ad
ad
Topview AI logo

AWS re:Invent 2023 - Build your first generative AI application with Amazon Bedrock (AIM218)

Science & Technology


Introduction

Overview

In this breakout session at AWS re:Invent 2023, the senior AIML specialist solutions architect at AWS, Sherid Deing, along with principal product manager Cab Ki, discuss building generative AI applications with Amazon Bedrock. They provide an introduction to generative AI, a walkthrough of Amazon Bedrock, and share customer stories and use cases. The session concludes with guidance on how to get started on the generative AI journey on AWS.

Generative AI Fundamentals

Generative AI is an AI technology that can create new, original content similar to content generated by humans. It utilizes foundation models, large neural networks trained on massive amounts of data, to perform tasks like text summarization, question answering, and image generation. The models in generative AI are more advanced than traditional machine learning models and can map complicated inputs to complicated outputs.

Amazon's Generative AI Journey

Amazon has been working on artificial intelligence and machine learning for over 20 years, incorporating generative AI into various aspects of its business. AWS plays a key role in democratizing machine learning and making it accessible to customers of all sizes and industries. With the launch of Amazon Bedrock, AWS offers a fully managed service that combines high-performing foundation models with comprehensive capabilities for building generative AI applications.

Challenges in Building Generative AI Applications

Customers often face challenges when using foundation models, such as the need for customization, data privacy and security, and complex systems integration. Amazon Bedrock addresses these challenges by providing a range of foundation models, offering customization options through techniques like fine-tuning and retrieval augmented generation (RAG), and simplifying application integration through agents. Bedrock ensures data security and privacy, supports compliance requirements, and provides monitoring and logging capabilities for governance and auditability.

Use Cases and Customer Stories

Generative AI can be applied across various industries and business functions. Use cases include improving customer experience through chatbots and virtual agents, boosting employee productivity with conversational search and content creation, powering creative content production, and enhancing business operations with intelligent document processing and quality control. Examples of companies using Amazon Bedrock include Lonely Planet, NatWest Group, and Salesforce.

Getting Started with Generative AI on AWS

To explore and select relevant use cases, AWS provides the AI Use Case Explorer, a search tool that helps find use cases based on industry, business function, and desired outcomes. Developers can access training opportunities through AWS Skill Builder, which offers over 600 digital courses. AWS also offers programs like AWS Academy, AWS Restart, and AWS Educate. To further support customers, AWS offers proof of concept assistance through AWS Experts and the Generative AI Innovation Center, a program connecting customers with AIML experts.

Keywords

Generative AI, Amazon Bedrock, Foundation models, Customization, Data privacy and security, System integration, Use cases, Customer stories, AI Use Case Explorer, Training opportunities, Proof of concept, AWS Experts, Generative AI Innovation Center.

FAQ

Q: What is generative AI? A: Generative AI is an AI technology that can produce new, original content similar to content generated by humans, using large neural networks known as foundation models.

Q: How does Amazon Bedrock address challenges in building generative AI applications? A: Amazon Bedrock offers a range of foundation models and customization options, simplifies application integration through agents, ensures data security and privacy, supports compliance requirements, and provides monitoring and logging capabilities for governance and auditability.

Q: What are some use cases for generative AI? A: Generative AI can be applied to various industries and business functions, including improving customer experience, boosting employee productivity, powering creative content production, and enhancing business operations.

Q: How can developers get started with generative AI on AWS? A: Developers can explore and select relevant use cases using the AI Use Case Explorer, access training opportunities through AWS Skill Builder and other programs, and receive assistance with proof of concept through AWS Experts and the Generative AI Innovation Center.