We live in a world of chatbots. Chatbots improve human interaction with systems by giving a response based on the user input. This means chatbots are simple automated programs that can process simple user inputs and provide a meaningful output. But with time, chatbots evolved and now are impacting the industries around us. The last […]
We live in a world of chatbots. Chatbots improve human interaction with systems by giving a response based on the user input. This means chatbots are simple automated programs that can process simple user inputs and provide a meaningful output.
But with time, chatbots evolved and now are impacting the industries around us. The last decade has been glorious for chatbots. In fact, the growth has already prompted the increased availability of learning material on the internet.
This being said, current chatbots work in a very simple way. They take input in the form of language which is then processed by the computer using natural language processing. Once they understand the meaning, they give the most accurate answer to the user. The accuracy of the chatbot interaction depends on the algorithm being used. Chatbots also use expert systems to make decisions and act accordingly.
The most recent chatbots are using deep learning to break the next barrier of communication between humans and machine. The aim is to create a chatbot that can completely imitate a human response and not let the user understand if he/she is talking to a chatbot.
Right now, chatbots are used in almost every sector. From social media to management to healthcare, chatbots just cannot be ignored anymore. For example, Siri, a personal assistant helps iOS users to get answers. It uses a natural language user interface to respond to questions from users.
Limitations and Opportunities
There are limitations to what has been currently achieved with chatbots. The limitations of data processing and retrieval are hindering chatbots to reach their full potential. It is not that we lack the computational processing power to do so. However, there is a limitation on “How” we do it. One of the biggest examples is the retail customer market. Retail customers are primarily interested in interacting with humans because of nature of their needs. They don’t want bots to process their needs and respond accordingly.
So what is the solution? Artificial Intelligence (AI).
Artificial intelligence has been evolving at a rapid pace. The growth has been so substantial that the best AI minds are concerned with how journalists are interpreting information without understanding it. Despite the misinterpretation by journalists, it is evident from the current progress that AI has the potential to completely make chatbots more mainstream and indistinguishable from a real human interaction.
If you are curious on how modern chatbots work, you can try out these chatbots built by Cuor99, Cookkkie, and DasCode. All of them work at a different level and try to solve a problem which would require real human interaction.
The future of AI and Chatbots
The future of AI bots looks promising and exciting at the same time. The limitation in regards to accessing big data can be eradicated by using AI techniques.
The ultimate aim for the futuristic chatbot is to be able to interact with users as a human would.
Computationally, it is a hard problem. With AI evolving every day, the chances of success are already high. The Facebook AI chatbot is already showing promises as it was able to come up with negotiation skills by creating new sentences.
E-Commerce will also benefit hugely with a revolution in AI chatbots. The key here is the data collection and utilization. Once done correctly, the data can be used to strengthen the performance of highly-efficient algorithm, which in turn, will separate the bad chatbots from the good ones.
Automation is upon us, and chatbots are leading the way. With a fully-functional chatbot, e-commerce, or even a healthcare provider can process hundreds of interactions every single minute. This will not only save them money but also enable them to understand their audience better.
Nevertheless, for this to happen, companies should restructure their approach and start investing in the Machine Learning (ML) infrastructure so that they can gather new data on a regular basis, feeding the algorithm and improving its performance over time.
In the end, the only thing that matters is how chatbots fulfill the emotional needs of the people for whom they are made for.
So, what do you think about the future of chatbots and AI? Do you think that the day is near when it will be impossible to distinguish a chatbot from a human?
Comment below and let us know.