AI Emotion Recognition Training

It is widely known that AI itself has no emotions and cannot perceive emotions. However, human emotions expressed through facial expressions vary significantly across contexts and cultures. Currently, there is insufficient evidence to suggest that facial structures can accurately and reliably reflect human emotional states. JUNLALA, based on the theory of "basic emotions," has decided to tackle the challenge of AI emotion recognition and cultivate AI's understanding of human emotions. The entire process of emotion training tasks includes data uploading, cognitive learning, simulated training, and practical application. Users participate in the first step by uploading required emotion photos as part of daily tasks provided by the system. System reviewers score the quality of photos provided by users and provide corresponding rewards. Detailed rules can be found in the "How to Earn" section of the whitepaper. The next three steps are completed by AI. To enhance the effectiveness of AI training, we will also release tasks that users can participate in, such as assessing whether AI successfully learns to recognize different emotions and evaluating whether its responses are close to human reactions, akin to a small-scale "Turing test." Our AI model identifies and processes challenging images by learning how different individuals express various emotions in the database. These images are returned to the system, seeking assistance from the public. Of course, the more people participate in training, the richer the learning data AI acquires, and the more precise its grasp of emotions becomes. Ultimately, emotion recognition technology will be applied to AI chatbots. In the near future, you may experience video chats with AI robots where they can perceive your emotions by scanning your facial expressions and communicating with you in warm, appropriate language based on your current expression. This promises to be a transformative experience in AI conversation.