mlsanityData to 14 Oct 2026

A Glimpse in ChatGPT Capabilities and its impact for AI research

arXiv 2305.06087 ↗First posted 10 May 2023cs.AI cs.CL cs.HCcited by 6

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Abstract (arXiv)

Large language models (LLMs) have recently become a popular topic in the field of Artificial Intelligence (AI) research, with companies such as Google, Amazon, Facebook, Amazon, Tesla, and Apple (GAFA) investing heavily in their development. These models are trained on massive amounts of data and can be used for a wide range of tasks, including language translation, text generation, and question answering. However, the computational resources required to train and run these models are substantial, and the cost of hardware and electricity can be prohibitive for research labs that do not have the funding and resources of the GAFA. In this paper, we will examine the impact of LLMs on AI research. The pace at which such models are generated as well as the range of domains covered is an indication of the trend which not only the public but also the scientific community is currently experiencing. We give some examples on how to use such models in research by focusing on GPT3.5/ChatGPT3.4 and ChatGPT4 at the current state and show that such a range of capabilities in a single system is a strong sign of approaching general intelligence. Innovations integrating such models will also expand along the maturation of such AI systems and exhibit unforeseeable applications that will have important impacts on several aspects of our societies.

Key facts. Cited by 6 papers in the map (data through 14 Oct 2026). Builds on 34 of its 73 references that are in the map. First posted on arXiv 10 May 2023.

Builds on

34 of 73 references.

References · 34

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22 more
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Built on by

Cited by year (2026 to 14 Oct)

Citing papers per year: 2023: 3; 2024: 2; 2025: 0; 2026: 1.

6 papers.

  1. 2023CoPAL: Corrective Planning of Robot Actions with Large Language Modelscited by 40
  2. 2023Analysis of ChatGPT on Source Codecited by 12
  3. 2023Testing the Depth of ChatGPT's Comprehension via Cross-Modal Tasks Based on ASCII-Art: GPT3.5's Abilities in Regard to Recognizing and Generating ASCII-Art Are Not Totally Lackingcited by 7
  4. 2024Large Language Models Understand Layoutcited by 3
  5. 2024Technical Language Processing for Telecommunications Specificationscited by 1
  6. 2026Conversational AI for Rapid Scientific Prototyping: A Case Study on ESA's ELOPE Competitioncited by 0