Speaker 1: Hello everyone, Thanks for joining us from where where you are.
Speaker 1: Welcome to another new episode of Startup Still Say Today.
Speaker 1: I'm super excited to welcome Vishnu Subra Money into this podcast.
Speaker 1: Vishno and I have been talking on and off the
Speaker 1: last three months or so. We first met on LinkedIn
Speaker 1: through a common post, like many connections these days, and
Speaker 1: I also had a great opportunity to meet him in
Speaker 1: person while I was visiting India a couple of months ago.
Speaker 1: So Vishnu was super kind enough to invite us to
Speaker 1: his offices, his studio, his lab which he'll tell us
Speaker 1: all about very soon and talk about his journey. And
Speaker 1: I thought it was fascinating in this current world and
Speaker 1: that we live in where anything and everything we turn on,
Speaker 1: whether it's news or a podcast or whatnot, everybody talks
Speaker 1: about AI. And we thought, Okay, why don't we bring
Speaker 1: Invisioner here and talk here from him about what he
Speaker 1: is doing in the world of AI and Soshioner. Welcome
Speaker 1: to the show. Hi untanny, thanks for inviting me to
Speaker 1: your podcast. I hope you enjoy the session.
Speaker 2: A little intro of me. My father was a banker
Speaker 2: and I grew up when the banks were getting digitized,
Speaker 2: so he had a Unix book. That's how my introdiction
Speaker 2: to computers got started. I kind of went through some
Speaker 2: of the Linux commands without really practicing. And I've been
Speaker 2: fighting at my father from probably my third standard to
Speaker 2: get a computer. And I got one when I finished
Speaker 2: twelve standard. And I spent most of my colleges in
Speaker 2: school bunking them and spending in the college library or
Speaker 2: in the browsing center on the gaming center. That's where
Speaker 2: I learned a lot. So I've been in the evolution
Speaker 2: of a computers much before I understood a lot of things,
Speaker 2: like I was an early adopter for Yahoo, Male MS
Speaker 2: and hot Mail. Many people may not understand it at
Speaker 2: this point of time, but first will understand my first
Speaker 2: Internet connection was a personal dialup and things are super slow.
Speaker 2: From fighting with my father for getting a computer. Now
Speaker 2: we are running pretty decent sized GP cloud cluster, and
Speaker 2: we also through our partners, we bring in some of
Speaker 2: the advanced GPS. So before we get that, let me
Speaker 2: tell you my journey how it started into AM One
Speaker 2: day after my marriage, when everyone was watching my marriage video,
Speaker 2: I was in my Mac and reading through the TensorFlow documentation.
Speaker 2: That Google announced Sensorflow one day on my problem on
Speaker 2: my day of marriage, and I was like thinking that
Speaker 2: I had a new Mac back then, and having a
Speaker 2: Mac was a big deal back then in India, not
Speaker 2: many had it, and I was thinking that, oh, I
Speaker 2: should be able to run this the TFM and I
Speaker 2: st on my laptop. I tried doing that and the
Speaker 2: Mac started crying badly. Was it got very hot. That's
Speaker 2: how I got introduced to the concept of GPUs and
Speaker 2: me being a great fan of Terminator movie, I wanted
Speaker 2: to get into the AI. Tried understanding couple of things,
Speaker 2: but dropped it a couple of times, thinking that it's
Speaker 2: more for PhD, not my kind of stuff, but did
Speaker 2: not give up. It was still curious and then luckily
Speaker 2: I came across some of really good content by people
Speaker 2: like Jeremy Howard from fast A, where some of the
Speaker 2: things started getting clear. I was able to build things,
Speaker 2: and luckily on the way, I got introduced to Cagle,
Speaker 2: where I started competing in Cagle competitions. Was able to
Speaker 2: get into the top of the leaderboard top one percent
Speaker 2: in the world, and luckily got some consulting assignments for
Speaker 2: companies Fortune and mid sized companies where help companies build
Speaker 2: their implementation. It was not called a back then. It
Speaker 2: was usually a lot of deep learning, which kind of
Speaker 2: morphed into AGE and and all these stuff, but the
Speaker 2: basics still remained the same. During this stint, I realized
Speaker 2: that the GPU's the GPU compute is provided by the
Speaker 2: hyperscalers are very complicated to use and very expensive. Some
Speaker 2: of the companies in the US were trying to address this,
Speaker 2: but they were still expensive for a lot of people
Speaker 2: out there and countries like India and other places. So
Speaker 2: I really thought that why not we do it in
Speaker 2: India and make it cheaper and make it super simple.
