Building your own deep learning computer is 10x cheaper than AWS

There are two distinct problems with that:

One is that AWS (and Azure and Google) are taking advantage of their brand recognition and are pricing their services extremely high compared to their competition. For some that is worth it as they need services they don't get elsewhere, but for a lot of people there are far cheaper cloud services out there. Sometimes even hybrid solutions (e.g. a particular problem with AWS are the absolutely insane bandwidth prices - if you "need" to store your data on S3 because they're the only ones you trust for durability or because it fits in with other parts of your workflow - but you access most objects regularly enough from outside AWS that bandwidth prices are a high part of your cost, for example, it can often pay to rent servers somewhere like Hetzner just to act as caches)

The other problem is that while it looks straightforward, as much as we might like to think so, servers are not as much of a commodity as we'd like to think. Components are.

The really big savings in running your own comes when you measure how much RAM you need and what CPU you need, and whether or not disk IO is an issue, and configure servers that fit your use better. If the cloud providers have instances that fit your needs, awesome, you can get a decent price (if you shop around). If they don't, you can easily end up paying a lot for components in your instances that you don't need.

When you don't know what you need, it might be ok to pay that premium, but as soon as you know what you need, there are many cases where buying your own allows you a degree of specialisation that does not pay for the cloud providers because it's better to provide a smaller range where they can get economy of scale. I've seen cases where e.g. being able to shove enough RAM in a server cut costs by 90% or more vs. splitting the load over multiple lower RAM cloud instances.

I'm not saying it will stay this way forever - there are certainly regularly more and more combinations that you can find decently priced cloud instances for - but there are still tons of cases where building your own (or having someone configure one for you) is so much cheaper that it's nearly crazy not to.

I used to manage hardware in several datacentres, and I'd usually visit the data centres a couple of times a year. Other than that we used a couple of hours of "remote hands" services from the datacentre operator. Overall our hosting costs were about 30% of what the same capacity would have cost on AWS. Once a year I'd get a "why aren't we using AWS" e-mail from my boss, update our costing spreadsheets and tell him I'd happily move if he was ok with the costs, as it would have been more convenient for me personally, and every year the gap came out just too ridiculously huge to justify.

In the end we started migrating to Hetzner, as they finally got servers that got close enough to be worth offloading that work to someone else. Notably Hetzner reached cost parity for us; AWS was still just as ridiculously overpriced.

There are certainly scenarios where using AWS is worth it for the convenience or functionality. I use AWS for my current work for the convenience, for example. And AWS can often be cheaper than buying hardware. But I've never seen a case where AWS was the cheapest option, or even one of the cheapest, even when factoring in everything, unless you can use the free tier.

AWS is great if you can justify the cost, though.

Curious of the MTBF (mean time between failure) rate of a GefForce/Titan series GPU under continuous utilization in datacenter conditions vs a desktop computer with intermittent usage. I don't want to believe Nvidia is just out to stiff cloud providers. Maybe it's to protect themselves from warranty abuse?

But not commercially viable due to https://en.wikipedia.org/wiki/Economies_of_scale

Exactly. I recently had a discussion on the costs of an RDS setup on AWS. Yes, renting a dedicated server or buying a server and setting up replicated MySQL is much cheaper than the montly cost of two RDS instances. Until you add the labour cost of setting up, maintaining and monitoring.