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TBPN is a live tech talk show hosted by John Coogan and Jordi Hays, streaming weekdays from 11–2 PT on X and YouTube, with full episodes posted to Spotify immediately after airing.
Described by The New York Times as “Silicon Valley’s newest obsession,” TBPN has interviewed Mark Zuckerberg, Sam Altman, Mark Cuban, and Satya Nadella. Diet TBPN delivers the best moments from each episode in under 30 minutes.
You're watching TBPN. We are live from Fal.Con here with George Kurtz from CrowdStrike. Welcome to the show.
Speaker 2:Thank you so here.
Speaker 3:Always great to be back here with you.
Speaker 1:Always great to have you. Congratulations on everything so far. I'd love for you to start by taking us through the big announcements today.
Speaker 3:Well, big announcements just coming out of my keynote today. First, we started with our Falcon Guardian product
Speaker 2:Yep.
Speaker 3:Which is in the category of AIDR.
Speaker 1:Yep.
Speaker 3:So if we think about the category that CrowdStrike really helped create around endpoint detection response Yep. Now this is taking really what we do for a human and a computer and applying it to AI agents. Yep. Obviously, AI agents are more sophisticated. They have access to data.
Speaker 3:They have access to compute, to networking resources. They do bad things. Yeah. Because they're like a bunch of drunk interns they put on your network. And and
Speaker 2:They can do a lot of damage.
Speaker 3:They can do a lot of damage. Right? So we built this technology. We talked to our customers. Mhmm.
Speaker 3:We worked with some of our largest customers to really figure out what they wanted like Amazon. Yeah. And we're super excited because the missing link to accelerating security sorry, AI adoption is security. Yep. Customers for the first time wanna go faster somewhere and they need security to go faster as opposed to a brake pedal.
Speaker 3:It's actually a gas pedal.
Speaker 1:Yeah. If you go back throughout your career, I mean, you've been working in security for decades, and I've just been really struggling with the order of operations for the predictions that have come true. Like, we got the hugging face attack, and then, like, three weeks later, someone was able to use ChatGPT to book a haircut. And it's just weird that we're getting capabilities in this very spiky way. Does this match your expectations?
Speaker 1:How does what you're seeing today go back to your original thesis when you started the company?
Speaker 3:Well, it's interesting. When I first started the company, it was really based upon what we called AI, but it was machine learning back then.
Speaker 1:Sure.
Speaker 3:But again, it was being more predictive and using algorithms to figure out whether something was good or bad.
Speaker 1:Yeah.
Speaker 3:And now, you fast forward to generative AI agents, you know, it's important to to leverage all of the data that we've accumulated over the last fifteen years to get to a point where we're still doing that. One of the the second announcements we made was really the super intelligent cyber lab. Yeah. This was very exciting. And we actually partnered with NVIDIA to create really the first, what I would call the agentic security platform
Speaker 1:Yep.
Speaker 3:That is focused on a red, a blue, and a harness that continually learns from each other.
Speaker 1:Yeah.
Speaker 3:So we based some of our models on Nemo Tron.
Speaker 2:Nemo Tron.
Speaker 3:Yeah. Right? We can probably get to that, but just overall announcement. So if you think about what we're doing, it's really creating a frontier type model and harness Yeah. At frontier levels specifically built for just the defenders.
Speaker 1:Yes. So with that super cyber super super intelligence lab Right. You're going to have more tailored models, more specification, probably spikes that go beyond what's available with the stock frontier products, I imagine, over time. Yep. If not immediately.
Speaker 1:But I'm interested in the, the benefits of open source, the benefits of, thinking economically because I imagine that part of the battle between attackers and defenders is starting to become economic. How much? How many megawatts can I put behind this attack? Is that what's happening? Well, the compute
Speaker 3:the the limitation, you're exactly right. The limitation for these attacks are really gonna come down to sort of compute and cost. Yeah. Because the knowledge, and I talked about this in my keynote, has now been democratized. Yeah.
Speaker 3:Where whether it's a hacktivist, an e crime actor, a nation state, they're they're all now equivalent because of agentic technology.
Speaker 1:Yep.
Speaker 3:And we called it the rise of the agent state.
Speaker 1:Yes.
Speaker 3:Right?
Speaker 1:Yes.
Speaker 3:Meaning that now those
Speaker 1:Post nation state.
Speaker 3:Post nation state.
Speaker 1:Yes.
Speaker 3:Right? So the apex predator is now the the agent state. Yes. And I think what's really interesting is, and it kinda gets back to your spikes in the in these models and those sort of things Yeah. Is that when you go back to hugging face Yeah.
Speaker 3:It's a fascinating read. You probably have Yeah. Have read it. There's some great papers. We were actually called in
Speaker 1:Yeah.
Speaker 3:To to help OpenAI Yeah. Go through some of it. I'll leave it at that, but the papers are out And when you look at what these agents were capable of doing Mhmm. And just how sophisticated they were with note taking and communicating and maybe working as part of the collective, it's incredible.
Speaker 1:Yeah.
Speaker 3:But the thing that I really called out in my keynote was, that's all groundbreaking, but really what was the moment? The moment was the same incredible frontier caliber AI was available for the adversary. In this particular case, were, you know, it was agent trying to pass a test, but it wasn't available
Speaker 2:The drunk interns.
Speaker 3:For the defenders. Yeah. And and these spikes come with the model refusals and all the guard railing that that was put in place. So, again, our models are specifically trained on our data, which we think is a huge advantage. Yeah.
Speaker 3:Harnesses that we built.
Speaker 2:Yeah.
Speaker 3:And, again, we fine tuned in the model creation and and and post training Yeah. In concert with NVIDIA Yeah. To come out with incredible efficacy
Speaker 4:Yeah.
Speaker 3:At the lowest cost. And this is what you were just getting to because customers want the best outcome at the lowest cost.
Speaker 1:And I want and I want probably AI review, AIDR at every endpoint, every transaction, every API call, every single possible moment. And that could be very expensive if it's running on a really expensive model. Right?
Speaker 2:Right.
Speaker 3:Yeah. So so our AIDR is gonna again, they're two separate announcements. Sure. But you're gonna be able to run that from the platform. Yep.
Speaker 3:It's in it's in we announced it today. But the the red Tempest, which is the name of that model, and the blue Solano, which is the defensive model, are part of the Safemind system. Sure. Okay. So Safemind, think about it as a harness.
Speaker 3:Right? Yeah. But those models and harness will be available in the platform
Speaker 1:Yep.
Speaker 3:To make everything smarter and better and faster.
Speaker 1:Yeah.
Speaker 3:And then we have a trusted access program for customers in our QuiltWorx program that they would be able to use the models directly.
Speaker 1:Yeah. Okay. So when you read the agent traces from the Hugging Face attack, do you see anything in there that feels difficult to detect? Because when I look at those, I'm I'm like, okay. They're crossing a line.
Speaker 1:This is odd. This would flag something in me. But we've seen examples like the how many r's are in the word strawberry where AI just kinda falls flat on its face when you're trying to analyze a particular shape of problem. Yep. Do you how tractable is this problem?
Speaker 1:How optimistic are you about solving it?
Speaker 3:Well, it's tractable because when we when we built our system, it was designed to look at sort of these we call them indicators of attack. Mhmm. So if you look at the whole attack chain and if you saw the keynote this morning, you know, it's just linking all these together. Yeah. So irrespective of, like, what happened, these are these are kind of a known attack chains.
Speaker 1:Sure.
Speaker 3:Part of the issue was it was sort of flooded with so much information that I think it was a sort of buried, you know, what's going on? Is it real? Is it not real? And what is gonna really take place is the defenders have to use AI to be able to connect the dots on those, which we do. Mhmm.
Speaker 3:But you also then have to strip out all the noise. So you have to separate the signal from the noise. Yep. And that's where these sort of models perform well.
Speaker 1:I mean, obviously, there's an incredible amount of attention on AI. What is the role of deterministic threat detection these days? Is there there still is that a useful tool in the tool chest? Is there are there still advances being made there? Because I imagine that for certain problems, throwing a more deterministic, you know, security structure around something could actually be beneficial.
Speaker 3:Well, you have to. And if you look at in the hugging face incident Yeah. This was more of a forensics what happened.
Speaker 5:Sure.
Speaker 3:Yeah. Right? If you think about deterministic security Yeah. It has to be in line and you have to make a decision. You know, you have to be right the first time.
