Summary of Aios Compiler: Llm As Interpreter For Natural Language Programming and Flow Programming Of Ai Agents, by Shuyuan Xu et al.
AIOS Compiler: LLM as Interpreter for Natural Language Programming and Flow Programming of AI Agents
by Shuyuan Xu, Zelong Li, Kai Mei, Yongfeng Zhang
First submitted to arxiv on: 11 May 2024
Categories
- Main: Computation and Language (cs.CL)
- Secondary: Artificial Intelligence (cs.AI); Machine Learning (cs.LG); Programming Languages (cs.PL)
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| Summary difficulty | Written by | Summary |
|---|---|---|
| High | Paper authors | High Difficulty Summary Read the original abstract here |
| Medium | GrooveSquid.com (original content) | Medium Difficulty Summary The paper proposes CoRE (Code Representation and Execution), a system that uses Large Language Models (LLMs) to interpret and execute natural language instructions. This approach aims to democratize programming by providing greater flexibility and usability. The system unifies natural language, pseudo-code, and flow programming under one representation, allowing for the construction of language agents. LLM serves as an interpreter, interpreting and executing agent programs. The paper defines a programming syntax that structures natural language instructions logically, incorporates external memory to minimize redundancy, and equips the interpreter with the ability to invoke external tools. |
| Low | GrooveSquid.com (original content) | Low Difficulty Summary The researchers created CoRE, a system that lets people write code in natural language. This means you can tell a computer what to do using everyday language, rather than writing complicated programming code. The team used big language models to make this happen. They designed a way for these models to understand and follow instructions written in natural language. This makes it easier for more people to learn how to program. |
Keywords
» Artificial intelligence » Syntax
