Amazon Bedrock FAQs changed AWS, Nov 28, 2024

1. +Added: Amazon Bedrock is a fully managed service that offers a choice of industry leading foundation models (FMs) along with a broad set of capabilities that you need to build generative AI applications, simplifying development with security, privacy, and responsible AI. With the comprehensive capabilities of Amazon Bedrock, you can experiment with a variety of top FMs, customize them privately with your data using techniques such as fine-tuning and retrieval-augmented generation (RAG), and create managed agents that execute complex business tasks-from booking travel and processing insurance claims to creating ad campaigns and managing inventory-all without writing any code. Since Amazon Bedrock is serverless, you don't have to manage any infrastructure, and you can securely integrate and deploy generative AI capabilities into your applications using the AWS services you are already familiar with.
2. -Removed: Amazon Bedrock is a fully managed service that offers a choice of high-performing foundation models (FMs) along with a broad set of capabilities that you need to build generative AI applications, simplifying development with security, privacy, and responsible AI. With the comprehensive capabilities of Amazon Bedrock, you can experiment with a variety of top FMs, customize them privately with your data using techniques such as fine-tuning and retrieval-augmented generation (RAG), and create managed agents that execute complex business tasks-from booking travel and processing insurance claims to creating ad campaigns and managing inventory-all without writing any code. Since Amazon Bedrock is serverless, you don't have to manage any infrastructure, and you can securely integrate and deploy generative AI capabilities into your applications using the AWS services you are already familiar with.
3. +Added: Amazon Bedrock customers can choose from some of the most cutting-edge FMs available today. This includes language and embeddings models from:
4. +Added: AI21 Labs : Jurassic - 2 Ultra, Jurassic - 2 Mid
5. +Added: Anthropic : Claude 3 Opus, Claude 3 Sonnet, Claude 3 Haiku
6. +Added: Cohere : Command R, Command R+, Embed
7. +Added: Meta : Llama 3 8B, Llama 3 70B
8. +Added: Mistral AI : Mistral 8X7B Instruct, Mistral 7B Instruct, Mistral Large, Mistral Small
9. +Added: Stability AI : Stable Diffusion XL 1.0
10. +Added: Amazon Titan : Amazon Titan Text Premier, Amazon Titan Text Express, Amazon Titan Text Lite, Amazon Titan Text Embeddings, Amazon Titan Text Embeddings V2, Amazon Titan Multimodal Embeddings, Amazon Titan Image Generator
11. -Removed: Amazon Bedrock customers can choose from some of the most cutting-edge FMs available today. This includes Anthropic's Claude, AI21 Labs' Jurassic-2, Stability AI's Stable Diffusion, Cohere's Command and Embed, Meta's Llama 2, and the Amazon Titan language and embeddings models.
12. +Added: Choice of leading FMs: Amazon Bedrock offers an easy-to-use developer experience to work with a broad range of high-performing FMs from Amazon and leading AI companies like AI21 Labs, Anthropic, Cohere, Meta, Mistral AI, and Stability AI. You can quickly experiment with a variety of FMs in the playground, and use a single API for inference regardless of the models you choose, giving you the flexibility to use FMs from different providers and keep up to date with the latest model versions with minimal code changes.
13. -Removed: Choice of leading FMs: Amazon Bedrock offers an easy-to-use developer experience to work with a broad range of high-performing FMs from Amazon and leading AI companies like AI21 Labs, Anthropic, Cohere, Meta, and Stability AI. You can quickly experiment with a variety of FMs in the playground, and use a single API for inference regardless of the models you choose, giving you the flexibility to use FMs from different providers and keep up to date with the latest model versions with minimal code changes.
14. +Added: Native support for RAG to extend the power of FMs with proprietary data: With Amazon Bedrock Knowledge Bases, you can securely connect FMs to your data sources for retrieval augmentation-from within the managed service-extending the FM's already powerful capabilities and making it more knowledgeable about your specific domain and organization.
15. -Removed: Native support for RAG to extend the power of FMs with proprietary data: With Knowledge Bases for Amazon Bedrock, you can securely connect FMs to your data sources for retrieval augmentation-from within the managed service-extending the FM's already powerful capabilities and making it more knowledgeable about your specific domain and organization.
