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If you've used AI coding models in a large corporate setting, you'll know that a lot of big corporate deployments basically require using AWS Bedrock for two simple reasons:

1. Large companies tend to already have an existing relationship with AWS, which makes things way easier to go through vs. setting up a new vendor relationship 2. Large companies tend to have strong internal requirements about making sure that internal data stays under company control. With AWS Bedrock, you can be a lot more confident that what you're feeding into the models is not going to end up in someone's training set somewhere. For where I work, this requirement is a dealbreaker for going directly through OpenAI's API instead of going through AWS Bedrock.

To go a step further, the reason it's often impossible to add a new vendor if that you've signed a bunch of contracts with your customers saying you're not going to send their data to other vendors in all sorts of various flavors.
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3. from my opportunity - For many (not all) LLMs, Bedrock gives you control over which country the data stays in. You have no control over that with the Claude API, for example. We do not work in the US and have strong requirements for the data to stay in our country, which Bedrock gives us control over.
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A very interesting comment.

Curious to understand how AI will continue to grow if this is the trend. Assuming most valuable data is behind such firewalls. And whatever is public has been harvested, trained on top of whatever has been acquired illegally (this is a grey area).

Will it become a closed ecosystem without outside input?!

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How is one certain bedrock data isn’t being shuttled to external providers?
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