Claude 2.1 delivers key capabilities for enterprises, such as an industry-leading 200,000 token context window (2x the context of Claude 2.0), reduced rates of hallucination, improved accuracy over long documents, system prompts, and a beta tool use feature for function calling and workflow orchestration.
Llama 2 models are next generation large language models (LLMs) provided by Meta.
Amazon Titan Multimodal Embeddings helps customers power more accurate and contextually relevant multimodal search, recommendation, and personalization experiences for end users. You can now access the Amazon Titan Multimodal Embeddings foundation model in Amazon Bedrock.
Amazon Titan Text Express and Amazon Titan Text Lite are large language models (LLMs) that help customers improve productivity and efficiency for an extensive range of text-related tasks, and offer price and performance options that are optimized for your needs.
Amazon Titan Image Generator enables content creators with rapid ideation and iteration resulting in high efficiency image generation.
SageMaker HyperPod removes the undifferentiated heavy lifting involved in building and optimizing ML infrastructure for training FMs.
Vector engine for OpenSearch Serverless is a simple, scalable, and high-performing vector database which makes it easier for developers to build machine learning (ML)–augmented search experiences and generative artificial intelligence (AI) applications without having to manage the underlying vector database infrastructure.
With vector search for MemoryDB, you can develop real-time machine learning (ML) and generative AI applications with the highest performance demands using the popular, open-source Redis API.
Amazon OpenSearch Service zero-ETL integration with Amazon S3, a new way for customers to query operational logs in Amazon S3 and S3-based data lakes without needing to switch between tools to analyze operational data.
Amazon Redshift introduces Amazon Q generative SQL in Amazon Redshift Query Editor, an out-of-the-box web-based SQL editor for Redshift, to simplify query authoring and increase your productivity by allowing you to express queries in natural language and receive SQL code recommendations. Furthermore, it allows you to get insights faster without extensive knowledge of your organization’s complex database metadata.
Model Evaluation on Amazon Bedrock allows you to evaluate, compare, and select the best foundation models for your use case. Amazon Bedrock offers a choice of automatic evaluation and human evaluation.
The full keynote is available at: https://www.youtube.com/watch?v=8clH7cbnIQw
Eyal Estrin is a cloud and information security architect, the owner of the blog Security & Cloud 24/7 and the author of the book Cloud Security Handbook, with more than 20 years in the IT industry.
Eyal is an AWS Community Builder since 2020.
You can connect with him on Twitter
Opinions are his own and not the views of his employer.