Rishad Usmani: Hi, Adam, thanks so much for joining me today.
Artem Trotsyuk: Hey? Thanks for having me.
Rishad Usmani: There are things that we learned in our childhood which help us and contribute to our success in lots of ways, both career and personal life.
Rishad Usmani: And there are things we have to unlearn from our childhood.
Rishad Usmani: What? What are some things you learned from my childhood which have helped you? What are some things you've you've had to unlearn.
Artem Trotsyuk: Totally so. It's super interesting question. Um, I think as a kid, there was a lot of.
Artem Trotsyuk: As a 1st child. There's a lot of the need to.
Artem Trotsyuk: Find and be independent, and find um.
Artem Trotsyuk: Find solutions to problems because no one else is going to be there to help you out to do those problems, to solve those problems.
Artem Trotsyuk: And I'd say that was the thing that I had to do early on. And it's something that continued on into a lot of the work that I do now.
Artem Trotsyuk: One thing I did have to unlearn is the fear of public speaking.
Artem Trotsyuk: So growing up. I never liked to take the stage, even speaking in front of a class was always a difficult thing.
Artem Trotsyuk: Uh, it gets so nervous to do that. And you know, nowadays it's still kind of you can't kind of get the jitters, but.
Artem Trotsyuk: You. There's there's psychological tricks that I've learned that help me be a better public speaker.
Artem Trotsyuk: And not worry so much when I'm on the stage, for example. And so that's been one thing that I've had to unlearn.
Artem Trotsyuk: But I'd say everything else has been kind of like. I'd say you. You're you.
Artem Trotsyuk: And say, you're the nature and the nurture arguments. I do think that there's an aspect of once you're the environment that you're born in and kind of can help mold you into the next stage of your life.
Rishad Usmani: And maybe extrapolate that environment into AI.
Rishad Usmani: And as we get into AI learning new things.
Rishad Usmani: How much of. And and maybe this question doesn't.
Rishad Usmani: Completely apply for AI. But how much of AI learning, do you think is nature versus nurture?
Rishad Usmani: Was something inherent in AI, and its capabilities was something it's learning from its environment.
Artem Trotsyuk: Oh, you hit, I mean, you brought up a super interesting point. So the interesting part is, um.
Artem Trotsyuk: AI right now is very much in the.
Artem Trotsyuk: Non-physical domain for the most part, meaning that it's all on your screen. You can't physically touch it yet.
Artem Trotsyuk: You could. I mean what self-driving cars and waymos, and some Tesla robots.
Artem Trotsyuk: They're kind of learning from their environments.
Artem Trotsyuk: But the concept is that majority of AI tools are Sas tools, and those tools are.
Artem Trotsyuk: Primarily in a non-physical, tangible world.
Artem Trotsyuk: And so a lot of the models that are used to kind of interact with the world. They're evolving with the.
Artem Trotsyuk: The premise that um.
Artem Trotsyuk: Someone's coding them. So that's kind of the the nature component. Right? You're kind of ingraining in their coding certain lines of code on how action items and scenarios.
Artem Trotsyuk: The more.
Artem Trotsyuk: Interesting part will be when.
Artem Trotsyuk: AI is more interacting with the physical world. And that's where it starts to learn new things and.
Artem Trotsyuk: I. It's not there yet, but I feel like that is the next frontier with robotics, for example.
Artem Trotsyuk: Um robotics right now, primarily are, they're programmed to do specific sets of tasks. So.
Artem Trotsyuk: I went to.
Artem Trotsyuk: I got a smoothie the other day just because the thing that was making it was one of those robots that kind of.
Artem Trotsyuk: Just that had a bunch of fruit, and it just was self programmed to pick up the fruits. And then.
Artem Trotsyuk: To put it into a into a blender, and then mix it, and then pour it into a cup and push that cup out. But it was pre-programmed with a specific set of instructions.
Artem Trotsyuk: Now.
Artem Trotsyuk: It would have been a different experience if, instead of there was just a touch screen, I selected what I wanted, and then it just output for me a drink.
Artem Trotsyuk: Imagine it was a humanoid robot standing there, and I would have a conversation with it.
Artem Trotsyuk: What would that be like? That's kind of where this.
Artem Trotsyuk: Like the future state of.
Artem Trotsyuk: If this is going to be a future reality.
Artem Trotsyuk: Like that. Then imagine having the AI continually learn by interacting not only with humans, but also.
Artem Trotsyuk: With other AI robots, for example, or AI, other AI systems.
Artem Trotsyuk: What is that gonna look like? I don't know. But uh.
Artem Trotsyuk: I think it's an interesting.
Artem Trotsyuk: Next shift in technology development that we're in right now that we're observing a lot of it's moving pretty quickly.
Artem Trotsyuk: But it's still more or less.
Artem Trotsyuk: Not not everything, but more or less constrained to the computer, for now.
Rishad Usmani: So currently, you're an AI fellow at Stanford. Tell me more about kind of your day to day.
Rishad Usmani: Work there, and then walk me through the trajectory of your career, and you can start as early as high school. And and what does your career look like so far.
Artem Trotsyuk: Yeah, my career is pretty nonlinear. I grew up.
Artem Trotsyuk: Wanting to be a doctor.
Artem Trotsyuk: And instead of going to medical school, I ended up going to graduate school.
Artem Trotsyuk: So kind of still became a doctor.
Artem Trotsyuk: But not that type of doctor. The other doctor.
Artem Trotsyuk: Um, I always get sometimes get asked the question I'm like, Oh, can you prescribe me something I'm like? No, I can't. Unfortunately, I'm not that type of doctor, you know.
Artem Trotsyuk: Ah, so things were very nonlinear. And actually, I'm very happy that I chose the Phd. Route rather than Md. Routes. There's a lot of.
Artem Trotsyuk: Um. I feel like opportunities that have been uh.
Artem Trotsyuk: Ones. I've been able to kind of.
Artem Trotsyuk: Tap into because of having the.
Artem Trotsyuk: More um.
Artem Trotsyuk: Research, heavy experience that you get through. A Phd allows for you to kind of see a lot of different components. So.
Artem Trotsyuk: I studied engineering computer science. Through that we developed smart devices for wound care. And then, seeing clinical translation from the research to a bedside.
Artem Trotsyuk: Application was super interesting. But then, also, how do you integrate AI safely and patient data and going through and mining the data for.
Artem Trotsyuk: Useful corollaries to predict wound healing. What sensor should I.
Artem Trotsyuk: Put into a device.
Artem Trotsyuk: That would output a successful result, meaning that I.
Artem Trotsyuk: A wound is getting better. And here the sensors are changing. Here's what I need to. And here's how I need to modulate the treatment parameters, etc.
Artem Trotsyuk: And then, in doing that, it was quite interesting to see.
Artem Trotsyuk: How AI is being deployed in the clinical space, and then how AI development.
Artem Trotsyuk: Where AI research is happening on the research side with.
Artem Trotsyuk: With patient, related data. I was interested in that.
Artem Trotsyuk: And that I transitioned into more a fellowship role. After graduating to.