Speaker 2: That's how the journey started off. My current company called Javaslabs,
Speaker 2: and the company name was inspired by the Javas from
Speaker 2: Marvel Movies, which is an AA probably which Sam Adman
Speaker 2: is trying to build right the AGI out the world,
Speaker 2: which is like super smart, does everything and all. Is
Speaker 2: inspired by that. Started this company around twenty nineteen during
Speaker 2: the COVID. Before the COVID started, the COVID hit us badly.
Speaker 2: We got stuck in place for more than eight months
Speaker 2: without able to do anything. But then things started slowly
Speaker 2: picking up and now we are doing pretty well.
Speaker 1: Awesome, So, mich I mean, based on what you said,
Speaker 1: I was going to ask you what is your inspiration?
Speaker 1: You kind of touched upon your inspiration. What I gathered
Speaker 1: is obviously your dad helped you early on with eunuchs
Speaker 1: and whatnot, with your first computer. Then looks like your
Speaker 1: marriage video was the cause of you getting inspired for
Speaker 1: as well. And then of course terminators. So three people
Speaker 1: you need to thank for for your journey. I guess right,
Speaker 1: anyone I missed for your journey?
Speaker 2: Yeah, I mean I take inspiration from a lot of people. Here,
Speaker 2: Jeremy Howard from Fast Andredge carpaty. If it's not for
Speaker 2: a Stanford open source curriculum, I have not picked up.
Speaker 2: Yeah right, there are a lot of inspirations the way
Speaker 2: move on, how to do business, bootstrapped way, how to
Speaker 2: think long term. I take inspiration from a lot of people.
Speaker 1: Yeah. Yeah, that is amazing because I tell myself this
Speaker 1: as well. I mean, you know you you you cannot
Speaker 1: shy away from taking inspiration even from a little child.
Speaker 1: Or there are times when I look at my dog
Speaker 1: do certain things and I'm like, I mean, if if
Speaker 1: the dog think that way, there's something in it for
Speaker 1: us to learn from that as well, you know, so
Speaker 1: I love.
Speaker 2: That absolutely right. The dogs can teach us a lot.
Speaker 1: Yeah, So let's let's go back a little bit in
Speaker 1: your journey vision. I mean, obviously you're having fun doing
Speaker 1: Jarvis Labs right now, but looking at your profile, looking
Speaker 1: at what you've done, I mean you've done a lot
Speaker 1: on the data side of things, right, I mean you know,
Speaker 1: whether it's HADOO or analytics or even business intelligence for
Speaker 1: that matter. I mean, so you data was kind of
Speaker 1: in your ingrained in your blood, or from the beginning
Speaker 1: of your career, that's what you were doing. I'm assuming
Speaker 1: there was some sort of pivot you wanted or something
Speaker 1: that you didn't like or you loved about data, because
Speaker 1: I mean, without data, AI is nothing, right. I mean,
Speaker 1: you know you put in bad data. I mean you
Speaker 1: have bad data. Your AI is as bad as the
Speaker 1: data you put in. So can you tell us a
Speaker 1: little bit about that journey of where you started you know,
Speaker 1: what what in I mean, where you ended up taking
Speaker 1: the pivot to this from your data journey, so to speak.
Speaker 2: Interesting question. The way I look at it is slightly different.
Speaker 2: I'll give you some history towards it. My first job
Speaker 2: was in withprow which is a major I service company
Speaker 2: in India, and I did not know the difference between
Speaker 2: services and products, so I was kind of getting bored
Speaker 2: of each of the projectile was in the pro so
Speaker 2: I used to fight with my manager and say that no,
Speaker 2: I'm not interested to get to something else. So I
Speaker 2: started working with business I think it's sap Bo sap
Speaker 2: business objects. Then move to Java swings and applet's building
Speaker 2: a product for best Buy where probably you guys would
Speaker 2: sign it that we did some parts of building that,
Speaker 2: so I have not been to best Buy. Then my
Speaker 2: last project was MasterCard. I think a lot of things.
Speaker 2: So what also happened was until two thousand and twelve
Speaker 2: or something, it was primarily proprilatary software sap IBMB software.
Speaker 2: So if you want to get into these, you need
Speaker 2: to have some account which helps you do it, or
Speaker 2: you need to get into an expensive training to get it.
Speaker 2: But the moment open so started kicking in in the
Speaker 2: form of Android, Spring, Hibernate or how do things started changing.
Speaker 2: As long as you have a good Internet, that's why
Speaker 2: we got three G in India, So you do one
Speaker 2: hundred dollars or Rube reach outs. You get like two
Speaker 2: GBO three GB connection. Now you can start download things,
Speaker 2: a lot of things. Right. That allowed me to do
Speaker 2: get into the open source and when I was working
Speaker 2: on business objects, I came across an interesting problem which
Speaker 2: was also the root for me jumping into her. So
Speaker 2: we had a business objects report which was running for
Speaker 2: one of a big client, which started crashing because it
Speaker 2: was running for more than an hour, and I got
Speaker 2: curious when Google was able to do a search in
Speaker 2: like seconds, why does this happen? Why we were not
Speaker 2: able to do that. So I namely asked my architect,
Speaker 2: who was a very smart lady, why is this happening?
