You are someone who's just been allocating, interestingly, to a public company that's, of course, based in Europe, but thinking about infrastructure, about access to the cloud. Nimbus is the name of the company you were looking at, but you're also just

thinking of the turf warfare that's out there to allocate money to generative AI. This is just going to add to the party, right? Yeah, absolutely. Well, first, thanks for having me on. But we at Excel are big believers that

we're only in the early innings of laying down the infrastructure that's going to be required to actually support this massive technological wave of AI. So this committed investment doesn't surprise me at all to see it coming in because we do need that infrastructure. So I'm excited to see more

infrastructure being laid down for it. Okay. Where are you seeing the biggest opportunities? You've just made this allocation of funds into a publicly traded provider of cloud? We've got CoreWeave already up there as a big pivot from all these companies that were looking at Bitcoin

mining and now getting into the world of cloud computing. But what next in terms of areas that you think are fruitful? Yeah, absolutely. So at Excel, we broadly invest across two different facets of AI. We think about infrastructure, which is

very much an example of that. Also investing in companies like Scale AI in the infrastructure layer, helping build the data engine for AI. But then we can't forget about the applications that are going to run on that infrastructure. So we see great opportunities in both

enterprise and consumer applications. Our most recent investment on the consumer side of things was in a company called Speak, supporting language learning for AI. So that is the tussle right at the moment. There is an awful lot of money being allocated to building picks and shovels, infrastructure, and many feel the

valuations potentially have gone out of whack there. We now go into the killer applications that many are still waiting on. Do you think we're actually there, and people aren't seeing the application of generative AI right now, the real productivity gains?

Absolutely. We see it from the ground up, and we see companies that are gaining real traction and driving real value, both in enterprise and consumer. So although it is still the early innings, and a lot of the emphasis has been on that infrastructure, the

training to get us to the point where we can actually run inference on these models and get the value out of them. I think you're going to start to see, particularly across 2025 and 2026, applications spring up both in

enterprise and consumer that drive real value to the end user. But then when I think of enterprise, you've got Salesforce all in on agent force, you've got Microsoft trying to offer it. So, Co-pilot, where is the space? Or is it actually that a lot of these startups

will end up being eaten up by these bigger enterprise companies? That's the exit strategy. Yeah, that's a good, it's a really good question. So, speaking on the infrastructure layer, what we actually see is that by pairing their software and hardware

engineers against the problem of standing up infrastructure, but doing it with an AI-specific approach, we're able to offer a level of flexibility that the large incumbents offering generalized clouds just don't have in the ecosystem today. So that means that people can come to us

that need large amounts of compute, that want bare metal. And people can also come to us that just want an on-demand flexible experience with their infrastructure. So as always, you see the innovation in the early startups tackling some of the holes and open opportunities in the large

incumbents. And I expect to see the same thing. Salesforce is obviously defending its territory, but we see a ton of activity and tech approaches and apps going after their exact market. So we'll continue to see it. Is Gen AI going to be the next sort

of over-allocated area? I mean, we all got way too in the weeds when it came to chips and semiconductors for 2024. When it comes to 2025, we're all going to be playing an agenda.

I don't think it's overhyped at all. I think the reality is we're still in the early innings, and the expectations are quite high on what agents are going to do within the enterprise application arena. And so it's easy to point at the flaws

in agents today, but I tend to look at the progress of agents, and as an investor, I look at where value is going to be created over the next decade. And over the next decade, I think you're going to see really mature agents hit

the market and scale in a meaningful way.

Laying Down the AI Infrastructure

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인프라 및 향후 적용 가능성에 초점을 맞춘 제너레이티브 AI의 현재 투자 환경에 대해 논의합니다.

인프라 및 클라우드 액세스에 중점을 둔 유럽 상장 기업인 Nimbus에 자금을 할당했습니다.

현재 인프라 개발은 아직 초기 단계에 머물러 있으며 AI의 성장을 뒷받침하기 위해서는 상당한 투자가 필요하다는 믿음이 있습니다.

클라우드 컴퓨팅 및 기타 AI 인프라 관련 분야에 대한 투자 기회를 모색합니다.

인프라와 애플리케이션을 모두 아우르는 Excel의 AI 투자 전략.

AI용 데이터 엔진에 중점을 둔 Scale AI와 같은 인프라 회사에 대한 투자.

최근 언어 학습 AI 회사인 Speak에 투자하는 등 기업 및 소비자 AI 애플리케이션 모두에 대한 관심이 높아지고 있습니다.

현재 인프라 투자에 대한 집중과 향후 AI 애플리케이션의 성장에 대한 기대에 대해 논의합니다.

제너레이티브 AI를 통한 생산성 향상 실현과 향후 잠재적 영향력에 대한 토론을 진행합니다.

현재 제너레이티브 AI의 실질적인 생산성 향상 효과가 나타나고 있는지 의문이 듭니다.

엔터프라이즈 및 소비자 AI 애플리케이션 모두에서 실질적인 견인력과 가치 창출을 관찰합니다.

2025년과 2026년에 걸쳐 가치 있는 AI 애플리케이션이 크게 성장할 것으로 예측됩니다.

엔터프라이즈 AI 시장의 경쟁 환경과 스타트업의 인수 가능성을 분석합니다.

세일즈포스나 마이크로소프트와 같은 대기업의 제너레이티브 AI 분야 진출에 대한 논의가 활발합니다.

스타트업은 기존 대기업에 부족한 유연성을 갖춘 특화된 AI 인프라 솔루션을 제공합니다.

제너레이티브 AI가 반도체처럼 과잉 투자되는 분야가 될지 여부에 대한 추측이 난무합니다.