In the battle of hundreds of models, the development of the AI industry is undergoing unprecedented changes. This competition not only promotes the rapid development of AI technology, but also reveals new trends in the AI industry. These trends not only affect how we view and use AI, but also indicate the future development direction of AI. In this rapidly evolving field, understanding these new trends is critical to understanding the future direction of the AI industry.
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Table of contents
- What is generative artificial intelligence?
- What is Amazon Bedrock
- Why use Amazon Bedrock
- Supported models
- Amazon Bedrock Features
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- Experimentation Tips and Configuration
- Enhance response generation using information from data sources
- Create apps that reason by how they help customers
- Use training data to adapt models to specific tasks and domains
- Improve efficiency and output of FM-based applications
- Determine which model best suits your use case
- Prevent inappropriate or unwanted content
- Application scenarios
- Benefits of Amazon Bedrock Products
- Application scenarios
- Come and experience Amazon Bedrock
- appendix
What is generative artificial intelligence?
Before understanding Amazon Bedrock , let us first have a general understanding of generative artificial intelligence
Generative AI is a type of artificial intelligence that can be used to create new content and ideas, including conversations, stories, images, videos, and music. Artificial intelligence technology attempts to imitate human intelligence in non-traditional computing tasks such as image recognition, natural language processing (NLP) and translation. The core capability of generative AI is to create new content, not just the repeated application of known patterns. Among them, the generative artificial intelligence model is an important part of generative AI and the development direction of artificial intelligence.
The principle of generative AI is based on deep learning, especially neural network technology, which can learn the distribution and patterns of data by analyzing a large amount of training data, and then use these learned patterns to generate new data. Generative AI can not only generate high-quality text, but can also be used in various fields such as image generation, music creation, and video generation.
You can train it to learn human languages, programming languages, art, chemistry, biology, or any complex subject. Generative AI can reuse training data to solve new problems. For example, learn English vocabulary and create a poem based on the words it deals with. Your organization can use generative AI for a variety of purposes, such as chatbots, media creation, and product development and design.
What is Amazon Bedrock
The Amazon Bedrock service, generally available on September 28, 2023, is the easiest way to build and scale generative AI applications using foundational models.
Amazon Bedrock is a fully managed service that offers a variety of high-performance FMs and a broad set of features. You can easily try out a variety of top FMs, customize them privately with your own data, and create managed agents that perform complex business tasks.
Why use Amazon Bedrock
Amazon Bedrock is a fully managed service that makes high-performance foundational models (FMs) from leading AI startups and Amazon available to you through a unified API. You can choose from a variety of base models to find the one that best suits your use case. Amazon Bedrock also provides a broad set of capabilities for building generative AI applications with security, privacy, and responsible AI. With Amazon Bedrock, you can easily experiment and evaluate top-level base models that fit your use cases, customize them privately with your data using techniques like fine-tuning and retrieval-augmented generation (RAG), and build agents that perform tasks using your enterprise systems and data source.
With Amazon Bedrock's comprehensive capabilities, you can easily try out a variety of popular FMs , personalize them with your data using techniques like fine-tuning and retrieval-augmented generation (RAG) , and create creations that perform complex business tasks , from booking travel and processing insurance claims to hosting agents to create ad campaigns and manage inventory), all without writing a single line of code . Because 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 Amazon cloud services you're already familiar with.
Supported models
Claude
Claude is based on Anthropic's research into creating reliable, understandable, and controllable artificial intelligence systems. Claude is a model built using technologies such as Constitutional AI and harmless training, and specializes in deep conversations, content creation, complex reasoning, creative work, and coding.
AmazonTitan
The Amazon Titan base model (FM) is a series of FMs used for text and image generation, summarization, classification, open question and answer, information extraction, and text or image search. It is pre-trained by Amazon Cloud Technology on large data sets to make it Become a powerful general model designed to support various application scenarios. You can use it as-is or privately customize it based on your own data.
StableDiffusion
Able to produce high-quality images in almost any artistic style, Stable Diffusion XL is the best open model for generating photorealistic images. Image generation models produce unique, realistic and high-quality visuals, artwork, logos and designs.