Artem Trotsyuk: Ah! To extrapolate more of these risks that are tied into AI development, and so.
Artem Trotsyuk: That's where a lot of the.
Artem Trotsyuk: The work now has been thinking about.
Artem Trotsyuk: If you are to deploy AI systems.
Artem Trotsyuk: What is reasonable? How do we ensure that we are mitigating bias within the algorithms? How do you make sure that patients are.
Artem Trotsyuk: Save that we want to. Uh.
Artem Trotsyuk: Ah! Not have unforeseen risks or problems for vulnerable, patient populations.
Artem Trotsyuk: And how do we like equitable deployment of AI tooling and.
Artem Trotsyuk: A lot of these different topics. We get to kind of think about more on the.
Artem Trotsyuk: From the ethics lens. And then thinking about, how do we work with policymakers to to translate that into more policy efforts that can.
Artem Trotsyuk: Help people not only understand the limitations and the possibilities of AI systems.
Artem Trotsyuk: But also, okay, if we were to create policies, how do we not hinder innovation, but also make sure that we are.
Artem Trotsyuk: Uh um uh.
Artem Trotsyuk: Modulating risk such that it's not.
Artem Trotsyuk: It's not propagating and just kind of doing whatever. And we're we're considering.
Artem Trotsyuk: Considering patient safety and so forth. So that's kind of how.
Artem Trotsyuk: How my research work informed me in terms of the AI. Work at Stanford.
Rishad Usmani: I have. I have 2 different questions.
Rishad Usmani: The 1st one is. This is something I find in in academics and physicians quite a bit.
Rishad Usmani: Um is as they value their product.
Rishad Usmani: And the technical problem they're solving. And the technical solution, they're developed. I would say 80 to 90%.
Rishad Usmani: And the value distribution, the other 10 to 20%. And there's a graveyard of.
Rishad Usmani: Excellent solutions, which would have.
Rishad Usmani: Done a lot of good in the world.
Rishad Usmani: And saved a lot of lives.
Rishad Usmani: That didn't make it to market, and did not commercialize because of not valuing the latter.
Rishad Usmani: What are kind of your thoughts here.
Rishad Usmani: And and you know, to kind of build on this as a physician.
Rishad Usmani: Wound. Healing. A lot of it is just clinical, right? I look at a wound I'm like. Is it healing.
Rishad Usmani: There's certain things I look at, but it's very subjective. There's no.
Rishad Usmani: You can get into pressure and and vac wounds and.
Rishad Usmani: You know the specific pressure in the wound, and if it's a.
Rishad Usmani: If it's alive, or if it's there's dead tissue and.
Rishad Usmani: And measuring it. But, to be frank, in most of the clinical community, we just look at it.
Rishad Usmani: And we just say it's necrotic or it's not necrotic. Is it warm? Is it cold?
Rishad Usmani: But it's very subjective. And then asking me to use a solution to replicate that.
Rishad Usmani: Usually requires tons of data and FDA approval.
Rishad Usmani: So I guess I guess it's a 2 part question. One is, how do you think about distribution? And then what do you think drives.
Rishad Usmani: Clinical adoption for medical devices and technologies such as these.
Artem Trotsyuk: The hardest part is, I think, what you're alluding to. There is changing a physician's mind.
Artem Trotsyuk: In how to do their job.
Artem Trotsyuk: Right, and because there's a certain aspect of kind of like.
Artem Trotsyuk: And if I were to make a parallel with sports, athletes.
Artem Trotsyuk: Um. They got to a certain place in where they are in their career by doing things a certain way, and it's been working.
Artem Trotsyuk: And things have been doing, going well.
Artem Trotsyuk: So why would a sports athlete.
Artem Trotsyuk: Change their diet if they made it to the Nfl. By eating burgers and nachos, for example.
Artem Trotsyuk: And telling them that you can't eat that anymore, because now you have to do something better, I was like, well, don't tell me what to do.
Artem Trotsyuk: I've gotten here because I've been doing what I've been doing, and it works really well for me. Clearly, I'm performing on the field.
Artem Trotsyuk: Similarly with physicians. Often it's there's an aspect of.
Artem Trotsyuk: I've seen a lot of cases. I've treated a lot of cases. I know how this is done. Why would I adopt a new solution? That is.
Artem Trotsyuk: Not within my workflow, or is going to disrupt my.
Artem Trotsyuk: My my flow, standard care, etc.
Artem Trotsyuk: And I think what's super important there is tie in and having physician partnership and buy in earlier on. So if you're developing solutions.
Artem Trotsyuk: There's a component of working with the physicians to actually develop something that's useful because there are problems that are still.
Artem Trotsyuk: Not solved in the medical domain that physicians don't have the time to solve.
Artem Trotsyuk: But they'd love for someone to go solve that problem. And so that's the biggest part is.
Artem Trotsyuk: If I were to partner with you, for example, and create something, what would be actually useful for you that you'd be like, yeah.
Artem Trotsyuk: That would help me do my job better rather than that is not a useful tool for me to use, and I'm not interested in that tool.
Artem Trotsyuk: So that's where I think the differences between things that are more adopted within the community versus not. And even if you can get more physician buy-in by, say, having a co-founder as a physician. If you're developing a med tool.
Artem Trotsyuk: Or if you have some folks on the board, those folks at least can advocate for you, or advocate on the behalf of what you're developing.
Artem Trotsyuk: So on our smart bandage technology. We were fortunate that it was being.
Artem Trotsyuk: Led by Dr. Jeffrey Gertner, who is.
Artem Trotsyuk: A physician scientist. He sees patients. He was at the wound care center. Frequently he was treating wounds, so he saw the problems that were happening in that space.
Artem Trotsyuk: And he was keen on having solutions that actually can be put on. Patients lives and.
Artem Trotsyuk: Create things that would actually be useful. And so for him it was a very clear.
Artem Trotsyuk: Roi, investing the research time into it in terms of having some sort of product that can then be eventually shipped onto patients.
Artem Trotsyuk: But then, again, that is because of his interest in it. If he didn't have an interest in it, it would be a different story.
Rishad Usmani: You've kind of touched both the academic world, but also the finance and the Vc. World.
Rishad Usmani: Tell me about how you got into.
Rishad Usmani: Your gig as an entrepreneur in residence, and then maybe tell me a bit about your work with Openai.
Artem Trotsyuk: Yeah. So the the beautiful part about Silicon Valley is that there are so many.
Artem Trotsyuk: Opportunities for you to just show up and participate in.
Artem Trotsyuk: And I mean that in a like, in a.
Artem Trotsyuk: In a way of one of my mentors, Ron John Nag. He 1 point, said.
Artem Trotsyuk: You know, there's there's ideas laying on the ground. You just got to pick one up and go with it. Kind of thing like there's.
Artem Trotsyuk: There's there's plenty of things to do. It's just a matter of execution. That's the 1st thing he's like. Another part is.
Artem Trotsyuk: Just show up. You don't know who's going to be in the room. You don't know who's there. You don't know what what you can do if you're not there, and you're not present.
Artem Trotsyuk: And so there's this. If you've seen now this more push of people going back into the office or returning back into work and so forth.
