TBPN
🔴 Alex Karp LIVE from AIPCon 10 | Alex Karp, Peter Zaffino, Chad Wahlquist, Sam Berry
04 Jun 2026
Transcript generated automatically by AI and may contain errors.
Chapter 1: What is discussed at the start of this section?
You're watching TBPN. Today is Thursday, June 4th, 2026. We are live from Palantir AIP Con with the Temple of Technology. It's back in LA. The Fortress of Finance. We will return to it, but it is also a state of mind. That's right. We are also sponsored by Rampant. Time is money. Save both. Easy to use corporate cards, bill pay, accounting, and a whole lot more all in one place.
Big news from Ramp today. Massive fundraise. We're going to cover it in a little bit. But first, we've got to talk. Oh, is it still going? I like it. The Ramp song's back. This was early days. We really talked about Ramp so much. Turn it into a song. Anyway.
uh the topic of conversation in dc has uh it's still in ai world but instead of talking about uh approving models before they're released today it's about the bio threat brandon gurel wrote in the tbp newsletter today the great houses of ai have united behind the bio threat there's actually a lot more to that because it was a big long list of signatories
from AI, but also from the bio world and biotech and even startups. We've seen former guests of the show sign on. I'm excited to bring some of those folks back on the show in the coming weeks and hear more about this because I have this belief that as AI advanced, we got cyber because it was such a tight feedback loop, such a tight verifiable reward.
Reinforcement learning works really well in that context. Bio has some similar characteristics.
And it was a very tangible Y2K-style moment. Exactly. Where there was, let's just say, a powerful business strategy.
Yeah. It was like, is it over? You start thinking about the consequences of this. And you don't need to get to AGI, super intelligence god.
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Chapter 2: What are the implications of AI on national security?
You can just have a really powerful tool that creates a new problem. And that... creates full employment for Nikesh Varora over at Palo Alto Networks, who we had a chance to talk to yesterday. And he's been very fortunate in implementing the solutions to the cybersecurity threats posed by new AI systems, some of the new AI capabilities that are rolling out.
But bio might be next, and so it's exciting to see that the great houses of AI are uniting behind the bio threat. Let's take you through this. First, I'm going to tell you about console.com. Console builds AI agents that automate 70% of IT, HR, and finance support, giving employees instant resolution for access requests and password resets.
So in 1981, a group of researchers published the primary structure of the poliovirus genome in the journal Nature. So they were basically open sourcing the sequence for making polio, which... just a few years earlier. Polio, I think, was on the decline by 1981, but a very, very problematic virus.
It's an RNA virus, meaning that its nucleobases or building blocks are A, C, G, U, if you're familiar with RNA, adazine, cytosine, guanine, and uracil. Put more plainly, Thanks, Brandon Gorel. He says, when the researchers published the primary structure of the polio virus, they gave the world the literal sequence of polio virus building blocks in order from start to finish.
By the mid-20th century, before mass vaccination, polio was paralyzing and killing more than half a million people per year worldwide. So you have this pretty deadly virus killing more than half a million people per year worldwide, and you have just open-sourced it. What happens? So in 2002... researchers synthesized infectious poliovirus from its publicly available sequence data.
So they didn't actually need any of the poliovirus RNA to start. They didn't need it on hand. It's not like they took a little sample and they just cloned it up and made it bigger. They just took the data and they made the actual virus. So this is the shape of the threat.
If there's a new virus or an existing virus or a forgotten about virus and you have the code to it, you can potentially print that RNA. and then have the virus in your hands, even if you don't have a sample. You weren't able to collect a sample.
So instead, these researchers in 2002, they were able to take the published sequence, chemically synthesize short DNA fragments, assemble them into a full-length DNA copy of the poliovirus genome, and then use the DNA to make the viral RNA to fully recover the infectious virus.
In 2005, researchers used these same technologies to reconstruct the Spanish flu, a virus in 1918 that killed 675,000 Americans and had a 2% to 3% mortality rate among those infected. Very, very dangerous stuff. So basically, these two reconstructed viruses showed that having a physical virus on hand was no longer necessary anymore. as source material to create viruses.
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Chapter 3: How is Palantir addressing the bio threat with AI?
We're on board with 80%. And the government isn't coming in and checking the records. They're not actually saying, okay, well, we have a different number because we're the government. and you have this number, let's verify this number. It's self-reported by that organization, but there's no reason not to trust that organization necessarily. So what else?
A bunch of other factors contribute to the relative flimsiness of this agreement. HHS also has guidance in place around the issue, but again, it's voluntary, meaning that the possibility of bad actors getting their hands on dangerous nucleic acid sequences, at least from American companies,
still cannot be ruled out overall it's good to see industry leaders signing this letter and doubly refreshing uh that the letter is not yet another warning of apocalyptic ai doom which i think the public has unfortunately come to expect from announcements like this hopefully the relevant legislators are paying attention and can make this happen in short order so i thought that was a good uh a good breakdown and i agree with a lot of that
Andrew Curran also has some deep dive on this with some more of the signatories. He shares screenshots of all of these, and it really is everyone. Yeah, Y Combinator, DeepMind, Microsoft, Interconnects AI, Harvard, tons of stuff.
