Interpreting the human language is essential for communication between humans and machines. It happens through the natural language processing method (NLP), whose evolution is key for the future of artificial intelligence.
Check below some points covered in the e-book Human & Artificial Brains in order to understand how the natural language is processed, and the importance of continuously investing in the development of that method.
The languages behind artificial intelligence
Language is, by means of definition, any systematic means of communicating ideas or feelings through signs, whether conventional, sound, graphics, or gestures. Language decoding is fundamental in order to communication to happen, and to the message to be conveyed.
Decoding takes place through the processing of natural language, a discipline that navigates between three fields: computer science, artificial intelligence, and linguistics. Its evolution began in the 1950s and has gone through three phases:
- Symbolic: considered lexical rules developed by man and followed the literalness of human speech, without considering ambiguity and unstructured rules.
- Statistics: based on mathematical models and observable and recurrent samples of linguistic phenomena. This approach does not take into account language rules, but only mathematical analyzes to deduce and recognize speech themes and trends.
- Neural: it is based on supervised machine learning, and is totally numerical. It works in a unique way: First of all, it turns the language into numbers, where each number represents a word, and then the neural network algorithms can analyze and find patterns in the numbers to “interpret” a text or speech.
The future of communication between humans and machines
Within NLP approaches in artificial intelligence, there is still an element in constant improvement by scientists: the context.
Although the machines have the intelligence to decode and interpret symbols, they cannot fully understand the context or interpret feelings and emotions, as both of them are caused by chemical reactions in the human brain.
Nowadays, some algorithms already manage to generate texts and to interpret them in a precise and coherent way, but the machine cannot feel anything genuinely yet, as it is still and exclusive human characteristic.
NLU x NLG
The progress in NLP research is fundamental for the improvement of the interactions between artificial and human intelligence. This area is commonly divided into two parts:
- Understanding of Natural Language (NLU)
The NLU is already widespread with the popularization of voice recognition and activation systems.
- Natural Language Generation (NLG)
The NLG is one of the fastest-growing technologies and has been applied in theoretical research in order to understand how humans produce language. This field can be applied to automate reports, chatbots, and other programs that have metrics to be analyzed.
The next steps in the evolution of IA
The evolution of artificial intelligence is continuous and growing. Besides the increase in the interest of companies in using technology to improve processes, there is also an increase in the number of projects and academic research in this area as well as more events related to the topic.
Governments are also more interested in the regulation of artificial intelligence, and this could be a sign of the high potential impact of technology on contemporary society.
Although we are far from achieving Strong AI, the artificial intelligence programs available today are the peak of the technological evolution and show that machines do not need human awareness to be extremely useful.
Download the full Human & Artificial Brains e-book and read about how machines think compared to humans, and learn even more about natural language processing and the future of artificial intelligence.