July 11, 2024
Legendary technology founder and venture investor Vinod Khosla joins host Michael Marks for a wide-ranging discussion on the future of AI, major tech cycles, the importance of being honest with founders, and much more. Vinod shares his predictions for the next 25 years of technology advancement and how we should be assessing the risks and benefits as the adoption of artificial intelligence continues to accelerate.
This transcript is AI-generated and may contain minor inaccuracies.
Michael Marks - Hi everyone. This is the TechSurge Deep Tech podcast presented by Celesta Capital. Each episode we spotlight issues and voices at the intersection of emerging technologies, company building, and venture investment. I'm Michael Marks, founding managing partner at Celesta.
Today we're delighted to welcome Vinod Khosla, who I am pleased to have and proud to have be my friend. So we're really excited to have you, Vinod. Thanks for taking the time.
VInod Khosla - It's great to be here.
MM - So Vinod is, of course, the founder of Khosla Ventures and has been a technology investor for 40 years. He's been a founder and investor in some of the great technology companies of the past several decades, including Sun Microsystems, NextGen, Juniper Systems, and many, many others.
Khosla Ventures, which has now been around for 20 years, has invested in countless iconic companies, including Stripe, Instacart, Impossible, and others. So again, Vinod, thank you for joining us.
So there's a lot going on in the tech world right now. And gosh, it seems to be on everybody's lips. It's a very dynamic time. Of course, everybody's talking about AI. And sometimes for me, it gets a bit tiresome that that seems to be all anybody wants to talk about.
We are going through a bit of an adjustment period with venture capital. Tech is becoming much more integrated in everything we do, both at the business and consumer level. When venture got started back in the 70s, 80s, 90s, it was a pretty small industry. We had Intel and National Semiconductor and Fairchild, and over these last 30 years, it's become everywhere and integrated in everything. We'll get a little bit later talking about biology and so on.
You recently spoke at a tech conference and laid out your plausible tomorrows, which is fascinating, this vision, and looking at what the next 10 to 25 years might look like. We have several cool startups at Celesta that we invested in that overlap in these areas, including Boom in the supersonic flight area and Biomason, making zero carbon concrete. But maybe we could dive into a couple of these things a little deeper. I would love for you to talk about a few of these predictions, how you've thought through it, what the implications are, what it will take to get there. So the first one, if you don't mind me saying so, is expertise will be free. So can you talk about that a bit?
VK - Yeah. AI is human intelligence, and it can learn any area, whether you're talking about structural engineers or oncologists, whether you're talking about mental health therapists, are you talking about primary care doctors? Are you talking about teachers? All of that expertise will be in the AI and hence essentially available at the cost of computing.
MM - Yeah. And you say labor will also be near free, which is a little bit different from expertise.
VK - Yeah. The expertise raises the questions, what will humans be better at than AI? The answer is probably nothing. There'll probably be a few areas we collaborate with AI, like in creativity. It'd be an area for partnership, but almost certainly AI would be more creative than any human, but AI plus a human could be much more creative together. And that may happen in a number of areas. But labor is just a matter of getting our robots right. We've had dumb robots so far.
We've very good mechanical engineering or what's called mechatronics. We know how to move limbs and arms and stuff like that. We've not had intelligence in these robots. And within the next five years, we will see the kind of explosion in capability that we've seen in language models happen in robotics. And whether it's three years or five years or seven, it doesn't really matter.
Once we're there, you won't be programming robots for a task. You'd just be telling a robot to do a task and it learns how to do it. It self -programs itself. At that point, it's the cost of building a robot. And there every manner of robot from your pet dog to your home robot to your factory robot, farm worker, you name it, because labor rule in this country, I would guess get to a couple of bucks an hour, two bucks, three bucks, something like that. Of course, it'll start higher, but when you get to the kind of scale that the auto industry has today, hundreds of millions of cars produced a year, I think the US is like seven, 16 million cars, any scale like that, robots would be cheap.
Even the robots will do the assembly of robots and they'll make more robots. The intelligence will be all software that's replicated plus the chips. And I can't imagine why it wouldn't be free.
