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Large Language Model: A Guide To The Question ‘What Is An LLM”
- Large language models (LLMs) are artificial intelligence systems trained on vast amounts of data that can understand and generate human language.
- LLMs use deep learning technology and natural language processing (NLP) to perform an array of tasks, including text classification, sentiment analysis, code creation, and query response.
- Advancements in AI and generative AI are pushing the boundaries of what was once considered far-fetched in the computing sector.
- LLMs bridge the gap between human understanding and machine learning to offer a better content output.
- LLMs continue to improve their ability to provide logical and trustworthy responses across many complex knowledge sectors.
- Pre-trained language representation models (LRM) can be fine-tuned for specific tasks like text classification and language generation.
- LLMs are highly beneficial for problem-solving and helping businesses with communication-related tasks.
- LLMs can generate natural-sounding translations across multiple languages, enable code and text generation, and perform tasks with minimal training examples or without any training at all.
- Large language models have challenges and limitations that may affect their efficacy and real-world usefulness.
- Duke University's specialized course teaches students about developing, managing, and optimizing LLMs across multiple platforms, including Azure, AWS, and Databricks.
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