Build Powerful Generative AI Applications with Alibaba Cloud

Table of Contents

• Introduction
• The Ongoing Generative AI Industry
• The Retrieval Framework
  • The Limitations of Large Language Models
  • Introducing the Retrieval Plugin
  • Connecting Knowledge Base with Large Language Models
• Building Generative AI Projects with Alibaba Cloud
  • The Analytic DB for PostgreSQL
  • Deploying Components on Alibaba Cloud
  • Combining Commercial Large Language Models
• Live Demo

👉 Introduction

Welcome to today's session on how to use the Animated DB with its Vector engine to support the development of generative AI projects. In this article, we will cover various topics related to generative AI and how Alibaba Cloud's products can help businesses build their own applications.

👉 The Ongoing Generative AI Industry

Generative AI has gained tremendous popularity recently, with the release of Chat GPT 3.5 in November 2022. This language model has become the most popular app in just three months, with over 100 million registered users. The advancements in generative AI go beyond just text generation. For example, there are models like Laura and ControlNet that generate human images based on specific inputs. The introduction of fully motion-controlled models like Ty 4.0 has taken generative AI to new heights. Furthermore, tools like Microsoft 365 Co-Pilot and Baidu's earning bot have significantly improved work efficiency. It is clear that generative AI has made remarkable progress across various industries, including medical and security.

👉 The Retrieval Framework

While large language models have revolutionized the AI industry, they have certain limitations. They primarily rely on general internet information and cannot fully understand domain-specific knowledge. Fine-tuning helps to some extent, but it can be expensive and not suitable for real-time applications. Furthermore, fine-tuning has its limitations in terms of memory management and constant updates. To address these challenges, Alibaba Cloud developed the Retrieval Plugin in March. This plugin allows companies to build their own domain-specific knowledge base, enabling them to answer both general and domain-specific questions. By combining this knowledge base with large language models, companies can provide more accurate and specific answers to their users.

👉 Building Generative AI Projects with Alibaba Cloud

To facilitate the development of generative AI projects, Alibaba Cloud offers the Analytic DB for PostgreSQL. This Vector database provides an easy SQL interface and incorporates a text Search Engine. It supports both vector and text-based searching, ensuring accurate and efficient retrieval of information. The Analytic DB stores company-wide knowledge, enabling businesses to build their own applications, such as chatbots and real-time news feed analysis. By combining the Analytic DB with large language models like KatoRe, companies can leverage the power of both approaches for enhanced performance.

The deployment process on Alibaba Cloud is straightforward, with all the necessary components available in one place. Businesses can utilize ECS (Elastic Compute Service) for deploying retrieval services and can take advantage of powerful GPUs for large language models. Additionally, the Analytic DB for PostgreSQL is an ideal choice for storing and retrieving information from knowledge bases. Alibaba Cloud provides a simple and efficient way to set up these components, ensuring businesses have full control over their resources.

For those who prefer commercial large language models, Alibaba Cloud offers seamless integration. Whether it's the 20 Channel from Alibaba or models like GPT from Google, they can be easily connected to the retrieval framework. This eliminates any barriers while ensuring complete control and security of the data.

👉 Live Demo

In the live demo, Farooq, our co-worker, will showcase the usage of Easy Dispatch and Analytic DB to build a deliverable Scenario application. This demonstration will highlight how Alibaba Cloud's products can be combined to create powerful and efficient generative AI projects.

Highlights:

• The popularity and advancements of generative AI
• The limitations of large language models and the need for domain-specific knowledge
• The introduction of Alibaba Cloud's Retrieval Plugin for answering domain-specific questions
• Connecting knowledge bases with large language models for accurate and specific answers
• Building generative AI projects with Alibaba Cloud's Analytic DB for PostgreSQL
• A live demo showcasing the usage of Easy Dispatch and Analytic DB for a deliverable scenario application

FAQ

Q: Can I use the Analytic DB for PostgreSQL with other cloud providers?

A: The Analytic DB for PostgreSQL is specifically designed for Alibaba Cloud and may not be available on other cloud platforms. However, alternative options may be available on different cloud providers.

Q: Can I fine-tune the large language models on my own?

A: Fine-tuning of large language models is possible, but it can be expensive and time-consuming. Additionally, constant updates and memory management may pose challenges. The retrieval framework offers an efficient alternative by leveraging both large language models and domain-specific knowledge bases.

Q: How can I ensure the security of my data when using commercial large language models?

A: When integrating commercial large language models with the retrieval framework, all data can remain within your control. By setting up a long chain and redirecting the requests to commercial models, you can ensure that your organization's data is not compromised.