From the course: Generative AI and Large Language Models on AWS

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Development environment for AI

Development environment for AI - Amazon Web Services (AWS) Tutorial

From the course: Generative AI and Large Language Models on AWS

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Development environment for AI

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- [Instructor] There are many different options for development environments for AI development on AWS. Let's talk through some of the workflows here. First up, we have AWS CodeCatalyst, a CPU-based, a cloud-based development environment. And what's interesting about CodeCatalyst is that you can pick from instances that are preconfigured with AWS options, like Amazon Linux 2, for example. All the tools are there. And also, it works with a local IDE as well. So you can interface with it from IntelliJ, for example, and talk to that particular cloud-based environment, and even have a whole series of specialized environments depending on what problem you're solving. So this is helpful in a AI pipeline, because you can build, let's say, serverless pipelines in Rust with Step Functions and Lambdas. And this could be a great place to rapidly develop solutions. Now, there's actually even more interesting emerging cloud environments, and these new ones have GPU embedded inside. So one of them…

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