Artem Trotsyuk: And there, there's a certain aspect of convenience, of being working from home and being able to do a lot of the work from home.
Artem Trotsyuk: And I feel like there's a good balance between work from home versus work in the office. But there's a certain value. Add where, if you're doing.
Artem Trotsyuk: Problem solving or critical problems that you need to identify solutions for.
Artem Trotsyuk: To be in a group set setting where you can work there together with folks, and so.
Artem Trotsyuk: Um with kind of the entrepreneurial side. There is a lot of.
Artem Trotsyuk: When I was doing my Phd program.
Artem Trotsyuk: Um. People are doing startups all the time at Stanford. There's.
Artem Trotsyuk: The graduate school business. There's the there's a ton of startups coming out from there. There's the.
Artem Trotsyuk: Biodesign, folks, there's the.
Artem Trotsyuk: There's a lot of other entrepreneurship hubs on campus and so forth. So I was quite keen on understanding what that.
Artem Trotsyuk: Ecosystem was like, particularly from a scientist science perspective.
Artem Trotsyuk: Where we, as a scientist, bring technical expertise to the table.
Artem Trotsyuk: However, and that we don't necessarily know the the non technical stuff.
Artem Trotsyuk: And how do we learn the non technical in order to talk to people about technical, but also have a frame of reference. For like earlier, talking about the value of death and.
Artem Trotsyuk: Translating technologies.
Artem Trotsyuk: How do we? If if you weren't exposed to that value, you didn't know what that existed, you would have one perspective on it. So it's the flip side of the coin that I think is super valuable, that you get from an ecosystem.
Artem Trotsyuk: And at Stanford you just you get that as an ecosystem. And so that's where I was able to.
Artem Trotsyuk: Plug in and kind of, participate, and learn from that ecosystem, and then learn and.
Artem Trotsyuk: Bring the domain expertise of computer science and engineering.
Artem Trotsyuk: Biology, all a wound, healing all that to the table when evaluating a company and looking at a company deal.
Artem Trotsyuk: And then taking that as reference point, and understanding how the market dynamics respect and view that situation so.
Artem Trotsyuk: That's kind of how I got involved on on the on the investment side, because there was a certain aspect of technical domain expertise that I was able to bring to the table that.
Artem Trotsyuk: Someone say, who's only getting an Mba does not have because there's a component of just like when you're doing a Phd program, you go deep into a topic. And you're you're the world's expert in a specific topic.
Artem Trotsyuk: So you're going to be able to talk about that topic. I can talk about wound healing and stuff that works and doesn't work. I've been on to all those conferences, all those trade shows a lot of stuff that doesn't work. There's a lot of people trying solutions, but they're all within the same scope. Right? Everyone's trying.
Artem Trotsyuk: A better dressing, a better hydrogel, a better skin substitute. There's all the stuff that people are trying, but.
Artem Trotsyuk: Isn't moving the needle forward is, and is that going to really push the needle on innovation forward? Is, or is this just another thing.
Artem Trotsyuk: That isn't really going to do anything. And you're just not going to have a product market fit and so forth.
Artem Trotsyuk: So that's kind of how I got involved with that. And it was. It's been a fun journey to be able to be on both the investment side.
Artem Trotsyuk: As well as the operation side.
Artem Trotsyuk: And kind of straddle both, and see.
Artem Trotsyuk: 2 sides of the coin necessarily just quickly.
Rishad Usmani: We're seeing this with AI scribes. And even though they don't technically as.
Rishad Usmani: Work as well as the standard of care. They're worse than the standard of care.
Rishad Usmani: They're receiving.
Rishad Usmani: Immense market adoption because they make things easier for me.
Rishad Usmani: Do you think there's a parallel here to be drawn in medical device where maybe something doesn't even work as well as the current standard of care.
Rishad Usmani: But it just makes my job easier and.
Rishad Usmani: Or do you think success, and by success I mean an exit for a startup.
Rishad Usmani: Is more contingent on the product working.
Rishad Usmani: Or their ability to sell into clinical workflows and.
Artem Trotsyuk: You too, both so.
Artem Trotsyuk: In order for them to sell into the clinical workflow. I hope the product has some sort of workable something or another.
Artem Trotsyuk: So in your example of scribes. Uh.
Artem Trotsyuk: You're right. They're not fully there, but at least to get you 80% or 90% of the way there, and you can quickly correct it, which makes it faster for you.
Artem Trotsyuk: And actually makes it better for the patient, because then you have all the.
Artem Trotsyuk: Quick transcription notes, and you can kind of make sure that the patients have enough.
Artem Trotsyuk: Documented history such that you have a more representative view of what you and the patients talked about.
Artem Trotsyuk: Um for medical devices.
Artem Trotsyuk: You would have.
Artem Trotsyuk: A certain need to have the device work. Well, I hope because in order for it to get approved.
Artem Trotsyuk: You would need to.
Artem Trotsyuk: Document and prove that the device actually works.
Artem Trotsyuk: Uh the.
Artem Trotsyuk: What I've noticed on the adoption side, it goes back to one. Is someone going to pay for something that you're developing. So in the medical device space. It's quite difficult, because.
Artem Trotsyuk: You need to find someone who's willing to buy what you're building, and if you don't have someone who's willing to buy what you're building. Don't build it, to begin with, as kind of the model that I have now adopted.
Artem Trotsyuk: Because you can spend all this money.
Artem Trotsyuk: Invest your money, your money, to build something, and then you have no.
Artem Trotsyuk: Interesting party to say, here's some money for it.
Artem Trotsyuk: And then you're stuck because you've developed something. You think the hospitals are going to buy it. Hospitals are actually not going to buy it.
Artem Trotsyuk: And then what? And then you're kind of stuck with just holding the bag of your device that you just developed.
Artem Trotsyuk: So there's this.
Artem Trotsyuk: True component around. If you're going to build something in the medical device space, if it's something that you're planning on implementing with patients who needs to be.
Artem Trotsyuk: If it's something that needs to be prescribed by a physician.
Artem Trotsyuk: You want that to work? Well, if it's something that people can just buy at your Walgreens or your Cvs.
Artem Trotsyuk: As as kind of their own option. That's really up to them. They can go and buy something as a device.
Artem Trotsyuk: Or some sort of feature like, say.
Artem Trotsyuk: Uh! I don't know uh.
Artem Trotsyuk: A a specific type of walking instrument, for example, or right now. Uh, I've seen on uh.
Artem Trotsyuk: I've seen ads where there's the.
Artem Trotsyuk: The exoskeletons that help people walk upstairs and so forth, and they're lighter, faster, better. And you can kind of buy them for only $799, or something like that for the basic one. But if y'all want the faster battery pack, it's 1,200 or something like.
Artem Trotsyuk: There's there's a whole gamut of things, but those are, if you like.
Artem Trotsyuk: The ones that are.
Artem Trotsyuk: Consumer oriented. So it's a consumer market.
Artem Trotsyuk: Play rather than specifically a hospital play. And so it really depends on what the the.
Artem Trotsyuk: The entrepreneurs building.
Artem Trotsyuk: And what they want to deploy through the market fit. But.
