Large Language Models (LLMs) with Google AI (original) (raw)

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Large Language Models powered by world-class Google AI

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Overview

What is a large language model (LLM)?

A large language model (LLM) is a statistical language model, trained on a massive amount of data, that can be used to generate and translate text and other content, and perform other natural language processing (NLP) tasks.

LLMs are typically based on deep learning architectures, such as the Transformer developed by Google in 2017, and can be trained on billions of text and other content.

What are some examples of popular foundation models?

Vertex AI offers access to Gemini, a multimodal model from Google DeepMind. Gemini is capable of understanding virtually any input, combining different types of information, and generating almost any output. Prompt and test in Vertex AI with Gemini, using text, images, video, or code. Using Gemini’s advanced reasoning and state-of-the-art generation capabilities, developers can try sample prompts for extracting text from images, converting image text to JSON, and even generate answers about uploaded images to build next-gen AI applications.

What are the use cases for large language models?

Text-driven LLMs are used for a variety of natural language processing tasks, including text generation, machine translation, text summarization, question answering, and creating chatbots that can hold conversations with humans.

LLMs can also be trained on other types of data, including code, images, audio, video, and more. Google AI's Veo, Imagen and Chirp are examples of such models that will spawn new applications and help create solutions to the world’s most challenging problems.

What are the benefits of large language models?

LLMs are pre-trained on a massive amount of data. They are extremely flexible because they can be trained to perform a variety of tasks, such as text generation, summarization, and translation. They are also scalable because they can be fine-tuned to specific tasks, which can improve their performance.

What large language model services does Google Cloud offer?

Generative AI on Vertex AI: Gives you access to Google's large generative AI models so you can test, tune, and deploy them for use in your AI-powered applications.

Vertex AI Agent Builder: Allows developers to build agents with an open approach and deploy them with enterprise-grade controls.

Customer Engagement Suite with Google AI: Intelligent Contact Center solution which includes Dialogflow, our conversational AI platform with both intent-based and LLM capabilities.

How It Works

LLMs work by using a massive amount of text data to train a neural network. This neural network is then used to generate text, translate text, or perform other tasks. The more data that is used to train the neural network, the better and more accurate it will be at performing its task.

Google Cloud developed products based on its LLM technologies, catering to a wide variety of use cases you can explore in the Common Uses section below.

Tips to becoming a world-class Prompt Engineer

Common Uses

Build a chatbot

How-tos

Research and information discovery

How-tos

Additional resources

How-tos

Additional resources

Document summarization

How-tos

Process and summarize large documents using Vertex AI LLMs

With Generative AI Document Summarization, deploy a one-click solution that helps detect text in raw files and automate document summaries. The solution establishes a pipeline that uses Cloud Vision Optical Character Recognition (OCR) to extract text from uploaded PDF documents in Cloud Storage, creates a summary from the extracted text with Vertex AI, and stores the searchable summary in a BigQuery database.