Artificial Intelligence in Chatbot Security
There are three distinct subsets of Artificial Intelligence in Chatbot Security. In the first, we have the remote sensing models. These models use the information gathered from sensors such as cameras or sensors mounted on traffic light poles. The information from the sensors is fed to a processing device, which in turn, makes decisions about the most appropriate actions to take based on what it has learned from the data. In a way, it is a form of self-driving traffic light system, where the best decisions are made without any human intervention. In this deployment model, the global community in which the ChatBots is deployed is classified as the collection of the intelligence from the sensors and the conversations that happen in the Cloud.
The second type of Artificial Intelligence in Chatbot Security is represented by the natural language processing (NLP) system. Unlike remote sensing and the natural language processing systems, artificial intelligence in the ChatBots security market is defined by the ability to understand natural language dialogues. This may sound difficult but it is actually quite easy given that artificial intelligence is able to grasp the meaning of the words being used in a conversation.
Another form of Artificial Intelligence in Chatbot Security is machine learning. Machine learning is the process of training a machine to recognize and make a decision based on facts and input that it receives from a user. An example of this technology is Google's Knowledge Engine. When the system is trained on specific keywords, it can recognize when it encounters a web page that contains that keyword and will then automatically direct the user to the appropriate page or site. Another example is the Airspace Weather Forecast software developed by NASA.
A very interesting development in this field is Yahoo's Answers for Life. This is a computer program developed by Yahoo that uses both natural language processing and artificial intelligence (AI). What is interesting about this program is that it uses both of these technologies. Users answer the questions in a discussion forum, and the system analyzes the responses and classifies the questions into viable answers. The system uses both the actual voice and the online user's speech to come up with the best possible response. In essence, Yahoo's Answers for Life is taking the online world of internet chat and turning it into a real-life setting.
Another important development in the field of chatbot security is the use of the cloud in its deployment model. The cloud-based deployment model provides a scalable infrastructure for application deployment. It also enables easy maintenance and zero downtime for applications while in the cloud. Unlike an on-premise deployment model, one does not need to have a personal network, servers, or software.
In the end, all these factors are driven by one factor i.e. engagement. Engagement is primarily driven by mobile devices. All these things will help the future of the IT industry to grow dynamically. And we can expect plenty of innovations in the field of chatbot technology in the coming years.
