Cloudflare

What is Cloudflare?

Cloudflare + AI is a tool that lets you run fast, low-latency AI inference tasks using pre-trained machine learning models right on Cloudflare Workers. This makes it easier to build and deploy advanced AI applications across Cloudflare’s global network, which is known for its wide availability and scalability. You can use various full-stack AI components, like serverless AI on GPUs, a selection of popular models, and the ability to run AI models from Workers, Pages, or anywhere via its REST API. Cloudflare + AI also helps improve reliability and scalability with features like caching, rate limiting, and analytics through its AI Gateway. Plus, you can create and store embeddings in a globally distributed vector database called Vectorize, which is great for efficient searches on your data when working with machine learning models. The tool focuses on simplicity and quick deployment, offering templates from a curated list of pre-built models. It supports many tasks, including image classification, sentiment analysis, speech recognition, text generation, and translation. With Workers AI and Vectorize, you can run AI inference tasks on Pages, popular frameworks, or any setup using an API with just a little code. Big names in AI like Meta, Nvidia, Microsoft, Hugging Face, and Databricks trust Cloudflare + AI. Its main goal is to help you build AI infrastructures that are dependable, secure, and cost-effective, without any surprise bills. It also offers affordable storage for training models and AI assets with R2, making it cost-effective to set up multi-cloud environments for training large language models.

Who created Cloudflare?

CloudflareAI was developed by Cloudflare and launched on August 21, 2023. This platform allows users to perform fast, low-latency inference tasks using pre-trained machine learning models through Cloudflare Workers. It provides comprehensive full-stack AI building blocks, including serverless AI on GPUs and a variety of popular models. CloudflareAI’s aim is to empower the creation and deployment of ambitious AI applications across Cloudflare’s extensive global network, offering features like caching, rate limiting, and analytics via its AI Gateway. Leading AI companies such as Meta, Nvidia, Microsoft, Hugging Face, and Databricks rely on CloudflareAI for building AI architectures that are reliable, secure, and cost-effective.

What is Cloudflare used for?

• Running fast, low-latency inference tasks on pre-trained machine learning models.
• Building and deploying ambitious AI applications across Cloudflare’s global network.
• Using full-stack AI building blocks for serverless AI on GPUs and popular models.
• Improving reliability and scalability with features like caching, rate limiting, and analytics through the AI Gateway.
• Generating and storing embeddings in a globally distributed vector database for efficient searches with Vectorize.
• Quickly deploying applications using templates for tasks like image classification, sentiment analysis, speech recognition, text generation, and translation.
• Running AI inference tasks on various platforms using Workers AI and Vectorize.
• Supporting AI inference tasks with just a few lines of code.
• Being trusted by well-known AI companies such as Meta, Nvidia, Microsoft, Hugging Face, and Databricks.
• Helping build reliable, secure, and cost-effective AI architectures with affordable storage for training models and AI-generated assets.
• Providing full-stack AI building blocks for serverless AI on GPUs and popular models.
• Enhancing reliability and scalability with features like caching, rate limiting, and analytics.
• Generating and storing embeddings in a globally distributed vector database with Vectorize.
• Enabling quick deployment with templates for image classification, sentiment analysis, speech recognition, text generation, and translation.
• Running AI inference tasks on Pages, favorite frameworks, or any stack via API.
• Being trusted by well-known AI companies like Meta, Nvidia, Microsoft, Hugging Face, and Databricks.
• Offering cost-effective storage for training models and AI-generated assets with R2.
• Supporting affordable multi-cloud architectures for training large language models.
• Running fast, low-latency inference tasks on pre-trained machine learning models on Cloudflare Workers.
• Building and deploying AI applications globally on Cloudflare’s network.
• Utilizing serverless AI on GPUs with various popular models.
• Running AI models from Workers, Pages, or anywhere using the REST API.
• Enhancing reliability and scalability with features like caching, rate limiting, and analytics via AI Gateway.
• Choosing templates from a curated catalog for quick deployment of off-the-shelf models.
• Supporting tasks like image classification, sentiment analysis, speech recognition, text generation, and translation.
• Running AI inference tasks on Pages, favorite frameworks, or any stack via API with just a few lines of code.
• Providing cost-effective storage for training models and AI-generated assets with R2 for multi-cloud architectures.

Who is Cloudflare for?

• AI companies
• Developers
• AI professionals
• Data scientists
• AI architects
• Builders of AI applications

How to use Cloudflare?

To get started with Cloudflare + AI, just follow these simple steps:

1. Sign Up: If you don’t have an account yet, create one with Cloudflare.
2. Set Up Cloudflare Workers: Get comfortable with Cloudflare Workers. It’s the serverless environment where you’ll run your AI tasks.
3. Access Cloudflare AI: Head over to ai.cloudflare.com and log in with your Cloudflare credentials to access the AI tool.
4. Choose a Model: Pick a pre-trained machine learning model from the options available that best fits what your application needs.
5. Build Your Application: Use the full-stack AI building blocks Cloudflare + AI provides to easily create your AI application. You can run AI models from Workers, Pages, or through the REST API.
6. Enhance Reliability: Make your AI application more reliable and scalable by using features like caching, rate limiting, and analytics via the AI Gateway.
7. Deploy: Deploy your AI application on Cloudflare’s global network to ensure it’s available and scalable worldwide.
8. Optimize Performance: Make the most of efficient search by generating and storing embeddings in a globally distributed vector database with Vectorize.
9. Choose Templates: If you need them, select templates from the catalog of ready-to-use models for quick deployment.
10. Utilize Worker AI and Vectorize: Run your AI inference tasks on Pages or any setup you prefer using an API with minimal code.

Cloudflare + AI is designed to be an easy-to-use platform for building and deploying AI applications reliably and scalably. It’s trusted by major AI companies like Meta, Nvidia, and Microsoft. By following these steps, you can use Cloudflare’s infrastructure to create and run powerful AI applications efficiently and cost-effectively.