Cloud Provider Gets $2.3B Loan Using Nvidia's H100 as Collateral
anandtech.com
anandtech.com
Are you suggesting funding with lines of credit vs "free" money from VC which diminishes the founder's control?
I've seen more than one case where a company was looking to do a round but they had not even considered the option of taking out a bank loan against their inventory. Especially for short term liquidity that's much, much better than VCs buying stock.
it's expensive in the long term, if your company is successful. In the short term, it is cheap, because you don't pay interest on VC money, which makes your cashflow much better.
Bank loans/bonds are expensive up-front, because you are obligated to service interest. It's cheap in the long run because once your business generates revenue, you can use them to pay off the loan, and slowly wean it off, or find an even lower interest loan to refinance off.
Of course, a bank will only lend if you have collateral, while VC will "lend" if the business idea is good.
The problem for the lender is that it's a bet against progress in the field obsoleting the thing. If the user can cancel and send the thing back because there's a more cost-effective model, the lender has a problem. That mistake hurt Lloyds of London in the 1970s.[1]
[1] https://www.nytimes.com/1979/07/30/archives/lloyds-insurers-...
It's a bet against progress in the field only to the extent that they depend on the collateral if the lessee fails. Lessors hate getting collateral back. So they've probably looked at the lessee's capital structure and decided that, along with whatever interest rate they're getting, it's a reasonably priced risk. They're likely mapped out their estimated risk of default by year along with a declining recovery value of the collateral by year.
https://www.reuters.com/technology/coreweave-raises-23-billi...
> Last month, Inflection AI built a supercomputer worth hundreds of millions of dollars powered by 22,000 NVIDIA H100 compute GPUs.
What? InflectionAI has relatively little brand recognition, do I not know something about them, are they just the first in line, or is nvidia just selling this many cards in general? I can only imagine all the typical ones like lambda, AWS, openai, apple, <insert large tech company here> are buying even more?
EDIT: Wait if the collateral is for a 2.3B USD loan - how many cards do they have?!
Or signs of an exponentially accelerating technological singularity
But their sales team or other execs who have incentives to keep sales prices inflated for as long as possible will fight against such a move.
There's also the fact that if you are not training LLM, you can get a better deal using some older hardware.
Also, the Reuters article says that they have a depreciation schedule built into the contact. Compute hardware can depreciate pretty quickly, if I remember correctly major tech companies have around 3 years planned for the depreciation.
Historically yea, though now I think it's being stretched to 5+ years as they see hardware last longer in production (but you're atiop correct, it's very quickly relative to a lot of other loan collateral, still a short term deal even if it's 7 years)
Personally I think the bigger risk is software innovations making CPU training (and/or inference) sufficiently viable that it's cheaper to train models on a commodity CPU cluster than on some proportionally expensive GPU cluster. I don't know enough about the space to say whether that's likely, but it seems like a low risk, since pretty much any parallel algorithm will always be faster on GPU than CPU - it's just a question of the marginal benefits and cost (e.g. maybe it takes more CPU to train same model in same time, but cost of CPU is so much lower that it's worth buying more of them).
But some value as long as computing power can be sold above running costs(power, cooling, etc.). Good question is when the newer model is so much more efficient it makes sense to replace them.
Worse the collateral side of the equation is currently in max AI hype bubble frenzy pricing while the loan is well what it says.
Very much feel like we're getting half the story...specifically the part that makes for good PR "Look at us we have lots of H100s and they're really valuable".