Xiaofamao for Developers
Xiaofamao has a certain level of writing ability, but surpassing humans is still a challenge. Today, people are used to dividing artificial intelligence into three steps: computational intelligence, perceptual intelligence, and cognitive intelligence, with cognitive intelligence sitting at the top of the AI pyramid.
Xiaofamao AI can be integrated with Locoy
At present, computational intelligence and sensory intelligence can rival or even surpass humans, but there is still a gap between cognitive intelligence and human beings.
Cognitive intelligence is the future trend of artificial intelligence development.
Cognitive intelligence involves semantic understanding, knowledge representation, associative reasoning, intelligent question answering, and self-learning. An important goal of artificial intelligence is to enable machines to communicate with humans more naturally and effectively, hoping that machines can understand deep human language and interact in the way we are used to.
Among these tasks, making machines understand profound human language is best represented by reading comprehension, the most typical task of cognitive intelligence. The semantic library relies on neural networks for computation.
In addition, the Xiaofamao bot implements every basic NLP functional module based on machine learning and deep learning methods, covering lexical analysis, syntactic analysis, semantic analysis and other core techniques, including machine reading comprehension.
In terms of cognitive intelligence, beyond the currently popular NLP capabilities, the Xiaofamao bot also specializes in another unique technical direction — affective computing, which quantifies human emotions into values that machines can understand.
In fact, the development of cognitive intelligence is divided into three levels: language understanding, analytical reasoning, and personality and emotion. Emotion can be said to be the very top of the AI pyramid, one of the final difficulties that AI needs to overcome.
The concept of affective computing was first proposed by Professor Rosalind Picard of the MIT Media Lab in 1997. She pointed out that affective computing relates to, arises from, or deliberately influences emotions.
However, the representation of emotional interaction information on user interfaces still lacks standardization and unified standards. This makes the understanding of users' emotional information in human-computer interaction increasingly difficult and gives rise to emotional feedback problems, which hinders the application and development of affective computing in user interfaces.
In fact, the application prospects of affective computing are broad. There are still emotional and expressive barriers between users and computer systems. If relevant international standards are established, it will facilitate the application of affective computing in user interfaces.
More NLP resources:
1. Online Sentence Converter