GPT 4 is the latest model addition to OpenAI’s deep learning efforts and is a significant milestone in scaling deep learning. GPT 4 is also the first of the GPT models that is a large multimodal model, meaning it accepts both image and text inputs and emits text outputs.
What GPT-4 can do?
Since GPT 4 is a large multimodal model, it is able to accept both text and image inputs and output human-like text. The intellectual capabilities are also more improved in this model, outperforming GPT 3.5 in a series of simulated benchmark exams, as seen by the chart below.
What does GPT-4 do differently?
GPT 4 boasts several new impressive capabilities. These advancements are just a glimpse of what GPT 4 can do, and OpenAI plans to release further analyses and evaluation numbers soon.
Ability to process text and images together represents a major step forward in language modeling. This means it can now handle tasks involving both vision and language, such as generating captions for images or answering questions about a video.
OpenAI’s demo showed off this update with style. GPT 4 took a photo of a hand-written website mock-up and turned it into a colorful website in a matter of moments. Initial results suggest that GPT 4 can perform similarly to state-of-the-art vision models on various tasks.
What was Before GPT 4?
The current AI revolution for natural language only became possible with the invention of transformer models, starting with Google’s BERT in 2017.
Before this, text generation was performed with other deep learning models, such as recursive neural networks and long short-term memory neural networks. These performed well for outputting single words or short phrases but could not generate realistic longer content.
BERT’s transformer approach was a major breakthrough since it is not a supervised learning technique. That is, it did not require an expensive annotated dataset to train it. BERT was used by Google for interpreting natural language searches, however, it cannot generate text from a prompt.
What is GPT-1?
In 2018, OpenAI published a paper (Improving Language Understanding by Generative Pre-Training) about using natural language understanding using their GPT-1 language model. This model was a proof-of-concept and was not released publicly.
What is GPT 2?
OpenAI published another paper about their latest model, GPT 2. This time, the model was made available to the machine learning community and found some adoption for text generation tasks. GPT 2 could often generate a couple of sentences before breaking down. This was state-of-the-art in 2019.
What is GPT 3
In 2020, OpenAI published another paper about their GPT-3 model. The model had 100 times more parameters than GPT-2 and was trained on an even larger text dataset, resulting in better model performance.
The model continued to be improved with various iterations known as the GPT-3.5 series, including the conversation-focused ChatGpt.
This version took the world by storm after surprising the world with its ability to generate pages of human-like text. ChatGPT became the fastest-growing web application ever, reaching 100 million users in just two months.
What is New in GPT-4 other then Previous Versions of ChatGpt?
GPT 4 has been developed to improve model alignment. Ability to follow user intentions while also making it more truthful and generating less offensive or dangerous output.
Key Improvements in GPT 4
GPT 4 is much improved from GPT 3.5 models regarding the factual correctness of answers. The number of illusions, where the model makes factual or reasoning errors, is lower, with GPT 4 scoring 40% higher than GPT 3.5.
It also improves steerability, which is the ability to change its behavior according to user requests. For example, you can command it to write in a different style or tone or voice. You can read more about designing great prompts for GPT models here.
A further improvement is in the model’s adherence to handle. If you ask it to do something illegal, it is better at refusing the request.
How to use Visual Inputs in GPT 4?
One major change is that GPT 4 can use image inputs and text. Users can specify any vision or language task by entering interspersed text and images.
OpenAI is releasing GPT 4 text input capability via ChatGPT. It is currently available to ChatGPT Plus users. There is a waitlist for the GPT 4 API. Public availability of the image input capability has not yet been announced.
OpenAI has open-sourced OpenAI Evals, a framework for automated evaluation of AI model performance, to allow anyone to report shortcomings in their models and guide further improvements.
Difference between GPT 4 and GPT3.5
The main difference between the models is that because GPT 4 is multimodal, it can use image inputs in addition to text, whereas GPT 3.5 can only process text inputs.
The distinction between GPT 3.5 and GPT 4 will be subtle in casual conversation, according to OpenAI. However, the new model will be more capable in terms of reliability, creativity, and even intelligence as seen by the higher performance on benchmark.
Can GPT-4 give Wrong Answers?
GPT 4 has similar limitations as previous GPT models. OpenAI even says that this model is, not fully reliable. Despite the warning, OpenAI says GPT 4 hallucinates less often than previous models with GPT 4 scoring 40% higher than GPT 3.5 in an internal adversarial factuality evaluation. The chart is included below.
GPT 4 refers to a hypothetical next iteration of OpenAI’s GPT series of language models. Developing a language model like GPT 4 is a complex and time-consuming process that requires significant resources and expertise, so it may be some time before it is released.
However, if and when GPT-4 is developed, it may offer improvements in language generation, natural language processing, and enable more advanced language-based applications. In the meantime, the existing GPT models continue to be used in a wide range of applications and are constantly being improved and refined.
What are language models?
Language models are artificial intelligence models that can generate human-like text based on a given input. They are trained on massive amounts of text data and use complex algorithms to learn patterns in language and generate responses.
What are the benefits of GPT-4?
If and when GPT 4 is developed, it may offer improvements in language generation, natural language processing, and other related fields. It may also enable more advanced language-based applications, such as chatbots and language translation tools.
How does GPT-4 differ from previous versions of GPT?
It is impossible to say how GPT-4 would differ from previous versions of GPT, as it does not exist yet. However, based on the improvements seen from previous versions of GPT, it may offer more advanced language processing capabilities and better accuracy in generating human-like text.