Artem Trotsyuk: Anyone who's building a startup needs to have.
Artem Trotsyuk: Some sort of product market fit idea earlier on. And then, especially if you're going in something that is going to be more.
Artem Trotsyuk: Business development heavy. You should start those relationships early.
Artem Trotsyuk: As the general just now.
Rishad Usmani: What are your thoughts on digital therapeutics as a category? A. After what happened with their health.
Rishad Usmani: Um. We're kind of seeing.
Rishad Usmani: The category not take off as much, and it seems like we have this inherent.
Rishad Usmani: Um. You know.
Rishad Usmani: Inherent feel that I can take a pill.
Rishad Usmani: To make something better. But if it's a if it's a digital solution, it's less likely to work. And it's not really grounded on fact or any logic.
Rishad Usmani: It's just the way I think we as a market.
Rishad Usmani: Or as humans feel. What are your thoughts on digital therapeutics? Do you kind of see them.
Rishad Usmani: Are you Bullish on them, or are you bearish on them?
Artem Trotsyuk: Uh depending. What domain uh they're in.
Artem Trotsyuk: I think right now we're in a space where digital anything is easily disrupted.
Artem Trotsyuk: And it's a question of if they are to invest in a company that has a digital angle.
Artem Trotsyuk: Of digital therapeutics. For example, a mental health app.
Artem Trotsyuk: For example, if I were to invest specifically in that.
Artem Trotsyuk: Ah category does.
Artem Trotsyuk: That bring a return to the fund. That is kind of like a a big question here.
Artem Trotsyuk: I don't know if it does right now. At this moment, on May 30, th 2025.
Artem Trotsyuk: It could be something different tomorrow it might have been something different yesterday. I bring this up because.
Artem Trotsyuk: There. It is a very.
Artem Trotsyuk: Disruptable space, and a consumer play is very hard, especially in digital.
Artem Trotsyuk: You're trying to get people to use your app.
Artem Trotsyuk: Versus another app attention. Spans are difficult to capture. People are busy, people are distracted with everything.
Artem Trotsyuk: Trying to have them get yet another app is quite hard.
Artem Trotsyuk: And right now there's something called vibe coding, where you can just build your own app if you want.
Artem Trotsyuk: So then the higher order question. Now, I'm literally asking if someone's pitching a idea of like an app.
Artem Trotsyuk: I ask, and I say, can I vibe code this up myself?
Artem Trotsyuk: Because if the answer is Yes.
Artem Trotsyuk: Then you have no business. It kind of. I hate to say it, but.
Artem Trotsyuk: If I can take your app.
Artem Trotsyuk: Recreate it for 1, 99.
Artem Trotsyuk: In 30 min, and launch it by.
Artem Trotsyuk: We're using a few services to kind of launch it onto a web app store or something.
Artem Trotsyuk: What is the business model for people who are developing digital health apps.
Artem Trotsyuk: So it's it comes down to have you captured a market segment and consumers willing to.
Artem Trotsyuk: Buy into your service. Specifically, that's your date. That's your moat. It's the data that the people are allowing you to capture and the people that you've.
Artem Trotsyuk: Pulled in and said, Please stay, and they want to stay and use your service. Otherwise you have no digital moat.
Artem Trotsyuk: Everyone else can now pull that up. I think I even heard.
Artem Trotsyuk: A talk from, or a mention.
Artem Trotsyuk: That the Linkedin founder.
Artem Trotsyuk: Said that he, Vibe, coded up. Linkedin.
Artem Trotsyuk: In 30 min. The same website that they spent many, many, many like many dollars, and many.
Artem Trotsyuk: But a lot of time on.
Artem Trotsyuk: One person 30 min. He's like.
Artem Trotsyuk: Crazy. You can do literally the same thing.
Artem Trotsyuk: By just using some of these new tools that are being developed.
Artem Trotsyuk: So then that mean that for all the founders listening.
Artem Trotsyuk: Rethinking that strategy like what is your modes.
Artem Trotsyuk: That is the most important part, and specifically in digital, how fast you're getting it into people's hands. And are they staying.
Artem Trotsyuk: Are these people staying with you versus going somewhere else?
Rishad Usmani: How, how far are we from.
Rishad Usmani: A point where a person like me, who has.
Rishad Usmani: No coding knowledge.
Rishad Usmani: Um. I can maybe say Hello, world, and that's about it.
Rishad Usmani: Now, how far are are we from me being able to vibe code.
Rishad Usmani: A solution. Um.
Rishad Usmani: For a mental health lab, say which which has that.
Artem Trotsyuk: You can do it today.
Artem Trotsyuk: You can do it. Today, you can go on.
Rishad Usmani: So that beings.
Artem Trotsyuk: Lovable dot dev. That's like one example, and you can use language, and you can chat in that.
Artem Trotsyuk: Site and say, I want to create mental health app with these features, measuring these markers.
Artem Trotsyuk: It's going to go and think for about 10 to 15 min.
Artem Trotsyuk: And it's going to output you an app.
Artem Trotsyuk: And then you can kind of say, Oh, I don't like this feature. Can you please modify this? Or can you change this and etc, etc?
Artem Trotsyuk: And you modify as you like, but you can do it now. There's tools out there that.
Rishad Usmani: And it will, it will debug the the back end as well.
Artem Trotsyuk: It's do. Yes. And so if something's not working, it'll like, for example, if you're trying to push something, it's not working. It says error. You tell the app you tell lovable like.
Artem Trotsyuk: There's an error. I'm confused. It's not allowing me to do it, and it will say things like running a script to identify errors, fixing the errors. It looks like we identified errors, and we fixed them and stuff.
Artem Trotsyuk: So you'll get workable something. And then, if you were to deploy that, then there's a few other steps you take in terms of.
Artem Trotsyuk: Qc. And making sure that it's on a specific server and stuff. And so.
Artem Trotsyuk: Those those few things say, you can use chat to identify. What are the steps for you to launch an app and what vibeco tools exist for you to go from a prototype version to a full deployable version.
Artem Trotsyuk: But you don't necessarily need to.
Artem Trotsyuk: Ah, write your own code. It you can do it now if you want.
Rishad Usmani: So for for an AI solution.
Rishad Usmani: Does. Defensibility now lies solely in the distribution advantage? Or is there some.
Rishad Usmani: Inherent product defensibility.
Artem Trotsyuk: That's that's the hard part right now. Everyone's trying to figure that out like, what is the defensibility of AI solutions in which, if I can.
Artem Trotsyuk: Vibe coded out.
Artem Trotsyuk: What happens to the you know, how do you, IP? AI, and it's quite hard. Right? That's a very hard problem to do.
Artem Trotsyuk: That people are so solving right now.
Artem Trotsyuk: But I go back to. If you're develop developing any kind of AI solution.
Artem Trotsyuk: Your your moat.
Artem Trotsyuk: Is your people aspect or your business, or your clients, whoever you're.
Artem Trotsyuk: Saying are going to use that. That's your moat. Because if you have a solution which you have hundreds of thousands of people on.