And then over in the nucleic acid synthesis industry, you have Twist Bioscience, Anza, Emerald Cloud Lab, and Kathleen McMahon from Valthos is on here, former guest of the show. So good news, but obviously just an early step. This is just an open letter to the government saying, hey, we think you should, we want to support this. We think that the government should start thinking about this.
The other news in the bio world,
Yeah, I mean, the news is just that there's incredible momentum in biotech. It feels like it. Early-stage biotech.
Yeah, momentum, but not volume, not scale yet. Because you're looking at $3 trillion IPOs going out this year, potentially. So much news in AI, microns at a trillion. Every chip stock is in the hundreds of billions, trillions. This is much smaller, but...
but it's notable because biotech had been uh left for dead in some ways we had a biotech investor on probably 14 months ago at this point who said i don't even know i mean just looking at the return so far i don't know why you would invest in this asset class yeah But of course, every asset class kind of goes through that kind of phase. And clearly, there's a lot of momentum.
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Chapter 4: What challenges does AI pose for government regulation?
Here's what's interesting, though. So, Arthur Rock usually... It's pretty dialed. Pretty dialed. Pretty dialed. It's almost like he has inside information. It's almost like he somehow...
Yeah, but I mean, we've talked about the game theory of like, does he work at a real like tier one venture capital firm? What's the benefit of leaking everything? Is he a lawyer that's seeing all the docs turn around?
Oh, I mean, zero benefit for a lawyer. Right?
The rush of getting likes on the timeline is pretty universal.
You're a lawyer, you're just like, I need a banger.
out of fund okay for sure yeah and uh i don't i don't know anything else um but uh he's always taken the view that it can be helpful to the founder to build because a bunch of people are going to see this sure that that this didn't sort of land in their deal flow or land on their desk and they're gonna reach out right so it does create momentum um but uh can certainly be annoying for teams as well
This was notable, though. So 200 million of LOI from B2B customers. And so very curious what the enterprise play is here. But we can work on getting Rahul.
Does that mean like through hospital networks or through like the health care system? Or is it like Mark Zuckerberg wants to go further? He wants to track the brainwaves of the employees, not just the mouse movements. We're going to track your screen and your brain. I mean, it could go either way.
You imagine Neuralink has had a bunch of traction and a bunch of amazing... I saw Nolan, the first patient, P0, on Rogan talking about playing COD with Neuralink. Amazing. And you can imagine at a certain point some sort of partnership
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Chapter 5: What are the key insights shared by Peter Zaffino about AIG's operations?
Oh, they want me to stay for two minutes or what? I'm only going to stay. He's got to be the star.
The other headset is right here.
I'm going to take off after a minute.
And why don't you put that headset on.
Why don't you introduce our guest. Microphone on the left. Perfect. One of the smarter people in business has developed unique ways to underwrite that did not involve firing people and someone I admire. Thanks, Alex. With that, I'm going to let you guys go. Make sure to tell them that the ontology powers. It's everything. Always selling. Fantastic. Thanks for coming on the show.
It's great to meet you.
Pleasure. Yeah, please. Kick us off with a bit of a more formal introduction. Yes. I'm Peter Zafino. I'm the executive chairman as effective on Monday of AIG. I used to be the chairman and CEO and have worked with the company for nine years to help transform it. It was in a place where underwriting profitability was challenging. Operations were challenging. Data was challenging.
Capital was challenging. So I had a great team of people with me to transform the company. So give us the shape of the business in terms of the different business lines, the different products, the international footprint, the workforce. Give us the scope and the scale here. Global company with a little bit of a unique footprint. We're 50% international, 50% North America.
But our second largest country after US is Japan. We have a big business in India. And then we have a very big business in the UK. We do complicated risks. So you can think about what's happening in the Middle East now with shipping, marine energy. We're heavily involved in that. So something where there's not an existing futures contract that a company can just go and hedge.
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Chapter 6: How does Chad Wahlquist describe the integration of AI in problem-solving?
Part of that feels like, if you're talking about insuring a Fortune 500 company against a geopolitical risk, That feels like a meeting that takes place in a boardroom. It feels like there's a lot of folks with a lot of trust built up over years to understand each other's businesses.
But then there's probably a lot of other underwriting happening and teams putting together comps and spreadsheets and data. And I want to know about the intersection there. It feels like the business is, and I don't know if it ever will be, just one-click checkout for insurance products for Fortune 500 companies.
But what is the interface between the quantitative, the qualitative, the relationship and the data, and then how is that changing? So the quantitative, you have to start at the portfolio level. Okay. And you want as much data as you possibly can to look at deterministic, modeling, probabilistic, and then stochastic.
And I think once you understand your mean and you understand the standard deviation around that, then you have to apply it to sort of the widgets, which is each policy throughout the globe as well as... ways in which you structure insurance. So you can't look at an individual policy in isolation.