Speaker 3:Mhmm. Right? First time final as we call it. So I haven't seen any sort of models, if you will, actually stop a breach in its tracks because it's, you know, as it's happening, you're kinda looking at data and those sort of things. It's not in line.
Speaker 3:Sure. So a lot of what the models are good at is sort of sorting out what happened, you know, sifting through lots of data and those sort of things, finding vulnerabilities. But you have to have a deterministic system, which is what we've built. Yeah. And I think what people maybe get confused on or maybe aren't quite sure is when they hear things like mythos.
Speaker 3:It's like, wow, you know, this super powerful model is gonna hack the world. Mhmm. It really hasn't come up with a new invention of hacking. Sure. Okay.
Speaker 3:This is very important. It's come up with, it can find more vulnerabilities, so more of
Speaker 2:Yeah.
Speaker 3:And faster.
Speaker 1:Yeah.
Speaker 3:Yeah. Right? And when you combine those, you have and you combine and link these things together, you have greater success. But they haven't invented a new way to hack. Yeah.
Speaker 3:This is very important because I think the the public may look at this and say, well, Jesus, a super weapon that can hack anything.
Speaker 1:Yeah.
Speaker 3:And it it really is the same techniques. It's just more of it and it it can Yeah.
Speaker 4:Keep track
Speaker 2:of the things. The turn is like you're taking a a 10 x hacker and making them a thousand x hacker Correct. Potentially.
Speaker 3:Yeah. Yeah. It's it's almost like Iron Man. You put the suit on. Somebody who's smart Yeah.
Speaker 3:Is a heck of a lot smarter.
Speaker 2:Yeah. So how how are the threats evolving? I imagine you you're you've been talking about agent states which makes sense as a new concept, but I imagine that you still have nation states that are deploying their own agent states
Speaker 3:Correct.
Speaker 2:On their behalf. I'm sure the same thing is happening with various loose loosely tied hacker groups. But how is the threat evolving? What are you talking with customers about these sort of new threats?
Speaker 3:Well, it's interesting and it it is the agent state is gonna help the nation state, the e crime and the hacktivist. Right? Everybody So, in obviously, that's just an umbrella. But I think if you look across those different groups, they all have capabilities. They're all leveraging things like these open weight models.
Speaker 3:Right? We talked about obliteration really taking the guardrails off an open weight model.
Speaker 1:And
Speaker 3:you go to Hugging Face now and you can download these obliterated models. And you can run them basically on a on a beefy system. Right? It's incredible and you put a question in and you're like, there's no way it can answer this and and it builds like, you want a full malware ransomware kit, boom, it's done. Crazy.
Speaker 3:Great. So this is part of the issue. This isn't theoretical, it's here. Mhmm. And what customers are asking for is we want we want to give visibility if these agents got it.
Speaker 3:We want to stop these sort of threats, but we also want to know if it's an AI attack. It's actually a very important question that they need answered. Is it an AI attack or is it sort of an adversary with maybe AI assisted? Mhmm. That's been one of the number one questions because it informs them on what they need to defend against, but it also informs them on how they express this to the rest of the company, the CEO, the board.
Speaker 1:Yeah. What's been the biggest or what do you see as the the biggest bottleneck for you in terms of actually deploying solutions to customers? They're asking you, do you need more sales reps? Do you need more just more customers to come to you? Just scale up what you already have.
Speaker 1:The shape of the next twelve months for you?
Speaker 3:The the great part of what we built at CrowdStrike is it's a very scalable model. It's a single agent, single platform with a single control plane. So you know what people need to do to roll out AIDR?
Speaker 1:Turn it on.
Speaker 3:You know, sign the PO. I think they turn it on. That's it. Right? It's the same agent that's there.
Speaker 1:That's great.
Speaker 3:And we spent a lot of time making sure that we can instrument, we can find shadow AI. Yeah. Is it Claude? Is it Codex? Whatever it is.
Speaker 3:Sure. We can instrument every action that agent has taken. Every action
Speaker 1:Yeah.
Speaker 3:With a specific identity. Every tool call. Every spawn of an agent. Yeah. Every network connection.
Speaker 3:Yeah. Every prompt. We have that visibility. It's incredible. So it's sort of like the EDR moment when we developed EDR.
Speaker 3:Mhmm. When we first showed people, they were like, I've never seen this before. And when you do this to an agent, they're like, we've never seen this. We've been dying to see this. So I think when you look at our model, we're combining a very scalable platform, turn it on same agent.
Speaker 3:That's a huge win for us and huge barrier to entry for other competitors. We have the most agent security agents deployed of any pure play security company. So that's one. Yeah. And two, we combine that with a very flexible licensing model
Speaker 1:Yep.
Speaker 3:Which is Falcon Flex. Yeah. So you'll be able to to use it's a it's a token based system. Sure. So the more AI you use them, the more you pay.
Speaker 3:Yeah. Because there's, you know, more cost to this. But at the end of the day, you'll be able to use those credits and burn down from your Falcon Flex licensing model.
Speaker 1:Yeah. And I imagine with Nemotron and just the advances in models, like, there's a world where token prices come down over time if if, you know, you're scaling up and stuff. So there's a lot of flexibility there.
Speaker 3:Well, and we we have different models which makes it a lot more cost efficient. Yeah. So the the goal for us is to really yeah. Is actually to real it is. It's not just one model.
Speaker 1:Yeah. Of course.
Speaker 3:So we're we're really driving down the cost. Yeah. And I think that's a huge advantage for our customers. And then providing that sort of trusted access. We've been doing this a long time.
Speaker 3:And customers wanna retain their data and the the prominence of that data Yeah. The sovereignty of that data with us.
Speaker 1:Yeah. Take me a couple quarters for it, a couple of years for it, far as you can, because it feels like we there was there were sci fi stories about cybersecurity incidents related to AI. Then we got the mythos moment, the hugging face moment. Now we have a really solid response. Mhmm.
Speaker 1:And it feels like there's you know, the the the never ending cold war continues. Yeah. But are are we are we in a stable equilibrium here? Are you expecting some big change one way or another in the posture between the two warring groups here, the red team, the blue team?
Speaker 3:I think it goes back to the story as old as time. Yeah. It's good versus evil. It really is. It just plays out now in the modern day with agents at a speed that we can never really contemplate.
Speaker 3:But we can fight. But we can fight and
Speaker 1:we will. Yeah.
Speaker 3:They'll get better, we get better. Yeah. And, you know, part of part of our what we delivered today with the lab is the red blue training loop.
Speaker 1:Sure. Very important. Mhmm.
Speaker 3:Is that the blue learns from the red. Right? So the defensive model continually learns from the offensive model, and you have a very fast cycle. Yeah. It's very important.
Speaker 3:But, you know, there's gonna be all kinds of new technologies, new agents, new systems, things that we haven't even heard of today.
Speaker 1:Yeah.
Speaker 3:And we have to be able to defend against that. And I think what remains while there's a will be a lot of change, what remains constant is security parallels the slope of the technology curve. Yeah. So the technology curve, I mean, you know, I started in the early nineties doing this. Right?
Speaker 3:It was like this and then it it's like that. So you have to have security that actually parallels that. We don't do everything. You know, what we do, we do really well. We're a big platform company.
Speaker 3:There's only a few of us. Think I that's gonna win in this market. But it's a big market you can see by all the the companies around here.
Speaker 2:Yeah. And this is like a for those of you that are tuning in, this is a where it feels like you set up a town here. Like 10,000 people.
Speaker 3:It's massive. It's unbelievable. Yeah. I mean, you know, maybe you'll see some of this in b roll or whatever. But Yeah.
Speaker 3:This is a massive security conference. We have companies coming to this going. We're not going to any other conference. Yeah. And it was just an offshoot because we've got the best customers.
Speaker 3:It's a big audience. But I think what's important to realize is we understand and value the ecosystem. Mhmm. We can't do everything. Like, what we do, we do really well, but it's part of the whole ecosystem and network, which is why NVIDIA was here.
Speaker 3:Yeah. Obviously, Jensen this morning. Lib Butan from Intel. Yeah. Greg Brockman from OpenAI.
Speaker 3:Yeah. All partners, plus all the many that you see here.
Speaker 1:Yeah. Sorry. George,
Speaker 2:please. What groups or institutions are not paying enough attention to this new technology cycle that everyone here is, like, paying attention to this, obviously the AI boom, new threats, things like that. But is is there a set of groups globally that that need to be, paying more attention to the new set of threats that aren't today?
