AI cloud startup TensorWave bets AMD can beat Nvidia
theregister.com
theregister.com
It could be great for everyone else that TensorWave is willing to invest in it and hopefully help drive improvements in the software.
https://www.techpowerup.com/318652/financial-analyst-outs-am...
The best I could see is developing a service platform that frictionlessly and more efficiently runs CUDA workloads on AMD using a proprietary translation. Not a bad bet, IMO.
In my company 90% of computers have a Nvidia card so you can get started with CUDA immediately to start data aggregation and planning your AI training and infercing while waiting for deployment. Totally forget that approach with AMD.
Nvidia also assist larger customers with DGX cloud access through their large deployed super computers.
Nvidia's AI workbench helps a lot here as you can easily transfer your applications from local RTX cards to on-prem or cloud data centers.
MI300x was released in Dec of last year, only months ago. It has 192gb, while H100's only have 80.
There are at least 4 companies now providing bare metal cloud access to these cards. +2 more are hyperscalers (Oracle and MSFT).
It is critically important for the long term safety of AI that we are not dependent on a single source for all of the hardware and software related to AI.
It takes a lot of effort to course correct a large ship, give it some time.
A 15k AMD part vs a 60k nvidia part. For 100 Nvidia GPUs, you can buy 200 AMD GPUs and at least 2-3 engineers for 3 years at 300k to fix the specific library for that GPU. If you can make that work for a lower level library right now, then it makes to sustain it in future.
Hmmm. This seems like an odd risk for the lenders. Asymmetrical with little upside and security depends on continuing demand for GPUs. When the AI tide goes out who will be left with the losses.
Upside and risk are usually priced into the loan as the interest rate
I see this as super risky as well. I'm taking a totally different approach with my business. We are only growing with customer demand. First off, we are getting a decent number of GPUs to rent, which should cover our initial capacity needs. Then as we grow, we will push revenue + further investment back into more purchase orders. We can also order and deploy compute on a very short timeframe, so if we have a customer that wants a bunch of compute that we don't have today, we will get it online relatively quickly. Grandiose claims of 20k GPUs by the end of the year, almost never works out the way you want it to.
Disclosure: competitor to TW.
CoreWeave is doing the same stuff but with Nvidia. Also using collateral. But CoreWeave did it last year when H100 was way more valuable for collateral than it is today. And CoreWeave has actually been backed up by Nvidia and Microsoft in some funding rounds.
For Nvidia HW there are like 10x as many AI startups doing what TensorWave is doing. TensorWave is going a more risky way to go with AMD instead of Nvidia. Being among few startups might give them a large benefit but it also depends a lot on AMD support in the SW field. I wouldn't bet on that, especially not with AMD HW as collateral.