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  2. Stochastic parrot - Wikipedia

    en.wikipedia.org/wiki/Stochastic_parrot

    Stochastic parrot is now a neologism used by AI skeptics to refer to machines' lack of understanding of the meaning of their outputs and is sometimes interpreted as a "slur against AI". [6] Its use expanded further when Sam Altman, CEO of Open AI, used the term ironically when he tweeted, "i am a stochastic parrot and so r u."

  3. Timnit Gebru - Wikipedia

    en.wikipedia.org/wiki/Timnit_Gebru

    Gebru had coauthored a paper on the risks of large language models (LLMs) acting as stochastic parrots, and submitted it for publication. According to Jeff Dean, the paper was submitted without waiting for Google's internal review, which then concluded that it ignored too much relevant research. Google management requested that Gebru either ...

  4. Large language model - Wikipedia

    en.wikipedia.org/wiki/Large_language_model

    Advances in software and hardware have reduced the cost substantially since 2020, such that in 2023 training of a 12-billion-parameter LLM computational cost is 72,300 A100-GPU-hours, while in 2020 the cost of training a 1.5-billion-parameter LLM (which was two orders of magnitude smaller than the state of the art in 2020) was between $80,000 ...

  5. File:On the Dangers of Stochastic Parrots Can Language Models ...

    en.wikipedia.org/wiki/File:On_the_Dangers_of...

    English: The past 3 years of work in NLP have been characterized by the development and deployment of ever larger language models, especially for English. BERT, its variants, GPT-2/3, and others, most recently Switch-C, have pushed the boundaries of the possible both through architectural innovations and through sheer size.

  6. Generative artificial intelligence - Wikipedia

    en.wikipedia.org/wiki/Generative_AI

    There is free software on the market capable of recognizing text generated by generative artificial intelligence (such as GPTZero), as well as images, audio or video coming from it. [99] Potential mitigation strategies for detecting generative AI content include digital watermarking , content authentication , information retrieval , and machine ...

  7. Q-learning - Wikipedia

    en.wikipedia.org/wiki/Q-learning

    Q-learning is a model-free reinforcement learning algorithm that teaches an agent to assign values to each action it might take, conditioned on the agent being in a particular state. It does not require a model of the environment (hence "model-free"), and it can handle problems with stochastic transitions and rewards without requiring ...

  8. Jimmy Buffett's beloved 'Parrotheads' are carrying on his ...

    www.aol.com/entertainment/jimmy-buffetts-beloved...

    Ask any Jimmy Buffett fan and they’ll tell you that his music isn’t just catchy, it’s a state of mind.. Widely known for hits like “Margaritaville,” “It’s 5 O’Clock Somewhere ...

  9. Chinchilla (language model) - Wikipedia

    en.wikipedia.org/wiki/Chinchilla_(language_model)

    Based on the training of previously employed language models, it has been determined that if one doubles the model size, one must also have twice the number of training tokens. This hypothesis has been used to train Chinchilla by DeepMind. Similar to Gopher in terms of cost, Chinchilla has 70B parameters and four times as much data. [3]