Summary of The Artificial Intelligence Ontology: Llm-assisted Construction Of Ai Concept Hierarchies, by Marcin P. Joachimiak et al.
The Artificial Intelligence Ontology: LLM-assisted construction of AI concept hierarchies
by Marcin P. Joachimiak, Mark A. Miller, J. Harry Caufield, Ryan Ly, Nomi L. Harris, Andrew Tritt, Christopher J. Mungall, Kristofer E. Bouchard
First submitted to arxiv on: 3 Apr 2024
Categories
- Main: Machine Learning (cs.LG)
- Secondary: Artificial Intelligence (cs.AI)
GrooveSquid.com Paper Summaries
GrooveSquid.com’s goal is to make artificial intelligence research accessible by summarizing AI papers in simpler terms. Each summary below covers the same AI paper, written at different levels of difficulty. The medium difficulty and low difficulty versions are original summaries written by GrooveSquid.com, while the high difficulty version is the paper’s original abstract. Feel free to learn from the version that suits you best!
| 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 Artificial Intelligence Ontology (AIO) is a comprehensive framework that systematizes AI concepts, methodologies, and their interrelations. Developed through manual curation and assisted by large language models (LLMs), AIO aims to address the rapidly evolving landscape of AI by providing standardized terminology and concepts within the AI domain. The ontology comprises six top-level branches: Networks, Layers, Functions, LLMs, Preprocessing, and Bias, designed to support modular composition of AI methods and facilitate understanding of deep learning architectures and ethical considerations in AI. AIO is primarily intended for AI researchers, developers, and educators seeking a standardized framework for their work. |
| Low | GrooveSquid.com (original content) | Low Difficulty Summary Imagine trying to understand all the different parts that make up artificial intelligence (AI). It’s like trying to organize a huge library with millions of books! The Artificial Intelligence Ontology (AIO) is a way to do just that. It takes all the complex concepts and ideas in AI and puts them into one organized framework. This will help people working with AI, such as researchers and developers, understand how everything fits together. AIO has six main parts: networks, layers, functions, language models, preprocessing, and bias. These parts are designed to work together like LEGO blocks to help us build a better understanding of AI. |
Keywords
* Artificial intelligence * Deep learning
