah actually I co-founded the startup from the Cambridge other campus pin off just after MBA with my friends at Cambridge Department of Chemistry and Engineering the company was in relation to the hydrogen rated technology and it was not good timing to be honest because it was like 2014 15 just the end of the Green Tech bubble so to say so timing wasn't applied but but the company survived but unfortunately I have to leave but still my advice if I can make any do that I think we should jump on some like early artists counseling the find of other founder to create a company then you can learn something a lot a lot actually that learning helped me to how we how I should behave at the investor side even though I became and I became again the founder on the investor side and I I really wanted to help like that kind of div Tech Founders like afti and tried to they try to trying to change the world [Music] right my advice would also also be actually actually the same that that tried to join an early team of of of a startup I would actually not give the advice of you know straight out of University to go and find and found and found the startup uh on your own you can do that of course nobody's nobody is forbidding you to do that but your chances of success are higher if you actually have worked on an existing team team before uh and uh startups I think the internal life of startups these like early stage startups are very different from more established companies I would say everything is much more dynamic and much less systematic in the sense that decisions are done very quickly there is very high uncertainty that we don't know are we going to get this customer next month or not are we going to deploy in Japan or not are we going to you know um you know manufacture a thousand robots are we going to manufacture 500 robots there's a there's a lot there's there's differences that there's decisions that decision points that that that need to be then executed super quickly in order to make these things happen we can't plan ahead for a year or something like that or we couldn't plan ahead for a year when we were very very early stage now that we're actually much more mature we can actually plan ahead for a year there's some projects that we are planning right now ahead for a year uh about five years ago we could only plan ahead three months I would say and it takes a certain kinds of people and mindset to actually survive in an environment where you can plan ahead for just three months Artie I want to follow up on that point about how you say the in the life cycle of a startup in the beginning you've got a small team you need to work really fast there's not much structure to things but then once you grow you get more structure you can plan ahead and you need different kinds of people or different kinds of mindsets and skills how do you see um from your own experience how you to manage that kind of transition from a different you know from that very small you know we're just scrambling scraping through to now we can we need to think longer term so that people like shin would invest in US hmm I would say it is this transition is continuous it's happening as the company grows and it is a lot of management it which is ultimately communication so a lot of communication alignment between people but gradually also as the company matures then you know actually people also change you know some people join the company you know very early on and they stay in the company for four years and maybe they decide okay now they move somewhere else and the company hires somebody else who is maybe experienced in more mature companies in the place of that person right sometimes also people also grow or change they change their own way of of thinking and working like I myself as a Founder you know I was I was at the company where we were three people and we were much more Dynamic and much more it was much more uncertainty than than there is right now and I am now a person who is leading projects where we plan ahead ahead for a year uh maybe in five years I will be the person who is planning planning ahead for two years or three years have you seen um what have you seen in terms of companies that have made this successful transition between different operating modes what really worked for them it's a very good question but we always focus on the team and because especially like from The Fast funding teams in a fast customer like a fast paying project is very very important how they then how they can really build on the business model based on that the continuous like a girl scalable business model is okay so in the sense maybe the uh what I would say especially in terms of deep Deck Tech founder and maybe the commercial founder maybe this kind of combination could be very interesting because I there's some like genius people who can do both but other reality as I have a time limit like 24 hours like a 63 65 to five days so in this sense if you have a strong ties between the two three founders who can totally different prayer different low key role but still a tight correctly connected very much very much then I think I see the clear pattern then as an investor we like to see even though we are investing like as a ninja we're missing a series a series like Starship but we'd like to see they know the company the founders already even like from beginning like from field stage so that we can stay we can stay keep in touch and communication as an artist said also communication to the investors is important so that we will make sure that okay this is a live team even though there's some mistakes some setbacks of course that is happening because the people are not always perfect but still we can see like okay how they can solve the problems this is more important to understand when we decide to invest well just very quickly one last question from the audience so Stephen asked what advice do you have for other Hardware startups raising Capital to scale um should they use VC or debt or other sources you know Shin do you have a view on it let's still see around maybe rer is this they are currently in the uh a lot of the governments putting some like a subsidiary grants this should be leveraged first then the series a ish stage I think still the equity will be the most positive you have to find out right we see who can do that who can be a foreign on the risk of the hardware maybe after series b or later if you can really build on the business model and based on Hardware then you can make a forecast based on how much this Hardware business can generate the cash flow then you can leverage more like a project Finance model how do I buy Hardware asset yeah Auntie anything you wanted right right we completely agree of course but everything what what she said you know like Beyond you know serious B essentially it becomes you know finance and based on financial metrics regardless of whether it is whether it's hard Hardware or not essentially um overall definitely Hardware startups are complicated to build also complicated to fund uh I would I would give advice to have have your numbers right and have your unit economics good hmm all right well thank you so much um RT and shin for sharing your stories and your experience and insights into startups and of course the Starship uh journey I think we all really enjoy that and I'm waiting to see when Kevin or the badger next comes by my street and I want to thank all the audience as well for with your questions and comments I'm sorry we couldn't get through all the questions today you can join us and our next episode where we will look at Healthcare specifically um what would Healthcare look like if certain parts of it could be thought of or reimagined as utilities where things can be commoditized and delivered at scale so we have Professor Stefan schultes will join us and we'll also have Carter dredge a current student in cjbs he's also the lead futurist at a non-profit Health provider in the U.S so please join us on the 24th of Feb at a slightly later time of 2 45 PM UK time so with that I just want to thank once again shin and Artie and I hope to see all of you in two weeks time [Music]
2023-02-17