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Large Language Model
https://en.wikipedia.org/wiki/Large_language_model


 * language model characterized by emergent properties enabled by its large size
 * built with artificial neural networks,
 * (pre-)trained using self-supervised learning and semi-supervised learning, typically containing tens of millions to billions of weights.
 * trained using specialized AI accelerator hardware to parallel process vast amounts of text data, mostly scraped from the internet.
 * As language models, they
 * work by taking an input text and repeatedly predicting the next token or word.
 * The 2017 discovery of the transformer architecture has helped drive a series of breakthroughs using LLMs.

Specialized supervised models for specific linguistic tasks, have been made largely obsolete by the emergent abilities of LLMs.

LLMs are thought to


 * acquire embodied knowledge about syntax, semantics and "ontology" inherent in human language corpora,
 * but also inaccuracies and biases present in the corpora.

Notable LLMs include


 * GPT-4,
 * LLaMa,
 * PaLM,
 * BLOOM,
 * Ernie 3.0 Titan, and
 * Claude.

https://en.wikipedia.org/wiki/Machine_learning

https://en.wikipedia.org/wiki/Active_learning_(machine_learning)

https://en.wikipedia.org/wiki/Crowdsourcing

https://en.wikipedia.org/wiki/Human-in-the-loop

https://en.wikipedia.org/wiki/ChatGPT

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