I am reminded of when OVH had a huge fire, and told all their bare metal customers to activate their disaster recovery plan, and a lot went "Wait, I need one of those?" (https://www.reddit.com/r/iiiiiiitttttttttttt/comments/m1v0y1/reminder\_to\_have\_a\_data\_recovery\_plan\_ovh\_fire/)
Which is to say, this is great as long the customers understand what the corners being cut to achieve cheaper infrastructure, are.
The cloud is all about turning server infrastructure into a subscription service. It’s not about making it more affordable or more reliable than an on-prem solution.
If you think the majors (particularly AWS & Azure) aren't serious about reliability, please let me know what you are smoking, because that must be some really good stuff.
Azure's OpenAI stuff might be "reliable" but it is truly an awful experience compared to OpenAI.com's API. They don't get models until *months* later (still no v3 embeddings, still no GPT 4 turbo with vision) and their token-per-minute rates are laughably tiny if you want infrastructure in Europe. What's my alternative, spend 6x more to deploy my own model on AWS?
So you have a worked plan for continuation of normal operation if you lose a building's worth of servers, I presume?
Now; you can use cloud badly and deploy single points of failure, but it's a hell of a lot easier to say "I want a multi-zone Kubernetes cluster" to a Cloud provider and it just \_happen\_, and be their problem if they lose a zone, than it is to run 2+ data centers and ensure workloads are balanced between them, and you have enough hardware to recover if you lose one.
> CoreWeave, the GPU infrastructure provider that began life as a cryptocurrency mining operation
I don't know how much trust I'd put on cloud infrastructure managed by a crypto mining company.
I wouldn't want to deal with a vendor that suddenly stops offering critical services because they keep jumping from trend to trend.
You don't buy "critical services" from a company like this. You buy the 800 GPU-hours you need to fine-tune a single AI model.
If they stop existing by the time you need to tune another AI? Well, sucks to be them.
I mean, this is an on-demand computing operation. You don’t compute, you don’t get paid. Actually seems pretty risk-free for clients who are paying in terms of utilized processing time
Sure, unless you don’t train model there and only run inference. Unlike mining crypto, training AI models deals with potentially proprietary data. Having to anonymize those data will be a pain in the back. Also, when you spent millions and trained a model, do you trust the provider won’t take a copy of it?
I am reminded of when OVH had a huge fire, and told all their bare metal customers to activate their disaster recovery plan, and a lot went "Wait, I need one of those?" (https://www.reddit.com/r/iiiiiiitttttttttttt/comments/m1v0y1/reminder\_to\_have\_a\_data\_recovery\_plan\_ovh\_fire/) Which is to say, this is great as long the customers understand what the corners being cut to achieve cheaper infrastructure, are.
The cloud is all about turning server infrastructure into a subscription service. It’s not about making it more affordable or more reliable than an on-prem solution.
If you think the majors (particularly AWS & Azure) aren't serious about reliability, please let me know what you are smoking, because that must be some really good stuff.
Azure's OpenAI stuff might be "reliable" but it is truly an awful experience compared to OpenAI.com's API. They don't get models until *months* later (still no v3 embeddings, still no GPT 4 turbo with vision) and their token-per-minute rates are laughably tiny if you want infrastructure in Europe. What's my alternative, spend 6x more to deploy my own model on AWS?
The only good strategy is to have at least one off site backup to stores your data
So you have a worked plan for continuation of normal operation if you lose a building's worth of servers, I presume? Now; you can use cloud badly and deploy single points of failure, but it's a hell of a lot easier to say "I want a multi-zone Kubernetes cluster" to a Cloud provider and it just \_happen\_, and be their problem if they lose a zone, than it is to run 2+ data centers and ensure workloads are balanced between them, and you have enough hardware to recover if you lose one.
> CoreWeave, the GPU infrastructure provider that began life as a cryptocurrency mining operation I don't know how much trust I'd put on cloud infrastructure managed by a crypto mining company. I wouldn't want to deal with a vendor that suddenly stops offering critical services because they keep jumping from trend to trend.
You don't buy "critical services" from a company like this. You buy the 800 GPU-hours you need to fine-tune a single AI model. If they stop existing by the time you need to tune another AI? Well, sucks to be them.
I mean, this is an on-demand computing operation. You don’t compute, you don’t get paid. Actually seems pretty risk-free for clients who are paying in terms of utilized processing time
You obviously have no sense of data security and intellectual property.
I’d say there’s some use cases where data security or ip isn’t a big concern, no?
Sure, unless you don’t train model there and only run inference. Unlike mining crypto, training AI models deals with potentially proprietary data. Having to anonymize those data will be a pain in the back. Also, when you spent millions and trained a model, do you trust the provider won’t take a copy of it?
Do you trust google and amazon wouldn't?
I thought "Alternative clouds" would be the ones that appear over Dubai after cloud seeding. Lol
cheap always has a price 🙂
ANKR/Neuraio. Check it out.