16. -Removed: How does Amazon Bedrock work with other services?
17. -Removed: Amazon Bedrock works with AWS Lambda for invoking actions, Amazon S3 for training and validation data, and Amazon CloudWatch for tracking metrics.
18. -Removed: What is Amazon Bedrock Chat Playground?
19. +Added: You can easily fine-tune FMs on Amazon Bedrock using tagged data or by using continued pre-train feature to customize the model using non-tagged data. To get started, provide the training and validation dataset, configure hyperparameters (epochs, batch size, learning rate, warmup steps) and submit the job. Within a couple of hours, your fine-tuned model can be accessed with the same API (InvokeModel).
20. -Removed: You can easily fine-tune FMs on Amazon Bedrock. To get started, provide the training and validation dataset, configure hyperparameters (epochs, batch size, learning rate, warmup steps) and submit the job. Within a couple of hours, your fine-tuned model can be accessed with the same API (InvokeModel).
21. +Added: Yes, you can train select publicly available models and import them into the Amazon Bedrock using the Custom Model Import feature. Currently, this feature only supports Llama 2/3, Mistral, and Flan architectures. For additional information, please refer the documentation .
22. +Added: Amazon Bedrock Agents are fully managed capabilities that make it easier for developers to create generative AI-based applications that can complete complex tasks for a wide range of use cases and deliver up-to-date answers based on proprietary knowledge sources. In just a few short steps, Amazon Bedrock Agents automatically break down tasks and create an orchestration plan-without any manual coding. The agent securely connects to company data through an API, automatically converting data into a machine-readable format, and augmenting the request with relevant information to generate the most accurate response. Agents can then automatically call APIs to fulfill a user's request. For example, a manufacturing company might want to develop a generative AI application that automates tracking inventory levels, sales data, supply chain information and that can recommend optimal reorder points and quantities to maximize efficiency. As fully managed capabilities, Amazon Bedrock Agents remove the undifferentiated lifting of managing system integration and infrastructure provisioning, allowing developers to use generative AI to its full extent throughout their organization.
23. -Removed: Amazon Bedrock is a managed service that you can use to access FMs. You can fine-tune a model and use it with the Amazon Bedrock API.
24. -Removed: What are Agents for Amazon Bedrock?
25. -Removed: Agents for Amazon Bedrock are fully managed capabilities that make it easier for developers to create generative AI-based applications that can complete complex tasks for a wide range of use cases and deliver up-to-date answers based on proprietary knowledge sources. In just a few short steps, Agents for Amazon Bedrock automatically break down tasks and create an orchestration plan-without any manual coding. The agent securely connects to company data through an API, automatically converting data into a machine-readable format, and augmenting the request with relevant information to generate the most accurate response. Agents can then automatically call APIs to fulfill a user's request. For example, a manufacturing company might want to develop a generative AI application that automates tracking inventory levels, sales data, supply chain information and that can recommend optimal reorder points and quantities to maximize efficiency. As fully managed capabilities, Agents for Amazon Bedrock remove the undifferentiated lifting of managing system integration and infrastructure provisioning, allowing developers to use generative AI to its full extent throughout their organization.
26. +Added: You can securely connect FMs to your company data sources using Amazon Bedrock Agents. With a knowledge base, you can use agents to give FMs in Amazon Bedrock access to additional data that helps the model generate more relevant, context-specific, and accurate responses without continually retraining the FM. Based on user input, agents identify the appropriate knowledge base, retrieve the relevant information, and add the information to the input prompt, giving the model more context information to generate a completion.
27. +Added: What are some use cases for Amazon Bedrock Agents?
28. +Added: Amazon Bedrock Agents can help you increase productivity, improve your customer service experience, and automate workflows (such as processing insurance claims).
29. +Added: How do Amazon Bedrock Agents help improve developer productivity?
30. +Added: With agents, developers have seamless support for monitoring, encryption, user permissions, versioning, and API invocation management without writing custom code. Amazon Bedrock Agents automate the prompt engineering and orchestration of user-requested tasks. Developers can use the agent-created prompt template as a baseline to further refine it for an enhanced user experience. They can update the user input, orchestration plan, and the FM response. With access to the prompt template developers have better control over the Agent orchestration.
