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Preface

Large model applications are developing rapidly, and the demand for deploying a set of AI applications is increasing. Deploying from scratch takes too long. However, Amazon Technology's fully managed generative AI service Amazon Bedrock simplifies the complex process from basic models to generative AI application construction, paving a direct and efficient path for customers. Users only need to follow a few intuitive and easy-to-follow steps to quickly create and deploy fully managed agents, which can flexibly call APIs and efficiently execute diverse and complex business logic.

This innovative service model not only greatly accelerates the popularization and application of generative AI technology, but also provides unprecedented convenience and possibilities for the exploration and practice of artificial intelligence in various industries. This article mainly explains how to use Amazon Bedrock to deploy a fully managed generative AI service.

Amazon Web Services offers free trial packages for new users (free for 12 months, free forever, etc.), including Amazon Bedrock Users canAmazon Web Services overseas free trial page Learn more details and start a free trial. This not only lowers the entry threshold for users, but also allows users to explore and learn Amazon Web Services without burden.

Visit Amazon Bedrock

First you needAmazon Web ServicesAccount Registration. OpenAmazon Bedrock, and then click the Get Started button.

Then we can see the backend interface of Amazon Bedrock. We can see that Amazon Bedrock supports multiple models, including Amazon Titan, Claude, Jurassic, Command, Stable Diffusion and Llama2.

Model Access

Select "Model Access" in the left menu to authorize the model, then select Manage model access on the right. For some models, you may first need to submit use case details before you can request access.

Next, select the models you need. It is recommended to select all of them. For the GPT-dialogue function, you need to select any model with the Text tag, and for the Stable Diffusion-text-to-image function, you need to select the model with the Image tag. Finally, click the button below to complete the authorization: Request model access.

Then confirm whether the model is authorized successfully.

Building Stable Diffusion-Text to Image Generation

Select the Playgrounds column in the left navigation bar to see three modes of the model:

• Chat mode: supports text interaction and code generation. It can also compare the results between different models and gain a deeper understanding of the performance of generative AI in different scenarios.
• Text mode: supports a simple process of text processing, with advanced algorithms that can efficiently process and analyze large amounts of text data.
• Image mode: supports the rapid conversion of text descriptions into images, enabling instant creative presentation. It can generate pictures described by users within seconds, providing a more intuitive and efficient way to convert ideas into visual form.

Then we select Select model and choose the model we want to use. These models are the models we just selected to authorize above.

Then we can enter the following prompt to let Amazon Bedrock generate images for us and click Run.
Prompt word case 1

1girl, masterpiece, best quality, high resolution, 8K , HDR, cinematic lighting, bloom, sun light, looking at viewer, outdoor, detailed shadows, intricate tree shadows, raytracing`
1

Prompt word case 2

1cute girl walking in street, half body, 64K, Professional,Makoto Shinkai, Katsuhiro Otomo, Masashi Kishimoto, Kentaro Miura
1

An introduction to the properties involved.

Among them, prompt words are very important and are the most basic requirement for generating images. Prompt words are composed of multiple affixes. Prompt words are divided into positive prompt words and negative prompt words, which are used to tell AI what is needed and what is not. Negative prompt words sound intriguing, but in fact, they are descriptions of what we don’t want to appear. Prompt words and negative prompt words actually depend on your imagination. They must be converted into English description terms to be more effective. I personally think that there is no fixed formula that will limit people’s imagination. In short, fill in whatever you want and give full play to your imagination.

Summarize

I was very surprised by Amazon Bedrock, a fully managed generative AI service. It seemed like I had found my home, as someone who hates troubles. Building models by myself was complicated, but Amazon Bedrock completely solved my problem. During the experience, I have some opinions on HAI application building:
1. Quick build and deployment. I think this is an advantage that many users can see. It is really convenient.
2. Amazon Bedrock uses advanced architecture and algorithms to handle a large number of concurrent requests and provide high-throughput and low-latency services, which gives users a better experience when using the application.
3. You can build a set of services and use multiple applications together, which not only saves money but also saves time.