How Capital is Powering the AI Infrastructure Buildout with Magnetar Capital Managing Director Neil Tiwari

**Sarah Guo** (0:05)
Hi, listeners. Welcome back to No Priors. Today, I'm here with Neil Tiwari of Magnetar Capital. This is a $22 billion alternative asset manager at the center of the AI Compute build-up. We talk about the financial innovation, depreciation of GPUs, and what's next in AI Compute. Welcome. Thanks so much for doing this, Neil.

**Neil Tiwari** (0:24)
Absolutely. Really happy to be here.

**Sarah Guo** (0:27)
So, you are leading AI infrastructure at Magnetar. You're at the center of the build-out, enabling it, financing it. For any of our listeners who haven't heard, can you just explain a little bit what Magnetar is?

**Neil Tiwari** (0:39)
Sure. So, Magnetar has been around for, actually, this is our 20th year. We're an alternative asset manager, and that can mean a lot of different things. But we have three primary strategies. The first one is private credit. The second one is a venture strategy.
And the third is more of a systematic or quantitative focused public strategy as well. And so, I think when people look at us and why are we here in this moment, especially on building out AI infrastructure, I think a lot of it has to do with our unique lens on helping to build capital intensive businesses and using creative financing, whether it's venture or other structures with unique elements. And I think we're going to talk a lot about that. But to build out and optimize the balance sheets for these capital intensive businesses.

**Sarah Guo** (1:28)
So, I remember hearing about you guys originally. You're the first investor I think we've ever had on the podcast.

**Neil Tiwari** (1:34)
That's exciting.

**Sarah Guo** (1:35)
Thank you. I remember hearing about you and Magnetar initially around, I was like, who's this big owner of CoreWeave? And also, you know, helping OpenAI with some of their early build outs. When did you guys first start looking at the problem and thinking about how to solve it?

**Neil Tiwari** (1:51)
Yeah, so we actually stumbled across the compute problem before it was compute. We met CoreWeave back in 2021, and that was when they were actually transitioning from mining Ethereum into high performance compute. And at that time, it was using the GPU as an instrument to mine cryptocurrencies. And interestingly, that same instrument could be used for high performance computing applications.
And the first one was visual effects. So think of things like movies, Marvel movies and things like that. And so they were transitioning at that point between crypto mining into the first kind of high performance compute use case. And this was all before AI. And so we made our first investment before the AI trade started. But we added a lot of optionality where we could envision a world where the GPU could be used for a lot of different high performance kind of computing applications.
I think AI was on the radar, machine learning was on the radar for us. But I wouldn't say that we could foresee everything that happened. We just happened to be at the right place at the right time. And we continued to double down as the company progressed and started shifting into more workloads that were machine learning and kind of AI training based.

**Sarah Guo** (3:12)
Did you have an existing significant data center investing footprint?

**Neil Tiwari** (3:17)
No, I think, interestingly at Magnetar, we have invested across asset classes. So we've done a lot of property investing, real estate investing as an example, investing in energy. We had an energy business historically. And so a lot of the elements for what constitutes a data center, power, energy, land, real estate, we had a lot of the background in those spaces. I think we were new to compute, right? That was a new sector for us. And so kind of those two worlds merging, we obviously came up on the curve on the compute side, but we had a lot of background on the elements that constitute what it means to build a cloud.

**Sarah Guo** (3:57)
So you guys just really, you were in this company, you saw the demand and you said like, it's going to grow and we're going to make this a big part of our business.

**Neil Tiwari** (4:04)
Exactly. I think what was interesting was we made our first investment in 2021 and then about a year later, we continue to see expansion of use cases. At that time, it was called high performance compute and then it was kind of towards the end of 22, the whole AI discussion started. As we entered 2023, CoreWeave started to train models for OpenAI. That's when things really started growing because the sheer amount of compute that was needed to train an LLM, this was the first time it had ever been done.