This article explores the idea that Rust is a particularly well-suited language for AGI, focusing on the Rust Coder project and its tools designed for both AI coders and their human assistants. The premise is that, going forward, AI will take precedence in code generation.
Introduction
Michael Yu introduces the concept of Rust as a language for AGI, emphasizing the development of Rust tools aimed at AI coders, with human assistance as a secondary, but important, aspect. He provides links to his GitHub page for contact information and open-source projects, highlighting the Rust Coder project.
What is Rust?
Rust, a programming language that recently celebrated its 10th anniversary, is known for its popularity among developers. The language boasts a strong and active community, growing rapidly since its inception.
Rust's Popularity and Learning Curve
According to Stack Overflow's developer survey, Rust has consistently been the most beloved programming language.
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Rust stands out with an impressive 82% admiration rate.
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However, while admired, its adoption rate is lower than languages like Python.
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This is because Rust has a steep learning curve due to its powerful compiler.
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The compiler enforces rigorous code correctness and optimization, which can be challenging for beginners. While difficult to learn initially, Rust ultimately simplifies writing correct code once mastered.
Rust: Not Always Human-Centric
In a human-centric world, ease of writing and quick results often take precedence, explaining the popularity of languages like Python and JavaScript. While Rust may not be as easy for humans, it offers advantages in other areas.
Why Rust for Machines?
Brett Taylor from OpenAI suggests that while humans might prefer Python, Rust is better suited for machines because of its efficiency and structural orientation.
Benefits of Rust for AI
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Rust's strong compiler and type system provide a tight feedback loop.
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Rust developers often experience minimal debugging after successful compilation.
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The compiler provides a robust reward function for AI, essential for reinforcement learning.
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The compiler ensures that a correct answer to a code generation request is accepted by the compiler
The Future of Code Generation
If AI increasingly writes code, using languages like Rust, which prioritize machine efficiency and verifiable correctness, becomes crucial. Rust is not only AI-friendly but also remains reasonably accessible to humans.
The Rust Coder Project
The Rust Coder project aims to teach Rust to AI and improve AI-generated Rust code, sponsored by the Linux Foundation with educational material from the Rust Foundation.
Goals of Rust Coder
The project focuses on making it easier for AI assistants to:
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Learn Rust
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Write code in Rust
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Work with Rust in IDEs.
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More importantly, the project aims to enable machines to generate Rust code on the fly. The vision is for large language models to generate code to perform tasks, making it essential for machines to generate correct Rust code in collaboration with the compiler.
Demos
Demo 1: Helping Humans Learn Rust
The project utilizes Rust education materials and generated tasks to build a knowledge base. This enables an AI agent to provide Rust answers to programming questions.
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This system has been used by thousands of developers in a university-based Rust camp.
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Rust Coder can solve complex exam questions and explain the answers to learners.
Demo 2: Aiding Humans in IDEs
An MCP (Machine Communication Protocol) server integrated into the Cursor IDE provides tools for generating, compiling, and fixing Rust projects.
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The "compile and fix" tool sends project files to the MCP server for compilation.
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The server uses the Rust compiler and a coding large language model to identify and fix errors, repeating the process until successful compilation.
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This integrated solution leverages a knowledge base of Rust compiler error messages and learns from each interaction, offering advantages over generic coding large language models.
How the MCP Tools Work
The Rust Coder project's MCP tools consist of an integrated stack of tools designed to work together, including:
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Coding large language models (commercial or open-source) optimized with tailored prompts.
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A self-improving knowledge base of Rust compiler error messages, allowing the system to learn and adapt over time.
Technology Stack
The underlying technology stack is open-source and includes:
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Llama.age project, a Linux Foundation project for running AI models across various hardware.
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An integrated knowledge base with various search and embedding models.
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GAA network, built on Llama.age.
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MCP server using the open-source M open MCP proxy.
MCP: Beyond Humans
While currently used to assist humans, MCP is fundamentally designed for machines.
The Evolution of Computer Users
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Early computing focused on human-computer interfaces, tailored to human senses and actions.
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The API-first approach emerged, where applications are designed for consumption by other computers or workflow engines.
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Large language models have shifted the paradigm, with computers behaving more like humans consuming software applications.
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Rust compiler service and bug-fixing services are presented as tools for large language models to use.
The Future Vision
Envision a future where systems, such as drone control, are managed by AI-generated Rust code. The code would be generated, compiled, debugged, and uploaded automatically, enabling autonomous operation with reasonable guarantees of correctness.
Getting Started with Rust Coder
Rust Coder is part of the Local Rust program, offering APIs and MCP services for workflow engines and large language models.
Installation and Usage
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The project has a GitHub repository.
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Installation is simplified with a Docker Compose script.
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The system can be accessed through web service APIs for code generation and error fixing.
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Integration with modern agent frameworks via MCP allows large language models to generate and fix Rust code.
Conclusion
The Rust Coder project is an ongoing effort to build a smarter, more functional system for AI agents. The speaker believes that the road to AGI involves AI coders, and Rust is the ideal language for this, better suited than Python or JavaScript. Contributions and collaboration are encouraged to expand the knowledge base and capabilities of Rust Coder.
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