MM - And so is your view sort of the implications of it that there will be jobs? And the reason I... Where I come from about this is that I always hear everybody predicting that technologies could eliminate jobs The statistic I always use about it, which I just think is a cool one, is that in the year 1900, 50 % of all jobs in the United States were connected to agriculture, and the year 2002 % were, but we still have no unemployment. So do you think this changes that dynamic?
VK - I think it does, but in a very different way. It is true, we went from 50% of jobs being in agriculture in 1900 to by 1970, I think, it was 4% of all US jobs.
But we had three generations to make that transition. I think we will have one generation to make this transition. And I like to say, and these are necessarily imprecise, within this period of time, whether it's 15 years or 20 years or 25, some short period of time in one generation, AI will be capable of doing 80% of 80% of the jobs.
So if you take all the jobs, it's very easy to predict that 80% of them will be done with an AI, and AI will be capable of doing 80%. That still leaves the 20% for humans to do, potentially. But in that world, we will, I think, have the need for work go away. First, we have to recognize we don't have jobs today.
If you work at the GM assembly line eight hours a day at one robot station, putting one tire onto a car, do the same thing for 30 or 40 years, that's not a job, that's servitude. Out of the necessity of feeding your family. Right. Right? It's almost like slavery because you have to survive. More respectable than slavery was, and yes, you can quit, but your next job is the same one for most bulk of the jobs on the planet.
MM - Well, it's a fascinating perspective. It really is. Another one of the things you said was in the Plausible Tomorrows is talking about the practice to the science of medicine. And of course, your firm and our firm were working together on Prellis Biologics, which is in this domain. It's a company I'm very excited about. So can you talk a little bit about that?
VK - First, there's a class of things. Healthcare is a very large percentage of US GDP. $4 trillion a year spent on it. And roughly a fourth of it is expertise, oncologists, primary care doctors, all that. Right. A fourth of it is about drugs and therapeutics. A fourth of it is diagnostics, imaging, blood tests, and a fourth of it is in hospital care. And you apply AI to all these and say, what won't change?
Any drug that comes on the market, my AI long before it's on the market will dwell up in analog that bypasses those patents. I'll tell my AI, develop a drug like that that hits this target receptor in your body but doesn't violate this particular patent. Super scientists because scientists will also be free. That leads to a lot more interesting possibilities in drugs.
Today it's a shame that most drug companies are developing more drugs for rare diseases than common disease, obesity being an exception with this accidental GLP thing. But everybody wants therapies that cost $500,000 to a million dollars per patient per year. CAR -T cells, most of cell engineering is that way. It's a shame. You will be able to design precise proteins for one gene defect in the body. Now, Prelis is doing antibodies. Those will become trivially easy to do. So if the expertise is free, the therapeutics design becomes much more accessible so many more people can do it. There's still the regulatory aspect in all my plausible tomorrows. I always say, and there's a slide on all the reasons they may not happen.
As much of an optimist as I am, I realize regulatory may not change. But if you're designing a drug for one person, there's no regulatory that's possible. You can't do a study. How do you do a study? And so I'm hoping you can fool the FDA with this. So who do you want me to do the study on?
MM - That's pretty interesting. Well, that's a wonderful segue to the next thing that I want to raise, which is you, you consider yourself a tech optimist, and you've just talked about some things that have pretty broad ramifications. So are you an optimist about AI? Are you worried about AI? How are you thinking about that?
VK - Techno -optimism, which I've called myself a techno -optimist forever, but sort of got labeled recently poorly. So I now say I'm a techno -optimist with empathy and caring.
MM - That's good.
VK - Not the techno -optimism without caring and without empathy. But I am generally very optimistic about AI. Let me address the negative side first. Do I worry about an AI going rogue, sentient AI, and destroying every human on the planet? No, I don't worry about it as one of my top five worries in AI. Humanity faces a large basket of risks.
