GPT-4-assisted safety research GPT-4’s advanced reasoning and instruction-following capabilities expedited our safety work. We used GPT-4 to help create training data for model fine-tuning and iterate on classifiers across training, evaluations, and monitoring.
GPT-4 Technical Report OpenAI 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
There are a few different GPT-4 models to choose from, including a new generation of GPT-4 models. There are a few main things to consider (not an exhaustive list) when choosing which GPT-4 model to use:
2023年3月14日 · GPT-4 is a large multimodal model (accepting image and text inputs, emitting text outputs) that, while less capable than humans in many real-world scenarios, exhibits human-level performance on various professional and academic benchmarks.
facilitated a preliminary model evaluation by the Alignment Research Center (ARC) of GPT-4’s ability to carry out actions to autonomously replicate 5 and gather resources—a risk that, while speculative, may become possible with sufficiently advanced AI systems—with the …
2024年5月13日 · As measured on traditional benchmarks, GPT-4o achieves GPT-4 Turbo-level performance on text, reasoning, and coding intelligence, while setting new high watermarks on multilingual, audio, and vision capabilities.
GPT-4V refers to the technology that enables the integration of multimodal vision capabilities with GPT-4. Our current body of work consists of multiple resources:
2024年12月8日 · The best alternative for you may be the one with the least changes in the model architecture, if you want to continue your application with similar performance, without needing complete re-evaluation and redesign of prompting to reach objectives.
2023年9月25日 · In this system card, we analyze the safety properties of GPT-4V. Our work on safety for GPT-4V builds on the work done for GPT-4 and here we dive deeper into the evaluations, preparation, and mitigation work done specifically for image inputs.
2024年11月20日 · Implementing the GPT-2 architecture involves coding the various components of the model, including the self-attention layers, feed-forward networks, and positional encoding. The following steps outline the process: