Learn about the development of chatbots, from their ability to recognise simple patterns to sophisticated models driven by machine learning, and how they became indispensable in today's world.

What was the first chatbot?

Eliza First Chatbot was launched in 1966 

The first chatbot was ELIZA it was developed between 1964 and 1966 with the intention of a chatbot therapist at MIT by Joseph Weizenbaum He programmed ELIZA to be a conversation between the patient and psychotherapist by using a person's responses to shape the computer's replies.

PARRY, Second Conversational Assistant 

Introduction of PARRY and its conversational capabilities. This was the second chatbot developed in 1972 at Stanford University by Kenneth Colby based on the same rule as ELIZA. It behaves like a person with diagnosable paranoia and can shift the mood based on anger, fear, or mistrust.

Evolution Through the 1990s and Early 2000s

The Rise of Scripted Chatbots

The development of chatbots came into its own during the 1990s and early 2000s with the rise of scripted or rule-based systems. These early commercial chatbots used prewritten scripts to interact with users by following specific responses programmed and brought out by the use of keywords or phrases.

In this era, important chat assistants like Jabberwacky were developed by Rollo Carpenter; this was the first chatbot that tried to incorporate voice interaction and was based on the same rules as PARRY and ELIZA. 

A.L.I.C.E. is another important step in the history of chatbots due to its universal language processing that uses a heuristic pattern to be able to have a conversation. This was created in 1995 by Richard Wallace compared with his predecessors; it simulates chatting with a real person over 

Precursore of SIRI?

Smart Child 

Smart Child was, in many ways, a precursor to SIRI, which was developed in 2001. It was available on OP IM and MSN Messenger and could carry out fun conversations.

The Breakthrough of AI Assistant in the 2010s

Siri 

This was formed by Apple for IOS in 2010 as an intelligent personal assistant that uses natural language, and it was one of the first to create a way for AI bots and AI assistants. 

Google Now or Google Assistant 

This was launched by Google in 2012 Google Now was designed to answer questions, execute actions through web service requests, and offer personalised recommendations, and it was created to compete with Siri.

Cortana 

Cortana, launched by Microsoft in 2014, is a virtual assistant designed to help users manage tasks, set reminders, and answer questions using natural language processing. Initially integrated into Windows 10, Cortana has since evolved to focus more on productivity features within Microsoft's suite of applications.

The Boom or NLU 2020s era

Advancements in Natural Language Understanding (NLU)

The 2020s have seen remarkable advancements in Natural Language Understanding (NLU), a key component of AI chatbots that enables them to interpret and respond to human language more effectively. Modern chatbots now leverage context-aware algorithms, allowing them to understand not just the words spoken but also the context and intent behind user queries. This capability transforms interactions, enabling more fluid and natural conversations that feel more human-like.

Additionally, the integration of deep learning techniques has further enhanced chatbot performance. By utilising large datasets, chatbots can learn nuances in language, handle ambiguous phrases, and adapt to various dialects and cultural references. This evolution has resulted in chatbots that can maintain context over longer conversations and provide personalised responses based on user history and preferences.

Today Era

In today’s rapidly advancing AI chat landscape, several prominent platforms stand out, each specialising in areas that support various business goals and user needs:

ChatGPT

Chat GPT took the world by storm when it was lunch at the end of 2022. Chat GPT serves as an all-round assistant using language models ChatGPT generates responses, making it efficient for customer service and personal assistance. Having the ability to be highly versatile makes it suitable for businesses and individuals.

Rasa

Rasa is an open-source framework that helps developers create unique chatbots that are customisable to their own needs. Rasa's adaptability and developer control make it a preferred platform for companies looking to create proprietary chatbot features or cater to niche sectors with highly personalised user interactions.

Dialogflow

The most accurate NLP from Google powers it, with multilingual capabilities. From customer service and e-commerce to omnichannel customer engagement, it powers seamless language support for more than 30 languages. Moreover, tight integration within the Google ecosystem ensures stronger functionality in the web, app, and smart device channels.

Raffle AI

Raffle AI is designed to provide secure, efficient, and engaging AI Chat solutions in an enterprise environment and is best for security and internal knowledge management. It is also noted for seamless integration and a very user-friendly interface that makes it the go-to choice for any organisation in search of a secure AI chat platform to handle sensitive information to customers and smoothen internal communications. Its strong security features with reliable interaction. 

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