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Comment by DaedalusII | Hacker News Reader

wall street analysts are starting to realise that software companies shouldnt trade on a P/E of 300.

DocuSign is currently valued at 30 times its annual earnings. Adobe is currently 16. Amazon is 28 -- has been as high as 50 recently. NVDA is 44.

Investors are basically starting to realise that enterprise are not going to subscribe to software like DocuSign for 50 years. They'll probably just move to odoo or zohosign or something and save a lot of money. So its probably a better bet to put that capital into something like Nvidia or Tesla or whatever. it also looks like the US Fed isn't going to cut rates, so capital is getting more expensive.

Of course, if you are a CEO its great to blame all this on AI and then tell your investors you are increasing AI in your business (see: salesforce whose stock price is down 42% in a year and is now trading at 25x earnings)

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> software companies shouldnt trade on a P/E of 300

You are playing pretty fast and loose with your definition of a "software company" when you include Amazon and NVIDIA in your list. Amazon is many things but it is not a "software company" and neither is "NVIDIA".

50% of amazon operating profit is from AWS. NVIDIA's GPUs aren't really that much better than AMD if it weren't for CUDA.

Software company is a pretty good description for both.

I’ve heard the same about Nvidia, quite a few times, but have never really understood it.

I don’t suppose you know a good “for dummies” explanation of why CUDA is such an insurmountable moat for them?

Like, what is it about that software that AMD can’t produce for their own hardware, or for a most important subset, with these $1T market stakes?

My understanding on this may be spotty (and I appreciate it if someone corrects me), but CUDA is not the software layer that allows you to use NVIDIA GPUs for AI processing?

AMD may develop their own software layer, but a lot of things already work on CUDA, and the job to port this to a different platform may be non-trivial (or even possible depending on the level of feature parity).

> I don’t suppose you know a good “for dummies” explanation of why CUDA is such an insurmountable moat for them?

Theoretically the moat isn’t insurmountable and AMD has made some inroads thanks to the open source community but in practice a generic CUDA layer requires a ton of R&D that AMD hasn’t been able to afford since the ATI acquisition. It’s been fighting for its existence for most of that time and just never had the money to invest in catching up to NVIDIA beyond the hardware. Even something as seemingly simple as porting the BLAS library to CUDA is a significant undertaking that has to validate numerical codes while dealing with floating point subtleties. The CPU versions of these libraries are so foundational and hard to get right that they’re still written in FORTRAN and haven’t changed much in decades. Everything built on top of those libraries then requires having customers who can help you test and profile real code in use. When people say that software isn’t a moat they’re talking about basic CRUD over a business domain where all it takes is a competent developer and someone with experience in the industry to replicate. CUDA is about as far from that as you can get in software without stepping on Mentor Graphics’ or Dassault’s toes.

There’s a second factor which is that hardware companies tend to have horrible software cultures, especially when silicon is the center of gravity. The hardware guys in leadership discount the value of software and that philosophy works itself down the hierarchy. In this respect NVIDIA is very much an outlier and it shows in CUDA. Their moat isn’t just the software but the organization that allowed it to flourish in a hardware company, which predates their success in AI (NVIDIA has worked with game developers for decades to optimize individual games).

Maybe nobody has reputably released non-fortran versions but they probably exist.

Lots of other versions exist including reputable ones like Intel’s MKL. The hard part isn’t reimplementing it, it’s validating the output across a massive corpus of scientific work.

BLAS is an example though, it’s the tip of an iceberg.

the first problem is a whole generation of people learned to code ai applications by fiddling around with the gpu in their gaming pc 10 years ago. so an entire generation of talent grew up with cuda

the second problem is that so many libraries and existing software is cuda only. even some obscure hardware stuff. i discovered the hard way that some AMD thinkpads dont support thunderbolt transfer speeds on their usb-c ports, whereas nvidia ones do

the third problem is that the cost to develop a cuda equivalent is so great that its cheaper for companies like google to make TPU and amazon to make Trainium. its literally cheaper to make an entire new chipset than it is to fix AMd. i dont see companies like apple/amzn/goog etc fixing AMDs chips

>its literally cheaper to make an entire new chipset than it is to fix AMd

Is it? Or does AMD expect to make a profit and it's cheaper to make your own chips at cost?

