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  2. The Pile (dataset) - Wikipedia

    en.wikipedia.org/wiki/The_Pile_(dataset)

    The Pile is an 886.03 GB diverse, open-source dataset of English text created as a training dataset for large language models (LLMs). It was constructed by EleutherAI in 2020 and publicly released on December 31 of that year. [1] [2] It is composed of 22 smaller datasets, including 14 new ones. [1]

  3. Whisper (speech recognition system) - Wikipedia

    en.wikipedia.org/wiki/Whisper_(speech...

    Whisper is a machine learning model for speech recognition and transcription, created by OpenAI and first released as open-source software in September 2022. [2]It is capable of transcribing speech in English and several other languages, and is also capable of translating several non-English languages into English. [1]

  4. BLOOM (language model) - Wikipedia

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

    BigScience Large Open-science Open-access Multilingual Language Model (BLOOM) [1] [2] is a 176-billion-parameter transformer-based autoregressive large language model (LLM). The model, as well as the code base and the data used to train it, are distributed under free licences. [ 3 ]

  5. Claude (language model) - Wikipedia

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

    Constitutional AI is an approach developed by Anthropic for training AI systems, particularly language models like Claude, to be harmless and helpful without relying on extensive human feedback. [6] The method, detailed in the paper "Constitutional AI: Harmlessness from AI Feedback" involves two phases: supervised learning and reinforcement ...

  6. BERT (language model) - Wikipedia

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

    On October 25, 2019, Google announced that they had started applying BERT models for English language search queries within the US. [26] On December 9, 2019, it was reported that BERT had been adopted by Google Search for over 70 languages. [27] [28] In October 2020, almost every single English-based query was processed by a BERT model. [29]

  7. I studied English literature and landed a job in AI out of ...

    www.aol.com/studied-english-literature-landed...

    Ramani Akkati transitioned from studying English literature to working in AI and data science. She self-studied coding and AI through online courses and resources like MIT OpenCourseWare.