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Ask HN: AWS vs. AZURE vs. G-CLOUD for an A.I/ML Type Application
Wanted to get HNs opinion - Who’s platform and stack do you like the best for AI applications?
- alexnewman 8y agoFor training I find wherever I can get the cheapest gpus for my training set, usually aws is the winner. But we operate in 3 clouds. For inference it’s complicated. A lot of that is cheaper to do on the right low priority/spot/preemptive machine. Tpus seem to be exceptional at operations like soft max. I wonder how well fpgas might be good at some ml applications you might be thinking of. It all depends honestly.
- martinpb 8y agoThis is one of my biggest concerns - The cost of gpu's with repeated training, etc. That's an interesting approach to use multiple clouds; I had not thought of that. So thank you for that insight. Cheers sir.
- abledon 8y agoAws is most straightforward with dL ami vm. Gcloud gives credits (300$) harder to set up tensorflow cuda env
- martinpb 8y agoI feel the same way re: GCloud...AWS/Azure seem the be the best route. Thanks abledon!
- redhale 8y agoThis knowledge is dated about a year, which is an eternity in this space, so take it with a grain of salt. I do not know anything about GCP, but between AWS and Azure, go with Azure if you are at all new to this space (or if you're just looking to get something up and running quickly to prove a concept). AWS takes the approach of giving you the building blocks which you then must assemble yourself. Azure gives you a silky-smooth GUI (ML Studio) with which you can have a model up and running in literally minutes. Of course you can also go lower-level in Azure if you want.
- martinpb 8y agoThnx redhale! Helpful insight!