Llama2
Llama 2 is a set of pretrained and fine-tuned large language models (LLMs) ranging in size from 7 billion parameters to 70 billion parameters. Fine-tuned models ideal for conversational use cases and natural language tasks such as question answering and reading comprehension.
Command and Embed
Command is a text generation model suitable for commercial application scenarios.
Text generation and representation models for generating text, summarizing, searching, clustering, classifying and leveraging RAGs.
Jurassic
Jurassic is AI21 Labs’ family of production-ready large language models (LLMs) designed to power natural language artificial intelligence for thousands of real-time applications.
Built specifically for enterprises, the instructions follow FM and can perform a range of tasks, including text generation, Q&A, summarization, and more.
Amazon Bedrock Features
Experimentation Tips and Configuration
Run model inference by sending prompts using different configurations and underlying models to generate responses . You can experiment in the graphical interface using text, images, and chat platforms in the API or console. When you are ready, set up your application to make requests to the InvokeModelAPI.
Enhance response generation using information from data sources
Create a knowledge base by uploading data sources to be queried to enhance the response generation of the underlying model.
Create apps that reason by how they help customers
Build agents that use the underlying model, make API calls, and optionally query the knowledge base to reason about and perform tasks for customers.
Use training data to adapt models to specific tasks and domains
Customize the Amazon Bedrock base model by providing training data for fine-tuning or ongoing pre-training to adjust the model's parameters and improve its performance on specific tasks or in certain domains .
Improve efficiency and output of FM-based applications
Purchase provisioned throughput for a base model to run inference on your model more efficiently at a discount.
Determine which model best suits your use case
Evaluate the output of different models using built-in or custom prompt datasets to determine the best fit for your application .
Prevent inappropriate or unwanted content
Use Guardrails for Amazon Bedrock to implement protections for your generative AI applications.
Application scenarios
Benefits of Amazon Bedrock Products
Leading base model
Amazon Bedrock provides an easy-to-use developer experience that works with a variety of high-performance FMs from leading artificial intelligence companies such as AI21 Labs, Anthropic, Cohere, Meta, Stability Al, and Amazon. Whichever model you choose, you can quickly try out a variety of FMs on the playground and use a single API for inference, which gives you the flexibility to use FMs from different providers and keep your models up-to-date with minimal code changes. Version.
Leverage data to easily customize models
FM can be privately customized with your own data via a visual interface without writing any code. Simply select training and validation datasets stored in Amazon Simple Storage Service (Amazon S3) and adjust hyperparameters if needed to achieve the best possible model performance.
Fully managed agent that can dynamically call APIs to perform tasks
Build agents capable of performing complex business tasks—from booking travel and processing insurance claims to creating advertising campaigns, preparing tax returns, and managing inventory—by dynamically calling company systems and APIs . Amazon Bedrock's fully managed agent extends FM's inference capabilities to break down tasks, create orchestration plans, and execute that plan.
Provide native support for RAG, extending FM capabilities with proprietary data
With the Amazon Bedrock Knowledge Base, you can securely connect FM to your data sources for enhanced retrieval within the managed service, extending FM's already powerful capabilities to make it even more relevant to your specific domain and organization.
Data Security and Compliance Certification
Amazon Bedrock offers multiple features to support security and privacy requirements, is HIPAA eligible, and is GDPR compliant . In Amazon Bedrock, your content is not used to improve the base model or shared with third-party model providers. Your data in Amazon Bedrock is always encrypted in transit and at rest, and you can encrypt your data using your own keys. You can use AWS PrivateLink with Amazon Bedrock to create a private connection between FM and your Amazon Virtual Private Cloud (Amazon VPC) without exposing the traffic to the Internet.
Application scenarios
- Text generation : Create new, original content such as blog posts, social media posts, and web assets.
- Virtual Assistants : Build assistants that understand user requests, automatically break down tasks, engage in conversations to gather information, and take action to fulfill the requests.
- Search : Search, find, and synthesize relevant information to answer questions from large corpora of data.
- Text summaries : Get summaries of long documents like articles, reports, or even books to quickly understand the key points.
- Image Generation : Quickly create realistic and visually appealing images and animations for ad campaigns, websites, presentations, and more
Come and experience Amazon Bedrock
