Unlocking the Power of Generative AI: Exploring Google’s PaLM API and Firebase Extensions
The recent Google I/O 2023 event marked a significant milestone in the world of artificial intelligence, with a major focus on Generative AI. This cutting-edge technology enables the creation of innovative models and algorithms capable of generating new content, such as text, images, code, videos, and more, from simple natural language prompts. In this article, we’ll delve into the exciting world of Generative AI, exploring Google’s PaLM API and Firebase Extensions, and how they can be leveraged to build intelligent applications.
What is Generative AI?
Generative AI is a subset of artificial intelligence that creates new content, including text, graphics, and even audio. It utilizes large neural networks called large language models (LLMs) that are trained on massive amounts of data to learn the patterns and structures of human language. When provided with a prompt, such as a word, phrase, or question, the LLM can generate a response that is relevant and coherent to the prompt. Generative AI has numerous applications and benefits across various domains and industries, including education, entertainment, healthcare, and more.
Introducing Google’s PaLM API
PaLM stands for Pathways Language Model, a transformer-based large language model developed by Google AI. The initial version of PaLM was announced in April 2022, and a new iteration, PaLM 2, was introduced in May 2023. PaLM 2 is trained on five times more data than PaLM and excels in math, coding, advanced reasoning, and multi-lingual tasks like translation. Currently, the Google PaLM API is comprised of three endpoints: chat, text, and embeddings.
MakerSuite: A Tool for Rapid Prototyping
Alongside the PaLM API, Google launched MakerSuite, a platform that enables developers to quickly build large language model applications with Google’s generative language models. MakerSuite simplifies the design of prompts, allowing developers to rapidly develop and share working prototypes of LLM-powered applications within minutes.
How Does PaLM Differ from Open AI’s GPT-3?
Both PaLM and GPT-3 are powerful language models that can handle various natural language processing tasks. While PaLM is similar to rival transformer-based models, including OpenAI’s GPT-3 and GPT-4 models, there are key differences. PaLM 2 is a larger model than GPT-3, with 540 billion parameters compared to 175 billion parameters. Additionally, PaLM 2 is trained on more data than GPT-3, with 300 billion tokens of data compared to 45 terabytes of data.
Accessing the PaLM API
Currently, there are two ways to access the PaLM API: by joining the waitlist and getting an API key via MakerSuite, or by using Vertex AI if you are already a Google Cloud customer. Note that the PaLM API is currently only available in the United States, with plans to expand to other regions in the future.
PaLM API Meets Firebase Extensions
Using the PaLM API directly can be challenging and time-consuming, especially when integrating it with Firebase apps. To simplify this process, Google has released several PaLM API Firebase Extensions, which are pre-packaged, serverless solutions that enable quick integration of the PaLM API into your app using Firebase Extensions. These extensions include:
- Chatbot with PaLM API: Enables developers to establish and manage conversations between users and large language models through the PaLM API, using Cloud Firestore as the database.
- Call PaLM API Securely: Provides secure API endpoints using App Check, allowing developers to interact with the PaLM API from their Firebase apps.
- Language Tasks with PaLM API: Enables developers to use the PaLM API to perform various text-based tasks, such as text translation, classification, and more.
- Summarize Text with PaLM API: Generates summaries for various applications, such as news articles, blog posts, product reviews, and more.
Building a Web App with Summarize Text with PaLM API
Let’s build a simple web app that allows users to enter some text and get a summary of it using the Summarize Text with PaLM API Firebase Extension. To follow this tutorial, you’ll need working knowledge of React, Node.js, and npm installed on your machine, and a code editor of your choice.
Conclusion
This article has provided valuable insights into the world of Generative AI and the recently launched AI extensions powered by the PaLM 2 API. We’ve explored four of the released extensions and built a sample app to demonstrate how to integrate one of them. You can take this further by trying to integrate the other extensions into your applications. Happy coding!