Speaker 2: She was also clueless. But then I started digging deeper
Speaker 2: into it. That's why I came into this concept called
Speaker 2: map reduce. How companies like Google, ads is, distributed computing
Speaker 2: and all those That's where my interests started and we
Speaker 2: pro luckily got probably one of the earliest projects in
Speaker 2: the big data space for MasterCard setting up on one
Speaker 2: of their largest big data clusters and cloud pioneer in
Speaker 2: that CLOUDA and Horton works and MasterCard was a super
Speaker 2: India partner with cloud Era, so we had access to
Speaker 2: Clouda engineers I learned. I got an opportunity to learn
Speaker 2: a lot from them. That's how my journey into data started.
Speaker 2: And I then started moving out. I moved out of
Speaker 2: a pro worked in a couple of startups on different
Speaker 2: things like reporting, and then I worked on an analytics
Speaker 2: company for some time where we were doing things like
Speaker 2: Spark and all those things. And Spark was also something
Speaker 2: super interesting. The problem with Hadoo was it was amazing,
Speaker 2: but the map produce was too complicated, the Java boiler
Speaker 2: plate and all this comes. And Spark what it did
Speaker 2: is it kind of simplified everything. Whatever you could do
Speaker 2: in a much bigger final and mapp produce, you were
Speaker 2: able to do in one single line dot map, dot
Speaker 2: reduce and do it. Things got simplified over the next
Speaker 2: coming years. But that's how I jumped into the Spark
Speaker 2: and then Spark had a subset library called machine learning.
Speaker 2: That's when I started getting to the came means and
Speaker 2: random for us, all those things, and we started implementing
Speaker 2: it for some of our customers in the company, and
Speaker 2: that's where the tagle thing also started. By we were
Speaker 2: able to apply all the open source knowledge that I
Speaker 2: was gaining all these years on real problems, challenge and
Speaker 2: learn from some of the best in the world. That's
Speaker 2: how the pivot happened. And I had to use GPUs
Speaker 2: in order to compete in Taglar competitions, which needs a
Speaker 2: lot of GPUs. I had one which my friend luckily
Speaker 2: got it when he was coming back from you as Titanic.
Speaker 2: We were not getting it back then. That's how the
Speaker 2: journey started.
Speaker 1: Yeah, yeah, So you spoke a little bit about GPUs
Speaker 1: and I think it's a nice kind of segue into
Speaker 1: what Jarvis Labs is doing right now, right, So maybe
Speaker 1: you can spend two minutes on where you've got the
Speaker 1: idea or the inspiration for Jarvis Labs, right and what
Speaker 1: are you trying to offer to home and you know
Speaker 1: who potentially should be looking at Jarvis Labs, So can
Speaker 1: you touch on that vision?
Speaker 2: Got it? So, as I told you earlier, right when
Speaker 2: I was working for one of the large companies, they
Speaker 2: were facing one specific problem. They had like huge service
Speaker 2: in place with GPS, but the develops team that they
Speaker 2: had were not able to address the needs of data scientists.
Speaker 2: So what was typically happening was the data scientists wanted
Speaker 2: a particular environment. Every time they want installations, they have
Speaker 2: to go to develop for permissions. It was the develops
Speaker 2: was built for a different kind of a beast, not
Speaker 2: for the air world. They did not know how to
Speaker 2: handle it, so a lot of compute time was getting wasted.
Speaker 2: This was in the bigger companies and in the smaller
Speaker 2: companies it was much different, and for individuals it was
Speaker 2: much different. It was much harder. Smaller companies cannot even
Speaker 2: have this develop steam, so spinning up GPU instances, installing
Speaker 2: Nvidia COUDA driver was very hard. So I wanted to
Speaker 2: kind of build a company, build a product which kind
Speaker 2: of makes this simplified, as I have done that several
Speaker 2: times for cable competitions on platforms like AABSGCP. Struggle getting
Speaker 2: GPUs in those platforms, even though I was ready to
Speaker 2: pay at times, the ex very expensive ones right three hundred,
Speaker 2: and if you want to get it at that time,
Speaker 2: you need to wait for pretty long. You need approvals,
Speaker 2: which you hardly get. There were one or two smaller
Speaker 2: players which were like kind of wrappers on these things.
