enow.com Web Search

Search results

  1. Results from the WOW.Com Content Network
  2. GPT-3 - Wikipedia

    en.wikipedia.org/wiki/GPT-3

    GPT-3 is capable of performing zero-shot and few-shot learning (including one-shot). [ 1 ] In June 2022, Almira Osmanovic Thunström wrote that GPT-3 was the primary author on an article on itself, that they had submitted it for publication, [ 24 ] and that it had been pre-published while waiting for completion of its review.

  3. List of large language models - Wikipedia

    en.wikipedia.org/wiki/List_of_large_language_models

    The first of a series of free GPT-3 alternatives released by EleutherAI. GPT-Neo outperformed an equivalent-size GPT-3 model on some benchmarks, but was significantly worse than the largest GPT-3. [25] GPT-J: June 2021: EleutherAI: 6 [26] 825 GiB [24] 200 [27] Apache 2.0 GPT-3-style language model Megatron-Turing NLG: October 2021 [28 ...

  4. 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.

  5. 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. The largest and most capable LLMs are generative pretrained transformers (GPTs).

  6. Prompt engineering - Wikipedia

    en.wikipedia.org/wiki/Prompt_engineering

    Large language models like GPT-4 can have accurately calibrated likelihood scores in their token predictions, [45] and so the model output uncertainty can be directly estimated by reading out the token prediction likelihood scores. But if one cannot access such scores (such as when one is accessing the model through a restrictive API ...

  7. OpenAI o3 - Wikipedia

    en.wikipedia.org/wiki/OpenAI_o3

    Reinforcement learning was used to teach o3 to "think" before generating answers, using what OpenAI refers to as a "private chain of thought".This approach enables the model to plan ahead and reason through tasks, performing a series of intermediate reasoning steps to assist in solving the problem, at the cost of additional computing power and increased latency of responses.

  8. AOL Mail

    mail.aol.com

    Get AOL Mail for FREE! Manage your email like never before with travel, photo & document views. Personalize your inbox with themes & tabs. You've Got Mail!

  9. Neural machine translation - Wikipedia

    en.wikipedia.org/wiki/Neural_machine_translation

    Instead of fine-tuning a pre-trained language model on the translation task, sufficiently large generative models can also be directly prompted to translate a sentence into the desired language. This approach was first comprehensively tested and evaluated for GPT 3.5 in 2023 by Hendy et al.