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00:00Certainly you still got obviously got some degree of exposure to a lot of the technological
00:04waves going on out there. Of course. Yeah. Yeah. We'll talk a little bit about kind of the risk
00:09and opportunities that have cropped up. We can certainly see it in public markets. Private
00:13markets has also seen a little bit of ruction as well. You know our world remain as you know
00:17is credit markets over the course of even the last 18 months 24 months underneath the surface.
00:25It is really wobbly. We have six percent default rates and high yield Moody's numbers elevated numbers for
00:33the last two years. So even before we are hitting this current wave of issues with software and what
00:40it will do. Even before that there was just underneath the surface a lot of stuff going on. Is there
00:47any sort of
00:48contagion risk though. I mean we heard earlier on Bloomberg television Bruce Flatt over at Brookfield
00:52Glenn August over at Oak Hill kind of saying that look there there is something going on under the
00:57surface but nothing widespread in terms of risk. It's not systemic. OK. You know the credit markets
01:04the high yield credit markets the broad definition five and a half trillion dollars. That's by the way
01:10a drop in the bucket. That's the video cap isn't it. But crypto you've lost I don't know a few
01:17trillion
01:17dollars over the last few months. Nobody seems to care that much. Right. So you don't want to overdo kind
01:24of what
01:24happens if there are credit problems in terms of broader systemic risk. I do think though software is a big
01:34stick.
01:36You know the credit market has had all these sticks being dropped on it. And one day it'll really buckle.
01:43And software is a big stick.
01:45And just to put it in perspective in 2015 2016 we had a energy crash. Equity markets didn't do headline
01:58equity markets didn't do very much. Energy was 1515 percent of the high yield index.
02:05And it took high yield spreads up to 900 basis points. Entire market. High yield spreads today are 300. So
02:14the contagion risk in credit.
02:17Yeah. Worry about it. Worry about it when UBS strategists are saying we could see a 15 percent AI trigger
02:24default rate surge across debt
02:26markets. Direct lenders in particular. They say have it financed software companies to the 40 percent of all sponsor backed
02:33loans. So is
02:34that the contagion. Is that the issue. When do we start to see transparency on that. I think somebody like
02:40a UBS and I read that report
02:43closely. That is their worst case scenario. OK. Right. So one can't just you know in the when you look
02:51at kind of how all of us
02:52invest. We build a base case and then we kind of build tailed risks to it. Yes. I think the
02:59one thing I would walk away with today.
03:02The tailed risk in credit is fat. Wow. This is a fat tailed risk. Now it's no longer a normal
03:10tailed risk. And something like software
03:12there. How big a problem it is. I don't think we even quite know yet. It's all. Yeah. So are
03:21you there for.
03:22Believing in many ways that software is exposed as much as the market fears to AI disruption like Snowflake managing
03:28to push it
03:29off. I've heard NVIDIA CEO Jensen Wang saying it's illogical to think AI is going to destroy all the software.
03:35Yeah. It's logical to think it's going to destroy clearly segments of the software business. Not all of it.
03:43And if those segments if companies are bought if private equity firms have bought software businesses at 20 plus times
03:52cash flow relying on growth.
03:55You are going to see large pockets of problems. But the 15 percent default rate the UBS number I think
04:05can get kind of a little overdone.
04:07But when we talk about the potential risk or the disruption here. I mean there's also a time frame element.
04:11And that's a treaty report rattled people partly because they were saying basically 2028 which is just around the corner.
04:17I know it's hard to look in your crystal ball and put a time frame for that disruption.
04:21But does that time frame end up being maybe a little longer than the duration of some of these some
04:26of these credit assets.
04:28Look we have over the course of the last year and a half. We are redrawing the geopolitical map of
04:36the world.
04:37Right. Just in terms of how it works. There is such a huge differentiation between AI and tech valuations and
04:46real economy business valuations.
04:49So so you know all this is coming with that. So add you say you know I think look we
04:57I do believe the U.S. economy can take a lot of buffeting.
05:02Right. But so I'm less concerned about the U.S. economy going into some deep deep dark recession. Right. More
05:10concerned that credit at 300 basis point spreads.
05:14Yeah. Which is kind of close to record lows today. Yeah. Is mispriced. That's mispriced. It is. But how does
05:21that correct.
05:22If at all. It widens out. Well yeah I know it widens out all at once or very slowly. You
05:28know we generally find these things. Yeah. These are three six month things.
05:32Yeah. It's not instantaneous. Why are you saying this with a smile on your face. There's always opportunity. Yeah. It's
05:42what we do. Yeah.
05:43Right. So we are we're in the business of lending money to help people tied over issues. Hybrid capital junior
05:52capital at 15 percent.
05:54Or we're in the business of kind of taking over businesses running them and improving them. And for us that
06:01opportunity pipeline.
06:03Right. Builds up. How would you how would you compare the opportunities you're seeing now relative to I don't even
06:09say five years ago.
06:12In early 2022 before the Fed really started to kind of hike rates. Our pipeline was seventy five billion dollars.
06:22We've got twenty three billion dollars of capital. Yeah.