You're managing portfolio risk, risk to the entire firm, and that's something that's happening probably 24-7, I imagine. It's hard, and that's what led me to Alex Karp. It's hard to get the aggregation done in anything that looks like real time. It's usually static. It can be 30, 60, 90 days, and your portfolio could change.
I mean, it's not going to change dramatically, but having the ability to sort of assess risk and use the quantitative data to make better decisions on a daily basis is the aspiration of the way the company is going.
Take us back to your first meeting with CARP. Curious what the experience was like. It's a unique individual.
Can we call you? Yeah.
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Chapter 7: What technological advancements are highlighted by Sam Berry in the USDA?
No. I was actually introduced by a board member many years ago. And it was really in this pursuit of... Not necessarily Foundry or AIP or Ontology. That's where it led us. But it was more on sort of the quantitative ways in which I was looking at the portfolio. Could he help me think through computing? And could he help me think through sort of portfolio optimization?
And I just got more and more intrigued. I mean, you see the brain. I mean, he just thinks about things. He doesn't hold back. So I always knew where he stood with me and with AIG, but just developed a very strong trusting relationship.
And there's such a tremendous partner that we're able to iterate with them almost like no other company because we do things in 90-day increments because going out like a year or two years is too static. And so we actually build our relationship on 90-day goals. And that's been incredibly effective.
A lot of the AI companies talk about scaling laws, exponential growth, and token production, or even revenue in many cases. But what's growing exponentially in your business? Are you bringing exponentially more data into the platform every year, exponentially more compute resources, teams, number of policies? What is the thing that's experiencing a boom right now?
The most important part, I believe, in terms of business is that you have to have a business solution you're trying to solve. So for us, it was more data, better data, and then reduced cycle time. So in other words, when we get the data that comes in from our distribution partners, how fast can we get it with higher quality data and more data to the underwriter to make decisions. Got it.
And then how do we actually make the adjustments? What's an example of distribution partner in this context? So it would be like an insurance broker or insurance agent. Makes sense, yeah. Or, you know, someone who has their client as a customer. The ability to sell your product effectively. Exactly, okay. Yes. Yeah, that makes sense. What else?
Jordy, do you have something? Where was I going to go? The... Alex wants us to cover ontologies. We'll get there. We primarily, I mean, we at least started covering early stage startups. There's been a debate in our kind of little sub-industry right now. around a bunch of new insurance-focused startups that are growing incredibly quickly.
And there's a debate going on as one, maybe AI makes it more possible to underwrite risk. And if you can do that well, grow very quickly. The other side, you know, says, hey, you know, if you're hyperscaling an insurance company, maybe that's not, maybe you don't want to work with a company that is, you know, going through that hyper. The iron law of the universe. Yes, yes, maybe.
What goes up fast must come down fast. But yeah, talk about what AI has actually enabled, where you're excited about it, where it's failing broadly, maybe where it's overhyped. And you can, I guess, tie that into everything you built with Palantir.
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Chapter 8: How is data collection evolving in the context of USDA's initiatives?
That's got to be a unique situation. First is making sure Alex and then two of the senior executives, Ryan and Ted, that everybody knows what we're trying to do together. So we start there. Then we wanted to embed the engineers with our team. So if we had a business leader that was trying to drive the underwriting output, you'd have technology from AIG,
you would have some of the change management, but you have the engineers sitting there with our teams throughout the entire process because the iteration is really important in terms of translating what you're trying to achieve from the business side and the engineers actually helping us think through the application of some of the LLMs or ways in which we could circumvent some of the things that we were doing.
Yeah, that makes a ton of sense. Jordy, anything else?
No. Insurance has to be the most important topic. If we do have a second, I was not sure on timing. How are you thinking about workforce planning? I asked Karp about this, and he said to ask you. We're token budget.
We've stayed, you know, as you've had this wave of AI layoffs, we've been over and over and over reminded people that if you have an individual, you give them more capability, you make them more productive, you make them more efficient, a thriving business will want to hire more people, right? Because you can get more out of every individual. Yeah.
And so we've tried to remind people that over and over and over as, you know, companies that oftentimes are, you know, underperforming or bloated for whatever reason. But what's your kind of philosophy around hiring, headcount planning, RIFs, all that stuff in this kind of new era?
We've been focusing on, I heard Alex at the tail end and I agree with him. So we're focusing on growth. We're focusing on reskilling and actually training our employees to be in a different part of the workflow. Now, you would do this, I believe in all of this, you have to still have great end-to-end process. And so things that have been
The human's been an LLM trained how to do things like outside of the normal workflow has to you have to get rid of that. So I think that's just normal business. Yeah. But, you know, our aspiration is not to implement, you know, AI or anything that we're doing with our partners to eliminate jobs.
I mean, it's about growth, reskilling and finding ways in different markets to have exponential growth and opportunity and having a lot more insight in the business that we run. That's a great optimistic vision. I love it. Thank you so much for taking the time to come chat with us. Thanks for coming on. Great to be with you. Have a great rest of your time. Thanks.
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