Amazon SageMaker introduces a new generative AI inference optimization capability

The article announces the general availability of a new generative AI inference optimization capability on Amazon SageMaker. This capability allows customers to achieve up to 2x higher throughput and up to 50% cost reduction for large generative AI models like Llama 3, Mistral, and Mixtral.

Specifically, the article covers:

• Model optimization techniques like speculative decoding, quantization, and compilation that can be applied to generative AI models
• SageMaker's automation of provisioning hardware, deep learning frameworks, and libraries for the optimization process
• Support for custom speculative decoding solutions, compatibility with different precision types and model architectures, and efficient model loading and caching
• Integration with AWS SDK for Python, SageMaker Python SDK, and AWS CLI
• Availability across multiple AWS regions