Artem Trotsyuk: And they like it, and they continue coming back to it. Then you have a growth strategy in which you can pull in more people.
Artem Trotsyuk: If you don't have that, and they can turn and go to another.
Artem Trotsyuk: Place doesn't matter how great your app is, someone else can develop that they can pull your customers away from you, and customers don't come back.
Artem Trotsyuk: Doesn't matter.
Rishad Usmani: That being said, what are your thoughts in the future of knowledge work? Are we all marketers in the future?
Artem Trotsyuk: I think we're all creatives in the future.
Artem Trotsyuk: Because.
Artem Trotsyuk: In order for you to get a good output from AI tools. You need to have a good.
Artem Trotsyuk: Way to prompt the tool to do the work.
Artem Trotsyuk: And prompting comes from having.
Artem Trotsyuk: What understanding, well good understanding.
Artem Trotsyuk: Of the English language in this case, because a lot of the tools are being built out primarily in English, but there are.
Artem Trotsyuk: Other languages coming online.
Artem Trotsyuk: Being able to ask.
Artem Trotsyuk: The AI, the right way.
Artem Trotsyuk: Comes from being able to communicate.
Artem Trotsyuk: In English the right way.
Artem Trotsyuk: In order for the tool to understand you. So you going back to being more creative thinkers.
Artem Trotsyuk: And creatively walking through a task is something that more people are going to get used to.
Artem Trotsyuk: I don't buy the.
Artem Trotsyuk: AI will replace people, because that's been an argument that's been said over the last 100 years.
Artem Trotsyuk: And we're still around. And there's still money to be made. And there's still different types of jobs. There's new types of jobs that come out every single time. There's 1 of these pushes.
Artem Trotsyuk: Right, you know, even an influencer. I didn't. When I was growing up. There was no such job as I can be an influencer.
Artem Trotsyuk: That's a whole category in a huge market right.
Artem Trotsyuk: Um.
Artem Trotsyuk: How does work?
Artem Trotsyuk: Change. That's the whole interest. That's no one really knows, because.
Artem Trotsyuk: Technology is moving so quickly. But if you've noticed, kind of.
Artem Trotsyuk: Some AI tools are growing really fast.
Artem Trotsyuk: But then there's some companies that are like.
Artem Trotsyuk: It's not working as well. So we're scaling back in the amount of deploying AI that we're having. We're gonna have more humans in the loop.
Artem Trotsyuk: Why is it that it's not working? Well, well, it's because the solution.
Artem Trotsyuk: Is hallucinating. There's an aspect that the solution was not trained on certain set of data.
Artem Trotsyuk: It wants to provide you with an output.
Artem Trotsyuk: And so it provides you with what it thinks is a reasonable output. Given the structure of the data.
Artem Trotsyuk: But it's not the correct output, because of what you know as correct by format.
Artem Trotsyuk: So then the higher order question is.
Artem Trotsyuk: How do we.
Artem Trotsyuk: How do we rectify this? Right? How do we? How do we balance that? And it's still gonna be. There's a lot of human in the loop component that still needs to happen. And so I'm not at the point that AI is going to replace us at this point. Yet I feel like it's.
Artem Trotsyuk: AI will only enable us, in terms of doing even more interesting fun stuff.
Rishad Usmani: This is a full circle moment where the most.
Rishad Usmani: Competitive, and the most useful degrees of the future might be arts and language, degrees.
Rishad Usmani: And and not stem degrees.
Artem Trotsyuk: Yeah, people.
Rishad Usmani: Which is a very, very interesting reality.
Artem Trotsyuk: I think people need to understand how computers work.
Artem Trotsyuk: How AI systems work.
Artem Trotsyuk: How how architecture stuff, works, how large English model works.
Artem Trotsyuk: But I don't necessarily.
Artem Trotsyuk: Us believe that.
Artem Trotsyuk: You shh.
Artem Trotsyuk: It would that you will not be able to get.
Artem Trotsyuk: Some interesting application layer on top of that.
Artem Trotsyuk: I think that we don't necessarily know.
Artem Trotsyuk: What jobs might be created, because it's moving so quickly.
Artem Trotsyuk: And it's uncertain what work will look like.
Artem Trotsyuk: Clearly work is being augmented and certain.
Artem Trotsyuk: Laborious tasks are being offset with tooling that's being developed.
Artem Trotsyuk: But it's still in its early phases of being iterated on and tested.
Artem Trotsyuk: And so the higher order question is, what is that equilibrium? Once we reach a certain.
Artem Trotsyuk: Adoption, a certain level of adoption.
Artem Trotsyuk: What is that equilibrium? And what does that look like?
Artem Trotsyuk: And I feel like that's still not decided yet.
Rishad Usmani: And do you kind of buy into the Sequoia philosophy that the future unicorns and decacorns.
Rishad Usmani: Will be application layers built on these platform companies.
Rishad Usmani: Versus should we still.
Rishad Usmani: Be building new models, new platform companies for AI.
Artem Trotsyuk: I've heard of that discussion around kind of web 1.0 web, 2 point. Oh, the Facebooks and the Googles and those are all built off of the Internet. And so this is similarly.
Artem Trotsyuk: AI tools are one set of or AI language models.
Artem Trotsyuk: Models themselves are your application, your your foundation level, and then the applications are built on top of that.
Artem Trotsyuk: I don't think any of us have seen strong, convincing applications that have come out just yet.
Artem Trotsyuk: Because they're all sort of integrated, even.
Artem Trotsyuk: For example, Google's recent announcements with Vo and a few others, the things that they come out.
Artem Trotsyuk: Pushed out.
Artem Trotsyuk: Not only like killed a bunch of snap.
Artem Trotsyuk: Literally, but in a way, a lot of startups were working in certain verticals specific to creating video and creating images and such.
Artem Trotsyuk: And then you have a Google showcase in which they're dropping video models, image models. And so.
Artem Trotsyuk: How does that redefine the application layer companies that work in that space to specifically be really good at specifically, video creation, for example.
Artem Trotsyuk: Uh.
Artem Trotsyuk: We don't necessarily know.
Artem Trotsyuk: Yet what the next? Facebook will be.
Artem Trotsyuk: In kind of looking at the landscape.
Artem Trotsyuk: But there's still a lot more work to be done in model development, to make them be.
Artem Trotsyuk: Similar to human thought, human reasoning.
Artem Trotsyuk: That a lot of people are still working through. So it's still pretty early stages.
Artem Trotsyuk: A lot of the exciting work happening right now in the AI space is focusing on reasoning, focusing on.
Artem Trotsyuk: The decision making, focusing on.
Artem Trotsyuk: Modeling, psychology.
Artem Trotsyuk: And AI systems, and that in itself.
Artem Trotsyuk: Is still fairly new. And that's where social science.
Artem Trotsyuk: Comes in and having people who are studying social science partner with computer scientists develop more.
Artem Trotsyuk: Human like models is super.
Artem Trotsyuk: Exciting, in my opinion.
Rishad Usmani: So one of the key things, I think, and I'm not technical.
Rishad Usmani: Is the Internet has no owner.
Rishad Usmani: Because the military kind of standardize the the Tcp. Or the Icp. And from what I understand, those like the.