Speaker 2: They make it easier, but they were very expensive, not
Speaker 2: suitable for the SMB's smaller companies to mid size companies
Speaker 2: or for the individuals like us. So that's why the
Speaker 2: idea came of Java slabs. Can we put twenty eighty
Speaker 2: TI the gaming cards and then build a software layer
Speaker 2: on top of it which kind of automates all the
Speaker 2: tools that are required for data scientists. So data scientists
Speaker 2: can just focus on model building or deployment and not
Speaker 2: worry about the software required for the infrastructure. Pad that
Speaker 2: Sidea with started the company. After we made some bunch
Speaker 2: of initial orders, NBDA made it pick to their licensing
Speaker 2: saying that you're not supposed to use this consumer GPUs
Speaker 2: in data centers. So we kind of had to take
Speaker 2: a pivot from that and say that, okay, let's buy
Speaker 2: the commercial GPUs. They're a bit expensive, but the story
Speaker 2: remainder the same. So who can use javaslaps If you're
Speaker 2: trying to do research, if you're trying to frame your
Speaker 2: models on MULTIGPU clusters or even on a single cluster
Speaker 2: with agpus or less GPUs, you don't want to get
Speaker 2: into monthly, yearly commitments. You want to pages for a minute.
Speaker 2: You want to deploy your models very quickly and you
Speaker 2: want to have a friendly tech team to support you
Speaker 2: in case you'll need something, then probably you should look
Speaker 2: at Javislabs. For people that have not really looked into
Speaker 2: cloud providers, we are an alternative solution to Google Cloud
Speaker 2: or abus. The way I tell some of the vcs
Speaker 2: that have met us as GCP is good. They have
Speaker 2: a purpose. They are like the ones who manufacture BMW casts,
Speaker 2: but unfortunately the entire world cannot buy a BMW or
Speaker 2: at Tesla. We need the smaller cast like Marthy Kundai
Speaker 2: for different use cases. Also, we offer that so if
Speaker 2: you're inn SMB spending huge amounts of money, you can
Speaker 2: just switch to a company like Javaslabs for US and
Speaker 2: reduce your DevOps cost, increase your efficiency and save a
Speaker 2: lot of money.
Speaker 1: That's a that's a nice USB. So, given given what
Speaker 1: you're offering, I mean, who is using it today?
Speaker 2: Can you?
Speaker 1: I mean again you don't have to mention names if
Speaker 1: you can't, but I mean, at least give us an
Speaker 1: idea of who is using and what they're potentially using
Speaker 1: it for.
Speaker 2: What they're potentially Okay, let's start with who is using it?
Speaker 2: Uh So we start Since I was into Cagle. Our
Speaker 2: initial focus was people who are doing tagle competitions, right,
Speaker 2: we started that. We had a lot of caglers who
Speaker 2: actually give us the initial feedback helped us remind product.
Speaker 2: But then the problem with Cacalus they are like the competition,
Speaker 2: so there's a huge demand peak during the end of
Speaker 2: the competition, and we do not have much crowd using
Speaker 2: the product in the weekdays or when the competition is
Speaker 2: not ending. Right, So we kind of started looking at
Speaker 2: more people colleges, labs or people who are offering online courses,
Speaker 2: companies who are doing researchers. Some of the top companies
Speaker 2: both in the US and India use Java slabs for
Speaker 2: their research and for their model deployment purpose. There are
Speaker 2: universities from uers where they want to research on building
Speaker 2: foundational models or diffusion models or multiple research, right, so
Speaker 2: they need clusters of eight hundreds or head hundreds. These
Speaker 2: are some of our potential customers.
Speaker 1: That's great, and then how long does it take for
Speaker 1: them to get started? I mean, is it like an
Speaker 1: easy plug and play. Let's say they say they want
Speaker 1: to start using it from today to when they can
Speaker 1: start using the GPUs and you know, apply a certain
Speaker 1: model using Jarvis Labs, I mean, what do you thay,
Speaker 1: what do you think is the run made?
Speaker 2: Yeah, so we offer two kinds of uh we or
Speaker 2: I'll say that we have two kinds of uses. One is,
Speaker 2: if you want to use the platform normally, you just
Speaker 2: put your credit card and you can start spinning your
Speaker 2: first instance and probably less than a minute putting the
Speaker 2: card thirty seconds and launching instances like fifteen seconds, and
Speaker 2: you can start building your models, downloading your data sets
Speaker 2: and all those things. But if I was talking about
Speaker 2: other use case where university took a large cluster, that's
Speaker 2: why you have like contracts in place. Then you have
Speaker 2: the banking transfer and then we block a huge set
Speaker 2: of GPUs for them and then they do it. That
Speaker 2: could probably take days because of the all the formalities
Speaker 2: that we have to go through. For a normal user,
Speaker 2: it's usually less than a minute or two. Great.
