Unsupervised and self-supervised learning, or learning without human-labeled data, is a longstanding challenge of machine learning.
Recently, it has seen incredible success in language, as transformer models like BERT,3 GPT-2, RoBERTa, T5, and other variants have achieved top performance on a wide array of language tasks.
However, the same broad class of models has not been successful in producing strong features for image classification. Our work aims to understand and bridge this gap.
Transformer models like BERT and GPT-2 are domain agnostic, meaning that they can be directly applied to 1-D sequences of any form.
When we train GPT-2 on images unrolled into long sequences of pixels, which we call iGPT, we find that the model appears to understand 2-D image characteristics such as object appearance and category.
This is evidenced by the diverse range of coherent image samples it generates, even without the guidance of human provided labels.
As further proof, features from the model achieve state-of-the-art performance on a number of classification datasets and near state-of-the-art unsupervised accuracy on ImageNet.
Image GPT:
Chatgpt is getting new every day. The recently introduced vision feature is proof of this. Normally we type sentences in chatgpt and ask questions.
Chatgpt is getting new every day. The recently introduced vision feature is proof of this. Normally we type sentences in chatgpt and ask questions. With the advent of the Win feature, it is possible to upload images as well. For example- what about uploading a photo of vegetables in the fridge? What dishes can be made with them? Don't ask. That's what it says. You can upload complex graph images and try to analyze them. Many people are already using it. If you know who is using its capabilities, you have to say Aura. But for now ChatGPT facility is available only for Plus and Enterprise users. May be extended to developers soon.
To learn:
The vision feature is great for students and those who want to understand things. That's why some are using the text in the form of images to make it easier to understand. For example- upload a human cell diagram and what are its parts? How do they work? Imagine asking that. Lists all of them in order including names. Their performance is also detailed. What more is needed to understand science lessons easily?
Description of complex messages:
Sometimes pictures don't mean things. So what does this mean? It is normal to nod. Now there is no need for such trouble. Just upload the image and ask chatgpt to explain it. If a user uploads an image with some incomprehensible figures and asks to explain its meaning, all the points are mentioned separately, along with the analysis and puzzled.
Identification of Movie Scenes:
That's not all of ChatGPT's vision intelligence. It can also recognize movie scenes. Someone uploaded a photo of an English movie and asked 'Which movie is this from? What does he mean?' he asked. Not only that it is a scene from the movie Gladiator.. She also explained in a pinch the name of the character and what he said in that scene. Everything is great vision.
To write codes:
Users are also taking advantage of ChatGPT's multimodal capabilities. After discussing with the team, the maps drawn on the white board are being uploaded. The task of writing the appropriate code is also assigned. Oh, that's it? Ani Vision is also writing code in a pinch. That is, if you have any idea about a computer program, draw it on paper and submit it to chatgpt.
Explanation of Parking Signs:
Some are also handing over complicated parking signs to ChatGPT. They are asking to tell whether vehicles can be parked there or not. Has chatgpt eaten anything less? When asked like this, it gives accurate answers. This will save you from getting fined in parking lots.
Second opinion:
What should a painter do to make his drawing look more realistic? ChatGPT was asked. It surprisingly detects the content of the uploaded figure and suggests where to make changes. She also made good suggestions for another film. ChatGPT Vision can be used to get a second opinion on any matter. Doll-e created dolls can also be used to criticize.
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