What is the Vision AI?
Vision Artificial Intelligence (Vision AI) is a field of artificial intelligence based on computer vision technology. Computer vision refers to the technology where computers process and interpret visual information, and Vision AI focuses on understanding and analyzing visual data such as images and videos using this technology.
In this way, Vision AI is the technology that enables computers to understand and process images. If this technology seems challenging to understand, I'll provide a more detailed explanation of how it works and what technologies it incorporates.
1. Image Processing:
Vision AI is used to extract information from photos or videos. It learns how to identify and detect patterns or features in images.
2. Machine Learning:
Vision AI learns through experience, a process known as machine learning. The model learns objects or patterns by examining a large amount of images.
3. Data Augmentation:
To enhance the learning of Vision AI, a significant amount of data is needed. Sometimes, images are transformed to enable the model to adapt to various situations.
4. Object Detection and Segmentation:
The model can identify objects in images and, if necessary, accurately distinguish the boundaries of objects.
Vision AI employs various methods to learn from images and finds applications in various fields such as medical diagnosis, autonomous vehicles, security systems, and games, making the processing and understanding of images and videos more intelligent.
What is the Chatbot?
A chatbot is a relatively familiar form of AI. With the increasing use of chat-based platforms like ChatGPT and giving commands to AI assistants like Siri or Bixby, users engage in conversations with these software applications. A chatbot is a software application that can interact with users using natural language to respond to questions or perform specific tasks. Here are some features that help understand chatbots:
1. Natural Language Processing (NLP):
Chatbots use NLP technology to understand and process user speech or text, enabling convenient conversations.
2. Artificial Intelligence (AI) and Machine Learning (ML):
Some chatbots continue to learn and evolve through user interactions, utilizing AI and machine learning algorithms.
3. Diverse Applications Based on Purpose:
Chatbots serve various purposes such as customer service, information provision, reservations, and task automation. When utilizing speech recognition technology, they can also respond to voice commands.
4. Improved User Experience:
Chatbots enhance user experience by efficiently handling service provision or issue resolution through real-time conversations. For example, a customer support chatbot can answer user queries, resolve problems, or provide product information.
Combine Vision AI and Chatbots
Imagine a product that combines Vision AI and chatbots. The most straightforward scenario is similar to visiting a dermatologist or plastic surgeon. You could receive a diagnosis of your skin condition, understand current issues, and learn which procedures or products could improve your situation. SkinChat is a product that operates on this premise. Users diagnose their skin type with three photos, ask questions based on the diagnosis, and receive recommendations for suitable procedures or products.
Currently adopted by establishments like Soko House in India, 3WAAU in Korea, and VOS Dermatology, SkinChat leverages AI technology to replace 1:1 private consultation services. Consumers can diagnose their skin conditions in their personal spaces, anytime and anywhere, and receive recommendations for necessary procedures and products. This signifies the elimination of spatial and temporal constraints in dermatological consultation systems.
If you're curious about how to utilize SkinChat, a combination of Vision AI and chatbot, for your business, send an email for a demo version. SkinChat is open to all businesses related to skincare.