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  2. Perplexity AI - Wikipedia

    en.wikipedia.org/wiki/Perplexity_AI

    Perplexity AI is a conversational ... The free model uses the company's standalone LLM based ... allowing for more seamless task management. [15] The Perplexity ...

  3. Perplexity - Wikipedia

    en.wikipedia.org/wiki/Perplexity

    The base of the logarithm need not be 2: The perplexity is independent of the base, provided that the entropy and the exponentiation use the same base. In some contexts, this measure is also referred to as the (order-1 true) diversity. Perplexity of a random variable X may be defined as the perplexity of the distribution over its possible ...

  4. Large language model - Wikipedia

    en.wikipedia.org/wiki/Large_language_model

    A large language model (LLM) is a type of machine learning model designed for natural language processing tasks such as language generation.LLMs are language models with many parameters, and are trained with self-supervised learning on a vast amount of text.

  5. Wikipedia : Using neural network language models on Wikipedia

    en.wikipedia.org/wiki/Wikipedia:Using_neural...

    Experienced editors may ask an LLM to improve the grammar, flow, or tone of pre-existing article text. Rather than taking the output and pasting it directly into Wikipedia, you must compare the LLM's suggestions with the original text, and thoroughly review each change for correctness, accuracy, and neutrality. Summarizing a reliable source.

  6. Master of Laws - Wikipedia

    en.wikipedia.org/wiki/Master_of_Laws

    In South Africa, the LL.M. is a postgraduate degree offered both as a course-based and research-based master's degree. In the former case, the degree comprises advanced coursework in a specific area of law as well as limited related research, usually in the form of a short dissertation, while in the latter, the degree is entirely thesis based.

  7. Retrieval-augmented generation - Wikipedia

    en.wikipedia.org/wiki/Retrieval-augmented_generation

    Retrieval-Augmented Generation (RAG) is a technique that grants generative artificial intelligence models information retrieval capabilities. It modifies interactions with a large language model (LLM) so that the model responds to user queries with reference to a specified set of documents, using this information to augment information drawn from its own vast, static training data.

  8. Institute for the Study of Knowledge Management in Education

    en.wikipedia.org/wiki/Institute_for_the_Study_of...

    ISKME's initial research focused on the capacity of college faculty and administrators to use educational data to inform decision-making as well as knowledge management in the philanthropic sector. In 2002, ISKME conducted a study for grantmakers in education on the sharing of data and information among foundations.

  9. Prompt engineering - Wikipedia

    en.wikipedia.org/wiki/Prompt_engineering

    GraphRAG [40] (coined by Microsoft Research) is a technique that extends RAG with the use of a knowledge graph (usually, LLM-generated) to allow the model to connect disparate pieces of information, synthesize insights, and holistically understand summarized semantic concepts over large data collections. It was shown to be effective on datasets ...

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