What Are Chatbots?
Table of Contents
What Are Chatbots?
What Technologies Do Chatbots Use?
How Do Chatbots Learn?
What Are Some Example of Chatbots?
A Building Block for the Future
What Are Chatbots?
Chatbots are computer applications that facilitate our use of digital products and services by engaging in written or verbal communication as if we were talking to another human. They can be designed to provide basic, single-sentence answers or be trained to adapt and learn as they chat and provide more detailed and specially tailored responses. Chatbots utilize what is called natural language processing, machine learning, and some creator-defined set of rules to operate.
What Technologies Do Chatbots Use?
Put simply, natural language processing is the science of teaching computers how to understand written and spoken words. It is not dissimilar from a child learning to recognize and respond to words when they are young or to them learning to read as they get older. Many nuances to human languages, like words with multiple meanings, or speaker sentiments like sarcasm, can affect how words are interpreted. Just like humans, computers need to be trained to recognize these nuances to improve their understanding of verbal or written communication and to respond in a more human-like manner. Natural language processing is how this training occurs as computers are taught to take words via text or audio and to distill their meaning, taking into account all of our human nuances.
Machine learning is used in more complex chatbot models that can become tailored to their users. These types of models actively learn while chatting, can adjust responses based on user history and preferences, and even predict user needs or initiate conversation. The idea is that machine learning models can find patterns in the data it uses, actively train and update themselves as they are used, and provide a much more human-like interaction than more basic models. This means users can start with very open-ended queries and still carry on an effective conversation with the chatbot.
All of this learning sounds impressive, but it begs the question, where are the bots being trained? How do they access information for their responses? How quickly can they learn? The answer can vary depending on the chatbot in question and what purpose it serves.
How Do Chatbots Learn?
A chatbot that is used for customer service may be trained using human-to-human chat logs or phone conversations. Ever heard “this call may be monitored for quality and training purposes?” While those logs may still only be used to train other humans, they will certainly be used to train future chatbots once the tech is further developed. The chatbots also have access to company databases to pull customer information or product information that is relevant to the chat. Other more complex chatbots like ChatGPT use open data from countless sources or data points around the internet. The program pulls from Wikipedia pages, message boards, and uses a broad swath of data collected from all corners of the web. ChatGPT does use data through 2021, but not beyond at the moment.
There is some human intervention in the chatbot training process. Data analysts have to clean up datasets and provide parameters for training the chatbot algorithms in what is called supervised learning. In this situation, labeled datasets are used where there are inputs that have assigned outputs and an algorithm is trained to connect the correct inputs to the correct outputs. The alternative is unsupervised learning, which entails using unlabeled data sets and machine learning. The algorithms begin to identify patterns in the data and learn to correctly assign certain outputs to certain inputs. There is still a need for some human intervention to validate the patterns that the algorithm identifies. Unsupervised learning requires more technically intensive work but requires less human oversight so is overall more appealing.
What Are Some Examples of Chatbots?
Chatbots have already been implemented in various industries and the applications are virtually endless. Below are a few companies that have already become front-runners in the application of chatbot technology.
Jasper Chat - This is a content creation-oriented chatbot that allows a user to enter a prompt and have unique content generated that is platform specific and optimized for conversion. Jasper can provide responses in 26 languages and even offers a browser extension so that you can use its services across any website.
Chatsonic by WriteSonic - Backed by Google, Chatsonic has access to the most up-to-date news, which gives it a distinct advantage over some other popular chatbots. It can generate both text and images based on user-defined prompts. ChatSonic also offers voice-command to give users an alternative way of interacting with the chatbot. Similar to Jasper Chat, ChatSonic offers a browser extension that lets you take its tools all across the web.
YouChat - While it may be less polished and still in development, YouChat offers a strong alternative to ChatGPT. It can answer queries in the same fashion as ChatGPT and has the ability to cite its sources for information since it pulls straight from Google.
ChatGPT by OpenAI - Probably the most well-known chatbot in the world, ChatGPT is extremely dynamic and has already been applied in many ways. ChatGPT can do everything from carrying on a simple conversation about cartoons to producing a block of code for web design or data analysis. A downside to ChatGPT is that it is not connected to the internet and has only been trained with data through 2021 so it is not as reliable for work based on current events. ChatGPT can be used for free, pending available bandwidth, but also offers a paid version with more premium features and access.
A Building Block for the Future
Chatbots are one of the first examples of how humans will interface with AI and they will be one of the essential building blocks in many businesses going forward. While this technology has already been widely applied, there are surely many more applications that we have yet to imagine, especially as the technology continues to improve.