What is Generative AI? Examples & Use Cases (original) (raw)

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Generative AI use cases and definition

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Overview

What is generative AI?

Generative AI or generative artificial intelligence refers to the use of AI to create new content, like text, images, music, audio, and videos.

Generative AI is powered by foundation models (large AI models) that can multi-task and perform out-of-the-box tasks, including summarization, Q&A, classification, and more. Plus, with minimal training required, foundation models can be adapted for targeted use cases with very little example data.

How does generative AI work?

Generative AI works by using an ML model to learn the patterns and relationships in a dataset of human-created content. It then uses the learned patterns to generate new content.

The most common way to train a generative AI model is to use supervised learning - the model is given a set of human-created content and corresponding labels. It then learns to generate content that is similar to the human-created content and labeled with the same labels.

Common generative AI applications

Generative AI processes vast content, creating insights and answers using text, images, and user-friendly formats. Generative AI can be used to:

- Improve customer interactions through enhanced chat and search experiences

- Explore vast amounts of unstructured data through conversational interfaces and summarizations

- Assist with repetitive tasks like replying to requests for proposals (RFPs), localizing marketing content in five languages, and checking customer contracts for compliance, and more

How has generative AI technology evolved?

The evolution of generative AI has been rapid, and continues to change. Early models, like Markov chains and RNNs, laid the groundwork, but often struggled with generating nuanced and coherent outputs. Generative adversarial networks (GANs) then emerged, pushing the boundaries of image creation and producing strikingly realistic visuals. However, GANs were not without their challenges, sometimes grappling with stability issues.

The introduction of transformer-based models, such as BERT and GPT, is often seen as a turning point. These models revolutionized natural language processing (NLP), demonstrating an unprecedented ability to understand and generate human-like text. Building on this success, GPT-2 and GPT-3 further showcased the immense potential of generative AI, captivating the world with their impressive text generation capabilities.

Meanwhile, variational autoencoders (VAEs) and diffusion models made strides in image synthesis, opening up new possibilities for creative applications. As generative AI continues to advance, the future holds immense promise, with ongoing research focusing on enhancing efficiency, improving interpretability, and addressing ethical considerations.

What generative AI offerings does Google Cloud have?

With Vertex AI, interact with, customize, and embed foundation models including Gemini family of models into your applications—no ML expertise required. Access foundation models on Model Garden, tune models using a simple UI on Vertex AI Studio, or use models in a data science notebook.

And, Google Cloud with Gemini serves as an always-on AI collaborator that helps users of all skill levels where they need it.

Need help implementing generative AI solutions?

Work with Google's experts to get up and running quickly with generative AI. Explore our consulting service offerings in generative AI which can help your organization with:

- Creating new text and image content

- Discovering trends and gaining insights from data

- Summarizing for faster decision-making

- Automating solutions and processes

- Productionizing your generative AI solutions

Check out the entire Google Cloud Consulting portfolio of service offerings.

Google’s approach to responsible AI

Google Cloud products and product updates have safety and security built in, are guided by Google's AI Principles, and are focused on helping enterprises control their use of IP, data, and individual privacy.

How It Works

Generative AI is poised to usher in a new wave of interactive, multimodal experiences that transform how we interact with information, brands, and one another. Harnessing the power of decades of Google’s research, innovation, and investment in AI, Google Cloud is bringing businesses and governments the ability to generate text, images, code, videos, audio, and more from simple natural language prompts.

Latest on generative AI with Google Cloud

Common Uses

Modernize customer service

How-tos

Improve developer efficiency

How-tos

Drive developer productivity with code assistance

Gemini Code Assist offers AI-powered assistance to help developers build applications with higher velocity and quality in popular code editors like VS Code and JetBrains. It supports your private codebase wherever it lives — even across multiple repositories.

Improving developer efficiency with generative AI

How-tos

Drive developer productivity with code assistance

Improving developer efficiency with generative AI

Gen AI for marketing

How-tos

Website modernization

How-tos

Generate a solution

What problem are you trying to solve?

What you'll get:

Step-by-step guide

Reference architecture

Available pre-built solutions

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View examples of prompts and responses from our generative AI models