Speaker 1: So the way I understood it, I mean it's almost
Speaker 1: like versus a custom build sort of thing, right. I
Speaker 1: mean so that so the first one is more swipe
Speaker 1: your credit card, create your account, You're ready to go.
Speaker 1: Your second one is a little more custom use case
Speaker 1: you need a larger you know, processing power, and larger
Speaker 1: amounts of data, so they need to work with you
Speaker 1: to create a custom project, so to speak, and the
Speaker 1: custom set of GPUs assigned for them. So that's a
Speaker 1: that's a nice way to probably differentiate. So you said
Speaker 1: you started in twenty nineteen, which I mean, where do
Speaker 1: you see yourself in the journey and you know, has
Speaker 1: it been as per your vision as to where you
Speaker 1: are in your journey? I mean, and what are your
Speaker 1: plans next? With Jarvis Labs, we have.
Speaker 2: Come a long way, for sure, and the Aspace sift
Speaker 2: has changed a lot. So our initial focus was towards
Speaker 2: a very niche community, very small crowd. The market was
Speaker 2: not as big assets today, the competition is not as
Speaker 2: fears as it is today, so a lot of things
Speaker 2: have changed. People are moving towards contractless GPU compute requirement
Speaker 2: or even people are moving towards token based billing right,
Speaker 2: so they don't want to get into some of the
Speaker 2: use cases. Do not want to get into I want
Speaker 2: this XGPO YGP You rather, I want to deploy my
Speaker 2: model and you just take care of the entire life
Speaker 2: cycle of that instance. Like what I mean is, let's
Speaker 2: say you find you in a model which is specific
Speaker 2: for your use case. You don't want to keep this
Speaker 2: model running twenty four bus seventy sixty l as you
Speaker 2: wanted to come up only when there is a request,
Speaker 2: just like how Aw'slambda works. Right function as a service.
Speaker 2: That's one of the projects which we are actively investing
Speaker 2: in it. We are hoping to go live probably in
Speaker 2: a month's time, the first version of it, and we're
Speaker 2: also seeing that huge research is going on what does
Speaker 2: the next thing right. We have evol platform where we
Speaker 2: enable companies to do a lot of things, so we
Speaker 2: are keeping a closed eye on how the industry is
Speaker 2: evolving and we're also making changes according to that to
Speaker 2: the platform. Okay, god so I was working My last
Speaker 2: company was in Bangalore. I used to work in Chennai.
Speaker 2: These two are some of the biggest cities in India,
Speaker 2: which probably most of you audiences have heard of. The
Speaker 2: challenge with Bangalore is it's a very happening place and
Speaker 2: it's also very crowded place. You want to move from
Speaker 2: your house to your office and to and fro, it
Speaker 2: can take anywhere between two to three hours, even though
Speaker 2: the distance is very short. That's one reason I did
Speaker 2: not want to continue in Bangalore. The second thing is
Speaker 2: I have been a huge fan of Shi the Remainbow
Speaker 2: where he has incorporated his one of his offices in
Speaker 2: a place called ting Ghasi, which is much smaller than Kayamato.
Speaker 2: And the idea of that is a lot of product
Speaker 2: companies in the automobile sector, or the companies which manufacture
Speaker 2: the rice preparation missions, right, they are in remote parts
Speaker 2: of Switzerland or remote parts of Europe, different Germany and
Speaker 2: all right, so you need a calm place for you
Speaker 2: to focus on building the product rather than getting into
Speaker 2: the rat race that the city offers you. So that
Speaker 2: inspired me to come to Kuiamatur. And we don't actually
Speaker 2: stay in Kaimatur. For people who are native to Kayamato,
Speaker 2: they say, oh, you are actually outside or your nearby village.
Speaker 2: That's how people used to say, oh that village, But
Speaker 2: it's technically part of Kaimatur. It's a place called Kuepu
Speaker 2: and it used to be called Miniuti. I'm not sure
Speaker 2: if it's still called right now. The climate is really good.
Speaker 2: It almost looks like Minioti. Kim is a very clean,
Speaker 2: calm place. People are very respectful here. There's a famous
Speaker 2: Nisha spiritual place by the tech, yoga, and there are
Speaker 2: mountains all around. It's pretty close to Western Ghatsan, so
Speaker 2: it's a very peaceful place away from all the happening things.
Speaker 2: And it's very closer to banglows like six sevenas to drive,
Speaker 2: So when I want to meet someone or when I
Speaker 2: want to go for a meetup, I just drive, have
Speaker 2: a break, I enjoy the bangalow's nightlife and come back
Speaker 2: to And staying in Kimator helps us to focus on
Speaker 2: the work and forget about everything else. And the cost
Speaker 2: is also way less than in Bangalore.
