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  2. Prompt engineering - Wikipedia

    en.wikipedia.org/wiki/Prompt_engineering

    Self-refine [38] prompts the LLM to solve the problem, then prompts the LLM to critique its solution, then prompts the LLM to solve the problem again in view of the problem, solution, and critique. This process is repeated until stopped, either by running out of tokens, time, or by the LLM outputting a "stop" token.

  3. 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.As language models, LLMs acquire these abilities by learning statistical relationships from vast amounts of text during a self-supervised and semi-supervised training process.

  4. List of datasets for machine-learning research - Wikipedia

    en.wikipedia.org/wiki/List_of_datasets_for...

    Website with research, news, and perspectives bout security topics. This data is not pre-processed Reviewed list of Trendmicro research, news, and perspectives. [380] The Hacker News News about cybersecurity topics. This data is not pre-processed data breaches, cyberattacks, vulnerabilities, malware news. [381] Krebsonsecurity

  5. Generative pre-trained transformer - Wikipedia

    en.wikipedia.org/wiki/Generative_pre-trained...

    Generative pretraining (GP) was a long-established concept in machine learning applications. [16] [17] It was originally used as a form of semi-supervised learning, as the model is trained first on an unlabelled dataset (pretraining step) by learning to generate datapoints in the dataset, and then it is trained to classify a labelled dataset.

  6. 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.

  7. Why Emperor Penguin Populations are Declining - AOL

    www.aol.com/why-emperor-penguin-populations...

    These birds stand anywhere from 3.5 to 4.3 feet and can weigh anywhere from 50-90 pounds. You can tell them apart from other penguins by their distinct black and white plumage.

  8. KFC's New Holiday Meal Deals and Festive Clothing Make the ...

    www.aol.com/kfcs-holiday-meal-deals-festive...

    1. What's Available to Wear? The streetwear-inspired, KFC-branded collection includes sweatshirts, T-shirts, a festive sweater, a hoodie, a beanie, socks, a tumbler, coffee mug, and even wrapping ...

  9. Wikipedia:Large language models - Wikipedia

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

    This page in a nutshell: Avoid using large language models (LLMs) to write original content or generate references. LLMs can be used for certain tasks (like copyediting, summarization, and paraphrasing) if the editor has substantial prior experience in the intended task and rigorously scrutinizes the results before publishing them.