Speaker 3:Well, it's a good question and I think the mythos moment has really provided much more visibility from the board all the way down to the CEO level. I mean, my phone was ringing off the hook from Fortune 10 CEOs going, hey, what does this mean? How can you help us, etcetera. Right? So, you know, from visibility standpoint, that's good.
Speaker 3:And then you look at a fortune we'll call it a fortune 500 company. For the most part, they have or will find the money to deal with some of this. It depends on the industry, how much they spend. But generally, they have a view and it's regulated, etcetera. The have nots, those are the have.
Speaker 3:Yeah. The have nots are
Speaker 2:mean I'm thinking like local utilities. Local utilities. Systems.
Speaker 3:Hospitals, NGOs. Yeah. Like utilities, forget. I mean, they're running such old software. Sure.
Speaker 3:So it's the have and the have nots. And I think part of what we wanna do and even working with open AI is how do we help, you know, give a hand up to people Sure. Who, you know, need it because they don't have all of the security people they need. They don't have the money for all of these sort of advanced software and technologies. But we gotta it's a collective community effort, and that's part of where what we're helping to drive in partnership with many others.
Speaker 1:What does it take to make it a CrowdStrike these days? You're hiring AI researchers now for Yeah. Yeah. We a You have a lab.
Speaker 3:With 270 PhDs.
Speaker 1:Wow. Oh. Significant. So what is the shape of the new all star up and comer at CrowdStrike look like?
Speaker 3:The up and comer, I mean, it depends on
Speaker 1:the I guess the question is just how much AI are they using? How much are the human skills still hyper relevant? What is the what is the balance? How how familiar do you have to be with these tools? What are the pitfalls?
Speaker 1:Because I think everyone's sort of realizing as they run large companies that people can get lost in the sauce if they're using too too reliant on it? How do you think about this in terms of, like, your own management style?
Speaker 3:Yeah. I think that's important because, I mean, we we try to be very deliberate about it. Security is very important to us. So where we use it, how we use it, what groups we use it in, you know, we've expanded out obviously. But Yeah.
Speaker 3:Obviously, a big part is gonna be around coding. Sure. And you have to make sure that you get the right secure code out of it. Yeah. You know, it used to be in the early models, I would say, a little less so now.
Speaker 3:But the early models, it was like the early days when coding when someone would go out to the Internet and they would just copy and paste snippet
Speaker 1:of code. Yeah. Forget it.
Speaker 3:You would take that vulnerability and would propagate for everybody that needed, you know, that snippet of code. Right? So AI was originally generating some code and you're, you know, I I have my own models I built. I, you know, have my own security agents that I built just to play around. Yeah.
Speaker 3:And it's like, the same model that just built my code that I built an agent to figure out whether it was secure. It was the same model because it's not secure. Like, okay, why don't you build it, know, in the first place? So you have to be aware of that. And but what I think is important getting back to your question is, if you don't buy into AI as an enabling technology and you're sort of scared for your job, you're not gonna you're not gonna be successful at CrowdStrike.
Speaker 3:Yeah. If you wanna use AI in the right places at the right time with the right cost, we have all the room in the world for you here.
Speaker 2:I love it.
Speaker 3:And we have these sort of AI builders and we're deploying them into all the different functions. So those are the folks that you go, hey, I it'd be great if we can do this And you turn around and get some coffee and they go, here, it's done. Yeah. That that's what we like.
Speaker 1:No. I love that too. I love that too even in our smaller organization. We would love for you to sign this helmet. We have a Sharpie here.
Speaker 1:Would you mind signing right here? We wanna get an autograph Okay. From you to commemorate the occasion. And we also have a gong with a mallet. We'd love to get you to smash this for the occasion.
Speaker 1:Here you go. Give us a gong Okay. We'll let you out I
Speaker 3:gotta get a backhand on this. Right?
Speaker 1:Yeah. Yeah. Can a backhand.
Speaker 3:Where where's the the sweet spot?
Speaker 1:Think the sweet spot's right here.
Speaker 4:It's right
Speaker 2:there. Just give it enough force. You'll be good.
Speaker 1:Oh. Nice to meet you.
Speaker 3:Alright. Authority. There we go. With authority.
Speaker 1:Well, thank
Speaker 2:you. I just will say I love the I love the aesthetics of everything here. You got agents of chaos back here. It's incredible.
Speaker 3:It's incredible. Well, congratulations to you because I know you you had a new baby?
Speaker 2:I did. Okay. That's breaking news.
Speaker 3:Okay. Had a new
Speaker 1:baby. No.
Speaker 2:No. It's great. It's not
Speaker 3:a secret.
Speaker 4:Did I scoop you?
Speaker 3:You scooped Okay.
Speaker 1:Sorry about that. No. No. No. It's great.
Speaker 2:Alright. Great to see you, George.
Speaker 3:Great to see you guys. I'm gonna leave it. There you But I Yeah. I won't walk away like I normally do. We'll see you at the track.
Speaker 3:Yeah. Stay tuned for the race this weekend.
Speaker 1:We're excited.
Speaker 3:Hopefully our men our men do well. Yeah. And we'll from there.
Speaker 2:Okay. Thanks, guys. Alright.
Speaker 3:Yeah. Bye.
Speaker 2:See you soon.
Speaker 1:We'll talk to you soon. Cheers. That was fantastic. Of course, the show is
Speaker 2:Breaking news.
Speaker 1:Sponsored by Ramp. Time is money. Save both, easy use corporate cards, bill pay, accounting, and a whole lot all in one place. Thank you, Graham, for making TBPN possible. We have a bunch more guests coming on from Fal.Con here in Las Vegas.
Speaker 1:And I believe we have our next guest ready to rock. We have Michael Sentonas, the president of CrowdStrike, here to take us deeper on everything CrowdStrike is doing in cybersecurity in the age of AI. The AI revolution is here. Are you ready? That's what it says outside.
Speaker 1:Little ominous, but probably accurate.
Speaker 2:Accurate.
Speaker 1:Good question to be asking. How are you doing? John, pleasure. Nice to meet you.
Speaker 2:Welcome.
Speaker 1:Welcome to the show. We're gonna have you throw this headset on. We'll get this out of the way. Get comfortable. And we will ask that the microphone just go a little bit close to your mouth because it's noisy in here.
Speaker 1:You've got a lot of a lot of partners here. It's a huge company, huge conference. Did you have anything to do with that? Are you the reason why everybody's here? Yeah.
Speaker 1:A little bit of reason. A little bit of a reason. Okay. Yeah. Yeah.
Speaker 1:Well, yeah, let's start with your role. What do you do at CrowdStrike? Little bit of your history. And then there's a whole bunch of hot topics I'd love to go into. Happy to go wherever you want.
Speaker 1:Let's start with your role, your day to day. President CrowdStrike? Yeah.
Speaker 5:So go to market reports into me. Okay. Product and engineering team. Researchers, our threat hunters.
Speaker 1:Researchers too. Researchers too. Researchers and go to market. How are those feel like different groups? How how does that work?
Speaker 1:Is that operational? Are you spending more time with one or the other? How does that blend? Look.
Speaker 5:I think my background started through the the product side of the the organization. I was the CTO of the company for for quite a while. One of the things that I talk a lot about is you can build the best technology in the industry Yeah. If you can't sell it, if you can't talk about the value, if people can't deploy it Yeah. And they can't ultimately keep themselves safe Yeah.
Speaker 5:It's kind of irrelevant. Yeah. So it's trying to bring together the smartest people. Obviously, you had George on before. Yeah.
Speaker 5:We worked really closely. He's got a bunch of people that report into him as well on the engineering and research side. Yeah. It's bringing it all together and then making sure that we keep people safe and secure.
Speaker 1:Yeah. What are what are customers in the go to market side actually concerned about? Because there's an immense amount of attention on cybersecurity right now. I imagine that makes sales easier, but at the same time, we've all seen token maxing and AI budgets and people, you know, they have to find the money somewhere. So what is the tension that you deal with?
Speaker 1:How are you thinking about positioning that for customers?
Speaker 5:Yeah. Look, every organization has huge requirements, but they've also got a budget. Yeah. They've got a business to run. The business is not there unless you're a service provider and your business is cyber.
Speaker 5:Yeah. You're you're building cars. You're building houses. Yeah. You're medicine.
