TechCrunch News 2024年10月21日
DataCrunch wants to be Europe’s first AI cloud hyperscaler — powered by renewable energy
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DataCrunch作为芬兰初创公司,致力于成为欧洲首批“AI计算”超大规模企业,以可再生能源为特色。该公司通过出售GPU‘服务’降低AI处理成本,已获1300万美元种子资金。其计划利用资金构建基础设施,服务包括索尼等企业客户及个人研究者,同时关注能源消耗与碳排放问题,但存在一定 latency 方面的权衡。

🎯DataCrunch成立于2020年,由Ruben Bryon创立,像其他同行一样,以‘服务’形式出售GPU,承诺降低AI处理成本。该公司获得1300万美元种子资金,其中760万美元为股权融资,540万美元为债务融资,这种融资方式利用物理资产作抵押来获取贷款,降低了股权出让风险。

💻DataCrunch的新资金将用于构建基础设施,以支持Nvidia的最新服务器和集群,包括H200 GPU,从而帮助其扩大客户群体,不仅包括索尼等企业客户,还包括在OpenAI等机构工作的个人AI研究者,同时为独立研究者和开发者提供灵活的按需定价服务。

🌍DataCrunch的数据中心位于芬兰首都赫尔辛基和冰岛,利用当地可再生能源优势。在赫尔辛基,可从电网获取绿色能源,且其中一个数据中心的废热可用于为城市供暖;在冰岛,环境温度低且能源完全绿色,这使其在运营的碳足迹方面具有优势。

⏳DataCrunch承认其服务在低延迟方面不具绝对优势,更适合对延迟要求不那么严格的工作负载。目前其数据中心位于共享的‘共置’设施中,但公司计划在2025年开始建设自己的数据中心,这需要更多资金。

A fledgling startup is setting out to become one of Europe’s first “AI compute” hyperscalers, with renewable energy playing a pivotal part in its pitch to prospective customers.

The AI goldrush has spurred unprecedented demand for “compute,” which refers to the processing power, infrastructure and resources needed for tasks such as running algorithms, executing machine learning models, and processing data. One of the big beneficiaries of this demand has been Nvidia, emerging as a $3 trillion powerhouse off the back of demand for its GPU (graphics processing units) and associated AI hardware.

In tandem, an industry of cloud infrastructure providers has sprung up off the back of Nvidia, raising bucket loads of cash en route. In the U.S., we’ve seen the likes of Lambda and CoreWeave hit lofty billion-dollar valuations to expand their datacenter operations. Now, Finnish startup DataCrunch is throwing its hat into the ring, touting itself as one of the “few serious players” in the space with all operations in Europe.

DataCrunch team in Finland. Image Credits:DataCrunch

Founded in 2020 by CEO Ruben Bryon, DataCrunch — like its peers — sells GPUs “as-a-service,” promising to reduce the costs for AI processing. The company today said it has raised $13 million in seed funding, constituting $7.6 million in equity financing from backers such as ByFounders, J12 Ventures, and Aiven co-founder Oskari Saarenmaa. The remaining $5.4 million debt segment hails from Local Tapiola and Nordea.

While it’s slightly unusual for a seed-stage startup to raise such a significant portion as debt, DataCrunch has done this for the exact same reason that others in the space, such as CoreWeave, have also been raising hefty amounts of debt. It’s all about using physical assets — e.g. Nvidia GPUs — as collateral to secure loans, rather than giving away more equity.

It’s also more efficient to secure large buckets of capital this way, as the banks can simply take away the GPUs if things go belly-up for DataCrunch. For those who control the purse strings, it’s much less riskier than investing in a pure-play SaaS startup, for instance.

“Given the business that we’re in, our main expenses for expansion are capex [capital expenditure] driven,” Bryon told TechCrunch. “This is the logical way to go about it, and as we grow, additional access to that financing becomes available.”

This new round takes DataCrunch’s total funding raised since inception to $18 million, and will go some way toward helping it build out its infrastructure to support Nvidia’s latest servers and clusters, including the shiny new H200 GPU. In turn, this will help it grow a customer base that not only includes corporate clients such as Sony, but individual AI researchers working at the likes of OpenAI.

“That has always been an important market for us, and I think that this ‘individual’ market has been left behind by many,” Bryon said. “For me, personally, it’s important — at the weekend, I’m often using our own services, and have been since the beginning.”

Indeed, flexible, on-demand pricing is a far more alluring proposition for independent researchers and developers who might just need a little bit of compute for personal or university projects.

“People who are studying for a Masters or a PhD — that’s a segment we want to stay connected to because it’s often people who are a few years away from doing something really great,” Bryon said.

Hook them in now, and reap the rewards later when they hit the big time. That’s the general gist.

But there’s no escaping the giant elephant in the room, one that all the cloud companies are having to reckon with: the gargantuan amount of energy required to power this AI revolution.

Part of DataCrunch’s “advantage” is the fact that its data centers are located in the Finnish capital, Helsinki, and Iceland — a country running on 100% renewable energy for years already.

“In Helsinki, we can subscribe to green energy from the grid,” Bryon said. “And currently, in one of our two Finnish data centers, the waste heat is captured to heat up Helsinki itself. In Iceland, we have the advantage that the ambient air temperature is always low, while the energy mix on the grid is already 100% green. So Iceland is pretty much one of the greenest places in the world to have these kinds of operations.”

This will be a big focal point for the company moving forward. While it plans to offer its services to any company globally, it will mostly remain anchored in the Nordics and Iceland. “Perhaps in the future we’ll look at Canada if we can find suitable locations, where we can have a similar advantage in terms of carbon footprint of our operations,” Bryon said.

It’s these “green” credentials that DataCrunch hopes will also set it apart from other European rivals: companies like FlexAI in France, which recently exited stealth with $30 million in seed funding; and Nebius, which recently emerged from the ashes of Russian internet giant Yandex and has just become a public company again.

There is a trade-off here, though: While low latency is often one of the big selling points for AI compute providers, DataCrunch isn’t necessarily going to be in that bucket, which means it will be better suited for a particular kind of workload.

“Our strategy is such that we’re not going to be the provider with the absolute lowest latency due to being in 100 locations around the world,” Bryon said. “We are more focused on the compute that doesn’t have that strict latency requirement. We can still have a decent enough latency though, it might not be 10 milliseconds, but it will still be something like 100 milliseconds.”

It’s also worth noting that DataCrunch’s data centers are in shared “co-location” facilities for now, but the company says it’s planning to start building out its own data centers in 2025 — something it will need significantly more capital for.

“I want us to be on a path toward going public with this company, and we’ll need access to plenty more capital to keep expanding the company,” Bryon said.

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