Using Amazon Bedrock

Index

• A
• A/B testing, for prompts, 47
• accept parameter, 92
• access control management, integrating, 337–345
• AccessDeniedException (403), 102
• Accessible Rich Internet Applications (ARIA), 124
• accuracy metric, 282
• actions, 274, 338–339
• advertising industry, Amazon Bedrock and, 11
• agents
  • for Amazon Bedrock, 252–253
  • creating from AWS web interfaces, 258–259
  • integrating guardrails with, 349–350
  • optimizing, 360
  • overview, 36–37
  • working with, 251–264, 342–344
• AI Assistants, 39–40
• AllGather, 290
• AllReduce, 290
• Amazon Athena, 325, 385–386
• Amazon Aurora, 414–415, 418–420
• Amazon Bedrock
  • agents for, 252–253
  • authenticity in age of generative AI with, 428–431
  • batch inference on, 423–424
  • capabilities of, 31–42
  • challenge approaches of, 17–19
  • chatbot customer service solution with, 40–42
  • configuring environment, 67–68
  • creating end-to-end text-to-SQL system with, 381–403
  • fine-tuning with instruction on, 194–217
  • guardrails for, 345–357
  • how it works, 27–30
  • industries using solutions with, 10–11
  • IoT and, 367–378
  • leveraging with data from Amazon Redshift, 420–423
  • monitoring, 322–327
  • overview, 4, 26–27
  • pricing, 30–31
  • problem framing with, 408–409
  • security and, 313–318
  • setting up knowledge base, 386–388
  • sustainability and scalability with (See sustainability and scalability)
  • testing batch inference on, 426–427
  • using IAM with, 338–342
  • watermark detection in, 429–431
• Amazon Bedrock API
  • building applications with, 89–132
  • coding text-to-image implementation, 113–116
  • configuring parameters, 96–99 ...