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Daily Archives: April 16, 2023

AI text gen icon

ChatGPT and generative AI is having a significant impact on multiple industries and how people are learning. Generative AI is a subset of machine learning. Machine learning models power ChatGPT and include large learning models (LLMs) and multi-modal models that can include text, images, video, and audio.

Artificial Intelligence in action on a laptop
Photo by Matheus Bertelli: https://www.pexels.com/photo/woman-laptop-working-internet-16094040/

To begin, note that Artificial intelligence (AI) is nothing new with Amazon Web Services. Examples of AI/ML models include Alexa, Amazon’s Just Walk Out, and Amazon Prime. Tech Reformers uses AI/ML in its document processing solution. OpenAI released ChatGPT to the public in November 2022. Within two months, it reached 100 million monthly active users. Researchers and those working on Neural Linguistic Programming (NLP) projects use ChatGPT. In sum, AI can be used for different tasks and is well-trained on data from textbooks, articles, and websites.

What is Amazon Bedrock

Natural-language processing has been around for a while at AWS. Years ago, AWS introduced Amazon Comprehend, an NLP service that uses machine learning to find insights and connections in text. Just recently, Amazon launched Amazon Bedrock in its AI/ML services. Amazon Bedrock is an easy way to build and scale generative Artificial Intelligence applications with foundation models (FMs). Foundation models are AI neural networks that are trained on raw data and can be adapted to accomplish a wide range of tasks. Bedrock provides the flexibility to choose from a wide range of foundational models built by AI startups and Amazon itself. Therefore, this allows Bedrock customers to select the best model for their needs and goals.

In true cloud computing fashion, Bedrock is a serverless service. Accordingly, it can allow customers to get started quickly. They can customize foundation models with their own data, and integrate them into applications. In short, all this can be done without having to manage any of the infrastructure.

The foundation models that Bedrock supports are Jurassic-2, Claude, Stable Diffusion, and Amazon Titan. Data scientists train Amazon Titan FMs on large datasets. Ultimately, this makes them powerful, general-purpose models that can be used as-is or by customers privately with their own data.

Use cases for Amazon Bedrock are:

  • Text generation
  • Chatbots
  • Search
  • Text Summarization
  • Image generation
  • Personalization

Get started with key use cases quickly

Text Generation icon
Text generation

Create new pieces of original content, such as short stories, essays, social media posts, and webpage copy.

Chatbots icon

Build conversational interfaces such as chatbots and virtual assistants to enhance the user experience for your customers.

Search icon

Search, find, and synthesize information to answer questions from a large corpus of data.

Text Summarization icon
Text summarization

Get a summary of textual content, such as articles, blog posts, books, and documents, to get the gist without having to read the full content.

Image Generation icon
Image generation

Create realistic and artistic images of various subjects, environments, and scenes from language prompts.

Image Classification icon

Help customers find what they’re looking for with more relevant and contextual product recommendations than word matching.

To sign up for this new service, complete this short form at https://pages.awscloud.com/generative-AI-interest-learn.html.

Tasha Penwell photo. She write about cloud and Artificial Intelligence.

Tasha Penwell is an AWS Educator, Authorized Instructor, and a Certified Solutions Architect. She is also a subject matter expert (SME) in web development, cloud security, and cloud computing. As a speaker, she talks about AWS education and AR technologies.