|
gptkbp:instance_of
|
gptkb:language
|
|
gptkbp:bfsLayer
|
4
|
|
gptkbp:bfsParent
|
gptkb:Hugging_Face
gptkb:Super_GLUE_benchmark
|
|
gptkbp:application
|
dialog systems
content creation
text completion
|
|
gptkbp:architectural_style
|
gptkb:Transformers_character
|
|
gptkbp:availability
|
API access
|
|
gptkbp:collaborations
|
academic institutions
industry partners
|
|
gptkbp:developed_by
|
gptkb:Microsoft
|
|
gptkbp:field_of_study
|
gptkb:Artificial_Intelligence
gptkb:software_framework
natural language processing
|
|
gptkbp:future_plans
|
increase efficiency
enhance multilingual capabilities
improve contextual understanding
reduce biases
|
|
gptkbp:goal
|
improve human-computer interaction
assist in creative tasks
automate content generation
enhance text generation quality
|
|
gptkbp:has_ability
|
natural language generation
|
|
https://www.w3.org/2000/01/rdf-schema#label
|
Turing-NLG
|
|
gptkbp:impact
|
technology advancement
AI ethics discussions
AI policy development
job automation concerns
|
|
gptkbp:influenced_by
|
gptkb:microprocessor
deep learning
transformer models
|
|
gptkbp:is_evaluated_by
|
gptkb:BLEU
ROUGE
perplexity
|
|
gptkbp:is_open_source
|
gptkb:battle
|
|
gptkbp:language
|
English
multiple languages
|
|
gptkbp:marketed_as
|
gptkb:battle
|
|
gptkbp:orbital_period
|
17 billion
|
|
gptkbp:performance
|
state-of-the-art
|
|
gptkbp:production_company
|
gptkb:Microsoft_Research
|
|
gptkbp:provides_information_on
|
large text corpora
|
|
gptkbp:receives_funding_from
|
government grants
private investment
|
|
gptkbp:related_to
|
gptkb:GPT-3
gptkb:BERT
gptkb:Research_Institute
|
|
gptkbp:release_date
|
gptkb:2020
|
|
gptkbp:successor
|
gptkb:Turing-NLG_2.0
|
|
gptkbp:use_case
|
gptkb:language
gptkb:literary_work
question answering
chatbots
summarization
|