Acting on their belief that model Fine-Tuning is the vehicle for customers to realize the power of their data and gain market differentiation, AWS announced that Bedrock now also supports Fine-Tuning, which lets you make a copy of an existing model and train it on data for your specific use case. Your application then uses this new model and is never shared with AWS. Many models from AWS, Meta, Cohere, and other bedrock-hosted third-party models are now entirely fine-tunable, with Anthropic’s Claude fine-tuning coming soon. Meanwhile, customers interested in fine-tuning the Claude model can work with AWS experts via the Custom Model Program to accomplish this goal.
AWS introduced continuous pre-training for dealing with highly volatile data, ensuring your models' relevancy to your data
As one uses Bedrock models, evaluating how they are doing is important. Bedrock now supports Model Evaluation, which lets designers evaluate a model and provide feedback.
Q and New Vector Support
Vectors are the key to LLMs, so vector support is critical to their evolution. Today, AWS expanded support for vectors to RDS Aurora, DynamoDB, DocumentDB, and OpenSearch Serverless, enabling customers to store source and vector data in the same database and eliminating the learning curve of learning new databases and APIs.
They also said that MemoryDB for Redis now supports vectors. This gives AWS-backed GenAI applications an incredible single-digit millisecond latency with 99% information recall accuracy, providing unparalleled performance in vector databases.
Khobaib Zaamout
Brian Tarbox