An asteroid could hit this planet, and that's a risk. We know it's happened before, it might happen again. Can an AI go rogue? Would I say it's impossible? No. Is it manageable? Very likely, but there's some risk. However small. And different people who disagree on this assign different risks. Are there much larger risks with AI? Yes. So the risks I worry about, but by far the biggest risk is China. And strong AI in Chinese hands is by far my biggest risk. My second biggest risk with AI, bioterrorism. Those are the things we should use. Now the thing with bioterrorism, if it's used, we will know. And we should spend a lot of time on fast response.
We had a pretty amazing damn response to COVID with vaccines and stuff in timeframes people thought couldn't be done. We're not doing enough to have more of that capability in place for bioterrorism. And if it's used, it'll be used locally and it'll be very visible when it's used.
MM - Right. Well, you know, I'm not nearly as sophisticated in this subject as you, but when people talk to me about I'm certainly an optimist as well, and I remind people that for 80 years we've had a tool that could destroy the world, which is a nuclear bomb, and nobody's ever dropped one, and for sure it could wipe out the world, and people decided that's probably not a good path to go down. So I don't know, it's kind of simplistic, but anyway, thank you for that. So the way I think about the way we think about AI is that you have tools. So you have the large language models and open AI and so on. But you also have application sectors. We have lots of them that we do, AI that does intellectual property management or AI that reads maograms or that type of stuff. Are there certain areas like that that you're interested in that you invest in or that you think would be really great places that are on the application side, not at the tool side?
VK - So leaving aside the fundamental models and the cloud infrastructure and the chips to run it, there's application areas and then there's applications. The most exciting are the ones that replicate expertise. I'll build an oncologist. I'll build a sales rep for you to use. I'll build a structural engineer. These are all things we are doing. So anytime you're replicating human expertise, it's very, very valuable if you can do it. And to me, it's not a question of if, but when and with how many dollars and how do the economics work.
By and large, anytime you can build expertise, a PhD in anything, in weather forecasting, in new materials design, new catalyst for chemical processes, in a new drug chemist, you we spend billions of dollars with Wuxi in China doing small molecule design, could be done by an AI. So anytime you're replicating expertise, it's a really good business. And it takes a great team.
MM - First of all, thank you for that because that's a very intelligent way to talk about it. It's how we think about it and how we do it, but maybe that was even a better way to say it. When you talk about teams, and we're investors, both of us, when we think about that, how important is the application knowledge, that person you're trying to replicate, versus the people writing the AI code and so on? How do you think about that?
VK - Before I go there, let me go somewhere else.
MM - Please.
VK - Most people think more incrementally. So they try and do what are now starting to be called copilots. And there's a copilot for software development. There's a copilot for using AutoCAD. There's a copilot for everything. And those are useful too in some categories, but particularly useful when you think the big task is hard to do.
MM - Ok, right.
VK - Can you develop a software engineer? Much harder risk than can you build a copilot that makes a software engineer much better, more productive, less error prone, all that stuff. That's sort of the category. To your question of teams, I've been doing innovation for 40 years now. I can't think of a single large innovation and biotech may be the only exception area, though even the vaccines, COVID vaccines were done by startups, not somebody with a lot of resources. I can't think of a single large innovation that came from somebody who knew the area or was expert in the area. Think about rockets. You'd think somebody from Boeing or Lockheed or Airbus would do this. No, it was SpaceX and Rocket Lab. Cars, you'd think there'd be somebody from General Motors or Volkswagen. No, it was Tesla. Or Waymo for self -driving cars.
MM - Classic innovators dilemma problems. You're right. Yep.
VK - Did somebody at Hertz or at Hilton or Hyatt do Airbnb? Did somebody at Hertz or Avis do Uber? No matter where I look, in 40 years, I can't find one example of a large innovation. Incremental innovations, yes. Intel can go from a seven nanometer process to five nanometer silicon process.
But that's sort of an obvious thing to do. And they only have to do better than the guy next door. They're not saying, let me attempt something that's impossible.
MM - I can think of two almost examples. One was when IBM hived off their group to go do the PC, which they just said, you can't be a part of us because of the reasons you're saying. And of course, that was reasonably successful.
