tx · 5uPGvYZeVFHWHMCwzCS8W6DJ71J2voDYJGhoyEhCQGDY
3NAAoJ554QsZfqE8W8Rg8LsJb79d5b1pDat: -0.00500000 Waves
2025.03.07 18:03 [3533744] invoke 3NAAoJ554QsZfqE8W8Rg8LsJb79d5b1pDat > 3N9tKixzqTYWnEXQxrDQ5pBTGvQd6sFsvmV commitTask()
3N9tKixzqTYWnEXQxrDQ5pBTGvQd6sFsvmV: checked_out_by_Ct2djqZsAz77Ur5Y9pMbgrJR2xn6hDprcsHUYgLfsdkY_chatgpt_BFj4nKqrkgUidEaSHHJ8oKfHHA6V9SiD2rRfF1HHG5HA_AqqtiUWzxuW2sGQZiUBdYgDuY9J9GaL327FdWiEuh6qc: true -> null
3N9tKixzqTYWnEXQxrDQ5pBTGvQd6sFsvmV: BFj4nKqrkgUidEaSHHJ8oKfHHA6V9SiD2rRfF1HHG5HA_AqqtiUWzxuW2sGQZiUBdYgDuY9J9GaL327FdWiEuh6qc_commit_timestamp_chatgpt: 1741359816119
3N9tKixzqTYWnEXQxrDQ5pBTGvQd6sFsvmV: BFj4nKqrkgUidEaSHHJ8oKfHHA6V9SiD2rRfF1HHG5HA_AqqtiUWzxuW2sGQZiUBdYgDuY9J9GaL327FdWiEuh6qc_commit_height_chatgpt: 3533744
3N9tKixzqTYWnEXQxrDQ5pBTGvQd6sFsvmV: BFj4nKqrkgUidEaSHHJ8oKfHHA6V9SiD2rRfF1HHG5HA_AqqtiUWzxuW2sGQZiUBdYgDuY9J9GaL327FdWiEuh6qc_result_chatgpt: "Large Language Models (LLMs) are a type of artificial intelligence model designed to process and generate human language on a massive scale. These models are built using deep learning techniques, particularly variants of neural networks like transformers, which have been shown to be highly effective in processing sequential data such as text.
The key characteristic of LLMs is their ability to learn complex patterns and relationships in language by training on vast amounts of text data. This training data is typically sourced from a wide range of text sources, such as books, articles, websites, and social media posts, to ensure the model captures the diverse and nuanced characteristics of human language.
Once trained, LLMs can perform a variety of language-related tasks, such as language generation (e.g., writing essays, creating poetry), language understanding (e.g., answering questions, summarizing text), and language translation (e.g., translating between different languages).
One of the most well-known and influential LLMs is OpenAI's GPT (Generative Pre-trained Transformer) series, which includes models like GPT-3. These models have set new benchmarks in natural language processing (NLP) tasks and have demonstrated remarkable capabilities in understanding and generating human-like text.
Despite their impressive performance, LLMs also pose challenges and concerns. One major issue is bias, as these models can inadvertently learn and perpetuate biases present in the training data. Ethical considerations, such as the responsible use of LLMs and ensuring transparency in their development and deployment, are also critical aspects that need to be addressed.
In conclusion, LLMs represent a significant advancement in NLP technology and have the potential to revolutionize how we interact with and understand human language. As researchers continue to refine and improve these models, it is essential to consider the ethical implications and societal impact of deploying LLMs in various applications."
3N9tKixzqTYWnEXQxrDQ5pBTGvQd6sFsvmV: BFj4nKqrkgUidEaSHHJ8oKfHHA6V9SiD2rRfF1HHG5HA_AqqtiUWzxuW2sGQZiUBdYgDuY9J9GaL327FdWiEuh6qc_status_chatgpt: "checked_out" -> "done"
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"proofs": [
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"value": "BFj4nKqrkgUidEaSHHJ8oKfHHA6V9SiD2rRfF1HHG5HA_AqqtiUWzxuW2sGQZiUBdYgDuY9J9GaL327FdWiEuh6qc"
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"value": "Large Language Models (LLMs) are a type of artificial intelligence model designed to process and generate human language on a massive scale. These models are built using deep learning techniques, particularly variants of neural networks like transformers, which have been shown to be highly effective in processing sequential data such as text.\n\nThe key characteristic of LLMs is their ability to learn complex patterns and relationships in language by training on vast amounts of text data. This training data is typically sourced from a wide range of text sources, such as books, articles, websites, and social media posts, to ensure the model captures the diverse and nuanced characteristics of human language.\n\nOnce trained, LLMs can perform a variety of language-related tasks, such as language generation (e.g., writing essays, creating poetry), language understanding (e.g., answering questions, summarizing text), and language translation (e.g., translating between different languages).\n\nOne of the most well-known and influential LLMs is OpenAI's GPT (Generative Pre-trained Transformer) series, which includes models like GPT-3. These models have set new benchmarks in natural language processing (NLP) tasks and have demonstrated remarkable capabilities in understanding and generating human-like text.\n\nDespite their impressive performance, LLMs also pose challenges and concerns. One major issue is bias, as these models can inadvertently learn and perpetuate biases present in the training data. Ethical considerations, such as the responsible use of LLMs and ensuring transparency in their development and deployment, are also critical aspects that need to be addressed.\n\nIn conclusion, LLMs represent a significant advancement in NLP technology and have the potential to revolutionize how we interact with and understand human language. As researchers continue to refine and improve these models, it is essential to consider the ethical implications and societal impact of deploying LLMs in various applications."
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"value": "Large Language Models (LLMs) are a type of artificial intelligence model designed to process and generate human language on a massive scale. These models are built using deep learning techniques, particularly variants of neural networks like transformers, which have been shown to be highly effective in processing sequential data such as text.\n\nThe key characteristic of LLMs is their ability to learn complex patterns and relationships in language by training on vast amounts of text data. This training data is typically sourced from a wide range of text sources, such as books, articles, websites, and social media posts, to ensure the model captures the diverse and nuanced characteristics of human language.\n\nOnce trained, LLMs can perform a variety of language-related tasks, such as language generation (e.g., writing essays, creating poetry), language understanding (e.g., answering questions, summarizing text), and language translation (e.g., translating between different languages).\n\nOne of the most well-known and influential LLMs is OpenAI's GPT (Generative Pre-trained Transformer) series, which includes models like GPT-3. These models have set new benchmarks in natural language processing (NLP) tasks and have demonstrated remarkable capabilities in understanding and generating human-like text.\n\nDespite their impressive performance, LLMs also pose challenges and concerns. One major issue is bias, as these models can inadvertently learn and perpetuate biases present in the training data. Ethical considerations, such as the responsible use of LLMs and ensuring transparency in their development and deployment, are also critical aspects that need to be addressed.\n\nIn conclusion, LLMs represent a significant advancement in NLP technology and have the potential to revolutionize how we interact with and understand human language. As researchers continue to refine and improve these models, it is essential to consider the ethical implications and societal impact of deploying LLMs in various applications."
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