Summary of How Good Is Chatgpt at Face Biometrics? a First Look Into Recognition, Soft Biometrics, and Explainability, by Ivan Deandres-tame et al.
How Good is ChatGPT at Face Biometrics? A First Look into Recognition, Soft Biometrics, and Explainability
by Ivan DeAndres-Tame, Ruben Tolosana, Ruben Vera-Rodriguez, Aythami Morales, Julian Fierrez, Javier Ortega-Garcia
First submitted to arxiv on: 24 Jan 2024
Categories
- Main: Computer Vision and Pattern Recognition (cs.CV)
- Secondary: Artificial Intelligence (cs.AI); Computers and Society (cs.CY); Machine Learning (cs.LG)
GrooveSquid.com Paper Summaries
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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 This research paper explores the applications of Large Language Models (LLMs) like GPT developed by OpenAI. The models have already had a significant impact on society, with ChatGPT allowing anyone to interact with LLMs in a conversational way without needing technical expertise. As a result, ChatGPT has been rapidly applied to various tasks such as code- and song-writing, education, and virtual assistants, demonstrating impressive results for tasks it was not trained on (zero-shot learning). The paper highlights the potential of LLMs in achieving quick changes in our society. |
| Low | GrooveSquid.com (original content) | Low Difficulty Summary This research is about big language models that can talk like humans. These models are very good at helping people with different tasks, such as writing code or songs, teaching, and even acting like personal assistants. Something called ChatGPT makes it easy for anyone to use these models without needing special knowledge. This has already led to many new uses for the models, showing that they can learn new things just by being shown what’s possible. |
Keywords
* Artificial intelligence * Gpt * Zero shot