VK - And they hugely leverage what Bill Gates was doing.
MM - Right.
VK - They didn't actually have their own idea.
MM - That's right. The other one, which is an interesting one to think about, is Xerox with Palo Alto Research Center, where they created all these things. Of course, they couldn't use them. It's Xerox.
VK - Yeah. So almost is not good enough.
MM - That's awesome.
VK - I mean, think about it. You'd think Walmart would do retailing, not Amazon.
MM - Of course.
VK - Right?
MM - Well, that's why it's so cool to be the investors we are. We get to back these people with new ideas that are disruptive.
VK - You know, we're doing a Hermes Mach 5 aircraft. Is there a single large company attempting that? Boom is trying to do that. Right. Hermes is trying to do that. Is there a single large company doing it?
MM - Well, in fact, a couple have tried and they just failed miserably. They can't hire the people who are excited to work on this stuff. Their bureaucracy gets in the way.
VK - So I feel like we're in an incredibly wonderful position to be able to finance these out of the box thinkers.
MM - Well, it's a perfect segue to the next thing that I wanted to talk about. You and I have both been around for a long time, and the technology world has expanded so rapidly and it's so cool. In these various cycles that you've seen, so it's chips and then networking and then dot coms and e -commerce, know, SaaS, now AI, are there any differences in these various groups or do you think about it all as the same kind of development but with just new technologies available?
VK - You know, 40 years ago, even 30 years ago, even 20 years ago, our world of technology innovation was innovative technology for the technology, a better computer, a better chip, better internet, better mobile. And starting about 2010, it became about the rest of the world. Uber affected transportation, Airbnb affected hoteling. It started to be about more parts of society.
And that was exciting to watch.
MM - Why do you think that happened?
VK - I think, and we can come back and talk about platforms. Platforms enabled that. We went from a computer you had to learn to use to, just need to touch this iPhone device. And it became a simple interface, but it was because of one in a way. Steve Jobs fundamentally put in our head the idea, there's the app for that.
MM - Right.
VK - That is the most fundamental change in computing is this idea that there's an app for that. In 2004, I gave a talk in the 140 -character conference when SMS messages, and I titled it, The Device That Used to be a Phone. And I postulated in 2004 that a phone wouldn't be used for talking, which was a ridiculous thing to say.
Every example I picked of how it might be used was wrong. But the fundamental idea that it wouldn't be used for talking was right. It was a powerful, great computer in your pocket. And Steve visualized it correctly and thoroughly and actually made it happen. He enabled this interface and the world expanded. And he built something that could be in everybody's pocket. Even people who didn't own a house or a car. Everybody could own a phone. And so he expanded the platform. And whenever you get a new platform, you get a whole lot of new creativity possible.
I started with the idea that the microprocessor was a platform at Sun and at Microsoft. You could leverage that platform and the applications exported. Then in 1996, and this is funny because every major telco in the US told me when we were starting Juniper, they would never use TCPIP. And Cisco's CTO, which was Ed Kozal, still around, I doubt he'll admit this, he said to me, Cisco will never do a TCPIP router above OC12. That was their last big router because they were going to ATM. The internet will be ATM. And Pradeep and I bet the internet would be TCPIP. By the way, I consider that probably the single most important achievement in my life is making that happen. This change in direction from telcos thinking, ATM, and precise circuits was the only way the world could work, not this haphazard world of the internet. But that platform opened up Google and other applications.
Amazon, others. And we invested in all of those at Kliener-Perkins when I was there. And then you got this iPhone. But last year, effectively, we introduced an AI platform that is bigger than the iPhone platform and bigger companies will be created. A long -winded way of saying, there's an AI for that, no matter what it is.
MM - That's a great way to think about it. Well, that's fascinating. You've been right about so many things over such a long period of time. What have you gotten spectacularly wrong? Anything?
VK - There's lots of things I've gotten wrong. I often say in my career, I've made more mistakes than almost anybody I know by a lot. And there's a talk I give called failure doesn't matter. You've been in the valley forever. You've known me. Do you know my startups I did before Sun?
