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Amazon Generative AI

Generative Artificial Intelligence or generative AI is a form of Artificial Intelligence that has ability to create various types of content  including conversations, stories, images videos and music.

Generative AI relies on large machine learning models known as foundation models, which are pre-trained on extensive data sets.

Foundation models have billions of Parameters and have experienced significant growth in size in recent years, with the largest models now exceeding 500 billion parameters.  Foundation models such as GPT 3.5 , bloom and stable diffusion are versatile and can perform a wide range of tasks across different domains and can perform a wide range of tasks across different domains. They can write blog posts, generate images, solve math problems, engage in dialogues, and answer questions based on documents.

Amazon provides several offering in the field of generative AI.  

Amazon Bedrock -- Streamlines generative AI by providing an accessible API for foundation models from AI 21 labs, Anthropic Stability AI, and Amazon.  Using Amazon Bedrock developers can efficiently build and scale generative AI-based applications, which opens the technology to a wider range of users. 

Machine Learning Hub -- Amazon Sage Maker and Amazon Sage Maker Jumpstart are valuable tools for customers seeking flexibility in machine learning model building. 

Amazon Sage Maker Jumpstart -- Amazon Sage Maker Jumpstart Serves as a machine learning hub, offering a wide range of open source foundation models for exploration and deployment including OpenAlame, Red Pajama, Moziak MPT 7B, FLT 5 UL2, GPTJ6B NO20B, and Bloom / BloomZ. 

Amazon Q Developer -- Amazon Q Developer uses a foundation model to enhance developer productivity by generating real-time code suggestions based on natural language comments and prior code in an integrated development environment or IDE.

Computing Infrastructure --  AWS provide infrastructure that prioritizes cost efficiency and performance.  AWS Trainium and AWS Inferentia chips were specifically developed to work providing the lowest cost options for machine learning tasks. 

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