Different models have different strengths and weaknesses, especially here in the early days when models and their capabilities progress several times per year. The apps, programs, and systems based on models need to know how to exploit their specific strengths and weaknesses. So they are not infinitely interchangeable. Over time some of that differentiation will erode, but it will probably take years.

AWS having customers using its own model probably improves AWS's margins, but having multiple models available (e.g. Anthropic's) improves their ability to capture market share. To date, AWS's efforts (e.g. Q, CodeWhisperer) have not met with universal praise. So for at least for the present, it makes sense to bring customers to AWS to "do AI" whether they're using AWS's models or someone else's.

> Different models have different strengths and weaknesses

I would add different errors as well. Here are two examples where GPT-4o and Claude 3.5 Sonnet cannot tell that "GitHub" is spelled like "GitHub".

GPT-4o: https://app.gitsense.com/?doc=6c9bada92&model=GPT-4o&samples...

Claude 3.5 Sonnet: https://app.gitsense.com/?doc=905f4a9af74c25f&model=Claude+3...

I don't think there will be one model that will rule them all, unless there is a breakthrough. If things continue on the same path, I think AWS, Microsoft and Google will be the last ones standing, since they can provide models from all the major LLM players.

If you play all sides, you’ll always come on top.

Yeah Copilot includes Claude now.

This is Amazon's core e-commerce business model but for AI. You sell everybody else's stuff and also offer an Amazon Basics version.

Customers want choices. They just sell all models.

Commoditizing complements

I can only guess.

1. A company the size of Amazon has enough resources and unique internal data no one else has access to that it makes sense for them to build their own models. Even if it's only for internal use

2. Amazon cannot beat Anthropic at this game. They are far a head of them in terms of performance and adoption. Building these models in-house doesn't mean it's a bad idea to also invest in Anthropic

Also not putting all of your eggs in one basket.

Not sure if this was the goal, but it does work well from a product perspective that Nova is a super-cheap model that is comparable to everything BUT Claude.

Why does RDS support Oracle and MS SQL databases? Because customers want them.

Bedrock might be the best way to consume sonnet 3.5. So people setup and use bedrock while might try other hosted models like Nova.

On the other hand, not many are going to onboard bedrock if they don't have SOTA models in the offering.