Speaker 5:And you need to keep yourself safe and secure. So every CISO, every CIO is trying to basically do the best at what they can. They they came into 2026. Suddenly, everyone's trying to work out how do I find tokens to pay for all of the things that the business is doing. You know, every second organization has token chuck.
Speaker 5:So at the end of every month, they just realized that they spent 20,000 more than they should have
Speaker 3:Yeah.
Speaker 5:Per employee. Yeah. Yeah. You know, we gotta work with everybody to show them there's a better way, there's a more efficient way. We give them a a a vehicle that they can procure and get CrowdStrike Flex that I think you guys have talked about with George in the past.
Speaker 5:Yeah. And and we show them that they get a much better solution. It's just easier to live with day to day. So it's not only showing them the the the cost of buying it, but how do they deploy it and then operationalize it. Yeah.
Speaker 5:Because cyber, you gotta live with it. You gotta use it every day.
Speaker 1:Yep. Yeah. Okay. So in deployment, let's talk about the balance between attackers and defenders. In terms of AI capabilities, I'm pretty confident that you, OpenAI, and Thrompik, the big labs have the advantage on raw power intelligence capabilities in terms of defense and probably offense too, but you don't use it for that, you know.
Speaker 1:But does that map to your reality that that the open force team
Speaker 2:the only difference is like you guys need to be successful every single time an attacker only needs to be successful one
Speaker 1:Yeah. Out of Yeah. Yeah.
Speaker 2:A 100,000 times. Right?
Speaker 5:Yeah. I mean, that's the way it works. Okay. Every organization can't get it wrong. And equally, they've got additional pressure.
Speaker 5:Yeah. They're gonna get it right a 100% of the time, but they also have to not stop business. Yeah. It's easy to get it right a 100%
Speaker 1:Turn off everything.
Speaker 5:If you turn off everything. Yeah. So, you know, it's not gonna it's not gonna fly with the CEO of the company Yeah. If every day, you know, the security technology is slowing people from browsing. You can't use the AI that you want.
Speaker 5:So Yep. There's an added level of complexity. Yep. The Defender has things like change control. The defender has things like, you know, regulatory guidelines and Sure.
Speaker 5:And process that they need to, you know, follow. Attacker doesn't care about any of that. Yep. You know, go to Europe where everyone in Europe is talking about, like, AI, and regulation. I said it in a conference, this is fantastic.
Speaker 5:You guys are leading the world in all of this regulation and everyone was proud. The adversary does not care. Yeah. The adversary
Speaker 2:Yeah. They're already breaking the law. So why would they not do?
Speaker 1:Why would they follow other regulars?
Speaker 5:They love it. They're in there. Yeah. That's that's kind of some of the challenges that people face with. And then you have the cost pressures.
Speaker 5:Yeah. You can't just pour everything into tokens. Yeah. You can't just pour everything into, you know, IT budget. Yeah.
Speaker 5:So that's why we spend a lot of time making sure that you get the best that you can.
Speaker 1:Yep. And a lot of
Speaker 5:the time we come in and say, okay. Here's a product. We're gonna try to take two out. Yeah. It's not one in one out.
Speaker 5:It's one in two out, three out. Sure. Sure. Sure.
Speaker 1:But so talk about the pace of AI diffusion, AI adoption in in cyber? Because it feels like even though there's immense go to market operations, AI adoption among the bad guys has to be incredibly quick because it's often free. It's it's, you know, highly motivated.
Speaker 2:Just go approved.
Speaker 1:Hugging face. Just download the thing. And so I feel like that's maybe more of the challenge than, like, raw intelligence. Is that a reasonable frame of mind to think about? The the real show escape of the problem is, like, the slope of adoption.
Speaker 1:Like, the the good guys need to adopt more security AI faster than the than the than the attackers.
Speaker 5:Look. We've talked about this for twenty plus years.
Speaker 2:Yeah. If you went
Speaker 5:to a security conference twenty years ago, everybody talked about this time in the future is gonna come Sure. Where attackers are finding vulnerabilities and they're weaponizing them at a speed that you're just not gonna be able to deal with. Sure. Sure. We're here now.
Speaker 5:Yeah. And if you think about the technology, I mean, the adversaries get access to everything. Yeah.
Speaker 4:And the
Speaker 5:best thing that's happened to them is the advancement in the open weight models. Yeah. They can go and get a Chinese model. They can go and get a model effectively from anywhere that they run inside their their sort of framework. They can build it.
Speaker 5:They can train it. They can tune it. And because they're running it in their environment, they can customize it in a way that you don't know what they're doing. Yeah. And then the first time they use it is the first time you have to deal with it.
Speaker 5:Yeah. And it's becoming cheap for them. Yeah. When they run it internally, they don't have the cost of sending you the tokens and everything else. They need the hardware.
Speaker 5:They need everything out there.
Speaker 2:Yeah. Do you do you feel like their adversaries are compute constrained right now or are they just able to do a lot with a little?
Speaker 5:Depends on the adversary, you know. The kid at home is gonna be compute constrained.
Speaker 1:Yeah.
Speaker 5:If you're dealing with a nation state, if you're if you're dealing with some of the most well funded, well structured, well trained adversaries that now have this capability as well, this is the challenge. That's why there was a packed arena this morning. That's why Jensen came out to talk about what they can do. Yeah. Because if we don't do something and if it's not a community, it's gonna be really hard to compete with this technology.
Speaker 5:It's so good.
Speaker 1:Yeah. Yeah. What kind of conversation are you having with governments these days? We were just talking about, you know, it's not just enough to secure the Fortune 10, the Fortune 500. You need to secure the local hospital, the local, you know, utilities operation.
Speaker 1:And it feels like the government various governments might try and incentivize different rollouts and speed things up there. What are you hearing from talking to people in government generally?
Speaker 5:I think I think you've nailed the point because the world's business runs a small business. The world's economy, I
Speaker 2:should say,
Speaker 1:runs a small
Speaker 5:business. They don't have the resource. They don't have dedicated people. They don't have the the dollars. And most often when they have a problem, it's also very hard where do they go.
Speaker 5:And they think, you know, I'm not gonna be able to get the resource of the largest banks, etcetera. We wanna spend a lot of time with it. Yeah. And that that's super important. But importantly, governments around the world that are also starting to say, hey.
Speaker 5:We need to make sure that our economy keeps working. We need to make sure that critical infrastructure, you know, the power is on, water is flowing, you know, rubbish trucks arrive. Mhmm. Otherwise, we're gonna have have chaos. And, you know, we've seen examples of critical infrastructure taken out.
Speaker 5:We can't have banks get compromised with ransomware. We can't have, you know, just pure chaos out there. And I think there's an opportunity now to work more collaboratively. Mhmm. And every every coming coming back to your question, every government wants to talk about AI.
Speaker 5:You know, what do we have to worry about? How do we use it? How do we embrace it? But But what do we have to be worried about when other people that have malicious intent Yeah. What could they do to us?
Speaker 5:You know, if they start using all of these open weight models, what what do we need to know about them? So a lot of partnership, a lot of collaboration. And I think, you know, that concept of community that we're talking a lot about this week is super important because if we don't do that, we're just not gonna be on top of it.
Speaker 1:Tons of attention on AI for very good reasons. Is quantum getting under discussed? And I say that because I've heard that there are adversaries who are hoovering up encrypted data with the hope that quantum computers in the future will be able to decrypt that data. They're stealing it now. They can't do anything with it.
Speaker 1:And so maybe even though AI is super important, we should be talking about it 99% of the time. Shouldn't we be talking about quantum 1% of the time?
Speaker 5:We are. And and it's look, it's a big topic. Not a day go by. Yeah. A customer, a partner, an analyst, someone asks a question about quantum and what that means.
Speaker 5:Yeah. I love the point. Just to kind of dive in Please. Where people are taking data. Yeah.
Speaker 5:A lot of the time, you see examples where attackers will basically exfiltrate all your data. Yeah. And then you don't see it again.
Speaker 1:And you get the email saying, yes. Your name was in clear text, but everything else was encrypted. And now you have to think in five years that might be decrypted. Sure. But sometimes
Speaker 5:when those attacks happen, you understand when when you see your name in the list, you understand what they'll do. Yeah. You understand that you are the person that they monetize. Sure. Sure.
Speaker 5:Sure. But what happens when they take terabytes of data? Yeah. They're not selling it. They're not acting on it.