Speaker 1: Yeah, yeah, I mean, you know, I've been a fan
Speaker 1: of Committer just personally speaking. You know, back in the
Speaker 1: day when I used to be in consulting, I mean,
Speaker 1: my company used to have an offshore facility in Comitor.
Speaker 1: I used to do a day trip coming into Committer,
Speaker 1: but leave in the evening to go to Bangalore for
Speaker 1: another visit. I always wondered, I mean, when would I
Speaker 1: stay there for a night to spend a little more time.
Speaker 1: This time, when I came to meet you, I was
Speaker 1: lucky enough to go around for a little bit cour
Speaker 1: to see my friend who got me there. So next time,
Speaker 1: even more even more time in Coimitto and the suburbs
Speaker 1: to learn about more. So I thoroughly enjoyed my trip.
Speaker 1: And I mean I hear all the reasons from you
Speaker 1: on why you know, especially building something brand new and
Speaker 1: a product, sort of a mindset and things like that.
Speaker 1: I mean, you need a lot more peace of mind
Speaker 1: and quiet that helps you do more with the less
Speaker 1: with less time than just worry about Oh, let me
Speaker 1: spend two hours to get to work, let me spend
Speaker 1: two hours coming back. And that stress itself is is big.
Speaker 1: So given that I'm assuming, given you're living in Bangal,
Speaker 1: I mean in Comito, you get a good night's sleep,
Speaker 1: but I'm sure Jarvis Labs keeps you up at night
Speaker 1: as well. On certain things. You know, your roadmap and
Speaker 1: what to do next. I mean one of the things
Speaker 1: that you worry about our challenges that you see lying
Speaker 1: ahead vision.
Speaker 2: That's a very interesting question, something very difficult founder to answer.
Speaker 2: Probably the founder gets worried about it the worst. Then
Speaker 2: we started Jervis Labs, there was little interest in our product,
Speaker 2: not many people who are interested in it, so we
Speaker 2: were like the dominant player and we didn't have much competition.
Speaker 2: People were happy using us. Then a lot of interest
Speaker 2: in the VC world came in during the COVID. You
Speaker 2: would have seen the zero interest rate heavy VC funding wented,
Speaker 2: which also went in subsidizing the services we offer. Some
Speaker 2: of our competitors have subsidized the costs a lot, So
Speaker 2: that's one challenge that we currently face. The second thing
Speaker 2: is we're also seeing the industry getting more mature. The
Speaker 2: efficiency is increasing. We also need the There are too
Speaker 2: many players today than what were the two years three
Speaker 2: years back, and more are coming into it. That's typically
Speaker 2: one challenge. Of course, we are kind of addressing that
Speaker 2: by not looking them as competitors rather than we are
Speaker 2: looking them at as partners. We're partnered with some of
Speaker 2: them for supplying us with the infrastructure. For example, we
Speaker 2: don't have a base in Europe, but now through one
Speaker 2: of the partnerships with one of the largest data centers
Speaker 2: over there, we are able to offer heat shendreds in
Speaker 2: the Europe region. We're also talking to some of the
Speaker 2: companies in the US, so sooner, in the next one
Speaker 2: or two months, you'll be able to launch GPUs in
Speaker 2: a closer to US region also, so we're looking we're
Speaker 2: trying to take that as an advantage. We're also reduced
Speaker 2: investing in GPUs because we feel there's abundance of GPS
Speaker 2: available suddenly. But thanks to all the VC money came in,
Speaker 2: not just we see real estate money and all this
Speaker 2: came in. In terms of technology, the technology has been
Speaker 2: evolving right now. It's not the small set of people
Speaker 2: who want to use AI, doctors, artists, lawyers, advocates. In
Speaker 2: the evening, I was talking to elite lawyers who are
Speaker 2: trying to bring an AI to ads. Some of their
Speaker 2: use cases dispute resolutions, automatic can also we are supporting them.
Speaker 2: So the technology has been changing. There are some misunderstandings
Speaker 2: of what the technology is capable of, so we are
Speaker 2: addressing those challenges. So it's an interesting time. A huge
Speaker 2: competition has increased. I think over the next few years
Speaker 2: it will be consolidated again thinking long term, keep lean
Speaker 2: and survive longer to actually have a better outcome.
Speaker 1: You mentioned we see is a few times. I mean
Speaker 1: in terms of where you are in the stage of
Speaker 1: the company, right, I mean, can you fare a little
Speaker 1: bit about you know, I mean, are you you know,
Speaker 1: just in seed stage, waiting a little bit before you
Speaker 1: go for Series A or Series B. Or what are
Speaker 1: your plans in terms of, you know, even getting investors
Speaker 1: into the company. I mean you might say you don't
Speaker 1: want investors, but I mean just for anyone listening and
Speaker 1: interested in Jarvis.
