Why the first GPU financiers are turning to inference chips in a $400 million deal; plus BP done with climate tech and X cracking down thieving creators
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What is the main topic discussed in this episode?
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General Compute, an AI inference cloud startup, has landed a $400 million loan from Upper90, a tech investment firm.
What is the $400 million chips-backed loan to General Compute and why does it matter?
It might be the first deal to put up inference-specific chips as collateral, chips built to run already-trained AI models quickly and efficiently, rather than the more expensive chips used to build the models in the first place. The financing is the latest signal that markets are responding to concerns over the price of AI tools and tokens by turning to infrastructure that runs open-source models more cheaply than the newest LLMs from Frontier Labs. Founded by CEO Finn Peklowski and CTO Jason Goodison, General Compute raised a $15 million seed round back in May to build an inference neocloud around silicon from Samba Nova, an Intel-backed chipmaker. NeoClouds are purpose-built for AI workloads, unlike the general-purpose infrastructure offered by traditional hyperscalers like AWS or Azure.
The company's SN50 chips are designed for inference. They're power efficient and do not require expensive water cooling systems, which means they can be deployed more quickly than GPUs across a larger variety of data centers.
How do inference-specific chips differ from GPUs and what advantages do they offer?
General Compute says the new chips will provide 16 times faster inference than GPU-based clouds. Now, the challenge is getting a lot of these chips, especially when you are a brand new company. Upper 90 co-founder and CEO Billy Levy, a former Goldman Sachs quantitative trader, had a playbook for that. In 2021, his firm financed GPU purchases by Crusoe, the energy-focused data center startup, which he believes was the first loan against the value of advanced chips. Traditional lenders eschewed such deals at the time because of the risks and uncertainties around GPU depreciation. But as CoreWeave made chips-backed loans into a business model and then the basis of a blockbuster IPO, well, this kind of financing has become common.
Libby told TechCrunch, when we financed NVIDIA GPUs as the first group to do that, the market was inefficient. We could really put together something as an early participant and kind of get compensated for the risk. Now that GPUs are comparatively well understood and perhaps overbought, upper 90 is turning to companies like General Compute to ride the next wave of the AI boom. Libby said, We think open source models are going to be important. And we went and looked for the player last year that was an inference.
Why are lenders like Upper90 now financing inference hardware instead of only GPUs?
Everyone doesn't need a supercomputer, but they do need inference and AI. That thesis has been growing stronger, with companies that provide access to open models like OpenRouter and Fireworks, raising new rounds at huge valuations. New models like Kimi's K3 have proven to compete with the latest releases from Anthropic and OpenAI on coding benchmarks. And new chipmakers like Grok and Cerebrus have drawn interest from acquirers and public markets alike. General Compute's ability to access chips outside of NVIDIA's ecosystem matters for the same reason. TensorFlow, another AI infrastructure company, is making a similar bet on a partnership with AMD. As more alternatives to NVIDIA emerge…
What does BP’s decision to sell most of BP Ventures reveal about its climate tech strategy?
compute providers that are not locked into NVIDIA deals may have an advantage in providing cost-efficient inference. Bukowski said, There are a bunch of chips that are starting to scale that have amazing total cost of ownership, or that can operate much faster than NVIDIA, but there's not too many buyers for them. By getting together with Upper90, this is not just a cool startup got some money to buy some compute. Like, this is the first signal of capital organizing itself and the fragmenting of NVIDIA's monopolistic dominance. Oil giant BP has had an on-again, off-again relationship with climate tech. Now it's definitely off.
How successful was BP Ventures financially and what happens to its portfolio and staff?
On top of pivoting away from clean energy earlier this year, the oil giant announced last week that it was selling the majority of its venture portfolio — more than 10 companies, according to the company —
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Chapters
7 chapters
1
What is the main topic discussed in this episode?
0:02–0:52
2
What is the $400 million chips-backed loan to General Compute and why does it matter?
0:52–2:01
3
How do inference-specific chips differ from GPUs and what advantages do they offer?
2:01–3:22
4
Why are lenders like Upper90 now financing inference hardware instead of only GPUs?
3:22–4:08
5
What does BP’s decision to sell most of BP Ventures reveal about its climate tech strategy?
4:08–4:53
6
How successful was BP Ventures financially and what happens to its portfolio and staff?
4:53–5:52
7
How is X using Grok AI to detect stolen content and change creator payouts?
5:52–8:52
Speakers
2 identifiedMore from TechCrunch Industry News
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