Speaker 5:They're doing
Speaker 1:what it is maybe.
Speaker 5:Well, they didn't do it just because they wanted to have fun. True. So there's intent. Yeah. Now now whether it's decrypting it down the road Sure.
Speaker 5:Whether it's training models. Yeah. You you know, need to think every attacker, there's a motivation for it.
Speaker 2:Yeah. Yeah.
Speaker 5:Yeah. And and it's fascinating when you actually start to get behind what's That's interesting. What's driving them. Yeah.
Speaker 1:Yeah. Yeah.
Speaker 2:You gotta imagine there's at least a few people out there
Speaker 5:Well, that's how that's how it used to be. Yeah. Back in the day, you wrote malware. Yeah. Because you wanted a company like CrowdStrike to say, hey, man, that Jordy guy, he he
Speaker 1:Oh, yeah.
Speaker 5:The cloud. Like, he nailed it. Like, this is an attack. This is really innovative. We talked about it.
Speaker 5:We Yeah. Started You you felt good about it.
Speaker 1:You got it in a hard place. Doesn't work that way anymore. Okay. Yeah. Two two How
Speaker 2:how is AI impacting various social engineering schemes?
Speaker 5:Well, it's funny because, you know, a few years ago, you you it was really easy to tell people about social engineering and said, you know, if you read something and it read you know, reads like, you know, a ten year old wrote it or someone with bad English, you know, it's probably not the bank that you have all your money in. Right? Yep. It was an easy telltale sign. Yeah.
Speaker 5:They they learn how to use Yeah. You know, chat GBT. They learn how to use Gemini. The the emails that they write are phenomenal. We used to say about a year ago, the click through rate in phishing was about 11 to 12%.
Speaker 5:Today with AI
Speaker 2:That still feels incredibly high.
Speaker 5:Over 60 now.
Speaker 1:My soul. Because Yeah. It's
Speaker 4:so
Speaker 5:real. They're written perfect. They're grammatically they probably write better than us now.
Speaker 2:Yeah.
Speaker 5:And you kinda look at what comes out. It's really hard to work out what's real, what's not. Yeah. So they're getting a lot of opportunity. The thing is you grab an open weight model and you you basically say, how how would I carry out this attack?
Speaker 5:Yeah. It's gonna give you the playbook. Yeah. You know, I've I've done cyber since university. You don't need any of that anymore.
Speaker 5:I kind of feel like wasted youth now because you just need a a model. You ask the question and it tells you what to do. Yeah.
Speaker 1:Yeah. The company is on oh, okay. We gotta move to the next we got one more question. We got time for one more question. I mean, the company's on an absolute tear.
Speaker 1:I'm interested in how you know, you oversee all these groups. What were you telling people during the SaaS apocalypse in earlier moments? Even go back further. Just just throughout the company's history, you've had a very clear vision of where things are going, the value that you're creating long term, but there's gyrations. What is it like actually managing all of these different teams?
Speaker 1:What do
Speaker 2:call It's gonna be funny that the the the height of the SaaS pocalypse, you probably had the phone ringing off the hook more than any other point in history because at the same time, people were realizing like, well, models are now at the point where Yeah. Yeah. Yeah.
Speaker 5:I I've known George who he had on just before for for over twenty years. And I remember one of the first things he ever said to me, look after the customer. Everything else takes care of itself. That's good. And that mantra goes throughout CrowdStrike.
Speaker 5:So all of this noise, you know, we just basically say, keep looking after the customer, keep innovating, keeping them safe and secure, things will take care of themselves. Yeah. We know the way the technology works. You know, for me, the SaaS pop apocalypse thing, there was no merit to it. Yeah.
Speaker 5:It didn't make any sense at all. Even today when people say, hey. All the models are gonna find all the vulnerabilities, and then we're gonna get this state of normality. No. We're not.
Speaker 5:We're gonna get more vulnerabilities. We're gonna get more attacks. It's only gonna get harder. And that comes from just having so many years of experience. It's having an engineering team that is at the cutting edge at the forefront.
Speaker 5:But it's putting the customer first and, you know, it's a it's a good formula and it always works.
Speaker 1:I love it. Well, thank you so much for coming on the show. Congratulations on fantastic Fal. Con. Up next, have Daniel Bernard, the chief business officer of CrowdStrike's.
Speaker 1:Got five minutes though.
Speaker 2:We got
Speaker 1:five minutes to hang out.
Speaker 2:60% click through rate on phishing emails. What are you guys what
Speaker 1:are guys doing out there? What are you guys doing? What are you doing? Speaking of phishing emails, there have been a raft of of password reset attempts on x. Yeah.
Speaker 1:Got another minute
Speaker 2:I wanted to ask him about.
Speaker 1:Oh, yeah. Yeah. Well, we can we can go into that with the next guest. Nick Carter posted on x. A lot of people getting unsolicited x password reset attempts in their email inbox.
Speaker 1:Do the following. Go to x settings, security account access, security, check password reset protection. Don't let people hack into your x account. It's too simply too valuable. You can't let
Speaker 2:And this is because x money is rolled out to a lot more people.
Speaker 1:Oh, I saw that notification financial now because you could potentially steal some of the money if you got in as opposed to just post a Bitcoin link or something like that. Anyway, the other story we gotta talk about is YouTube creator, director, Markiplier, has acquired eight per 8.5% stake in GoPro. Did you see this? The action camera maker. They've been
Speaker 2:Yes.
Speaker 1:Sort of in the doldrums. A lot of competition from China. But
Speaker 2:And then immediate questions because GoPro just got acquired today.
Speaker 1:Oh, wait. It was a full acquisition?
Speaker 2:Yes.
Speaker 1:Oh, I didn't know that. Wow. Yeah.
Speaker 2:So this news comes out yesterday. And just today GoPro has entered into a definitive agreement to merge with privately held Starman Optical in a deal valued at 285,000,000. So it seems like Markiplier is up massively, which is gonna immediately
Speaker 1:draw part of the deal. Yeah.
Speaker 2:Well, it's gonna immediately draw a lot of attention.
Speaker 1:Yeah. But a lot of times, things happen as one piece of a larger deal and the stake gets disclosed at a certain time because it's part of this remaking of the business. Do you think go GoPro can come back?
Speaker 2:That's a good question. I I I owned a GoPro back in the day. Yeah. I never I never GoPro was one of those things where for the average person, you're capturing footage that is only entertaining to you. Yeah.
Speaker 2:No one else is gonna care. Yeah. You know, I'm a I'm a pretty good snowboarder, pretty good surfer.
Speaker 1:Just pretty good?
Speaker 2:Sean Mcguire Sean Mcguire was like throwing throwing shots, but we'll we'll set up a heat, Sean. But but but but, anyways, I I always felt like I would I would film something with my GoPro, and then it would be mildly entertaining for me and not that entertaining for someone else.
Speaker 1:So you don't watch game footage? You don't get out there on the waves and rewatch what happened?
Speaker 2:If you're watching game footage, it's better to watch
Speaker 1:yourself from the third person. Don't wanna watch the first person. Interesting. Interesting. Yeah.
Speaker 1:So you're putting on a show. I I I bought a GoPro at at various points in time, but, again, like, never really found a good use for it.
Speaker 2:Yeah. And it felt like the GoPro budget for consumers shifted to drones. Yeah. They didn't they didn't get there.
Speaker 1:They tried.
Speaker 2:Again, that's a third person view that is, like, I think a lot more interesting
Speaker 1:to do. Some drones that will follow you out while you're surfing and track you well and stuff. Yeah. And then, yeah, just the
Speaker 2:innovation I would like China. I still have very positive feelings towards GoPro. They they work with so many amazing athletes over the years. They were a pioneer. Yeah.
Speaker 2:The bigger the bigger challenge was just the iPhone. The guy very durable. Yep. And the quality got amazing. So why would I A 100%.
Speaker 2:I can take you can take your phone out on a on a ski run or whatever. And and you'll be fine. The other thing, Meta Glasses too. True. Meta the Oakley Meta Glasses.