Speaker 2: Labs, I mean, what is your message to them? So
Speaker 2: we are a bootstrap company. We have not is an
Speaker 2: external funding. In the initial few years, we had opportunities
Speaker 2: to talk to vcs, but they did not turn postive.
Speaker 2: But right now we make enough, we don't need to
Speaker 2: raise money and we want to remind that way. I
Speaker 2: also believe that remaining bootstep offers a lot of freedom
Speaker 2: and I don't want to run behind millions or billions
Speaker 2: of dollars. As long as we make enough and as
Speaker 2: long as we grow organically, we are happy with it.
Speaker 2: One of the advantages of staying in a place which
Speaker 2: is far away from the Silicon Valley of India is
Speaker 2: also that you don't need to be part of the address.
Speaker 2: Right we love building products. We will continue doing it,
Speaker 2: but we don't want to run behind the money. We
Speaker 2: will make money, but we don't want to run behind it.
Speaker 2: So we don't want to go behind we see money
Speaker 2: because that it's like taking artificial way of scaling up.
Speaker 2: We want to see how we can take inspiration from
Speaker 2: companies like Zoo zero from on how we can grow organically,
Speaker 2: maintain a healthy lifestyle and build a long lasting company
Speaker 2: then a company that is built to be sold to
Speaker 2: someone else. So we are not raising funds at least
Speaker 2: as much as I can see in the future.
Speaker 1: That is super inspiring vision. I mean I wish every
Speaker 1: founder can say that, right, But I mean obviously you
Speaker 1: see you see you said rat race as well a
Speaker 1: few times. It's always a question of comparing one to
Speaker 1: the other. You know, what's my evaluation? You know all
Speaker 1: that sort of thing. But you you offer a very
Speaker 1: refreshing perspective, and I love the references you always make
Speaker 1: to Soho and others.
Speaker 2: I mean, I know a bunch of guys from.
Speaker 1: As well and understand their culture, how they operate. I mean,
Speaker 1: if anyone listening here has has not heard about Soho,
Speaker 1: I mean that's a super interesting case study and a
Speaker 1: big inspiration someone who comes from our state, Vish News
Speaker 1: and mine which is Tamil Nadu. So go look up
Speaker 1: Zoho as well. So probably the last question for you
Speaker 1: is you you worked in a big company, Like you said,
Speaker 1: you know you worked in smaller companies as well. Now
Speaker 1: you're a founder, you have a team, you have mouths
Speaker 1: to feed and build, you know, paychecks to give and
Speaker 1: all that. So and in today's generation, you know, probably
Speaker 1: different from twenty years ago, where people wanted a paycheck
Speaker 1: to take home, they wanted stability. I mean, there's a
Speaker 1: lot more kids and college students trying to be founders,
Speaker 1: you know, trying to be start their own company, bring
Speaker 1: their dream idea to life, and things like that. So
Speaker 1: having been through this, I mean, what what what are
Speaker 1: your learnings or your advice you would give to somebody
Speaker 1: who's in the third year of college or a fourth
Speaker 1: year of college trying to come out and be a founder.
Speaker 1: What are your nuggets of advice or three nuggets of advice?
Speaker 2: I would say, don't wait till you finish your college,
Speaker 2: right because when you're in college, you're lucky enough for
Speaker 2: your father to be for your mother to be funding
Speaker 2: you your life. So you don't need to maintain your lifestyle,
Speaker 2: and you don't need to go and convince someone to
Speaker 2: work for you or work with you. I prefer work
Speaker 2: with you. You can convince your friends to work with you.
Speaker 2: So pick up an idea and a lot of things
Speaker 2: have changed in the technology space. There is a concept
Speaker 2: called ind hackers. While you can build product and with
Speaker 2: tools like GPT cloud building products have become a lot
Speaker 2: easier if you put enough amount of time and if
Speaker 2: you kind of read so you can actually build product
Speaker 2: before you finish your finalier. And if you're lucky or
Speaker 2: if you're planning enough, you'll be making money also in
Speaker 2: the way. So by the time you come out, either
Speaker 2: you have the experience building the product or lucky. The
Speaker 2: best case scenario is you have built a product and
Speaker 2: you also made money, right, so then you'll have a
Speaker 2: better way to see whether you want to continue with
Speaker 2: that journey or you will know if it's not your
Speaker 2: cup of team. Being a founder is very hard. Before
Speaker 2: I started Javas Labs, I have heard a lot of
Speaker 2: talks oft from cred who also is a founder of
Speaker 2: I think free Charge, he sold that or Snapdean or
Speaker 2: something like that. He says founder's journey is a lonely journey.
