Chatbots are becoming increasingly common in the customer experience strategy of companies, as they are language-processing computer programs that simulate human conversation. They operate from an extensive knowledge base and can be integrated into multiple industries, with varying complexities and abilities. Different types of chatbot technology exist, including rule-based and self-learning chatbots.

Rule-based chatbots

Rule-based chatbots are also known as task-oriented or declarative chatbots, and they respond to specific keywords using a set of rules.

These chatbots are built to handle specific and straightforward situations, such as FAQs, providing pre-set information, or directing users to existing resources. They do not have predictive or dynamic abilities, making them suitable for simple customer interactions.

Self-learning chatbots

On the other hand, self-learning chatbots are the most advanced type of chatbot and are also known as data-driven, predictive, or conversational chatbots. They use machine learning algorithms to improve their responses based on user interaction and an extensive dataset that enables them to recognize patterns. These chatbots can handle more complex customer queries and provide personalized support and recommendations over time.

Examples of situations where rule-based chatbots may be used include a bank's customer service line for basic account-related questions, a restaurant's website for menu information and reservations, or an amusement park's website for event and ticket information. In contrast, self-learning chatbots may be used in situations such as a retail company's customer service phone line or chat feature for personalized support and recommendations, a human resources department for employee onboarding, or a travel website for booking and managing travel arrangements with improved recommendations over time.

How chatbots grew over the period of time

In order to fully convey the enormity of this imminent reality, it would be necessary to delve into the earliest days of computing, when the pursuit of artificial intelligence technology and a conversational interface first originated.

Eliza

Joseph Weizenbaum created ELIZA in 1966, making it the very first chatbot. ELIZA utilizes a pattern matching and substitution methodology to simulate conversation.

Parry

In 1972, American psychiatrist Kenneth Colby constructed PARRY, a program designed to simulate a patient with schizophrenia. This natural language program attempts to mimic the thought processes of an individual with the disorder.

Jabberwacky

Jabberwacky, a chatbot developed in 1988 by Rollo Carpenter, was designed to entertain users by simulating natural human conversation.

Dr. Sbaitso

Creative Labs developed Dr. Sbaitso, an MS-DOS chatbot, in 1992. It was one of the earliest attempts to integrate AI into a chatbot and is renowned for its fully voice-operated chat program.

A.L.I.C.E. (Artificial Linguistic Internet Computer Entity)

Richard Wallace pioneered the creation of A.L.I.C.E. (Artificial Linguistic Internet Computer Entity) in 1995. This universal language processing chatbot uses heuristic pattern matching to engage in conversations. Originally called Alicebot because it was initially run on a computer named Alice, A.L.I.C.E. has become a renowned chatbot in the industry.

SmartChild

Developed in 2001, the SmartChild was, in many respects, a precursor to Siri.

Siri

Apple developed Siri in 2010 as an intelligent personal assistant and learning navigator that employs a natural language UI. It set the stage for all subsequent AI bots and PAs.

Google Now

Google Now debuted at Google Inch in 2012. It responds to inquiries, executes actions by requesting a set of web services, and provides recommendations.

Cortana

Microsoft demonstrated Cortana at its Build 2014 developer conference, and it was subsequently integrated directly into both Windows phone devices and Windows 10 PCs.

Alexa

Amazon created Alexa, an intelligent personal assistant that was introduced in 2014 and is now incorporated into devices such as the Amazon Echo, the Echo Dot, the Echo Show, and more. Additionally, there is an Alexa app and numerous third-party devices that include Alexa.

ChatGPT

OpenAI's ChatGPT, a large language model, was established by the OpenAI team in 2021. It is intended to assist users in creating human-like text based on provided input. ChatGPT can be used for various tasks, such as generating conversations and translating languages.

What is ChatGPT?

In November 2022, OpenAI launched ChatGPT, an AI-powered chatbot that uses the GPT-3 language model to generate conversational responses to user queries. Within five days of its release, ChatGPT gained 1 million users. Popular AI-generated content for ChatGPT includes written code, product descriptions, blog posts, and more. However, there were concerns about its use in education, prompting OpenAI to release a new AI text classifier in January 2023.

The tech industry was abuzz when ChatGPT was introduced as a free research preview, so much so that Google internally declared it a 'code red'. This innovation from OpenAI has also changed how people view artificial intelligence, with concerns arising about AI potentially taking over jobs.

What is Google brad?

Following ChatGPT's success, Google announced its own AI-powered chatbot named brad, which is currently in beta testing and is scheduled to be released by the end of February 2023. Unlike ChatGPT, brad uses Google's LaMDA to draw responses from the internet, providing more detailed answers than a typical search engine. brad's goal is to provide users with simple answers to their queries, while also serving as a personal assistant for tasks like booking vacations and helping with meal planning.