Speaker 1:I think Best Buy reported earnings and said that smart glasses are, like, driving significant in store sales for them. Like, they're they're actually moving. They're selling well. We haven't even seen that in
Speaker 2:other So anyways, I don't like to see Insta three sixty Yeah. And
Speaker 1:DJI DJI
Speaker 2:take over. Take over. So I hope they can But
Speaker 5:if you
Speaker 1:watch the independent product reviewers, like, products have innovated in many in many, many ways that that GoPro has not been able to keep up with mostly because of the manufacturing Yeah. Side of the business. But interesting to see, you know, is this Markiplier's way of, like, buying a new merch line? Like, that's one potential view on this is like Yeah. Okay.
Speaker 1:You buy a stake in this, and then you run you basically run ads on your platforms to promote the new products. Maybe he has a vision. I mean, he didn't make a whole movie with a lot of VFX. Maybe he wants to grow GoPro into something that's more for filmmakers and cinematic cinematic creating.
Speaker 2:The Starman Optical, the acquirer, is an American company that describes itself as a privately held US optical photonics company focused on developing and domestically manufacturing optical transceivers. So when I first saw the news, I assumed it was a Chinese company buying it up. But but we'll see. Hopefully, they can make and sell a lot of GoPros
Speaker 1:for America. I I love his journey, and I think it it you know, this feels like an outside of the box move. It's not just another, you know, sparkling water brand or hard seltzer brand from a from an influencer. It's him thinking about business in a very different way. So it's exciting.
Speaker 2:More news. First, let me
Speaker 1:tell you about Railway. Railway is the only one intelligent cloud provider. Use your favorite agent to deploy web service databases and more while Railway automatically takes care of scaling, monitoring, and security.
Speaker 2:More news. Mister Beast has launched
Speaker 1:A book.
Speaker 2:A book for his audience of voracious readers. The people are clamoring. People in his audience have been asking for a book. Yeah. He delivered.
Speaker 1:Yep.
Speaker 2:Now he's turned the book into effectively a lottery.
Speaker 1:So give
Speaker 2:away a million dollars to somebody that buys the book.
Speaker 1:Was that on day one, or is that downstream? I know. I guess that's day one. That's the that's the promotion. So, anyway, he partnered with James Patterson, who is a huge author.
Speaker 1:Good news for the subset of mister beast beast fans who love to read mystery novels. The YouTube Giants collaboration with James Patterson is out Tuesday. That's today. Accompanied by a flurry of marketing on mister beast channels, read my book and you could win $1,000,000. Bad news for Harper Collins, The book buying subset of Mr.
Speaker 1:Beast fans appears to be vanishingly small. Two people close to the project say the most dangerous games is on track to be a historic bomb with preorders numbering in the four digits as of last week. But why would there be preorders if it hasn't launched the marketing yet? This I I'm I'm I'm sort of
Speaker 2:skeptical about time I'm hearing about it.
Speaker 1:This is the first time I'm hearing about it, and it seems like mister Beast just uploaded the the actual contest. And, like, you could say she shouldn't be running a lottery or I I I don't I don't like this type of book promote promotion, but, like, that's that's something that will work.
Speaker 2:Say if the pre if the preorders or the orders still stay in that in that four digits What do mean? Hedge funds get involved.
Speaker 1:Hedge funds?
Speaker 2:Buying up buying up more of
Speaker 1:the books Oh, go to win the million dollars. Yeah. Yeah.
Speaker 2:Yeah. You could win hedge funds.
Speaker 1:You could win. With it with a raftle like this, you don't have to actually buy the book. You usually can just sign in and and and send it over. But will you be reading it?
Speaker 2:I think one of us has to read it, or at least Tyler.
Speaker 1:Tyler. Tyler. Where
Speaker 2:are you?
Speaker 1:We can get Tyler to read it. Anyway, we'll have more fun with that in just a minute. Let me tell you about public.com, investing for those that take it seriously. They got stocks, stocks, options, bonds, crypto, treasuries, and more with great customer service. And our next guests are here.
Speaker 1:Welcome to the stage at Fal.Con with TBPN. Great to see you. How are you doing? Great to see you.
Speaker 2:What's happening?
Speaker 1:How are doing? Well, yes. John, Jordy. Ron of Kurtz. We're gonna have to throw on these headsets, and it's a little bit loud in here.
Speaker 1:There's a lot of CrowdStrike energy. The the CrowdStrike fan sounds going insane right now. And so just get the microphone sort of as close as you can. Let's move this around. Flip this up.
Speaker 1:Yeah. There we go. Is it oh, I think you put it on backwards. There we go. Anyway, let's start with introductions.
Speaker 1:Introduce yourself. Tell us who you are and what you do.
Speaker 4:Hey, guys. Daniel Bernard. You can call me DB, chief business officer at CrowdStrike.
Speaker 1:How many how popular are internal nicknames at CrowdStrike?
Speaker 4:They're super popular. There's only one DB. Okay.
Speaker 1:That's That's right. Thank
Speaker 6:you. Justin Boitano. I lead the enterprise business at NVIDIA. Good to see you guys.
Speaker 1:Yes. Good to see you again. And tell us about the partnership. Tell us about the news today.
Speaker 4:Well, big news today. Yeah. We launched Safemind. Yeah. Cyber security's first frontier models and harnesses custom for cyber.
Speaker 1:Okay.
Speaker 4:Made by Cyber for Cyber.
Speaker 2:Yeah.
Speaker 4:We built this on Nemotron. Yeah. It's bending the curve of Frontier AI and the and the and the advantage of defenders. Better protection. Harnesses?
Speaker 4:Plural? There's multiple harnesses.
Speaker 1:Why would you pick one? What what what's involved in in selection? What are the differences? Are we talking about pure economics, the tokenomics? Or are there more, like, you know, the right tool for the job?
Speaker 1:So
Speaker 6:ahead. Yeah. Let let me give a little bit of color. I think the the big news too is that the frontier is in the harness.
Speaker 1:Okay.
Speaker 6:It's not really about just the model. It's the entire system. And so what the CrowdStrike team have done a phenomenal job doing is tuning the harness for attack, tuning the harness for defense. And the harness is the thing that's going to sit there and reason and call tools and work through solving the problem, whether it's finding vulnerabilities or finding and writing detections. Yeah.
Speaker 6:And so I think the work that we've done both through the harness and through the open model creates this like super capable agentic system that is gonna always be on and be able to, let's say, learn from enterprise environments. Jensen talked a lot about how we're deploying it internally. We're building the digital twin of our environments. Sure. We can basically go through these attack defense simulations Yeah.
Speaker 1:To build the best defenses for our organization. That's great. As you went about building this, how important were benchmarks to you? Public benchmarks? Private benchmarks?
Speaker 1:How do you see that fitting into the tool chest of building a great product?
Speaker 4:Super important. Okay. We need it to be more performant than what's out there today.
Speaker 2:Yeah.
Speaker 4:Like, the goal here that we both set out to achieve is this thing needs to be better, faster, and more cost effective than the other open source and frontier models of the day. Sure. For cybersecurity use cases. Yeah. You know, that's the big thing.
Speaker 4:Like, we're not here to change the world of science, math Yeah. Manufacturing. We're here to stop breaches. Yeah. We're here to make cybersecurity better.
Speaker 4:Yep. That's offense, that's defense, and that's continuous learning.
Speaker 1:Yep.
Speaker 4:Better performance at each step of the way. And that's what the data we have that we're able to that we shared with the market today.
Speaker 1:Talk about the decision to go with Nematron. There's a lot of open source models. I can imagine why you didn't pick some of them, but break down the decision.
Speaker 4:Look. There's a really, really close relationship between CrowdStrike and Nvidia. So that we didn't even look at anybody else because, you know, when it comes to, like, the foundational layer of AI that we built the business on Yeah. You know, that's that's GPUs.
Speaker 3:Yeah.
Speaker 4:And who do we get our GPUs from? The creators of them.
Speaker 1:Sure. That's NVIDIA.
Speaker 4:And so when it comes to open source and you can look at NVIDIA and Jensen, such a strong perspective and really across everything you're doing too, Justin, like, the world needs open source. Yeah. The world needs choice. That just aligns with us very culturally as well. Yeah.
Speaker 4:So there was nowhere else, like, why would we go anywhere else?
Speaker 6:And and for us, the the feeling was mutual. I think Jensen said on stage, CrowdStrike is our number one partner in cyber security. They have the perception system that really understands what's going on in customer environments. Yeah. So if you pair that perception system with, we'll we'll say an open model that we built, it's built as general knowledge.