Rishad Usmani: How to design and Internet protocols.
Rishad Usmani: Um. Anyone can. Then go ahead and build.
Rishad Usmani: The Internet isn't 1 Internet.
Rishad Usmani: It's multiple autonomous networks.
Rishad Usmani: We're not seeing this in the AI Foundation models. People own these models. There's companies that own the base models.
Rishad Usmani: Do you think that.
Rishad Usmani: Um, you know, the same thing will happen to AI foundation models where they will just be ubiquitous and.
Rishad Usmani: What an AI, the the core structure of an AI foundation model will be public knowledge.
Rishad Usmani: And then everyone can build it. And it's kind of standardized or.
Rishad Usmani: Do you kind of see that happening in the AI Foundation model? What happened with Internet.
Artem Trotsyuk: It's it's already moving in that direction. Right? You have Facebook releasing Llama.
Artem Trotsyuk: You have the open source community deep, seek.
Artem Trotsyuk: People are developing different models. So.
Artem Trotsyuk: It's already moving in a direction of.
Artem Trotsyuk: The money.
Artem Trotsyuk: To be made in the potential future is going to be more on the application side.
Artem Trotsyuk: Rather than on the model side, since the models are becoming more a commodity like the Internet as you mentioned. So.
Artem Trotsyuk: I think that it is moving in that direction, and.
Artem Trotsyuk: You'll see a lot more of that.
Artem Trotsyuk: Every company.
Artem Trotsyuk: Models themselves will become more commodities.
Artem Trotsyuk: But the way in which the companies.
Artem Trotsyuk: Tune the models.
Artem Trotsyuk: For their specific applications.
Artem Trotsyuk: Is kind of what you were talking earlier about the application layer, in which, if you were to deploy.
Artem Trotsyuk: A custom Gpt or a specific video model or a specific image model.
Artem Trotsyuk: That might be tuned on what your company has as proprietary, that is, on top of.
Artem Trotsyuk: The layer data.
Rishad Usmani: What are you most excited about? AI and drug discovery.
Rishad Usmani: In AI, and generative models for large data and ambient intelligence. And what are some risks you see in those 3 categories.
Artem Trotsyuk: I think it's super interesting to have.
Artem Trotsyuk: The opportunity to mine a lot more data. Now.
Artem Trotsyuk: So if we're looking from a pure research perspective.
Artem Trotsyuk: Because of the.
Artem Trotsyuk: Ability for us to have lower costs on compute.
Artem Trotsyuk: And the ability for us to dissect larger amounts of data, there's still a very large foray of opportunity that we have not fully.
Artem Trotsyuk: Dissected that could lead us to identify new.
Artem Trotsyuk: Modalities for treating diseases.
Artem Trotsyuk: Or different interventions that we have yet to discover. So that's on the research side.
Artem Trotsyuk: I think that there's an opportunity there.
Artem Trotsyuk: Ah for research scientists. Now, if research scientists find some.
Artem Trotsyuk: Crazy version of Covid that we should probably not have be known as a.
Artem Trotsyuk: A variant, or releasing that data into.
Artem Trotsyuk: The Ethernet that might.
Artem Trotsyuk: Make sense for some more safeguarding or safe.
Artem Trotsyuk: Or guardrailing around certain AI tooling.
Artem Trotsyuk: To not have that be as an output, and that's where a lot of the folks in the trust and safety.
Artem Trotsyuk: Teams and a lot of folks who are doing preparedness work.
Artem Trotsyuk: Are tying in their efforts in that space, and.
Artem Trotsyuk: Are culminating this idea of how do we ensure reliable.
Artem Trotsyuk: And useful. AI.
Artem Trotsyuk: But also taking into account that we want to prevent.
Artem Trotsyuk: Bad actors from doing bad the general consensus, even with the work we've studied on.
Artem Trotsyuk: Risk mitigation is that.
Artem Trotsyuk: If a bad actor wants to do bad, they will still do bad. You cannot stop them.
Artem Trotsyuk: What you can do is you can make it harder for them to do that bad.
Artem Trotsyuk: For example, so you can make it harder for people to get a scalable.
Artem Trotsyuk: Product out that is going to scale.
Artem Trotsyuk: To uh.
Artem Trotsyuk: Infect a bunch of people, for example. Perhaps it's harder for them to develop a.
Artem Trotsyuk: Biologic. That is something that can be sequenced in a large scale. Facility.
Artem Trotsyuk: And for research scientists, it is important to kind of think about. If you are to publish some data.
Artem Trotsyuk: If you are to think about the risks associated with the work that you're doing.
Artem Trotsyuk: How does that fit in into the narrative.
Artem Trotsyuk: To make sure that you're developing AI that is safe.
Artem Trotsyuk: That is.
Artem Trotsyuk: Not going to harm people, but also moves the needle forward in discovery.
Artem Trotsyuk: I'm more bullish on AI tooling.
Artem Trotsyuk: As a mode for novel discovery, and I think that there's many more opportunities that we have yet to tap into.
Artem Trotsyuk: Protein sequencing, for example, as a means to identify.
Artem Trotsyuk: New modalities. Perhaps there's more personalized therapeutics as a.
Artem Trotsyuk: As a means to develop something for you as an individual that will work for your body has been research recently shown that.
Artem Trotsyuk: Even if you and I, for example.
Artem Trotsyuk: Eat a bag of chips. My body will react different to those chips than your body will react different to those ships.
Artem Trotsyuk: What does that mean for us if we are trying to create therapies.
Artem Trotsyuk: For drugs. If my body is reacting to trips by not spiking my glucose and your body spikes the glucose.
Artem Trotsyuk: Should you have a different type of.
Artem Trotsyuk: Therapeutic that built for you.
Artem Trotsyuk: That would allow for your body to be more receptive to that therapeutic, whereas for me, it wouldn't really make a difference right.
Artem Trotsyuk: That, I think is super exciting. That is something that you don't necessarily get to see.
Artem Trotsyuk: As a.
Artem Trotsyuk: As an opportunity. If you don't have the ability to mine.
Artem Trotsyuk: A bunch more data in an efficient way to get novel insights. So I I.
Artem Trotsyuk: As going back to what I was saying earlier. We're still way too early to kind of decide.
Artem Trotsyuk: And say, what's happening on the AI front that.
Artem Trotsyuk: That we should completely, not all do anything and mitigate risk. There's there's certain things we need to protect against.
Artem Trotsyuk: But also understanding that we have many, many more discoveries that have yet to happen.
Artem Trotsyuk: And so it's the balance of educating the researchers with the same time.
Artem Trotsyuk: Allowing for the researchers to do their jobs.
Artem Trotsyuk: By being able to develop and deploy these AI tools.
Rishad Usmani: Do you? And I'll ask a very broad question, and then it does lead to a more specific question. But I'd like you to answer the broad question.
Rishad Usmani: First.st Do you think the universe is more probabilistic.
Rishad Usmani: More based on correlation, such as kind of more. The quantum mechanics theory of the universe.
Rishad Usmani: Or do you think it is more deterministic, more causative.
