GPT-4 Technical Report
Publication/Creation Date
March 14 2023Creators/Contributors
OpenAI (creator)
Description
Abstract:
We report the development of GPT-4, a large-scale, multimodal model which can accept image and text inputs and produce text outputs. While less capable than humans in many real-world scenarios, GPT-4 exhibits human-level performance on various professional and academic benchmarks, including passing a simulated bar exam with a score around the top 10% of test takers. GPT-4 is a Transformer based model pre-trained to predict the next token in a document. The post-training alignment process results in improved performance on measures of factuality and adherence to desired behavior. A core component of this project was developing infrastructure and optimization methods that behave predictably across a wide range of scales. This allowed us to accurately predict some aspects of GPT-4’s performance based on models trained with no more than 1/1,000th the compute of GPT-4.Technology Keywords
Artificial Intelligence (AI),
Artificial General Intelligence (AGI),
Large Language Models (LLMs),
Large Multimodal Models,
Natural Language Generation (NLG),
Natural Language Processing (NLP),
Text Summarizer,
Machine Translation,
Reinforcement Learning From Human Feedback (RLHF),
Generative AI,
Visual RecognitionKeywords
Language,
Communication,
Translation,
Education,
Safety,
Ethics,
Privacy,
Bias,
Disinformation,
Information,
Trust,
Accuracy,
Economics,
Work,
Security,
Research,
Cognitive Enhancement,
AutomationSource
https://cdn.openai.com/papers/gpt-4.pdf
Date archived
March 15 2023Last edited
March 17 2023