Types of Foundational Models

(The content in this blog post is pulled from various websites and is not my own. The intent is to consolidate the concepts, examples, services and related content and make it easy for me (and other interested readers) to brush up my skills, periodically. If the original authors have any challenge, please reach out to me and I will take down the content.)

There are currently three main foundation model types in the market.

• Text-to-text: These natural language processing models can summarize text, extract information, respond to questions, and create content such as blogs or product descriptions. An example is sentence auto-completion.
  
• Text-to-embeddings: These FMs compare user search bar input with index data and connect the dots between the two. The result is more accurate and relevant results.
  
• Multimodal: These emerging foundation models can generate images based on a user's natural language text input.

AWS solution

1. AWS has a wide selection of FMs built by Amazon and top AI startups, including AI21 Labs, Anthropic, and Stability AI

2. Using Amazon Bedrock, customers can fine tune models for a particular task without having to annotate large volumes of data (as few as 20 examples is enough). No customer data is used to train the underlying models. All data is encrypted and stays within the customer's virtual private cloud (VPC).

3. AWS has support for  AWS designed ML chips and NVIDIA GPUs. 

4. There is no need to send the data to the model but rather bring the model to the data using integrations and services such as Amazon SageMaker and S3.

5. With generative AI built in, services such as Amazon CodeWhisperer, an AI coding companion, can help customers improve productivity. 

Summary:

1. Amazon Bedrock - easiest way to build and scale generative AI apps with FMs.

2. AWS Inferentia and AWS Trainium Amazon EC2 instances for training and inference in the cloud.

3. Amazon CodeWhisperer is a buit in generative AI coding companion that helps customers build applications faster and more securely.

4. Amazon SageMaker for access and fine tuning of a wide selection of FMs.

Amazon Bedrock

Fully managed service that makes FMs from leading AI startups and Amazon available through an API.

Customers can choose from a wide range of foundation models to find the model that is best suited for their use case.

Easiest way to build and scale generative AI applications with FMs.

Titan Text = Automate NLP tasks such as summarization and text generation

Titan Embeddings = Enhance search accuracy and improve 

References - AWS Skill Builder