MM - No.
VK - So one was Daisy and that was successful and went public.
MM - Yeah, yeah. I did know that.
VK - You had heard about it. There was another one Scott McLean and I, same founders, started at two months before we started Sun called the Datadump. Nobody knows it.
MM - I don't know that one.
VK - I try more shit than anybody else and so it doesn't matter I try and fail I don't fail to ever try. Like that's really fundamental difference. So was I wrong on biofuels? Yes, because I didn't expect electric cars to solve the problem. Now, I did expect, you know, an entrepreneur with the willpower of Elon Musk to come along. And because there was two -sided problem, you needed cars, you needed a charging network. And so I viewed that as complex. I didn't realize that one person's willpower could change the trajectory of the whole damn planet.
I call people like that instigators of change. But almost certainly, sustainable aviation fuel will be the same companies I've funded 15 years ago. Lanza Tech has now an operating sustainable aviation fuel facility. So if you're persistent and take the long view and the rational business view, you have a decent chance at making it. Of course, incumbents can always slow you down.
MM - Right. Of course.
VK - And if I build an AI oncologist so everybody in the world can have an oncologist if they get cancer, God forbid, the AMA may shut me down. So lots of reasons things don't happen. my view is these platforms allow innovation, allows for much more disruption, which is a lot of fun.
MM - Right, it is.
VK - Except if you're the disrupted and you fight back hard. And so the incumbents always fight back and sometimes they win.
MM - So your view really is the same as mine is that entrepreneurship and risk taking and all that has stayed pretty much the same. Tools have changed, but it's just the environment has changed. And now we have innovation happening everywhere, which I'm so excited about.
VK - Yeah. Look, take a ridiculous example. I think about four years ago, I said to my partners, I really want to build an incubation to build a public transit system. And everybody looked at me like, huh?
Public transit systems aren't incubations. Then I ran into an entrepreneur that was thinking the same way. So I transferred my patents over to him and said, let's build it together. And we bid on four systems, one, two outright, and our short -lived stayed under the other two. We haven't lost a bid. San Jose in the heart of Silicon Valley, put out a plan to build a transit system from the airport to downtown San Jose with the new Google campus is up to the Apple campus. 32 people invited to build. We weren't invited, but it's always open tender. So we bid over the transfer and we won outright. They didn't even shortlist vendors, which they normally do.
MM- So what's the name of this company?
VK - Glideways.
MM - Glideways. Okay, fascinating.
VK - There's no reason it shouldn't be in every city in every part of the world.
You know, my view was very simple. 200 cities of the 4,000 cities on the planet that need public transit have a 5% penetration jet. And we're the only public transit system that doesn't need public funding because the economics work the way we've designed it.
MM - So you're still an entrepreneur, aren't you, Vinod?
VK - I love large problems.
MM - Well, one of things I just had to talk to you about, because we've both been around for a long time and we both started in the hardware business, know hardware stuff the semiconductor business as we talked about, know earlier as a national semiconductor and Fairchild and Intel and then everybody went away to all these other things and what everybody's software, nobody wants to do hardware and It seems like you know we're back to the future here because now as you know our good buddy Jensen Huang's over there with a three trillion dollar market cap company and Hock Tan at Broadcom with 800 billion and all of a sudden hardware seems to be cool again, which is fun for Celesta because we like hardware, we always did. But what do you, are you investing in other hardware things? How do you think about hardware these days?
VK - Oh, absolutely, we are investing in hardware. Yeah, we are in the Rabbit device, which is getting a lot of flack right now. I'm not afraid of investing because think about it. This device in my hand, the iPhone, enabled a whole class of software that were based on touch.
MM - Absolutely, yes.
VK - But you still needed to learn how to use an application. You needed to know how to cancel your Uber, for example. I think AI enables a fundamental change in the way humans interface to technology. Humans had to learn computers. Now computers will learn humans, and I'll just say do X, and it'll do it for me. And whether that means looking up my calendar to see where my next meeting. If I just say, get me there on time to my next meeting, it knows to look up my calendar, knows where my meeting is, knows to look up Google Maps, knows to look up Uber to say, what's the time for a car tour? Figure all that out, the math and tell me when I have to leave and get me there on time. And by the way, also know how important it is. Can I afford to be late or not? All that.
MM - Yeah. Fascinating.
VK - Well, that's what a simple voice interface does. If it needs to show me stuff, it will show me a picture.
MM - So have you invested in the hardware technology that allows for voice assistant?
VK - It's really, I say it's a new user interface. The hardware enables it. And Steve Jobs always said his hardware enables him to do a set of software things.
MM - Okay, fair enough.
VK - And I would say a new experience is possible and there'll be new hardware to deliver that experience. But we are also investing in public transit. That's real hardware. Talk about real hardware.
MM - We invested in Boom, talk about real hardware, super-sonic of planes. Well, look, this is fascinating and thank you for your insights. It would be inappropriate to not touch on geopolitics as a part of all this. You talked a little bit about, I fear from the Chinese, we have the rise of India, we have Vietnam, we have all the discussion about jobs in the US. Any musings about geopolitics in terms of how it affects the investing world these days?
VK - I don't look at the investing world per se, but for the first time, we are at a time in history where we are in the real technology race between the liberal world and the Chinese world. I'll call it the President XI world. He has a genuine belief. He has a better political system and he's entitled to that. But I don't like that system. And I think those of us in the liberal world don't like that system. And I'm not separating liberal and conservative. The democratic world.
MM - Yeah, I understand. Right.
VK - I'm not just saying the West. I include other parts of the world like India and others that are fundamentally democracies and messy democracies. In that, there is a battle for technology supremacy. Whoever wins the AI race and possibly the energy race through fusion and technologies like that, will win the economic race and because of that the right will propagate their social philosophy.
MM - If that's what you believe, you must believe that the US and the Western world, which has such powerful technology, ought to be able to win that, or do you think that's not true?
VK - Generally, yes.
MM - I mean, there's raw innovative technology happening in China than in most of the rest of the world.
VK - Yeah, but China has a very focused effort to win a couple critical technologies. So the 14th five -year plan in China actually called out wireless and AI. These were called out specifically as we need to win that race. So they have a more focused effort. I think that's a real concern for me that they might win. They'll put more concentrated resources behind them. Fortunately, our world shows us that entrepreneurs tend to beat out those large efforts, but I don't want to be complacent.
MM - Okay. That’s very fair.
VK - I'm optimistic without being complacent.
MM - Okay. I like that. Maybe the last subject we could spend a few minutes on, I love this saying that your firm has, that we prefer brutal honesty to hypocritical politeness. Maybe we talk a little bit about the character of managing our companies that we invest in. So maybe you could riff on that a little bit. I really like that.
VK - Yeah. So take an entrepreneur. Let's say they're not doing well. What do a lot of VCs do? Move on, do the next thing. If they're in a potentially interesting area, if you tell them what's wrong with their plan in your best view, whether you're right or wrong, everybody is right or wrong sometimes, but those of us who screwed up more often than most tend to be more right than wrong.
MM - I'm going to go with that.
VK - Tend to have more scars on our back at the very least. We can advise them. You may not feel like their friend because you're now critiquing what they're doing, but you might save them spending three, four, five years of their life on a wasted effort. I've seen it so often.
MM - So have I. That people sit on the board, believe one thing, say another, and the entrepreneur keeps believing, everybody believes in him. And that is unfair to the entrepreneur, to all their employees. One time when I was on the board, it was around the year 2000, with a couple of the prominent venture firms. There was this company that had 50 some million dollars in the bank and they were doing some sort of avatars or something, I forget. And I was trying to explain at a board meeting to the entrepreneur why this was a bad idea. And others just were very nice to that entrepreneur, you know, like you're doing great, right? Four years later, 50 people had spent four years of their life and the company got sold for $3 million when it was obvious four years ago, well before that we should have told them the truth. I tried to, but I was drowned out by other people being nice, polite, great team or half of them.