Speaker 6:But we we put out there the data sets, the open techniques and the weights, so they can be customized by CrowdStrike. So they can build their own specific cyber domain intelligence and be able to build a new business model where they're, like, selling tokens, right, to secure enterprises, and they're doing it in the most cost effective way Yeah. By building on that open foundation.
Speaker 1:What else is NVIDIA bringing to the table around a project like this? Because Nematron is obviously the the model layer, but, obviously, the GPUs. But yesterday, I saw a fantastic deal with our our buddy at Lambda for, you know, a big You
Speaker 4:said they're busy.
Speaker 1:Yeah. You're busy. Big GPU cluster. Is there advisory that you can provide even if CrowdStrike is gonna be racking NVIDIA GPUs? Like, how deep does that partnership go beyond just like, cool.
Speaker 1:Here are the weights. We signed on the line. You can use them. Okay. Yeah.
Speaker 6:Yeah. I think most I mean, as I mentioned, most of the advancements at this point is research in the harness. Sure. So we're we're, our research teams, you know, George announced this Yeah. What what it's called cyber Cyber intelligence lab.
Speaker 6:And we have a bunch of cyber researchers. Sure. And basically what we're doing is we're constantly publishing where advancements are coming in in in the in the ecosystem or in these environments. Like we put out there a few weeks ago some new harness research that we called AVO that showed in Arc g ARC AGI three. Yeah.
Speaker 6:We could take a a frontier model from 30% accuracy to a 100% accuracy.
Speaker 1:What's called ARC AGI v three?
Speaker 6:Yeah. Yeah. That's insane. And that's all open Wow. You know, research Yeah.
Speaker 6:That we're sharing with
Speaker 4:With us.
Speaker 2:Big surprise in the last month is is people showing what's possible with a different harness versus Arc's standard harness. Yeah.
Speaker 6:So we share all of that open research together to advance the industry. And ultimately, we're not a cyber company, they're the cyber company. They have the domain intelligence, the perception into customer environments to understand like real attack paths that people are trying to exploit. You add to that these new agentic attack paths that people are trying to understand in their environment. And ultimately, we wanna help power defenders and give them this differential advantage that Jensen and George I
Speaker 4:feel like I'll add on to that. I think every meeting that I have and that that everyone at CrowdStrike has in NVIDIA, they all start the same and they end the same. How can we help you grow? It's the first question. It's the last question.
Speaker 4:It's from Jensen all the way to the person at the front desk.
Speaker 1:I love it.
Speaker 4:And so your answer to your question of where, like, what's on the table?
Speaker 1:Everything's on the Everything. Yeah.
Speaker 4:The whole shop's on the table. It's like, what do need from us?
Speaker 1:That's
Speaker 4:We're So like, when we who's the best AI partner that we have? It's NVIDIA because they're helping us take cybersecurity to a whole new space, and we're bringing them to over a 100,000 customers Yeah. And everybody that's on the show floor here today.
Speaker 1:Yeah. That's great. How important is human design of RL environments for this harness development? You obviously have the most insane data collection.
Speaker 4:Correct.
Speaker 1:Decades of experience across the entire organization. There's a lot of value and ways that I could see if you're there's a huge jump, I'm not surprised.
Speaker 4:I'm Sure.
Speaker 1:You know, congratulations. But but but how much how much is it about actually designing new environments and then go training?
Speaker 4:Intelligence, I believe, is really becoming somewhat commoditized. I think what's really real in this next chapter of AI is how you contextualize based off of specific situations. So the fact that we have Falcon Complete data that's managed detection response data from human analysts that took actions over the last number of years across, you know, all these different environments. The fact that we have frontline incident responders that stop the breaches, all that that data set lets us curate something that's super relevant and super focused. And then we take that and we we operationalize it with the harness so that we can bring a better model that's built on Emotron
Speaker 1:Yeah.
Speaker 4:And have appropriate harness for solving different problems and have an iterative learn learning loop. Like, where this all goes, in my opinion, is you'll see more models and more harnesses from us in the Safemind family that solve different security use case problems. And that's all based off of the experience of our practitioners.
Speaker 1:Yeah.
Speaker 4:You know, CrowdStrike is cybersecurity built by and for cybersecurity practitioners. I think that's really different in the market for us versus
Speaker 1:a lot
Speaker 4:of the other random companies that you find Sure. That that say that they're here to work in cybersecurity. Everything is based in solving a real problem.
Speaker 1:Yeah. How are you thinking about educating the customer, the buyer on cost and how to think about the shape of cost in this token maxing? I mean, a breach can be so devastating. Throw all the dollars at it. But at the same time, there's amazing trade offs that you can do with smaller models, different infrastructure, and different pieces of the puzzle.
Speaker 4:Let's start with Justin, because I think you've you've been Yeah. We evangelize open source and
Speaker 1:and Yeah.
Speaker 2:Trying to
Speaker 6:Well, in our environment, so you gotta remember, so one, we we are also a big enterprise. Yeah. We we have to look at the same threats as everybody else. Yeah. Right?
Speaker 6:Of course. So and I think a lot of the conversations has been steered around code vulnerabilities. But in a production environment, it's really about also the configurations in your running environment. Sure. And so, you know, for us, you know, mean, to your point, the harness should be able to use the best of frontier and the best of open to reason through and and figure out which problems you need to use which models for.
Speaker 6:And ultimately, we assume it's gonna be always on. Yeah. We wanna start by trying to make it as low cost as possible by providing open intelligence so they can domain adapt. So the Safemind models are probably the default Yeah. With the exception being the frontier if you wanna look for very novel new things.
Speaker 6:Sure. And that kinda gives you the best cost, you know, cost benefits when you run this all the time across code binaries and configurations in your environment.
Speaker 4:Yeah. We've heard it loud and clear from customers that just going one direction with Frontier Labs is just too cost prohibitive. Yeah. But open source at this point, like generic open source is sort of like, you don't have the it's it's a compass that's spinning in a circle. So what we need to do is have the best use cases, the best results, the best outcomes, and also delivered at the best cost.
Speaker 4:And that sort of is the the aperture that we that we need to play in with this thing. And so I think every enterprise is grappling with. We have this new line item in COGS that's called tokens. Yep. You know?
Speaker 4:Yeah. Five years ago, it didn't exist. Yeah. And and it's not like you necessarily say goodbye to anything else, by
Speaker 1:the way. Yeah.
Speaker 4:Yeah. You're you're doing more with your cloud providers. Yeah. You're using a lot of software. You need to secure all of it with CrowdStrike, of course.
Speaker 4:So, you know, I think everybody's in this redistribution or rethink of how you do budgeting in this Yeah. In this new AI first world.
Speaker 2:Yeah. And I think every enterprise is planning to spend more on AI next year, but at the same time trying to be a lot more efficient. Right? And so that's why these two, these closed models, open models can can coexist and actually the industry can continue to thrive. Yeah.
Speaker 1:How do you think about the we were talking about this earlier, but the the the economic warfare between attackers and defenders? Because the the benchmark performance, all the stats that you mentioned, those are great, but I'm almost more excited about the cost savings because this is a technology that needs to be always on, running all over the place. It needs to be, you know, too cheap to meter essentially as fast as possible so it can be everywhere. Because if an attacker's only trying to come through one door, you gotta make sure every door is secure. So how are you thinking about the economic balance between attackers and defenders?
Speaker 4:Well, the way I think about it is prices I mean, value creation is always measured economically in a p and a q. Yeah. What's happening right now
Speaker 2:is the q is going out of control. Yeah.
Speaker 4:So like, that's the big picture. Like Yeah. There's more attack surface than ever before. Yeah. And that means there's more opportunity to come back to your question.
Speaker 4:There's more opportunity for adversaries to play around. Yeah. And they don't have to be right every time. Yeah. They just need to be right once.
Speaker 4:Yeah. And go get something off the shelf somewhere and use the weapon. And if the weapon works, they've that's a good day for them.
Speaker 1:So do you think 2026, if if we look back in a decade, do you think the attackers are gonna be like that was the best year we ever had? Or do you think it's gonna be the moment when the defenders are saying that was the moment we figured things out?
Speaker 4:Going on a limb here. Please. Justin can back me up or you have your own opinion, but, like, Safemind changes the curve. Like Okay. I think Frontier AI has disproportionately advantaged well, one, everyone sees advantage.
Speaker 4:Yeah. But I think sort of until until like this time, it's sort of disproportionately advantaged to adversaries.
Speaker 1:Okay.
