Hina Dixit’s interest in supporting people and solving problems has its roots in her family’s call office business, where she helped people place telephone calls when she was growing up in India.
Later, after earning her bachelor’s degree in computer science, she was quickly recruited into the tech space, where her problem-solving and customer service skills have served her well as both a software engineer and tech investor. From a developer role at Symantec, to project leader at Apple, to an AI investor role at Samsung Next, Hina continues to leverage her communication and connection skills in seeking out and supporting innovations in artificial intelligence, as well as robotics, Web3, and other tech sectors.
On this episode of the Me, Myself, and AI podcast, Hina shares the criteria she considers when making investments in new entrepreneurial ventures. She also highlights the focus areas that are of most interest right now, explains why she enjoys mentoring other technologists, and shares her views on what the future of AI looks like.
Transcript
Shervin Khodabandeh: How does one technology leader approach AI investments? Find out her five criteria on today’s episode.
Hina Dixit: I’m Hina Dixit from Samsung Next, and you’re listening to Me, Myself, and AI.
Sam Ransbotham: Welcome to Me, Myself, and AI, a podcast on artificial intelligence in business. Each episode, we introduce you to someone innovating with AI. I’m Sam Ransbotham, professor of analytics at Boston College. I’m also the AI and business strategy guest editor at MIT Sloan Management Review.
Shervin Khodabandeh: And I’m Shervin Khodabandeh, senior partner with BCG and one of the leaders of our AI business. Together, MIT SMR and BCG have been researching and publishing on AI since 2017, interviewing hundreds of practitioners and surveying thousands of companies on what it takes to build and to deploy and scale AI capabilities and really transform the way organizations operate.
Sam Ransbotham: On today’s episode, we have Hina Dixit, an investor at Samsung Next. Hina, thanks for joining us. Welcome.
Hina Dixit: Thank you so much. It’s a pleasure being here with you.
Sam Ransbotham: Most of our listeners are likely familiar with Samsung — giant South Korean multinational, lots of consumer electronics — but people may be less familiar with Samsung Next, so let’s start there. Can you describe what Samsung Next is and what your role is?
Hina Dixit: Yeah, absolutely. Samsung Next is the private equity or venture capital arm of Samsung. We tend to be stage-agnostic, but at the same time, we have six focus areas where we invest. AI is one of them. We also invest in fintech, blockchain, and infrastructure, and media tech as well, along with health tech.
Along with these six focus areas, we tend to make more and more learned investments about the ever-changing, dynamic world as well. So if you or anyone has a cool idea, please feel free to reach out.
Sam Ransbotham: I should’ve prepared more and had a few pitches ready so that we could’ve put you on the spot here while we were recording and get you on record there. So, what, exactly, do you do, though?
Hina Dixit: I currently lead the AI investment segment area. If there is any deal which is associated with AI, I tend to lead that deal and also work on the investment strategy for Samsung Next.
When you head out to these startup demos, to these pitches and expos, you will see thousands of startups. Now, how do you ensure that you are focused on the right areas which matter to Samsung? It should also propel innovation further; [instead of simply] furthering the innovation, it should also be usable. So that’s why having a paradigm will help you make those sound decisions, where you can actually prioritize certain areas ahead of time compared to other investors, and understand which of the current technologies will be booming, say, a few years from now. And accordingly, you tend to segment and understand that, OK, these are my top-priority areas.
At the same time, I’m very, very passionate about mentoring entrepreneurs, mentoring fellow people in tech. I come from a tech background, so I can always understand the hiccups people face when they are moving from individual-contributor roles or management roles in these big techs and moving forward to a startup entrepreneurial journey. I love connecting with them and helping them out.
Shervin Khodabandeh: That’s really wonderful, Hina. So I want to talk about both things you said, both the mentoring, but also I want to go back to how you pick an investment. I mean, obviously, where you’re sitting, you are looking at thousands of opportunities probably, right? And so you mentioned there are some guiding principles in terms of how you prioritize where to focus and what fits strategically with Samsung, but tell us more about how you pick an investment once you’ve already gone through that filter, that “OK, it’s the right thing for the company. We want to do it.” Now you’re actually evaluating an AI company. Tell us how you pick. What are the factors you consider?