06:25It was our pipeline curated pipeline was about one hundred deals and seventy five billion. Today it's three hundred billion.
06:33All right. We're in conversation right now with Victor Kostela founder and CIO over at strategic value partners. He's sticking
06:40around with us as we await Caroline.
06:42Those numbers out of NVIDIA. We've kind of reiterated the actual numbers for the quarter which isn't going to be
06:47really be a surprise.
06:48Gil Loria was on earlier. D.A. Davidson. He made a great point here because of how late they report
06:52in the cycle and because all their customers are Microsoft Meta and all these others.
06:55We kind of have a general sense of what they're going to do. Sixty eight percent revenue growth. Phenomenal.
06:59There has been some anxiety coming from maybe a Lynx equities who says that maybe not all of the capital
07:04expenditure that you're seeing from these hyperscalers is going towards GPUs and CPUs.
07:08A lot of it goes towards energy. And then you've also got the worry of what really is OpenAI looking
07:11to spend?
07:11How much are they committing? Because that's a huge exposure for the likes of NVIDIA.
07:15But then if Meta is also doing deals with AMD, if you've got Amazon using their own chips, if everyone's
07:20TPU crazy, how much is that going to be a long term issue for NVIDIA?
07:25But you're right. At the moment, the fact that a $4.8 trillion company is getting anywhere near a 60
07:29percent growth in revenue is extraordinary.
07:30And we're going to talk a little bit later about the debt side of this as well because, I mean,
07:34we get these big numbers.
07:35And you cover this on BTEC every day, these gigantic commitments. But they're still, you know, it's not necessarily cash
07:40being kind of taken out the wallet.
07:42I mean, they've got to find the cash somewhere. Some of the companies have it on their balance sheet.
07:45But as we've seen, even the companies that have it on their balance sheet are going to the debt markets.
07:48How long are the debt markets going to be receptive to that type of borrowing?
07:51Particularly to the neoclouds. We've got Corleaf coming out tomorrow after the bell.
07:54How much are they still having to be very clever in which the way they finance some of these new
07:58data centers.
07:58We know that Meta and Alphabet and all the hyperscalers can issue debt and then some and people will lap
08:03it up.
08:04But what more broadly of the deal, how many times can AMD sell its shares to be able to win
08:08over a new client?
08:09It's a key question.
08:10We are still waiting on those numbers out of NVIDIA. If we can, I do want to bring Victor Khosla
08:15back into the conversation, particularly on that last point that Caroline was getting at, this idea of debt.
08:22And I know that you're not lending at that scale of what some of these companies look for.
08:26But I am curious that if a software company, a hyperscaler, somebody came to you and presented an opportunity where
08:32they needed the money, I mean, would you feel comfortable lending to them or taking an investment?
08:37These guys are issuing debt in the investment grade markets, very tight spreads.
08:44We don't get out of bed until we can make 15 percent.
08:49All right, no, be careful.
08:50But this is not really us.
08:53Yeah, we should point out, you do a lot of high yield and things like that as well.
08:57Some of these neoclubs are getting into the field of high yield.
08:59I mean, and software companies might end up being there if they suddenly get stuck to be shut out of
09:04the market in some way.
09:04Yeah, and it gets to the idea, though, too.
09:07And I do kind of want to link this back to some of the more real economy because AI has
09:10kind of infiltrated everything.
09:11It's not just really about building data centers anymore.
09:14I mean, we're seeing, you know, I mean, we had the trucking market got rattled a couple weeks ago because
09:17some karaoke maker decided it could, you know, had a better model.
09:19So it gets to this idea that the companies that you wouldn't even have thought would have been exposed to
09:23software or AI may now, at least in theory, have some exposure to that.
09:28Or, you know, we are a large investor in a steel company in Europe.
09:34OK. It's got round numbers about 500 million or so of EBITDA.
09:38So it's a good size business. Yeah. We think the AI opportunity to buy better to to buy better scrap
09:47metal, which is kind of what you need.
09:50And there are a few other places that can be relevant. Creates 50 million, 75 million even in EBITDA or
09:58cash flow.
09:59Big numbers. Industrial manufacturing company. And by the way, if you if you are invested in some of these businesses,
10:07you've got to invest to get that value because your competitors will.
10:12Where are you in terms of the so bullish it's bearish narrative? The idea that AI is going to be
10:18so enhancing of productivity for your steel maker that it eradicates white collar and blue collar work.
10:25And it starts to impact the broader economy. And I know you're someone who thinks a lot about the broader
10:28economy indication.
10:30But the one of the primary places we think AI comes is in these knowledge businesses.
10:36Yeah. And when you look at kind of what we invest 40 40 40 percent is real assets. Power plants,
10:45airplanes, real estate, toll roads.
10:49But just so you kind of get a sense. Real infrastructure. Real assets. Right. Yeah. So much of our business
10:55is investing in these kind of places.
10:58So when we look at kind of we are not in the not high knowledge growth game, which is where
11:05we think the largest parts of the disruption are going to come.
11:08I think we can see you guys.
11:08Okay.
11:08Okay.
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