31. -Removed: You can securely connect FMs to your company data sources using Agents for Amazon Bedrock. With a knowledge base, you can use agents to give FMs in Amazon Bedrock access to additional data that helps the model generate more relevant, context-specific, and accurate responses without continually retraining the FM. Based on user input, agents identify the appropriate knowledge base, retrieve the relevant information, and add the information to the input prompt, giving the model more context information to generate a completion.
32. -Removed: What are some use cases for Agents for Amazon Bedrock?
33. -Removed: Agents for Amazon Bedrock can help you increase productivity, improve your customer service experience, or automate DevOps tasks.
34. -Removed: How do Agents for Amazon Bedrock help improve developer productivity?
35. -Removed: With agents, developers have seamless support for monitoring, encryption, user permissions, and API invocation management without writing custom code. Agents for Amazon Bedrock automate the prompt engineering and orchestration of user-requested tasks. Developers can use the agent-created prompt template as a baseline to further refine it for an enhanced user experience. They can update the user input, orchestration plan, and the FM response. With access to the prompt template developers have better control over the Agent orchestration.
36. +Added: Amazon Bedrock offers several capabilities to support security and privacy requirements. Amazon Bedrock is in scope for common compliance standards such as Fedramp Moderate, Service and Organization Control (SOC), International Organization for Standardization (ISO), Health Insurance Portability and Accountability Act (HIPAA) eligibility, and customers can use Bedrock in compliance with the General Data Protection Regulation (GDPR). Amazon Bedrock is included in the scope of the SOC 1, 2, 3 reports, allowing customers to gain insights into our security controls. We demonstrate compliance through extensive third-party audits of our AWS controls. Amazon Bedrock is one of the AWS services under ISO Compliance for the ISO 9001, ISO 27001, ISO 27017, ISO 27018, ISO 27701, ISO 22301, and ISO 20000 standards. Amazon Bedrock is CSA Security Trust Assurance and Risk (STAR) Level 2 certified, which validates the use of best practices and the security posture of AWS cloud offerings. With Amazon Bedrock, your content is not used to improve the base models and is not shared with any model providers. You can use AWS PrivateLink to establish private connectivity from Amazon VPC to Amazon Bedrock, without having to expose your data to internet traffic.
37. -Removed: Amazon Bedrock offers several capabilities to support security and privacy requirements. Bedrock is in scope for common compliance standards such as Service and Organization Control (SOC), International Organization for Standardization (ISO), Health Insurance Portability and Accountability Act (HIPAA) eligibility, and customers can use Bedrock in compliance with the General Data Protection Regulation (GDPR). Amazon Bedrock is included in the scope of the SOC 1, 2, 3 reports, allowing customers to gain insights into our security controls. We demonstrate compliance through extensive third-party audits of our AWS controls. Amazon Bedrock is one of the AWS services under ISO Compliance for the ISO 9001, ISO 27001, ISO 27017, ISO 27018, ISO 27701, ISO 22301, and ISO 20000 standards. Amazon Bedrock is CSA Security Trust Assurance and Risk (STAR) Level 2 certified, which validates the use of best practices and the security posture of AWS cloud offerings. With Amazon Bedrock, your content is not used to improve the base models and is not shared with any model providers. You can use AWS PrivateLink to establish private connectivity from Amazon VPC to Amazon Bedrock, without having to expose your data to internet traffic.
38. +Added: Please see the Amazon Bedrock pricing page for current pricing information.
39. -Removed: See Amazon Bedrock pricing for current pricing information.
40. +Added: How do I use continued pre-training?
41. -Removed: How do I use Continued Pre-training?
42. +Added: Exclusive to Amazon Bedrock, the Amazon Titan family of models incorporates 25 years of Amazon experience innovating with AI and machine learning across the business. Amazon Titan FMs provide customers with a breadth of high-performing image, multimodal, and text model choices through a fully managed API. Amazon Titan models are created by AWS and pretrained on large datasets, making them powerful, general-purpose models built to support a variety of use cases, while also supporting the responsible use of AI. Use them as is or privately customize them with your own data. Learn more about Amazon Titan .
