Although chatbots have been around for a while, it has only been in recent years that both users and businesses have begun to take much notice of them.
With the whole world fussing about ChatGPT’s breathtaking features and functionalities, many have missed the main brain behind it, AI. ChatGPT is an AI that can write anything for you, including letters, song lyrics, research papers, recipes, essays, outlines, and even computer code.
With time and the rise, AI has become more efficient. AI was introduced with the notion to speed up the tasks of humans and now we have come a long way that has even surpassed the activities that can be done by a human. Thus it is no big surprise that the adoption of AI has more than doubled over the last five years, according to a 2022 McKinsey survey, and investment in AI is growing quickly.
Currently, there are many sectors using chatbots. In this blog, let’s examine their evolution along with current trends.
Evolution of chatbots over time
The first chatbot Eliza was created in 1966 by Weizenbaum, a professor at MIT.
To recreate a response by utilizing keywords from pre-programmed responses, ELIZA works by identifying important words or phrases from the input. For example, a human would remark, “My School gives more summer holidays than any other Institution.” When ELIZA hears the word “School,” she would say, “Tell me more about your School,” and then pause. Despite being a computerized procedure, this gave the impression that one was comprehending and interacting with a real person.
Pattern matching and response selection methods based on templates were used by ELIZA. Also, ELIZA can only discuss a limited range of topics due to its limited expertise. Additionally, it is unable to maintain lengthy dialogues or gather context from the conversation.
AIML – Artificial Intelligence Markup Language
To build the Knowledge Base for chatbots that use the Pattern Matching technique, engineers built the Artificial Intelligence Markup Language (AIML) between 1995 and 2000.
The first chatbot with an AIML-based knowledge base was ALICE. ALICE uses natural language processing (NLP) to engage in conversation by responding very naturally to human input. Instead of utilizing more complex NLP methods, she uses a set of rules that compare user input to patterns to assist her to decide how to reply.
Computers that can be used in conversational AI systems allow users to communicate with them. Voice-activated gadgets like the Amazon Echo are making it possible for the magical interactions of which we have long dreamed thanks to conversational AI.
Voice Chat Bots like Alexa, SIRI, Google Assistant, and Cortana may interact with people via a voice user interface in ways that feel natural. For instance, you can just say, “Alexa, play the best Rap songs,” instead of making multiple swipes and clicks.
Thus they make your activities easier and also become smarter over time.
AI that generates new content, including audio, code, images, texts, simulations, and videos, is referred to as generative AI. This includes algorithms like ChatGPT. Recent developments in the sector could dramatically change how we think about content creation.
That is why ChatGPT, also known as a generative pre-trained transformer, is currently attracting so much attention. Currently, it is a free chatbot that can produce responses to practically any questions that are posed to it.
AI has already made a significant impact in almost all domains. But many businesses still doubt if AI can be helpful to them. Several myths persist among firms opting for AI. In this blog, we have majorly discussed AI’s impact on chatbots while many more tasks can be simplified with AI. For any of your company needs or guidance to know about AI, reach out to [email protected].