What is GPT-4 Vision?
GPT-4 Vision (GPT-4V) is a model that allows the user to upload an image as input and interact with the model in conversation.
The conversation may include questions or instructions in the form of Prompt, directing the model to perform tasks based on the input provided as an image.
GPT-4 Vision Key Capabilities
Visual inputs : The main feature of the newly released GPT-4 Vision is that it can now accept visual content such as photographs, screenshots, and documents and perform a variety of tasks.
Object detection and analysis : The model can identify and provide information about the objects in the images.
Data analysis : GPT-4 Vision is proficient in interpreting and analyzing data presented in visual formats such as graphs, charts, and other data visualizations.
Decrypting text : The model is capable of reading and interpreting handwritten notes and text in images.
The GPT-4V model is built on the existing capabilities of GPT-4, offering visual analysis in addition to the textual interaction features that exist today.
Getting Started: Getting Started with GPT-4 Vision
GPT-4 Vision is currently (as of October 2023) available for ChatGPT Plus and Enterprise users only.
ChatGPT Plus costs $20/month, which you can upgrade from your free regular ChatGPT accounts.
If you are completely new to ChatGPT, here's how you can access GPT-4 Vision:
- Visit the OpenAI ChatGPT website and register to create an account.
- Log in to your account and navigate to the “Upgrade to Plus” option.
- Follow the upgrade to access ChatGPT Plus (Note: it's a $20 monthly subscription)
- Select “GPT-4” as your model in the chat window, as shown in the diagram below.
- Click on the image icon to download the image, and add a prompt asking GPT-4 to execute it.
In the world of AI, this task is known as object detection, which is very useful in numerous projects, such as the well-known autonomous car.
Let's look at some concrete examples right now.
GPT-4 Vision Real Examples and Use Cases
Now that we have understood its capabilities, let's extend them to some practical applications in industry:
1. Academic research
The integration of GPT-4 Vision of advanced language modeling with visual capabilities opens up new possibilities in academic fields, especially in deciphering historical manuscripts.
This task has traditionally been a painstaking and time-consuming undertaking carried out by qualified paleographers and historians.
2. Web development
The GPT-4 Vision can write code for a website when provided with a visual image of the required design.
It goes from a visual design to the source code for a website.
This unique capability of the model can dramatically reduce the time taken to build websites.
Likewise, it can be used to quickly understand what a piece of code means for academic or engineering purposes:
3. Data interpretation
The model is capable of analyzing data visualizations to interpret the underlying data and provide key insights based on the visualizations.
4. Creative content creation
With the advent of ChatGPT, social networks are filled with various prompt engineering techniques, and many have found surprising and creative ways to use generative technology to their advantage.
For example, with the recent release of GPTs, it is now possible to integrate the GPT-4V function into any automated process.
READ MORE: Link to the GPTS PikGenerator
GPT-4 Vision Limits and Risk Management
There is one last thing you should be aware of before using GPT-4 Vision in use cases — the limitations and associated risks.
- Precision and reliability : While the GPT-4 model represents significant progress toward reliability and accuracy, this is not always the case.
- Privacy and bias concerns : According to OpenAI, similar to its predecessors, GPT-4 Vision continues to reinforce social biases and worldviews.
- Restricted for risky tasks : GPT-4 Vision is unable to answer questions that require the identification of specific individuals in an image.
Conclusion
This tutorial has provided you with a comprehensive introduction to the newly released GPT-4 Vision model. You have also been warned about the limitations and risks that the model poses, and now understand how and when to use the model.
The most practical way to master the new technology is to get your hands on it and experiment by providing various prompts to assess its capabilities, and over time, you'll feel more comfortable with it.
Although this is a relatively new tool and is one month old, it is built on the principles of Large-Scale Language Models and GPT-4