43. -Removed: Exclusive to Amazon Bedrock, the Amazon Titan family of models incorporates 25 years of Amazon experience innovating with AI and machine learning across the business. Amazon Titan FMs provide customers with a breadth of high-performing image, multimodal, and text model choices through a fully managed API. Amazon Titan models are created by AWS and pretrained on large datasets, making them powerful, general-purpose models built to support a variety of use cases, while also supporting the responsible use of AI. Use them as is or privately customize them with your own data.
44. +Added: To learn more about data processed to develop and train Amazon Titan FMs, visit Amazon Titan Model Training and Privacy page .
45. +Added: What types of data formats are accepted by Amazon Bedrock Knowledge Bases?
46. +Added: Supported data formats include .pdf, .txt, .md, .html, .doc and .docx, .csv, .xls, and .xlsx files. Files must be uploaded to Amazon S3. Point to the location of your data in Amazon S3, and Amazon Bedrock Knowledge Bases takes care of the entire ingestion workflow into your vector database.
47. +Added: How does Amazon Bedrock Knowledge Bases chunk the documents before converting those chunks to embeddings?
48. +Added: Amazon Bedrock Knowledge Bases provides three options to chunk text before converting it to embeddings.
49. +Added: 1. Default option: Amazon Bedrock Knowledge Bases automatically splits your document into chunks each containing 200 tokens, ensuring that a sentence is not broken in the middle. If a document contains less than 200 tokens, then it is not split any further. An overlap of 20% of tokens is maintained between two consecutive chunks.
50. +Added: 2. Fixed size chunking: In this option, you can specify the maximum number of tokens per chunk and the overlap percentage between chunks for Amazon Bedrock Knowledge Bases, so your document will be automatically split into chunks, ensuring that a sentence is not broken in the middle.
51. -Removed: To learn more about data processed to develop and train Amazon Titan FMs, visit Amazon Titan model training and privacy .
52. -Removed: What types of data formats are accepted by Knowledge Bases for Amazon Bedrock?
53. -Removed: Supported data formats include .pdf, .txt, .md, .html, .doc and .docx, .csv, .xls, and .xlsx files. Files must be uploaded to Amazon S3. Point to the location of your data in Amazon S3, and Knowledge Bases for Amazon Bedrock takes care of the entire ingestion workflow into your vector database.
54. -Removed: How does Knowledge Bases for Amazon Bedrock chunk the documents before converting those chunks to embeddings?
55. -Removed: Knowledge Bases for Amazon Bedrock provides three options to chunk text before converting it to embeddings.
56. -Removed: 1. Default option: Knowledge Bases for Amazon Bedrock automatically splits your document into chunks each containing 200 tokens, ensuring that a sentence is not broken in the middle. If a document contains less than 200 tokens, then it is not split any further. An overlap of 20% of tokens is maintained between two consecutive chunks.
57. -Removed: 2. Fixed size chunking: In this option, you can specify the maximum number of tokens per chunk and the overlap percentage between chunks for Knowledge Bases for Amazon Bedrock, so your document will be automatically split into chunks, ensuring that a sentence is not broken in the middle.
58. +Added: At present, Amazon Bedrock Knowledge Bases uses the latest version of the Amazon Titan Text Embeddings model available in Amazon Bedrock. Titan Text Embeddings V2 model supports 8K tokens and 100+ languages and creates an embeddings of flexible 256, 512, and 1,024 dimension size.
59. +Added: Which vector databases are supported by Amazon Bedrock Knowledge Bases?
60. +Added: Amazon Bedrock Knowledge Bases takes care of the entire ingestion workflow of converting your documents into embeddings (vector) and storing the embeddings in a specialized vector database. Amazon Bedrock Knowledge Bases supports popular databases for vector storage, including vector engine for Amazon OpenSearch Serverless, Pinecone, Redis Enterprise Cloud, Amazon Aurora (coming soon), and MongoDB (coming soon). If you do not have an existing vector database, Amazon Bedrock creates an OpenSearch Serverless vector store for you.

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