Speaker 4:And I think it's time to change the tide. Sure. And that's why we're working together. We wanna see that change happen and make that a reality. Yeah.
Speaker 4:There's a lot of great technologies on the floor here. There's a of great cybersecurity companies and there's a lot of companies that we're keeping safe all the time, but it's too easy and it's too dangerous for these adversaries to get their hands on things that are way too powerful.
Speaker 6:Yeah. And I think it's a it's a another example of a domain where like general intelligence can like come and do attack, but it's gonna be pretty expensive to run these attack paths through these like frontier large models. Think of it like a battleship, right? Of course. And then what you want to do is you want to help defenders have the equivalent of drones, like super low cost models that they can run everywhere.
Speaker 6:They can run across their entire state. And to DB's point, the goal is I think to help specialized cybersecurity defenders have the tools. And their advantage is also, they know the code, they know the configs that they run, the people coming in from the outside don't. So on the inside, you can do all that recon, you can map your environment, you you know, use these lower cost models to find, you know, potential new attack paths and then continue to close them down and do it at a lower cost if you use, you know, these these new platforms like Safeline.
Speaker 1:Yeah. So there's
Speaker 2:a And you guys are in the position where you can be at the frontier with these capabilities, but there's not this, like, insane pressure from billions of users out there. Hey. You have to release these cyber capabilities to everyone. Right? Whereas the frontier labs are in a different position where you have hundreds of millions or billions of users that want the best capabilities for things like coding, right, and and these other capabilities.
Speaker 4:Well, we have the pressure of lots and lots of big numbers of attack surfaces. Those are endpoints, identities, cloud workloads. Yeah. And they're putting a lot of pressure on us because they all need protection. Yeah.
Speaker 4:You know, we can't let any of those things get compromised. So like, the the threat's real, the need is there, the budget's there, but the market's asking for something better and something different. You you don't treat a specialized illness with a generic pill. Sure. You need to have the right the right dose, the right the right therapy.
Speaker 1:Yeah.
Speaker 4:I think that that's really what we've we've done here.
Speaker 6:And I think with every platform company, you know, we're a platform company. Yeah. We know what we are and what we're not. We're an accelerated computing company. We're not a cyber security company.
Speaker 6:Yeah. So, these natural partnerships sort of emerge to allow us to go in a specialized way, solve the problem in a very focused way. Yeah. I think, you know, even the frontier labs are probably thinking to themselves like, where do they really want to own alpha and go Where try and do they want to partner? And I think in these areas of like specialized intelligence for cyber security, you know, we like generally think the best approach is help, you know, protect critical infrastructure, help make the world a safer place, and and we'll all be in a better place.
Speaker 1:Yeah. What as a platform company, what is the advantage that you see occurring over time around having diversification in the actual chip fleet? I mean, there's this Grok deal coming online. There's there's already a number of different configurations of rack scale servers and all sorts of different like, back to the gaming chips. I mean, I see people running AI loads on those too.
Speaker 1:What what is the what is the advantage and the shape of that over time?
Speaker 6:Oh, we're an accelerated computing company. Right? So we have to accelerate everything. Okay. And the the reality is, you know, different models need different, you know, capabilities.
Speaker 6:Yeah. And so ultimately, we wanna be able to provide the capabilities, whether you're doing pre fill and inference or decode, have the most performing capable architectures. And then ultimately, as Jensen always talks about, we're building rack scale infrastructure with seven processors. Yeah. We're trying to be best of read across all of those Yeah.
Speaker 6:So that we can build these large AI factories and drive the best token efficiency per watt. Yeah. And then ultimately have a great partner ecosystem that can extend that efficiency into these new domains and use cases.
Speaker 1:That's fantastic. Well, on the deal. Thank you so much for coming on the show.
Speaker 4:Pleasure to be here. Thanks, guys. TBPN.
Speaker 1:Have a
Speaker 2:good one.
Speaker 6:Thanks for having me.
Speaker 1:Thanks for having on.
Speaker 4:Thanks.
Speaker 1:This was fantastic. Thank you to everyone who's tuned in live from Fal.
Speaker 2:Great to see you. Cheers. Okay.
Speaker 1:There are a few more stories that we should get through. Let me tell you about Shopify. Shopify is the commerce platform that grows with your business, lets you sell in seconds online, in store, on mobile, on social, on marketplaces, and now with AI agents. Jordy, was there anything else that you wanted to get to?
Speaker 2:Give John Turnas
Speaker 1:Oh, yeah.
Speaker 2:Follow over on X.
Speaker 1:Yes. John Turnas has hit the timeline.
Speaker 2:What a what a what a moment for X Yes. In some ways. Yes. Right? You know, we're how many years in the platform?
Speaker 1:Yeah. It feels like if
Speaker 2:you assume an important position in the world of business, you simply can't afford not to be on x.
Speaker 1:Yeah. No. The the fact that I mean, it's not like he's, like, you know, tweeting random stuff or actually, like, breaking No. He is. There yet?
Speaker 2:Since we started the show, he started ship hosting. No.
Speaker 1:I'm kidding. No. No. I'm kidding. He's tweeting it lower case, very online, very, like, native.
Speaker 1:But the fact that Jensen's on there, Mark Zuckerberg's on there, like, the AI conversation is truly happening on X, and it's exciting to be a part of it. Apple investors want the new CEO to be an innovator. This is in the Wall Street Journal, Ralph Linklare writes, talking about there is one way, there is, yeah, there is one way which company observers have said, has been lacking since the Steve Jobs era, rev rev revving up Apple's innovation engine, especially in artificial intelligence. Tim Cook's brilliance was to take the company Jobs Built and scale it massively. The year Cook took over, Apple sold 72,000,000 iPhones.
Speaker 1:This year, it will to be 255,000,000, tripling volumes, hitting annual release dates like clockwork, minimizing risky capital investments, and returning more than $1,000,000,000,000 to shareholders. That is a size gone moment. Helped Cook multiply Apple's valuation by 13 times, but, Ralph Winclair in the Wall Street Journal says that Apple's investors now want to change things up. It's not enough to rest on your laurels. Just focus on operational efficiency.
Speaker 1:He's gotta innovate, according to the Wall Street Journal, they say. But in Wall Street parlance, the positives look priced in. Apple's trade Apple stock trades at 33 times next year's earnings compared with the S and P five hundred's collective multiple of 20 times. Apple gets that premium even though its earnings are growing half as fast as the market. Investors are paying up for Apple because it looks safe at a time of broad anxiety over returns to be had on massive investments in AI.
Speaker 1:But when the valuation gets stretched, safety isn't safe anymore, and there are negatives that investors may be overlooking. In the age of AI, Apple has lost its status as the consumer as the company that defines how consumers interact with devices, a title it held for forty years from Apple two to the iPhone. So The Wall Street Journal wants to take risks, launch new products, you know, go go aggressively. He certainly seems like he's stepping back from the Apple Vision Pro sadly, but we'll see we'll see what he does. It'll be exciting time.
Speaker 2:Last but not least, Dyson just released a new AI powered toothbrush with integrated 4,000 pixel macro lens camera for $499. I know a lot of you people have been asking for AI in your toothbrush. Yes. I certainly know I have. And I'm glad that
Speaker 1:This can't possibly be the first AI toothbrush. There have to
Speaker 2:be other ones. Somebody's gotta get this and try it out. I I certainly have never Also, wanted what are we
Speaker 1:doing with this 100,000 pixels?
Speaker 2:In my toothbrush or really a camera in my toothbrush. But
Speaker 1:That's not how people measure camera lenses. They'd say megapixels, which I think is a million pixels. So it's actually a point one megapixel lens camera.
Speaker 2:But I think we gotta give it a shot.
Speaker 1:Okay. We gotta give it
Speaker 2:a shot. I don't wanna judge it too much. I I do like a good wooden toothbrush.
Speaker 1:Wooden toothbrush?
Speaker 2:I like a wooden toothbrush, personally.
Speaker 1:Yeah.
Speaker 2:I think they get the job done. Yeah. But,
Speaker 1:oh, well.
Speaker 2:We gotta try it out. We'll be back in the UltraDome.
Speaker 1:Yeah. Back in
Speaker 2:the UltraDome tomorrow. Cannot wait.
Speaker 1:We're heading back to Hollywood. Thank you for tuning in. It's
Speaker 2:been an honor.
Speaker 1:My pleasure. A privilege. We'll see you tomorrow. Goodbye.