Summary of Can Chatgpt Make Explanatory Inferences? Benchmarks For Abductive Reasoning, by Paul Thagard
Can ChatGPT Make Explanatory Inferences? Benchmarks for Abductive Reasoning
by Paul Thagard
First submitted to arxiv on: 29 Apr 2024
Categories
- Main: Artificial Intelligence (cs.AI)
- Secondary: None
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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 proposed paper introduces benchmarks for assessing the ability of generative AI models like ChatGPT to perform explanatory inference, also known as abduction or abductive inference. The study uses these benchmarks to evaluate the creative and evaluative capabilities of ChatGPT across various domains, revealing its strengths in verbal and visual modalities. Notably, the research refutes claims that ChatGPT lacks explanation, understanding, causal reasoning, meaning, and creativity. |
| Low | GrooveSquid.com (original content) | Low Difficulty Summary This paper creates tests to see if a special kind of artificial intelligence called generative AI can make sense of things and explain them to us. The test is about ChatGPT, which is one type of generative AI that can create words, pictures, and sounds. Scientists found out that ChatGPT can do these clever thinking tasks in many areas, but only with words and pictures. Some people thought ChatGPT couldn’t understand things or explain them, but the scientists proved those people wrong. |
Keywords
» Artificial intelligence » Inference