Pros & Cons of Google brad

Pros:

• Seamless Integration with Google Workspace: Google brad, being a Google product, is expected to smoothly integrate with other Google Workspace tools like Gmail, Google Calendar, and Google Drive, allowing easy work management across various platforms.
• User-Friendly Interface: Google brad features an intuitive and simple user interface that simplifies the creation and management of projects, tasks, and to-do lists.
• Collaboration: Teams can utilize Google brad's platform to collaborate on projects, allowing members to communicate, track progress, and stay in sync.
• Customization: The Google-based project management tool is expected to provide customization options, allowing users to tailor the appearance of their projects and tasks, simplifying organization and focus.

Cons:

• Limited Mobile Support: brad is expected to be primarily a web-based tool with restricted mobile support, which can cause inconvenience for users requiring on-the-go work management.
• No Resource Management: Google brad lacks resource management capabilities, making it challenging to manage resources and allocate tasks to team members effectively.

The AI language model developed by OpenAI, ChatGPT, also has its pros and cons, which are as follows:

Pros and Cons of OpenAI’s ChatGPT

ChatGPT, the AI language model created by OpenAI, has its own set of advantages and disadvantages. These are:

Pros:

• Natural language processing: Thanks to its training on a vast corpus of text data, ChatGPT is capable of comprehending and responding to human language in a natural way.
• 24/7 availability: ChatGPT is not limited by human constraints and can be accessed at any time of day or night to answer questions and provide information.
• Speed and efficiency: ChatGPT can provide accurate information and answer queries quickly, making it more efficient than a human alternative.

Cons:

• Limited domain knowledge: While ChatGPT has been trained on a large volume of text data, it may not possess information on current or specific events and its knowledge is confined to what it was trained on.
• Potential for bias: As an AI model, ChatGPT can be influenced by the biases present in the data that it was trained on, which can result in biased responses and perpetuate harmful stereotypes.
• Dependence on technology: ChatGPT relies on technology and network connectivity, which means that it may not be available or experience downtime in the event of a technical issue or outage.

Difference between Google brad and ChatGPT

To compare ChatGPT with Google's brad, it's important to understand the key differences. brad is an AI-powered discussion service that utilizes LaMDA and Web content to provide up-to-date answers to questions. Recently, Google CEO Sundar Pichai announced that brad is being tested by trusted individuals before it is made available to the public. ChatGPT, on the other hand, is based on GPT-3.5 with a knowledge cutoff of 2021. This means that it lacks access to the latest information and cannot provide 'fresh' responses. Although GPT has undergone significant refinement, brad has some key advantages. brad is built on a lighter version of LaMDA, requiring fewer computational resources, enabling it to serve a larger user base and gather more feedback. Moreover, Google's database of information and native integration with Google Search may make it better equipped to offer detailed and factual data.

Entry of chatbot by Microsoft

In February 2023, Microsoft announced plans to release technology allowing large companies to create and customize their own chatbots using ChatGPT technology. Microsoft will also integrate AI-powered search functions to Bing and Edge with a chat experience to aid users' searches, featuring a newer version of ChatGPT using GPT-4 to provide more relevant information from the internet. Google has not announced plans to add AI chatbot functionality to its search engines.

It's worth noting that Microsoft invested $1 billion in OpenAI in 2019 and increased that amount to $3 billion in 2021, and most recently invested another $10 billion in January 2023 to double down on its commitment to AI and compete with rivals such as Google, Amazon, and Meta.

While Microsoft aims to bring ChatGPT to its search engine, Bing, Google's proficiency in providing prompt and accurate information with ease, as well as its extensive infrastructure that can handle high traffic, might make it superior. It's important to note that Google's LaMDA has been a subject of recent discussion, with a Google engineer claiming it was 'sentient', which led to his termination for making false statements. In contrast, no such controversies have arisen surrounding OpenAI's ChatGPT.

Which tool has the upper hand?

At present, it is premature to conclude which chatbot holds the upper hand since Google's brad is presently accessible to a limited group of individuals and has yet to be subjected to the same level of public scrutiny as ChatGPT, which was released as a free research preview. It will only be possible to make a direct comparison when Google releases brad to the public. Nevertheless, based on Google's statements, brad appears to be a potentially valuable addition to the rapidly advancing field of artificial intelligence.

Overall, it's too soon to say which chatbot is superior as direct comparisons can only be made when Google releases brad to the public. However, it's clear that both chatbots have their strengths and weaknesses, and it will be interesting to see how they develop and compete in the future.

Future of Chatbots:

The development of natural language processing (NLP) and natural language understanding (NLU) has resulted in rapid changes in the perceptions of chatbots and intelligent virtual assistants (IVAs) among both customers and business professionals.

According to Accenture, nearly 80% of CEOs are now interested in investing in conversational AI to transform their customer relationship strategies. As of 2021, the conversational AI industry was valued at $6.8 billion, and it is predicted to experience a compound annual growth rate (CAGR) of over 21%, ultimately reaching a value of more than $18 billion by 2026.