chatgtp4技术报告英文版

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 thanhumans in many real-world scenarios, GPT-4 exhibits human-level performanceon various professional and academic benchmarks, including passing a simulatedbar 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-trainingalignment process results in improved performance

on measures of factuality and

adherence to desired behavior. A core component of this project was developinginfrastructure and optimization methods that behave predictably across a widerange of scales. This allowed us to accurately predict some aspects of GPT-4'sperformance based on models trained with no more than 1/1,000th the compute ofGPT-4.