What is the current AWS portfolio on GenAI ?

Generative AI?needs massive computing power and large datasets, which makes the public cloud an ideal platform choice. From offering the foundation models as a service to training and fine-tuning generative AI models, public cloud providers are in a race to attract the developer community and the enterprise.

Over the race to attract Developer Communities and Enterprises, Amazon Web Services: Betting Big on Amazon Bedrock and Amazon Titan

AWS is late to the generative AI party but they are quickly catching up. When it comes to generative AI, there are three key services in which AWS is investing —?Amazon Sagemaker JumpStart,?Amazon Bedrock, and?Amazon Titan.

Amazon SageMaker JumpStart is an environment to access, customize, and deploy ML models. AWS recently added support for foundation models, enabling customers to consume and fine-tune some of the most popular open-source models. Through the partnership with?Hugging Face, AWS made it easy to perform inference or fine-tune an existing model from a catalog of curated open-source models. This is a quick approach to bringing generative AI capabilities to SageMaker.

AWS revealed Amazon Bedrock as a serverless environment or platform to consume foundation models through an API. Though AWS hasn’t shared many details, it does look like a competitive offering compared to Azure OpenAI. Customers would be able to access secure endpoints that are exposed through the private subnet of the VPC.

Amazon has partnered with GenAI startups such as AI21Labs, Anthropic, and Stability.ai to offer text and image-based foundation models through the Amazon Bedrock API.

Amazon Titan is a collection of home-grown foundation models built by its own researchers and internal teams. Titan is expected to bring some of the models that power services such as Alexa, CodeWhisperer, Polly, Rekognition, and other AI services.

AWS to launch commercial foundation models for code completion, word completion, chat completion, embeddings, translation, and image generation. These models would be exposed through Amazon Bedrock for consumption and fine-tuning.

Amazon may also launch a dedicated vector database as a service under the Amazon RDS or Aurora family of products. It supports?pgvector, a PostgreSQL extension for performing similarity searches on word embeddings available through Amazon RDS.

The table below summarizes the current state of GenAI services offered by the key public cloud providers: