Cloudflare

What is Cloudflare?

Cloudflare + AI is a tool designed to enable users to execute fast, low-latency inference tasks using pre-trained machine learning models directly on Cloudflare Workers. This tool facilitates the development and deployment of advanced AI applications on Cloudflare's worldwide network, which offers extensive global availability and scalability features. Users can leverage various full-stack AI components such as serverless AI on GPUs, a selection of popular models, and the capability to run AI models from Workers, Pages, or any location through their REST API. Cloudflare + AI also provides functionalities to improve reliability and scalability, including caching, rate limiting, and analytics via their AI Gateway. Moreover, it allows users to create and store embeddings in a globally distributed vector database with Vectorize, enabling efficient search operations on user data for repetitive use with machine learning models. The tool prioritizes simplicity and rapid deployment, offering users the option to select templates from a curated collection of pre-built models. It supports diverse tasks like image classification, sentiment analysis, speech recognition, text generation, and translation. Through Workers AI and Vectorize, users can execute AI inference tasks on Pages, popular frameworks, or any stack via an API with minimal code implementation. Cloudflare + AI is endorsed by reputable AI entities such as Meta, Nvidia, Microsoft, Hugging Face, and Databricks. Its primary aim is to assist users in constructing dependable, secure, and cost-effective AI infrastructures while avoiding unexpected expenses. Additionally, the tool provides economical storage solutions for training models and AI-generated resources with R2, which enables the cost-effective establishment of multi-cloud setups for training extensive language models.

Who created Cloudflare?

CloudflareAI was created by Cloudflare, and it was launched on August 21, 2023. The platform allows users to execute fast and low-latency inference tasks on pre-trained machine learning models through Cloudflare Workers. It offers full-stack AI building blocks, including serverless AI on GPUs and a variety of popular models. CloudflareAI aims to enable the development and deployment of ambitious AI applications on Cloudflare's global network with features like caching, rate limiting, and analytics through their AI Gateway. Notable AI companies such as Meta, Nvidia, Microsoft, Hugging Face, and Databricks trust CloudflareAI for building reliable, secure, and cost-effective AI architectures .

What is Cloudflare used for?

• Run fast, low-latency inference tasks on pre-trained machine learning models
• Build and deploy ambitious AI applications on Cloudflare's global network
• Utilize full-stack AI building blocks for serverless AI on GPUs and popular models
• Enhance reliability and scalability with features like caching, rate limiting, and analytics through AI Gateway
• Generate and store embeddings in a globally distributed vector database for efficient search with Vectorize
• Quick deployment with templates for tasks like image classification, sentiment analysis, speech recognition, text generation, and translation
• Run AI inference tasks on various platforms using Workers AI and Vectorize
• Supports AI inference tasks with just a few lines of code
• Trusted by well-known AI companies such as Meta, Nvidia, Microsoft, Hugging Face, and Databricks
• Helps build reliable, secure, and cost-effective AI architectures with affordable storage for training models and AI-generated assets
• Full-stack AI building blocks for serverless AI on GPUs and popular models
• Enhance reliability and scalability with features like caching, rate limiting, and analytics
• Generate and store embeddings in a globally distributed vector database with Vectorize
• Quick deployment with templates for image classification, sentiment analysis, speech recognition, text generation, and translation
• Run AI inference tasks on Pages, favorite frameworks, or any stack via API
• Trusted by well-known AI companies like Meta, Nvidia, Microsoft, Hugging Face, and Databricks
• Cost-effective storage for training models and AI-generated assets with R2
• Affordable multi-cloud architectures for training large language models
• Run fast, low-latency inference tasks on pre-trained machine learning models on Cloudflare Workers
• Build and deploy AI applications globally on Cloudflare's network
• Utilize serverless AI on GPUs with various popular models
• Run AI models from Workers, Pages, or anywhere using the REST API
• Enhance reliability and scalability with features like caching, rate limiting, and analytics via AI Gateway
• Choose templates from a curated catalog for quick deployment of off-the-shelf models
• Support tasks like image classification, sentiment analysis, speech recognition, text generation, and translation
• Run AI inference tasks on Pages, favorite frameworks, or any stack via API with just a few lines of code
• 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
• AI applications builders

How to use Cloudflare?

To use Cloudflare + AI, follow these steps:

1. Sign Up: Create a Cloudflare account if you don't have one already.

2. Set Up Cloudflare Workers: Get familiar with Cloudflare Workers, the serverless execution environment where you will run your AI tasks.

3. Access Cloudflare AI: Navigate to ai.cloudflare.com and log in using your Cloudflare credentials to access the AI tool.

4. Choose a Model: Select a pre-trained machine learning model from the available options that best suits your application.

5. Build Your Application: Use the full-stack AI building blocks provided by Cloudflare + AI to build your AI application with ease. You can run AI models from Workers, Pages, or the REST API.

6. Enhance Reliability: Utilize features like caching, rate limiting, and analytics through the AI Gateway to enhance the reliability and scalability of your AI application.

7. Deploy: Deploy your AI application on Cloudflare's global network for global availability and scalability.

8. Optimize Performance: Take advantage of efficient search capabilities by generating and storing embeddings in a globally distributed vector database with Vectorize.

9. Choose Templates: If needed, select templates from the catalog of off-the-shelf models for quick deployment.

10. Utilize Worker AI and Vectorize: Run your AI inference tasks on Pages or any preferred stack via an API with minimal code.

Cloudflare + AI aims to provide an easy-to-use platform for building and deploying AI applications with reliability and scalability, trusted by major AI companies like Meta, Nvidia, and Microsoft. By following these steps, you can leverage Cloudflare's infrastructure to create and run powerful AI applications efficiently and cost-effectively.