Hina Dixit: I tend to focus on very important factors for me personally. Every investor out there has a very different way of investing. Some people are very intuition-driven, and I have seen such investors make really great decisions. Some people are very theory-driven, and some people tend to take it as they go.
I am a mix of all of them. I tend to make these sound, learned decisions where I’m very comfortable and I know the space very well. One thing that is always very important for me is the team. Is there a right product-team fit here? Are these individuals capable of building these great products that they’re promising? I think that is an essential parameter for me.
And then, moving on to the problem itself: Is this pain point really [going to be] valid in few years? The pain point has to be there. The next thing is the technical innovation. Now, that is important, because that serves as a mode for you, or mode for these entrepreneurs, right? Otherwise, any big tech [company] can just go in and create what they have created. We want to have a solid mode around these products that they’re building and some sort of novelty.
And then, moving from technical innovation and the mode, obviously there has to be a decent market size. You might be building an awesome product, but at the same time, the market sizing [might be] very small. It becomes really hard to scale that kind of product. Even if it’s not monetizable, it should be solving a very solid pain point, plus the impact of that particular solution has to be global. And that’s another factor for me, where I tend to make my own decision that, OK, this is something which is going to change everything that we do today.
Shervin Khodabandeh: Tell us more about the team, because technology is one aspect, but how do you suss out both the capability of the team itself and then how well the team works with each other? I mean, a lot of startups have team issues, right?
Hina Dixit: Yeah.
Shervin Khodabandeh: How do you look into that?
Hina Dixit: Sure. I think it’s a very deep question, and I think it comes from my days at Apple. Apple has a very startuplike culture in some of their organization, and here I’m speaking about the culture because there were so many learnings from them. When I started, there was a very open culture where people would come on the weekends to support and mentor you and help you. They wouldn’t even ask for any kind of credit. They would help you move forward, and at the same time, they will not just stop there. They will empower you. They will connect you with the right connections across the organization.
I kind of felt that it is very difficult for people to be that selfless and just focus on making the product great, but I think that’s what the spirit of Apple is, and I tend to see a similar spirit in founders if I know that they’re very, very product-driven, or they’re very, very goal-driven in terms of [their] team. Then I tend to get that sense, OK, these guys will support each other.
Sam Ransbotham: You’ve got some extensive experience in this area. You mentioned Apple a couple of times. Tell us a bit about how you got to where you are now from where you started.
Hina Dixit: I come from a very humble family background. So while my dad would work very hard, I would help them out with our family business, which was a small public call office, or a PCO, where people [went] and used to make telephone calls. So I used to sit there, and I used to make those calls for people, handle the customers, and enable them to make these phone calls, and that was a very good learning point for me because I learned how to talk to people.
From being a very introverted child, I became very public-facing, right then and there. … Like, OK, these are my customers. They are top priority. I need to serve them, help them, and that’s where I think some of these qualities that I [espouse] or these passions that I have — that I love helping people, I love solving conflicts — probably arise.
I did my high school from Kanpur [City in India], which is Mercy Memorial School, and after my high school, I went to a women’s college because my parents were a bit conservative yet. I was the first girl in the entire family of my dad’s side who went outside of the city in order to get an education.
It was immensely fun. It was a very safe and secure environment. Obviously, it was very competitive — we women tend to be very competitive — and at the same time, I made great friends there, and I learned so much from my classmates at that time. We used to trade on these various ideas, and we used to create these JavaServer Pages-based applications, web applications for online quizzing, test banks, writing educational articles.
I remember, even buying a Starbucks coffee at that time used to be a very, very far-off thought because it was so expensive for me, and I used to work multiple jobs at the same time. And then I was placed at Symantec six months ahead of graduation. So that took some pressure off of me, and Symantec was a great starting point for me. I was in their data loss prevention team. I learned significantly from all the mentors there. I still share great relationships with all of them. And then Apple happened, and the rest is history.
