GPT-4: how to use the AI chatbot that puts ChatGPT to shame

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 plan to release further analyses and evaluation numbers as well as thorough investigation of the effect of test-time techniques soon. 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. 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 are releasing GPT-4’s text input capability via ChatGPT and the API (with a waitlist).

What’s different about GPT-4?

GPT-4 incorporates an additional safety reward signal during RLHF training to reduce harmful outputs (as defined by our usage guidelines) by training the model to refuse requests for such content. The reward is provided by a GPT-4 zero-shot classifier judging safety boundaries and completion style on safety-related prompts. Wouldn’t it be nice if ChatGPT were better at paying attention to the fine detail of what you’re requesting in a prompt?

Most people will use this technology through a new version of the company’s ChatGPT chatbot, while businesses will incorporate it into a wide variety of systems, including business software and e-commerce websites. The technology already drives the chatbot available to a limited number of people using Microsoft’s Bing search engine. Now the company is back with a new version of the technology that powers its chatbots. The system will up the ante in Silicon Valley’s race to embrace artificial intelligence and decide who will be the next generation of leaders in the technology industry. Chatbot that captivated the tech industry four months ago has improved on its predecessor.

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Overall, our model-level interventions increase the difficulty of eliciting bad behavior but doing so is still possible. Additionally, there still exist “jailbreaks” to generate content which violate our usage guidelines. Our mitigations have significantly improved many of GPT-4’s safety properties compared to GPT-3.5. We’ve decreased the model’s tendency to respond to requests for disallowed content by 82% compared to GPT-3.5, and GPT-4 responds to sensitive requests (e.g., medical advice and self-harm) in accordance with our policies 29% more often. We are releasing Whisper large-v3, the next version of our open source automatic speech recognition model (ASR) which features improved performance across languages. Another highlight of the model is that it can support image-to-text, known as GPT-4 Turbo with Vision, which is available to all developers who have access to GPT-4.

Even after paying $20 a month, you aren’t guaranteed a specific number of prompts from the GPT-4 model per day. OpenAI says clearly that the company will change the maximum number of allowed prompts at any time. While I was testing it out on a Friday afternoon, the cap was set at 50 messages for four hours. When I returned on Monday morning, the site new chat gpt 4 was glitchy and the cap was lowered to 25 messages for three hours. GPT-4 can also be confidently wrong in its predictions, not taking care to double-check work when it’s likely to make a mistake. Interestingly, the base pre-trained model is highly calibrated (its predicted confidence in an answer generally matches the probability of being correct).

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However, as we noted in our comparison of GPT-4 versus GPT-3.5, the newer version has much slower responses, as it was trained on a much larger set of data. It’s more capable than ChatGPT and allows you to do things like fine-tune a dataset to get tailored results that match your needs. OpenAI, the company behind the viral chatbot ChatGPT, has announced the release of GPT-4. At one point in the demo, GPT-4 was asked to describe why an image of a squirrel with a camera was funny.

• GPT-4 is a new language model created by OpenAI that can generate text that is similar to human speech.
• OpenAI, the company behind the viral chatbot ChatGPT, has announced the release of GPT-4.
• We are processing requests for the 8K and 32K engines at different rates based on capacity, so you may receive access to them at different times.
• GPT-4 was officially announced on March 13, as was confirmed ahead of time by Microsoft, even though the exact day was unknown.

The data is a web-scale corpus of data including correct and incorrect solutions to math problems, weak and strong reasoning, self-contradictory and consistent statements, and representing a great variety of ideologies and ideas. The model can have various biases in its outputs—we have made progress on these but there’s still more to do. 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.