AI Chatbots and Limitations
AI is an intelligence system put together artificially to learn and provide an output.
Learning can be done by providing data to the AI system. Data can be big data, customer data, unstructured text, audio, the visual, environment surrounding details, etc. Based on the data provided, an AI system would learn and identify hidden patterns and provide an output. For instance, if an AI recommends what food to order, it must know your food preferences, what you had ordered before, where usually order from, what days you usually order specific cuisine. A lot of other details to recommend the right cuisine for you. The output can be a list of the Top 5 food orders for today. Similarly, if an AI is assisting a doctor in providing options for cancer treatment, the system must have the complete patient medical history, must understand the complete cancer domain (or the respective specialization), and also periodically learn any new treatments or findings from medical journals. Understanding the complete cancer domain is a very complex process, where one needs to train the system to understand the medical terminology and the vast ever-growing cancer literature, identify patterns and correlations from existing patients, their suggestive treatments and outcome, and finally suggest options for treatment. There can be many more data points, and this is a continuous process where the system would be trained from the feedback and their outcome. While we keep hearing AI is helping solve cancer cases, this is far from reality, and systems have just started to touch the surface.
To make life simpler, just remember the following distinction – “AI can learn but can’t think“.
Thinking would always be left to humans on how to use the output of an AI system.
In this course, learn how the build AI chatbots, understand the current limitations and how to build AI chatbots by understanding the limitations.
Perquisite for the course
What is Artificial Intelligence
AI stands for artificial intelligence. It’s an intelligence system put together artificially to learn and provide an output. Learning can be done by providing data to the AI system. Data can be big data, customer data, unstructured text, audio, the visual, environment surrounding details, etc. Based on the data provided, an AI system would learn and identify hidden patterns and provide an output.
What are AI Chatbots
A chatbot is a software program that carries out a conversation with a human. The conversation can be through textual methods, voice, or even through recognizing human expressions.
Best Practices of building AI Chatbots
Chatbots work well when the domain is well understood by the AI system. As the AI chatbot relies on NLP to understand the semantics of the input message, unless the NLP parser is trained on the domain, the accuracy of recognizing the intent and topics of interest would be very low or not as per acceptable criteria.
Chatbot use cases
Chatbots provides an efficient way to stay connected with end customers directly and provides information at their fingertips – be it through a messaging chat application or through voice enabled service like Alexa and Google Home.
Chatbot Implementation
What are the high-level steps for building an AI chatbot?
Integrate chatbots with Facebook and Alexa
In this video, we will look at how ti integrate facebook and Alexa Integration with your AI Chatbots.
Develop chatbots using chatbot platforms
A chatbot platform provides you a set of services to design, develop and deploy your chatbot. They provide you with a framework and guided set of utilities to build a chatbot.
Some Facts about Chatbots
Chatbots are examples of Weak AI. The current generation of chatbots can be thought of smart dialog systems driven through techniques like NLP and fixed conversation flows.
Out of the box, a chatbot doesn’t understand any domain. We need to train the chatbot to understand the domain
Out of the box, a chatbot doesn’t understand any domain. We need to train the chatbot to understand the domain. Also, based on the complexity of the domain, you would incrementally train and add subdomains.
Will AI Chatbots replace Humans
Will chatbots make human agents obsolete?