Sam Ransbotham: One thing that’s fascinating: As you were saying that, I was thinking about how you tied your exposure to customer service through that very early call office job.
At the same time, much of what we’re talking about with artificial intelligence … it strikes me that the kind of job that would be suspect or likely to be replaced, and I have to wonder, how does the next Hina Dixit come along without that experience if we don’t have that introductory customer service-oriented jobs to learn those skills?
Hina Dixit: Yeah, I get the question. This has been a grave thought, and a lot of people are coming forward and discussing it. But I think AI is not going to replace people. AI is going to empower people, and that’s the thought process I come from. Just because phones became relevant, it didn’t mean that [the mail was] not relevant anymore. We still order Amazon packages, and we still get our bills in the mail and whatnot, and that’s how I think we will be able to push mankind. That’s how we keep on pushing each and every … mile toward the ultimate goal of humankind’s future, right?
Moving to the ultimate goal there, I think nobody should blindly trust that, OK, AI is going to replace their job, but they should be able to learn about AI. And that’s one of the things where I’ve been focusing on: finding these really cool technologies which can help people ramp up on AI.
Like, why do people need to write any single piece of code in order to use AI? Why can’t this be as simple as looking at an Excel sheet? Why can’t this be as accessible [as a] user interface, which is very easily programmable by just any business user out there? So finding that kind of interface between AI and the current users, is a very critical piece that I think investors should focus on, because the ultimate goal here is to normalize the usage of AI and make that publicly available and at the same time accessible as well.
Shervin Khodabandeh: I think this is a very, very good point. That vision you painted is actually quite appealing. It used to be, the human element of AI was around making the technology better, faster, cheaper, or [writing] the next-generation algorithm, which of course, we still do, but that’s going to be more and more in the R&D and innovation zone. I think, as you’re saying, the usage of AI will go from humans’ role as programmers and writers of code to more working at that interface, of having these building blocks and connecting those building blocks that AI provides to solve existing problems, but more importantly, as you’re saying, thinking about “What else can we do with this? How do you innovate, now that you have all this at your fingertips?”
Hina Dixit: Yeah. I kind of think the same way, because anybody … you know, think of Excel. Anybody can just jump into Excel and make applications out of it. I know there are a bunch of cool apps coming around productivity right now which are backed by AI.
Shervin Khodabandeh: Share with us a bit of your view on the coolest areas of technology that you are looking at right now. What piques your interest these days with everything that’s going on with cyber and Web3 and quantum computing and everything else? Can you share specific investments or areas you’re looking at?
Hina Dixit: Sure. We are focused a lot on infrastructure pieces of Web3, and at the same time, we are also focusing a lot on the AI aspect of Web3. So can we use these decentralized systems in order to make computing efficient? That’s a question that we are trying to … answer right now. We are also trying to dive in deeper on the health-tech side, where we want to digitize the normal health paradigm, and we want to empower users out there and give them more proper feedback, maybe in their diet, maybe connect them to the right agents or doctors or nurses.
The focus is on empowering humans. That’s where I think we are trying to focus. And then obviously there is meta-tech aspect, which is the metaverse. We’re trying to understand, how easy would it be to convert any image into a 3D asset and place it in the metaverse? And then, how do we make this metaverse accessible, just like the real world?
It seems surreal, but at the same time, there’s so much hard work and research for each and every aspect of this. We are also focusing a lot on the fintech perspective and trying to empower these LatAm [Latin American] countries, finding a way they can build very sustainable and safe credit-scoring systems in Asia, for example, [and in] India, East Asia, and LatAm countries. So building a lot of infrastructure around fintech in LatAm countries and Asian countries is another thing that we are focusing on.
Sam Ransbotham: Yeah, I think that infrastructure’s particularly interesting because that is an area where artificial intelligence can make a difference when you can get some scale through an infrastructure. It’s one of those situations that it seems like it opens up new possibilities when the economics change — when things that were no longer possible become possible. Are there other things that you’re working on that are next in the portfolio? What are we going to see from Samsung Next next?