Artem Trotsyuk: I don't know. I mean, that is a good question.
Artem Trotsyuk: Um haven't really thought about that too much. To be honest, I think.
Artem Trotsyuk: There's so many mysteries of the universe that we.
Artem Trotsyuk: Don't know, and it's our all of.
Artem Trotsyuk: The mysteries of the universe are tied to the best hypothesis.
Artem Trotsyuk: Of what's happening in the world.
Artem Trotsyuk: Or how we think certain things operate. But the more we study, the more we realize that some of our hypotheses might not make sense.
Artem Trotsyuk: So not sure. It's a good question, but I don't know if I have a good answer for you.
Rishad Usmani: But so when we think about, and I and I have a very strong inherent bias here which will come across in my questioning.
Rishad Usmani: When we think about medicine.
Rishad Usmani: And AI regulation specifically within healthcare, and the FDA.
Rishad Usmani: We seem to be stuck on this concept of explainability or causation.
Rishad Usmani: We must understand why this happens.
Rishad Usmani: And if AI say comes up with a new molecule that we cannot even detect.
Rishad Usmani: Right. It says there's a molecule that exists.
Rishad Usmani: Or there is a substance that exists in our blood.
Rishad Usmani: Um are in our body, called.
Rishad Usmani: You know, uh, uh. And I'm just making this called a genome or something, right? Something we haven't heard of. And this is what predicts cancer across the board.
Rishad Usmani: And AI says, you know, I have this much correlation data, millions of data points.
Rishad Usmani: This is where you should look out for what I need is a picture of you to detect it, that's all I need. I don't need a blood sample. I don't need anything, or I need your voice. Something we don't use as a diagnostic.
Rishad Usmani: So I'm kind of getting deeper into the woods here. But the the question is.
Rishad Usmani: Are we doing humanity? And AI a disservice by being stuck.
Rishad Usmani: On causation and explainability.
Rishad Usmani: And I'm kind of equating the 2 ended determinism.
Rishad Usmani: Versus just recognizing, you know, all we can find out is correlation.
Rishad Usmani: And and maybe it's because we're not smart enough. Maybe it's because we are limited by 5 senses.
Rishad Usmani: Um. And but we we just can't like it's it's it's an exercise in futility. And we're just wasting time.
Rishad Usmani: Being stuck on explainability and causation, we should just.
Rishad Usmani: Focus on correlation. What are your thoughts? There.
Artem Trotsyuk: Well, you know, like.
Artem Trotsyuk: So uh, you bring up 2 topics that I will.
Artem Trotsyuk: Push, based on what stuff that we talk about in our classes, that we teach on.
Artem Trotsyuk: Intro to AI, and there's an aspect of.
Artem Trotsyuk: Does correlation imply causation, and vice versa.
Artem Trotsyuk: If I were to say that, for example, it's.
Artem Trotsyuk: Today is dry and hot and sunny, sunny, and it's summer weather.
Artem Trotsyuk: Causation could mean that.
Artem Trotsyuk: I want ice cream or causation could mean that I get a sunburn.
Artem Trotsyuk: But does getting a sunburn.
Artem Trotsyuk: And getting ice cream.
Artem Trotsyuk: Is that a correlation meaning that.
Artem Trotsyuk: If if I get a sunburn, then I also get ice cream.
Artem Trotsyuk: But does does that necessarily correlate to it? Being dry, hot, and sunny weather, for example? And there's.
Artem Trotsyuk: There's there's many more different types of. For like.
Artem Trotsyuk: For example, if you have germs.
Artem Trotsyuk: A cause of that could be that it can lead to bad smells.
Artem Trotsyuk: Or a cause can be that it leads to diseases, but doesn't bad smell correlate to disease not always. And so.
Artem Trotsyuk: It's kind of this interesting foray of causation.
Artem Trotsyuk: Versus correlation that we bring up in our class all the time. When people try to link the 2.
Artem Trotsyuk: I think that.
Artem Trotsyuk: For.
Artem Trotsyuk: For what you touched upon on explainable AI.
Artem Trotsyuk: It's important for us to understand how the AI is making certain decisions, such that we can kind of evaluate to make sure it's not hallucinating.
Artem Trotsyuk: So for folks. When I hear explainable AI.
Artem Trotsyuk: For me. That means that I want to understand how it's making its decisions.
Artem Trotsyuk: So that I can evaluate against my knowledge base to determine if that makes sense. If I'm saying I'm going to trust the black box.
Artem Trotsyuk: There's been plenty of documented cases now in which the black box does not make a good decision.
Artem Trotsyuk: Or it makes a decision that is disadvantageous to certain individuals or certain populations of individuals who.
Artem Trotsyuk: Might not have their data.
Artem Trotsyuk: Represented in the data set that the AI is trained on. And so, because of that.
Artem Trotsyuk: It creates an output, but that output is perhaps.
Artem Trotsyuk: Going to impact them in a negative way. And so for me to have an explainable AI. It allows for me to understand, hey.
Artem Trotsyuk: I get, how you made your decision.
Artem Trotsyuk: I think this makes sense. I trust your output.
Artem Trotsyuk: Or I see how you made a decision. I see where the faults are. These are the faults we should address.
Artem Trotsyuk: This way you have AI! That's more fair.
Artem Trotsyuk: At the end of the day, and has a lot more.
Artem Trotsyuk: A equitable opportunity for everyone.
Artem Trotsyuk: And not just one demographic or another. So that's how I view that.
Artem Trotsyuk: But I do think that.
Artem Trotsyuk: If AI enables.
Artem Trotsyuk: Novel discovery.
Artem Trotsyuk: That's a great thing if it can say that if by this molecule like you mentioned earlier by this molecule.
Artem Trotsyuk: You can have this output, and all I need is a picture. Well, hey? If I get if I run a study.
Artem Trotsyuk: In which I identify that molecule in a bunch of people, and all I need is their picture. And I throw that into a system. And it's 99% accurate. Well, maybe that's a new way for doing standard of care. So.
Artem Trotsyuk: It goes back full circle to saying, Hey, AI!
Artem Trotsyuk: Can be an enabler and allow for you to be superhuman by doing your job better.
Artem Trotsyuk: But also having it be explainable, is super important. Because if you don't understand how it's making decisions.
Artem Trotsyuk: How much reliance are we putting on the system right and and low, use case scenarios like scribing you mentioned earlier.
Artem Trotsyuk: That's pretty self-explanatory audio in text out if it can listen.
Artem Trotsyuk: Create correct transcription, it can create a relatively good output. You understand how that system works.
Artem Trotsyuk: Now for more complicated systems that impact people.
Artem Trotsyuk: And their livelihoods, I would hope to understand how it works otherwise.
Artem Trotsyuk: I can just be following a black box and directions. And then whoever program that black box, and or if the AI has been programmed in a way that is.
Artem Trotsyuk: Detrimental to to individuals, right.
Artem Trotsyuk: So that's that's how I view it. It's an interesting topic.
Artem Trotsyuk: But often the idea of causation versus correlation does come up in terms of does one correlate to another.
Artem Trotsyuk: And for now.