Speaker 2: I used to think, oh, that's maybe it's not me,
Speaker 2: maybe it's a still But four years into it, I
Speaker 2: can say that's true, right, because you have a lot
Speaker 2: of things going on in your head which she may
Speaker 2: not be able to share with everyone, or you may
Speaker 2: not even have the time to share with people, right,
Speaker 2: So it's good. It's good to try it in your
Speaker 2: college days and see if you want to do it.
Speaker 2: For people who come out of college, I would say,
Speaker 2: try to get into a particular space which is usually upcoming,
Speaker 2: pick up a domain knowledge, and see how you can
Speaker 2: solve a problem differently. Watch a lot of videos of
Speaker 2: y combinators. There are a lot of videos of See
Speaker 2: the Way boves Zero. The learn from these people so
Speaker 2: that you will form a kind of insights on what
Speaker 2: you want to build, and probably that's a good way
Speaker 2: to start. Don't be dependent on VC money to start.
Speaker 2: That may or may not happen even if you want to.
Speaker 2: Just a small percentage of companies raised V see funding.
Speaker 2: A lot of college people I have spoken to, they
Speaker 2: expect that I will get funds to build this product
Speaker 2: through VC. Usually we see companies don't fund for your
Speaker 2: ideas unless until you have like successful exists or you
Speaker 2: have a very different background.
Speaker 1: Those are great pieces of advisation. I mean, I wish
Speaker 1: I'd spoken to someone like you when I was in college.
Speaker 1: You know, my first first task when I was in
Speaker 1: college was to find a job, settle down or go
Speaker 1: to my ms. But times of job definitely change, right,
Speaker 1: So your journey is super inspiring, not just for the
Speaker 1: next generation but even for people like me. I thank
Speaker 1: who've been working for plenty of years. And if you
Speaker 1: have an idea, if you have an inspiration, just go
Speaker 1: do it. Is you know, is what I learned from you.
Speaker 1: So maybe one last question and we can wrap up
Speaker 1: this question. I mean, because you're an AI there's a
Speaker 1: lot of talk these days about whether AI is just
Speaker 1: another this is just another bubble waiting to burst, or
Speaker 1: this is for real this time because of all the
Speaker 1: you know, money that is being pumped in. There's other
Speaker 1: stories about oh there's AI is way is waiting for
Speaker 1: a problem to solve?
Speaker 2: Right?
Speaker 1: I mean, is technology looking for a problem? Having been
Speaker 1: in this space much longer than you know, at least
Speaker 1: me and many others, and you know you've put in
Speaker 1: your days and nights into AI building this company, I mean,
Speaker 1: what is your general take on the state of the
Speaker 1: industry right now and where do you think it's going
Speaker 1: to go?
Speaker 2: So AIR is definitely not a bubble, right whether all
Speaker 2: the companies all the VC funding will make a profit.
Speaker 2: Maybe not. But let's say for hypothetical scenario where all
Speaker 2: the funding for AI and all the research work for
Speaker 2: a stops right this minute. Right even then, instead of
Speaker 2: have needing one hundred people team, you can build a
Speaker 2: lot of products with a small three or ten people
Speaker 2: company can still do the same. It revolutionizes education. For example,
Speaker 2: in Indian space right you have like for thirty or
Speaker 2: sixty students one teacher. So with AI that can completely
Speaker 2: change if we don't need much advancements in here. Of
Speaker 2: course there's a cost involved in it, but assuming that
Speaker 2: the cost, engineering is something easier, easier to solve than
Speaker 2: going towards the AGI. So I don't think it's a bubble.
Speaker 2: A lot can be done with We have just scratched
Speaker 2: the surface. That's how I see it. It's not searching
Speaker 2: for the problem. It's we have to figure out how
Speaker 2: to solve the problems that we have, rather than solving
Speaker 2: the fanciest problem. If you're trying to see innovative ways
Speaker 2: of how to use it, probably skies. Will it be agier,
Speaker 2: that's a completely different thing, which I don't agree and
Speaker 2: I don't want that to be true.
Speaker 1: Okay, awesome. That's a great insight and a nice perspective
Speaker 1: from someone who is breathing this day in and day out.
Speaker 1: So thanks so much for that ution. So let's wrap
Speaker 1: it up here. I sincerely appreciate you taking the time
Speaker 1: in the evening time to jump on this and share
Speaker 1: your insights about Jarvis Labs. I'm sure we'll do another episode,
Speaker 1: say six months down the line, see looking at your
Speaker 1: growth and what else you've learned, but wish thanks so
Speaker 1: much for joining us. All the best to you and
Speaker 1: Jarvis Labs and your team and we'll stay in touch.
Speaker 2: Thank you, Anthony, all the best for you too. Two