i mean its cheaper from an enterprise customer perspective. if a company is training an LLM, writing their training programs to use AMDs hardware instead of just using CUDA is so expensive and time consuming that it is cheaper to pay four times the price and use nvidia hardware. in this space its important to move fast, although that economic will shift over time

which is why nvidia hardware trades at a 4x premium to AMD

its not necessarily cheaper to make chips at cost either. nobody is making them, only designing them. so first you have to design your new chip, then you have to get a minimum order in with the chip fab so big it competes on unit economics, and then finally you have to get your dev team to write a CUDA equivalent software that is a problem so hard its only really been solved by apple, google, intel, and nvidia

only companies with big fab orders can get priority too.. if a company did all of the above and was ready to go, they probably wouldn't get fab capacity until 2030

CUDA is a GPGPU software layer that is very mature, and integrates with C,C++, Python, Fortran very well. AMD just never really got the same quality of GPGPU software in the last 20 years. 99% of scientific computing that uses GPUs (which is a lot since they are so much faster than CPUs for linear algebra) have gone to Nvidia because of this. All of the big AI libraries (Tensor Flow, PyTorch) basically ended up writing around CUDA, so they just didn't write things for AMD. Plus if you go and look at a job for signal processing or whatever at say Lockheed Martin or Raytheon, they specific CUDA.

AWS is not a software company either, it is a capital intensive computing infrastructure company. NVIDIA as well is a capital intensive computer hardware company.

Just because software plays a role, doesn't make them software companies. It is like saying all companies are "electrical companies" because they require electricity to operate.

Is a seal a sea creature or a land dweller? Well it eats at sea.

Argh, we first ignored the fact that most of its income comes from being the lead e-commerce retailer to just focus on AWS and then we need to discount the fact that the majority of AWS is CapEx towards hardware / datacenter (expected CapEx this coming year is $200B), to just leave the software. Whatever.

One thing is for sure: if the seal builds and manages hundreds of billions of dollars worth of computer infrastructure across seven continents, it isn’t just a software company.

youre right, i should say tech company. but at least my flawed epistemology reveals my humanity

although one could argue disingenuously that nvda is a software company because the product they ultimately manufacture is a bunch of blueprints they email to tsmc or samsung who then actually make the chips

> but at least my flawed epistemology reveals my humanity

Plenty of AIs have flawed epistemology. But nice try.

I actually don’t even think it’s a IaaS company. I mean it is, but Amazon seems to always excel at operations: whether it’s organizing a retail business, operating a logistics company, or managing a hyperscaler, it just seems like its real secret sauce is running ops.

(Which makes sense because all of their end user products suck)

I've always found it confusing how run of the mill SaaS trades at multiples assuming decades of doing business. The amount of change in software businesses has been massive and being able to run a successful software business even for 15 years from 2010-2025 requires a great deal of strategy and foresight and more likely than not that's not enough. Considering how these dynamics have been accelerating as technology accelerates it just seemed so off that the market was landing on a 20-30x multiples for software businesses that don't have much moat (e.g. swathes of B2B CRUD apps).

Investor analyst looks at earnings growth and determines Customer Acquisition Cost (CAC) and Customer Acquisition Cost Payback Period (CACPP). They determine that ABC Software Corporation has no marginal manufacturing cost because it makes software that it sells online, so if it invested 90% of its profit margin into marketing it could grow its ARR by 140% a year. Then they extrapolate that for 30 years and say ok the NPV of 30 years of 140% ARR on current CAC, etc etc...

If everyone in the industry benchmarks on more or less the same multiples, it becomes a good idea to buy any b2b crud saas trading at 10x earnings because if the big boys see it they'll probably bid it up to 30x

the other classic move is to take a business which really isn't even a new technology, like revolut, and call it a tech business. now suddenly a bank can trade on a 50x earnings multiple instead of 15x like say a bank. many such cases~

Hes not admitting his crimes, hes bragging!

Why would you put more money into Nvidia or Tesla right now? Don't you think they are priced in already?

we are only examining the valuation metrics here, not comparing the companies themselves as investments.

you could decide that if you are a very large company, building software internally to replace a SaaS product is a path forward. Or replacing a premium software like DocuSign with a cheap one like Zoho sign. or just building your own proprietary electronic signature app

It is however impractical for big company to start manufacturing cars or designing competitive GPUs

so the earnings of tesla and nvidia is theoretically more 'stable' than a software application company like salesforce, adobe, etc.

this analysis ignores both the size of the company, and what it does, or whether or not any one of them is a good investment

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