Hina Dixit: We are moving into robotics as well. I did invest in one of the companies, called Integral AI, and they are trying to use these large AI models or foundation models [to train] their robots. But at the same time, robotics is another area where we want to focus on the consumer robotics aspect, so any cool startups out there building these cool consumer robots, please feel free to reach out to us, and we’ll be happy to jump in and help out.
Sam Ransbotham: Hina, we’ve got a segment where we ask you a series of questions, and these are supposed to be rapid-fire. Just give us the first thing that comes to your mind.
Hina Dixit: OK.
Sam Ransbotham: You’ve got a past career that’s over a decade of being involved in these technologies. What’s your proudest AI moment? What’s the thing in this portfolio that you’re proudest of that involves AI?
Hina Dixit: I think I’ll have to say Stability AI because before that, there were a lot of research communities around, but at the same time, there was no way that somebody could go and commercialize that research works. And I really value Emad Mostaque’s work there — that he recognized this problem and he got these research facilities together in order to start commercializing and build more solid consumer-end products.
Sam Ransbotham: We’ve been very positive about artificial intelligence today, but is there anything that worries you about AI?
Hina Dixit: I think one thing that worries me is that we have seen a recent burst of these large languages model-based apps, and that does include ChatGPT. I love their work, but at the same time, there are other pain points. And then, obviously, there are copyright issues that we need to solve, and there are security issues. So those are some of the other areas we are trying to focus on, and trying to understand how those pain points can be resolved.
Sam Ransbotham: What’s your favourite activity that does not involve technology?
Hina Dixit: It’s basically gardening in my house. I just find that very therapeutic, and, secondly, I love playing with my dog, Jimmy. He’s absolutely adorable.
Sam Ransbotham: What was the first career you wanted? What did you want to be when you grew up?
Hina Dixit: I have always wanted to be a startup founder. I was 8 when I manifested that … I would be a founder, I would be building great products, and I would be helping out other people. So ever since I was 8, [I’ve been] chasing that dream.
Sam Ransbotham: What’s your greatest wish for artificial intelligence in the future? What are you hoping we can gain from this?
Hina Dixit: My biggest wish for AI would be enabling common sense in some way, because these large AI models, they do have some AI capabilities when they can be put together in conjunction. We know from the recent PaLM research paper that Google published that, OK, there is a way of having these multiple multimodel’s work together in order to create more sensible information and reliable information out there for users to believe in, and they basically used it to train their robots.
So that’s one application, but a lot can come forward from that particular research work that Google published, including chain-of-thought prompting as well. How do you use these several models to work together in order to perform better in real-world and unstructured environments? So that would be very cool to see.
Sam Ransbotham: OK, yeah, that seems so exciting to me, too, because we originally had the generative AI adversarial models, where, yes, we learned how to play chess really quickly, or we learned through a game, but the universe that has expanded from the idea that we can have bazillions of these models working kind of with and against each other — that seems very natural to, well, the way that we as humans or current biology works. It seems like there’s a lot of potential for that.
Hina Dixit: Yeah, yeah.
Sam Ransbotham: Well, Hina, thanks for taking the time to talk with us today. I think that there are lots — actually, particularly from your background — that is inspiring to people. Thank you for taking the time to talk with us.
Shervin Khodabandeh: Yeah, thank you so much.
Hina Dixit: Thank you so much for having me. It was a pleasure.
Sam Ransbotham: Thanks for listening. On our next episode, Shervin and I speak with Elizabeth Anne Watkins, research scientist at Intel Labs. Please join us.
Allison Ryder: Thanks for listening to Me, Myself, and AI. We believe, like you, that the conversation about AI implementation doesn’t start and stop with this podcast. That’s why we’ve created a group on LinkedIn specifically for listeners like you. It’s called AI for Leaders, and if you join us, you can chat with show creators and hosts, ask your own questions, share your insights, and gain access to valuable resources about AI implementation from MIT SMR and BCG. You can access it by visiting mitsmr.com/AIforLeaders. We’ll put that link in the show notes, and we hope to see you there.
“The MIT Sloan Management Review is a research-based magazine and digital platform for business executives published at the MIT Sloan School of Management.”
Post details > link to site
