As someone who works at big tech and spends countless hours in meetings hoping to get some small feature coordinated for deployment across two teams, I can't imagine the amount of meetings and 6-pagers that were involved in running these models on bedrock's hardware.
Remember that models on different inference platforms might not necessarily give exactly the same results, adding another axis of non-determinism to development. Things like quantization, custom model serving silicon, batching, or other inference optimizations might mean a model from the original provider performs differently from the hosted one :/
This paper isn't the exact same scenario, since it's an auditable open weight llama model, but shows the symptoms of this: https://arxiv.org/pdf/2410.20247
Availability through Bedrock has been a major driver in use of Anthropic in my org. And I am betting there is actual margin in it as well.
I wonder if this is directly linked to the split up with Microsoft. Just from my anecdata, OpenAI is getting completely ignored in serious enterprise deployments because what they offer on Azure sucks and there is no other corporate friendly way to get it. They probably saw themselves getting destroyed in enterprise and realised it was existential to be able to compete with Anthropic on AWS.
The enterprise sales motion here is interesting. A lot of regulated industries (finance, healthcare) have existing AWS contracts with data residency commitments baked in. OpenAI on Bedrock basically lets those orgs skip the separate DPA negotiation with OpenAI. Could be a bigger unlock than it looks on paper.
This would be a nice compliance win. One less sub-processor and all our data is already on AWS so less worrying about sending it off somewhere else
OpenAI is tailgating Anthropic apparently.
Great, I can now buy openAI through AWS with an interface that is totally incompatible with all my tools (unless AWS have finally given up and just made bedrock useful by adopting openAPI finally)
OpenAI marching towards its future as a dumb pipe.
The market might be increasingly hard on AI startups in general as enterprises adopt providers like Amazon Bedrock and refuse to sign other deals.
This doesn't mean you have the raw model weights, right? That's still entirely hidden / opaque?
You can just run "air gapped" inference?
Is this only of interest to enterprise customers already on AWS (who want "air gapped" behavior)? Is there any other use case for this?
This will be more expensive than calling OpenAI directly, right?
Now they are ruining amazon too. It's fascinating to see.
AI is kind of like the ultimate corporation drug. They are all on it. And can't get rid of it - ever again.
Claude got a looooot more buy in with a lot of privacy-concerned orgs I work with because they could access it through their "trusted" intermediate Amazon. OpenAI has been banned and is not trusted. I'm not sure that I agree with these orgs' legal teams' assessments, but they definitely read the terms of service far closer than I did.
We will see if this changes the equation, but it feels like OpenAI is pretty far behind and playing catch up on all fronts. Though to be honest, "pretty far behind" is like 2-8 weeks in the AI world, so it may not matter a ton, it's mostly perception. And for me and my information bubble, perception of OpenAI is rock-bottom due to Sam Altman. From appearing unethical to appearing unhinged with demands from fabs and everything else, I'm not a fan.