Only a few months after releasing ChatGPT based on the GPT 3.5 model architecture, OpenAI has released ChatGPT-4, a better and more efficient version of this language model. ChatGPT-3 grew in popularity as users discovered new and inventive ways to use the program. It has also resulted in a slew of AI firms built with the ChatGPT API. Many large corporations, like Microsoft, Stripe, and Waymark, have integrated ChatGPT into their businesses to enhance the possibilities of their services and products. ChatGPT-4 has already overtaken GPT-3.5 in its ability to answer questions and solve issues. So, let’s learn more about this amazing tool.
What Is GPT-4?
GPT-4 is a multimodal, large-scale, pre-trained generative transformer model that accepts text and image cues as input and generates related text output. Given the competitive landscape and the safety implications of large-scale models like GPT-4, OpenAI did not disclose additional details about the architecture (including model size), hardware, training compute, dataset construction, training method, or similar details. Check out this page to learn more about the GPT model and the previous version of ChatGPT.
GPT models are usually taught in two steps. They are first trained to guess the next word using a large dataset of text from the Internet. The models are then fine-tuned with more data, employing a method known as reinforcement learning from human feedback (RLHF) to produce outputs that human labelers prefer.
What Has Changed In ChatGPT-4?
ChatGPT already had numerous features far above those of most large language models and cutting-edge chatbots, and OpenAI has lately released a better version of it called ChatGPT-4. This version of ChatGPT has been trained to be more factually correct and to provide responses that are more relevant to the user’s intent than the previous version. It is also more capable of detecting and rejecting harmful and improper text cues. In some of the most realistic assessments designed to measure human intelligence and talents, ChatGPT-4 outperforms the previous version and even humans. Because some of these tests include both text and image questions, ChatGPT-4 can accept both text and image prompts from the user. GPT 4 outperforms GPT 3.5 and other big language models in English language performance and other languages in Massive Multitask Language Understanding (MMLU).
Does GPT-4 Remove The Limitations Of GPT-3.5?
Although the GPT-4 model beats the GPT-3.5 model in many features and tests, it retains some of the model’s drawbacks from prior versions. It “hallucinates” and can confidently provide incorrect facts and information to the user. As a result, it should not be utilized to retrieve information in critical situations when accuracy is vital. Because GPT-4 does not learn from experience, its knowledge may be limited to what it knew when it was trained. Furthermore, it can fail at reasoning and solving difficult problems, and it can accept false assertions from the user. Although OpenAI has removed most of these constraints from the GPT-4 model, some instances may still occur. Both GPT-3.5 and GPT-4 continue to reinforce detrimental stereotypes and degrading connections for certain underrepresented groups.
To reduce the frequency of such answers in GPT-4, OpenAI has implemented numerous additional risk mitigation methods. They invited over 50 experts from disciplines such as long-term AI alignment concerns, cybersecurity, biorisk, and international security to adversarially test the model in order to identify the scope of these hazards. GPT-4 features an extra set of safety-relevant RLHF training prompts and rule-based reward models (RBRMs) in addition to the original RLHF fine-tuning. The rule-based reward models (RBRMs) are a collection of GPT-4 zero-shot classifiers. During RLHF fine-tuning, these classifiers give an extra incentive signal to the GPT-4 policy model that targets the right behavior, such as declining to generate damaging content or refusing harmless requests.
Future Goals For The Next Version Of ChatGPT
Despite the fact that OpenAI has developed several safety measures to make ChatGPT-4 more trustworthy, safe, and efficient than earlier versions, it can nevertheless generate misleading or harmful content at times. They intend to address this issue further in future editions of ChatGPT by incorporating feedback from the use of ChatGPT-4 as more people use it for varied reasons. They will also have many levels of security as future versions become more powerful, such as adjustments to the model itself, oversight and monitoring of model usage, and product design for safe usage. They will also guarantee that these safety assessments cover emerging threats.
ChatGPT-4, as well as many other new and powerful language models, have demanded substantial research into the economic and social implications of such models for society. Automation of diverse tasks that require human abilities now has the potential to have a significant impact on the economic sector as AI begins to replace jobs. As a result, it is critical to have a well-structured plan in place to ensure that such transitions in all areas are as seamless as possible for society. Furthermore, more research in related areas like AI literacy, effective evaluation methods for such AI models, and technological advances in model safety is required.