The pressure cuff + stethoscope combo is called a sphygmomanometer. It's a pretty fascinating piece of technology: A heartbeat is only audible in the earpiece when the cuff is compressing between someone's systolic and diastolic pressure.
To use it, you get the cuff pressure high enough that you stop hearing a heartbeat in the earpiece. Start releasing pressure slowly. As it comes down, take note of where on the dial you start hearing the heartbeat. That's systolic pressure. Keep listening, and take note of where you stop hearing the heartbeat. That's diastolic pressure.
And if you use a mercury sphygmomanometer, you can actually see those pulses appear and then disappear. (It's harder to see them with a gauge-based one.)
> If there is truly a divorce between Europe and the US such that relying OpenAI or Anthropic is not an option, neither will relying on Nvidia and likely the thousands of smaller hardware and software suppliers that make Mistral work.
Well, you're pointing out a dissonance in a common AI (stock) booster argument: What if the hardware has lasting power?
If it does, then a company like Mistral can buy their capacity once from Nvidia (as in, once for each unit of capacity), then use it for a sustainable amount of time. No one forces them to scale beyond what's useful to the company and a mature user base. Provider dependence fades over time. That's a problem with Nvidia's current valuation.
If hardware doesn't last over that time, then the amount of cash invested in data center hardware can't really be reconciled with the expected revenue of running them at scale, and these projects are bound to run at a deficit over too long for them to be sustainable. That's a problem with Nvidia's valuation.
With independence as a target, Mistral can pretty safely bet on the former scenario, and then prepare for a future with either a mature market of diversified hardware providers, or innovations in quality and capacity for hardware they already have.
How would that work? What it means for the US AI bubble to burst is that tremendous amounts of inference capacity become open for pennies on the dollar. I don't see how Mistral is or could be sheltered from that.
Btw, this makes a great argument for workers' rights - if you have a company who owns datacenters - well, you can't fire your GPUs to make your Q2 look better
SLAs that are valuable to their clients, guarantees and mechanisms to protect them from data exfiltration, and generally long-term contracts with cash-stable orgs like they're currently doing.
So long as they're sufficiently liquid at the right time, they don't really need to shelter more. They need to plan for a fire sale on the bulk of their operating expenses.
It's extremely hard to plan for a fire sale on the bulk of your operating expenses when all of your customers can see the fire sale happening and know they're now paying you way too much. That's the whole intuition of a general "US AI bubble"; if OpenAI filed for bankruptcy tomorrow, most people expect that would be a crisis for Anthropic and Gemini rather than a windfall opportunity to pick up their compute for cheap.
The crash would come from being unable to fulfill financial engagements when total real income + funding fails to keep up with spending, and does it enough that the valuation mirage starts to fade.
What that reveals is the loaded cost of inference being more expensive than they've been showing, not cheaper. The crash would be the end of subsidized costs to users, not the revelation that it's a high-margin operation.
Selling compute/inference at more of a loss will probably not fly in the context of bankruptcy manoeuvers. They will need to shed spending engagements instead. I imagine Mistral would rather buy out some of their Nvidia purchase agreements for a discount if they want to build additional capacity at that time. I also don't think they'd be interested in US datacenters at all. If they want them they can get that in Canada, with a better ally and less political + financial risks, which is kind of the Mistral segment already.
> tremendous amounts of inference capacity become open for pennies on the dollar.
They can't be operated for pennies on the dollar, though. The likely current status is that these products are subsidized to disregard model cost, and part of the operating cost.
If the bubble bursts, inference that can't be made profitable when factoring in operating costs will be scraped, not sold for pennies.
I don't necessarily agree that's likely, but is it even the case that Mistral is more expensive than GPT or Claude? My understanding is that it's cheaper, which means it would fare worse in the scenario you're describing, unless they've perfectly calibrated the quality-cost tradeoff better than any American company.
To use it, you get the cuff pressure high enough that you stop hearing a heartbeat in the earpiece. Start releasing pressure slowly. As it comes down, take note of where on the dial you start hearing the heartbeat. That's systolic pressure. Keep listening, and take note of where you stop hearing the heartbeat. That's diastolic pressure.
Using one feels kind of magic.
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