I literally had to say, to them, you're going to waste your time with this team composition. The team will fail because of its weakest link. And it's a very risky position for me to take. When I do that, sometimes they hear four years later, that guy was really nasty. But I'm trying to do what I think increases the probability of success of that team, including telling them they have the wrong co -founder, for example. It's very unpleasant to do.
I have very little to gain except that I'm trying to do my best by the entrepreneur.
MM - Well, you've backed right into my final question, which is this whole thing about founder friendly in this valley, I don't get it. I don't personally feel like the obligation is to just tell the founder what they want to hear, never replace the founder if they're not doing the job right. Obviously, you just said about the same, but give me a thoughts.
VK - It's not good for anyone.
MM - Not for anyone.
VK - Right? It's dishonest.
MM - It's dishonest.
VK - It's unhelpful to the founder. I like to say you want to care for the founders.
MM - Agreed.
VK - Not be founder friendly. I care deeply about the founder. Monday we decided we wouldn't do a follow on financing. Sometimes we have to make a pitch. Our guys had done the diligence and they, we made the decision to not do the financing, which means shutting the company down. So the founder sent me a rational email explaining why our analysis were wrong. And I basically sent back an email saying, this is your life. I will definitely meet you for an extra hour just to hear you out more directly. And I did. And we reopened the decision. And I asked the guys to share our internal memo with them, even if it makes the internal guys look bad or something.
Take this memo, sit down with the founder and look for his explanations for each of these things. I don't know where it will come out, so it's a good time to talk about it. But treating founders, that's how I treat my children. Yeah, if I say, hey, eat all the candy and chocolate you want, that's not good for my kids over the long term. It's not good habits. Do what you want. Don't do your own work. They like me a lot for a short time, right? This is exactly the relationship with founders. And founder friendly says you give them complete license. Caring for founders means you help them the best you can over the long term.
MM - Well, I clearly share that point of view and I love the way you coined the term hypocritical politeness. If you don't mind, I'm going to use that in the future.
VK - Absolutely.
MM - Well Vinod, this has been fascinating. Thank you so much for doing this. It's a real pleasure for me, honestly, be able to have this wide -ranging discussion and hope our listeners will get a kick out of it. So thank you very much for taking the time. See you.
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In this episode, host Michael Marks dives into the transformative role of artificial intelligence in healthcare. Michael is joined by Dr. Alex Sardiña of WhiteRabbit.ai and Kalyan Sivasilam of 5C Network, two early adopters bringing AI to medicine through sharply contrasting market models in the U.S. and India, respectively. The discussion unpacks how AI is revolutionizing diagnostics, helping to address labor shortages, and improving patient experiences. Learn about breakthroughs in cancer detection, radiology efficiency, regulatory challenges, and the global potential of AI-driven solutions in medicine.
Host Sriram Viswanathan sits down with Qualcomm Chairman Mark McLaughlin, the former CEO of Palo Alto Networks and Verisign and a trailblazer in technology and cybersecurity. Mark shares his remarkable transition from West Point to the heights of the tech industry, drawing on the many powerful leadership lessons developed throughout his career. Mark shares advice on balancing family priorities and career choices, offering a deeply human perspective on leadership told through his unique experience of stepping down from Palo Alto Networks at the height of his prime as CEO. The discussion touches on the shifting terrain of cybersecurity, the growing influence of AI, and the complexities of board leadership during periods of CEO transition. This episode is packed with practical insights for anyone looking to navigate a c-suite career in tech.
Host Sriram Viswanathan speaks with Andy Lee and Anand Chandrasekaran from Crescendo AI about the transformative impact of AI on the customer service and call center industry. The conversation covers Crescendo's unique approach to integrating AI in business process outsourcing, the dynamics of the sector, and the potential future of human-AI collaboration. Discover how AI is poised to disrupt and enhance the BPO industry, and why Crescendo AI is at the forefront of this technological revolution.