GPT-4 Not Available

TODO: collapasable, copyable, download, etc

Is this GPT-4?As an AI language model, I do not have a specific name or version number like GPT-4. I am a product of ongoing research and development by OpenAI, and I am designed to continually improve as new data and techniques become available. I am a continuation of the GPT series of language models, which includes GPT, GPT-2, and GPT-3, but I am not specifically designated as GPT-4.How much of a text buffer can you acceptAs an AI language model, I can process and generate text dynamically, so I do not have a fixed buffer size for accepting input. The amount of text I can accept depends on various factors, such as the complexity of the input, the available computational resources, and the specific interface being used to interact with me.

In general, I can accept input ranging from a few words or a short phrase to several paragraphs or even entire documents. However, to ensure the best performance and accuracy, it is usually best to provide me with input in reasonably-sized chunks, rather than extremely long passages of text. This allows me to process the input more efficiently and generate higher-quality responses.Given the following launch announcement, what would be an insightful comment to put onto Hacker News?

We’ve created GPT-4, the latest milestone in OpenAI’s effort in scaling up deep learning. 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. For example, it passes a simulated bar exam with a score around the top 10% of test takers; in contrast, GPT-3.5’s score was around the bottom 10%. We’ve spent 6 months iteratively aligning GPT-4 using lessons from our adversarial testing program as well as ChatGPT, resulting in our best-ever results (though far from perfect) on factuality, steerability, and refusing to go outside of guardrails.

Over the past two years, we rebuilt our entire deep learning stack and, together with Azure, co-designed a supercomputer from the ground up for our workload. A year ago, we trained GPT-3.5 as a first “test run” of the system. We found and fixed some bugs and improved our theoretical foundations. As a result, our GPT-4 training run was (for us at least!) unprecedentedly stable, becoming our first large model whose training performance we were able to accurately predict ahead of time. As we continue to focus on reliable scaling, we aim to hone our methodology to help us predict and prepare for future capabilities increasingly far in advance—something we view as critical for safety.

We are releasing GPT-4’s text input capability via ChatGPT and the API (with a waitlist). To prepare the image input capability for wider availability, we’re collaborating closely with a single partner to start. We’re also open-sourcing OpenAI Evals, our framework for automated evaluation of AI model performance, to allow anyone to report shortcomings in our models to help guide further improvements. Capabilities

In a casual conversation, the distinction between GPT-3.5 and GPT-4 can be subtle. The difference comes out when the complexity of the task reaches a sufficient threshold—GPT-4 is more reliable, creative, and able to handle much more nuanced instructions than GPT-3.5.

To understand the difference between the two models, we tested on a variety of benchmarks, including simulating exams that were originally designed for humans. We proceeded by using the most recent publicly-available tests (in the case of the Olympiads and AP free response questions) or by purchasing 2022–2023 editions of practice exams. We did no specific training for these exams. A minority of the problems in the exams were seen by the model during training, but we believe the results to be representative—see our technical report for details.

We also evaluated GPT-4 on traditional benchmarks designed for machine learning models. GPT-4 considerably outperforms existing large language models, alongside most state-of-the-art (SOTA) models which may include benchmark-specific crafting or additional training protocols:

"Congratulations to the OpenAI team on the release of GPT-4! It's exciting to see the progress in scaling up deep learning and achieving human-level performance on professional and academic benchmarks. The collaboration with Azure on a custom supercomputer is also impressive. I'm particularly interested in the open-sourcing of OpenAI Evals, which could help identify shortcomings in AI models and guide further improvements. Looking forward to seeing the impact of GPT-4 and future advancements in AI!"

GPT-4 Not Available created at Tue Jan 20 1970 10:20:14 GMT+0000 (Coordinated Universal Time)