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Possible impacts of Large Language Models on X-ray spectroscopy (March 17, 2023). Recent announcement of releasing OpenAI's Generative Pretrained Transformer 4 (GPT-4) could mark the beginning of a new era of the practical application of artificial intelligence. Compared with the previous versions of OpenAI's Large Language Models (LLM), its function in handling the images even in the text-based chat system is surprising. In the presentation, which has been archived as a Youtube video (https://www.youtube.com/live/outcGtbnMuQ?feature=share), the chat system can handle a screenshot image of a handwriting note with some sketch, and can instantly transform it into an html code. Then one can create a new Web page. In addition, the reasoning ability has been upgraded considerably from the previous version, which had not been very good; previous ChatGPT seems to give the correct answer only to 26% of the junior high school level mathematics problems (see, for example, Simon Frieder et al., “Mathematical Capabilities of ChatGPT”, https://arxiv.org/abs/2301.13867). The new version seems to be much better and is now quite good at the tax calculation and the bar exam problem. Generally, the ability of text-based job has become further better than ever. The number of characters that can be handled has increased, and overall processing has become higher quality. One of the recent interesting discussions on the application of artificial intelligence to spectroscopy has been described in the article, by Jerome Workman, Jr., and Howard Mark, “Artificial Intelligence in Analytical Spectroscopy, Part I: Basic Concepts and Discussion”, Spectroscopy, 38, (2), 13–22 (2023). https://doi.org/10.56530/spectroscopy.og4284z8. Some of the related contents have been also discussed in the podcast, Analytically Speaking Podcast Episode 9, “Automating Advanced Chemometric Methods for Data Processing” (https://www.spectroscopyonline.com/view/ep-9-automating-advanced-chemometric-methods-for-data-processing). As the present artificial intelligence is more powerful in handling billions of images, for a while, image-based scientific applications could be preceding (see, for example, Lei Zhang and Shaofeng Shao, “Image-based machine learning for materials science”, Journal of Applied Physics 132, 100701 (2022). https://doi.org/10.1063/5.0087381; Samantha Phan and Christine K. Luscombe, “Recent trends in marine microplastic modeling and machine learning tools: Potential for long-term microplastic monitoring”, Journal of Applied Physics 133, 020701 (2023). https://doi.org/10.1063/5.0126358). On the same day of the announcement of GPT-4, Anthropic Inc, which is a rival company founded by former Open AI employees, released Claude. It has been tested in private systems on systems such as Notion, Quora, and DuckDuckGo, and has been very well received. The LLM and its application such as chatbots will be used more frequently than before. On the other hand, the system is like a black box, and therefore we will need to be careful when considering some real use (see, for example, Noah Giansiracusa, “Three Easy Ways to Make AI Chatbots Safer”, Scientific American, March 17, 2023, https://www.scientificamerican.com/article/three-easy-ways-to-make-ai-chatbots-safer/).