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E.G.S.Pillay Engineering College
An Autonomous Institution Affiliated to Anna University | Approved by AICTE
Accredited by NBA [CSE/IT/ECE] | Accredited by NAAC with Grade ‘A’
One among the Top 300 Engineering Colleges in India [NIRF-2022]
Old Nagore Road, Thethi Village, Nagapattinam – 611002, Tamil Nadu, India
------------------------------------------------
Department of Computer Science & Business Systems [CSBS]
TECHNICAL SEMINAR
Title :
CHATBOTS
Presented by,
KARTHIKEYAN
2nd YEAR CSBS
Presentation Overview
• What is Chatbots
• Working of chatbots
• Use Cases
• Real time usage
• Case study
• Popular development
• limitations
CHATBOTS
What is chatbots ?
o A chatbot or chatterbot is a software application used to conduct an
online chat conversation via text or text-to-speech, in lieu of providing
direct contact with a live human being
o A chatbot is digital text or voice-based applications. They help different
groups of people or individuals to put their inquiries via text or voice
o They are used to reproduce powerful interactions with users, to aid
business processes, to gain information from large groups, as a personal
assistant among others
WORKING OF CHATBOTS
• A chatbot performs routine automated tasks based on specific triggers and
algorithms, simulating human conversation. A bot is designed to interact with a
human via a chat interface or voice messaging in a web or mobile application, the
same way a user would communicate with another person. Like virtual assistants,
chatbots are a form of conversational AI
• The Artificial Intelligence-Powered Virtual Assistant uses advanced Artificial
Intelligence (AI), RPA, natural language processing, and machine learning to extract
information and complex data from conversations to understand them and process
them accordingly
• To perform its functions, It relies on artificial intelligence (AI) technologies such as
NLP and ML to understand what the user is saying and to make
suggestions or act on that language input.
Chatbots are software that simulates conversations with human users
• Deep learning is used in virtual assistants such as Alexa
and Siri, which use Natural Language Processing (NLP).
NLP analyses and understands unstructured data, such
as forms of human language (written and verbal). It also
analyses factors such as language recognition, sentiment
analysis and text classification and then creates the
appropriate response to your input. When using NLP, it’s
recommended to use deep learning as it better
understands unstructured data, such as written and verbal
language, which helps in scenarios of recognizing
sentiment analysis.
Chatbots Use cases
• 24/7 support
• Internal help desk
• FAQs responses
• Customer engagement
• Voice assistance
• Customer feedback collection
• Chatbot marketing
• Product recommendations
• Medication reminder
• Appointment scheduling
• Collect patient data
• Financial advice and insights
1. Chatbots are Now Based on Natural Language Processing(NLP)
Businesses are researching Natural Language Processing (NLP) to be able to send
accurate responses to users' inquiries. The goal is to allow users and Artificial Intelligence
to communicate naturally and understand complex requests. This would mean that
customer service agents would be able to focus on other tasks while the AI takes care
of customers' queries.
2. Bots for Internal Business Communications
Chatbots can be used for various purposes, including addressing common problems,
answering customer queries, communicating with employees, and finishing HR-related
tasks and transactional functions. Chatbot for website has become increasingly common
in the modern workplace, taking on several roles such as acting as a guide to new
employees through company protocols, recording answers for screen questions, and
assisting with the onboarding process for new employees. Chatbots can save time for
IT desk agents and help with more complicated issues.
REAL TIME USAGE
3. Voice-Bots are also Set to Help Businesses Enhance Customer Service
As customers' attention spans decrease and demand faster methods of consuming
information, companies are increasingly turning to voice search and text-based
messaging platforms to connect with their target
audiences.
4. Live Chatbots to Bring a Human Touch
Chatbots are increasingly used in different sectors.
They can communicate with your target market by
speaking with them in complete sentences with a
natural and easy-going conversational flow.
Some markets that these bots serve include customer
service and retail, amongst others.
CASE STUDY
1- HelloFresh Freddy { Customer service chatbots }
• HelloFresh launched its bot to manage its surveys and quizzes.
When Facebook users correctly responded to quizzes,
Freddy sent them automated deals.
• Even though bot does not seem impressive in its conversational
capabilities, it was able to:
• Reduce response time by 76%. This is not surprising as bot
Immediately responded to numerous queries, bringing the
Average response time down.
• Boost incoming messages by 47%
2 .Healthcare chatbots
• During the Covid-19 outbreak, the government of India
collaborated with conversational AI company Haptik to
develop a WhatsApp chatbot to counteract
misinformation, quickly address people’s questions, and
educate them. Within five days, Haptik created a chatbot
that can react in both Hindi and English.
• The chatbot assisted the government in managing the
pandemic and answered 110 million queries. Users can
access information about the virus, symptoms,
safety precautions, and other topics of interest using
chatbots.
3. Dr. A.I.? already makes recommendations like a Doctor
Developed by the healthcare app, HealthTap, Dr. A.I.? Reads
patients’ symptoms, asks follow-up questions, and analyzes
their data stored in the HealthTap app to connect patients with
a specialized doctor in the vicinity. Dr. A.I.? uses HealthTap’s
database of answers written by medical doctors to make the
right recommendations regarding what next steps the patient
should take. The latter can range from reading doctor
recommendations to scheduling a virtual or in-person
doctor visit or seeking urgent care.
POPULAR CHATBOTS DEVELOPMENT
ELIZA the first ever chatbot was developed by MIT professor Joseph Weizenbaum in the 1960s
The Chatbot ELIZA worked by passing the words that users entered into a computer and then pairing them
to a list of possible scripted responses.
 PARRY-1972
 Jabberwacky-1988
 Dr. Sbaitso-1992
 A.L.I.C.E-1995
 SmarterChild-2001
 Siri-2010
 Google Assistant-2012
 Cortana-2014
 Alexa-2014
 ChatGPT-2021
• As the database, used for output generation, is fixed and limited, chatbots can fail while dealing
with an unsaved query.
• A chatbot's efficiency highly depends on language processing and is limited because of
irregularities, such as accents and mistakes
• Chatbots are unable to deal with multiple questions at the same time and so conversation
opportunities are limited
• Chatbots require a large amount of conversational data to train. Generative models, which are
based on deep learning algorithms to generate new responses word by word based on user input,
are usually trained on a large dataset of natural-language phrases
• chatbots have difficulty managing non-linear conversations
• uncomfortable with chatbots due to their limited understanding
Limitations of chatbots
Thank You

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chatbots presentation .pptx

  • 1. E.G.S.Pillay Engineering College An Autonomous Institution Affiliated to Anna University | Approved by AICTE Accredited by NBA [CSE/IT/ECE] | Accredited by NAAC with Grade ‘A’ One among the Top 300 Engineering Colleges in India [NIRF-2022] Old Nagore Road, Thethi Village, Nagapattinam – 611002, Tamil Nadu, India ------------------------------------------------ Department of Computer Science & