Chat-GPT
As artificial intelligence (AI) continues to develop, so do the capabilities of large language models (LLMs). Using machine learning and deep training algorithms, these models are becoming proficient in generating and understanding human language to simplify and facilitate human-machine interactions.
Microsoft took a giant leap in this area by introducing Visual GPT shortly after introducing Chat GPT in conjunction with OpenAI. This artificial intelligence metaphor uses the Visual Foundation Model (VFM) to make the visual understanding, presentation, and editing process more efficient and yield better results.
ChatGPT is a language model trained extensively on a large set of texts and human interactions to produce consistent and grammatically correct results for a wide variety of dialogues and queries. Microsoft didn’t stop there and looked at whether Chat GPT could go beyond words and sentences. Can it think about how its functions can become helpful to humans in successfully and easily performing various tasks in the physical and virtual worlds?
With this thought in mind, Microsoft has released its latest invention, Visual GPT. It is a revolutionary tool that can generate an accurate caption or description for images using AI. It allows its users to cleanly highlight any object or part of the photos. This makes it easier for people with low vision to understand visual content. It is able to create images based on dialogue and signs. and can enhance the image as desired by the use of continuous dialogue and additional cues.
They say that a picture is worth a thousand words. So based on this concept, Visual GPT is an extraordinary innovation that goes beyond the limitations of AI-powered communication at present, bridging the gap between language and visuals and strengthening the machine-human relationship by making it more engaging, dynamic and interactive. Opens new doors of possibilities.
Image-GPT combines a variety of Visual Foundation models for generating an image and understanding and editing the information it contains. This technique also uses Control-Net, Stable Fusion and Stable Diffusion along with the visual foundation model.
This technology can have many possible uses like while shopping online a customer can upload the image of the desired product and Image-GPT can generate and display a list of similar products and also suggest complementary items.
Another possible use case is in the field of art, where users can share a description of an artwork they want to create, and Visual-GPT can generate the desired image based on the description they provide.
This technology is made possible through the use of artificial intelligence and computer vision algorithms that can recognize objects and their features. This opens the door to a wide range of possibilities for customization and personalization across various industries.
It can be expected that future VFMs will be more mature and better able to understand the details of enigmatic images.
Source- Rajkumar Jain
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