Artem Trotsyuk: There there is, there is this balance of actually understanding how AI works, such that it's not who's saying creating stuff up. That's not.
Artem Trotsyuk: Completely irrelevant to what you're trying to do.
Rishad Usmani: Last question, Arden. Say, tomorrow is a hot, sunny day. You're having your ice cream.
Rishad Usmani: Not getting a sunburn, and and you run into your 20 year old self to.
Rishad Usmani: Tomorrow and your 20 year self asks you.
Rishad Usmani: Um! What what advice do you have for me? What would you tell them.
Artem Trotsyuk: Great question, the thing that and I get that a lot.
Artem Trotsyuk: Um.
Artem Trotsyuk: There's 2 ways to look at that lens.
Artem Trotsyuk: There's 1 lens is.
Artem Trotsyuk: I am where I am today.
Artem Trotsyuk: Because of this, the decisions and the things that happened to get me to the point in where I am today.
Artem Trotsyuk: So then, if I am happy with where I am today, would I have changed anything any.
Artem Trotsyuk: Chain, of.
Artem Trotsyuk: Actions that happen to get to where I am. That's that 1st step is.
Artem Trotsyuk: I'm great today.
Rishad Usmani: The caveat being the world is very different today. So if you do the same steps you did in the past 20 years. In the next 20 years. You probably won't get to where you are today.
Rishad Usmani: So you probably have to change some things to get to where you are today.
Artem Trotsyuk: Yeah, but true, true, true. But uh.
Artem Trotsyuk: But also it's kind of like this idea of.
Artem Trotsyuk: The guided path on which you were on.
Artem Trotsyuk: If that so if we're saying that if I met my 20 year old self in 2025.
Artem Trotsyuk: And I told my 20 year old self.
Artem Trotsyuk: These are the lessons that I've learned, and then these are the mistakes you should avoid. From 2025 onward.
Artem Trotsyuk: That would be like a different framing if I'm thinking about. If I were to go back in time and restart.
Artem Trotsyuk: And redo things. I would not change anything, because everything that has happened has taught me certain lessons that have helped me get to where I am today.
Artem Trotsyuk: Now, if I'm saying, if if the question that you're asking is.
Artem Trotsyuk: In 2025, your 20 year old self is kickstarting their career.
Artem Trotsyuk: Is that the question kind of like.
Rishad Usmani: Yeah.
Artem Trotsyuk: Okay. So in 2025, if you are kickstarting your career and learning.
Artem Trotsyuk: And jumping in first, st I would tell my 20 year old self to pick up Cs.
Artem Trotsyuk: So learn how systems work. You don't have to be a professional coder proficient. But you should understand. You should generally understand how computer systems operate.
Artem Trotsyuk: More so now than before. How large language models operate! What is chain of thought? What is reasoning? What's persuasion?
Artem Trotsyuk: I would encourage myself to read more books on social science and psychology.
Artem Trotsyuk: Because understanding how the mind works, will and help you understand how.
Artem Trotsyuk: Future computer systems will work.
Artem Trotsyuk: First.st That's that's inherent, and I would encourage myself to diversify my experiences.
Artem Trotsyuk: In different forays that allow for me to.
Artem Trotsyuk: To capture a broad scale of.
Artem Trotsyuk: Exposure and experiences earlier on, and then test those out in different application layers.
Artem Trotsyuk: There's a lot of uncertainty exactly on. What will the job market look like in a year from now, 2 years from now, 5 years from now, what is safe, what is not safe.
Artem Trotsyuk: It's hard to tell, because today it's safe tomorrow, it's not safe. Today. It's changing. Tomorrow. They're reverting back. Policies are changing all the time.
Artem Trotsyuk: What is safe is identifying something that you are really good at.
Artem Trotsyuk: By bringing certain types of skills to the table.
Artem Trotsyuk: And whatever those skills are that you're just good at, you bring those. And you sell those skills. Your skills are more valuable.
Artem Trotsyuk: Then you can always learn how to vibe code. You can always learn new tools that are being developed. But how are you applying your skills with those new tools.
Artem Trotsyuk: In a in a demographic, and so.
Artem Trotsyuk: Yeah, for for my, that's what I would tell my 20 year old self. Uh.
Artem Trotsyuk: As a starting point. But if we were to reflect back from 20 years ago till now.
Artem Trotsyuk: I would not have changed anything.
Rishad Usmani: Awesome thanks. So much for joining me today.
Artem Trotsyuk: Yeah, no, this was fun. I hope that your audience has a kick and they take an AI class or 2.
Artem Trotsyuk: Uh! We teach them regularly at Stanford. They can take a class with me or Ron John.
Artem Trotsyuk: And kind of learn about these systems and.
Artem Trotsyuk: Or reach out to me directly. If they have any questions.
Rishad Usmani: So if there's anything you said, you kind of you want me to remove, feel free to email me.
Rishad Usmani: Um.
Artem Trotsyuk: You can cut whatever you don't want to to include there. Totally fine. With that.
Rishad Usmani: Okay, um, are you? I think you mentioned someone who would be interested in speaking about ethics and AI.
Rishad Usmani: And consciousness of AI.
Rishad Usmani: And AI writes.
Artem Trotsyuk: Yeah.
Artem Trotsyuk: Wrong John nag oops.
Artem Trotsyuk: See if you're interested.
Rishad Usmani: Are you able to.
Rishad Usmani: Okay, I'll I'll look at their profile in.
Artem Trotsyuk: Yeah, look him up. If you're said, send me a note and I will reach out. I'll ask him. And you guys can talk about AI. Consciousness and boundaries of humanity.
Rishad Usmani: Yeah.
Rishad Usmani: Thanks. Yeah, that was very interesting. I really enjoyed that.
Artem Trotsyuk: Cool. No, Ron Jones love to talk to you, I'm sure. But look, look up! His profile.
Artem Trotsyuk: And see if he'd be useful for you.
Rishad Usmani: Yeah, and I'll I'll release this. I'll tag you in all social media. But this this was, I love this, you know.
Rishad Usmani: I need to have more people such as yourself.
Rishad Usmani: Cause. I just have physicians and Vcs, and it kind of gets a little bit mundane. So.
Rishad Usmani: More AI experts that I can learn from is amazing. Thanks for taking the time to join me.
Artem Trotsyuk: Ron Johnson would love Ron John would be super keen on talking. AI. It's his also bread and butter. He's also an investor.
Artem Trotsyuk: Founder, but his passion stuff right now, right now he's like all about vibe coding, and how he can build something up super quickly and trying all these tools out.
Rishad Usmani: Yeah.
Artem Trotsyuk: And then customizing tools for your own different needs and applications, and so forth, so.
Artem Trotsyuk: Yeah, look up his profile. Send me a ping if he'll be useful for you.
Artem Trotsyuk: And if yes, then I'll go ahead and reach out to him and make an intro.
Rishad Usmani: Awesome. Yeah. And if I can help in any way.
Rishad Usmani: I'm happy to.
Artem Trotsyuk: Sounds good. Alright, Rishad, thank you so much. Talk to you soon.
Rishad Usmani: Thanks, Arthur, bye.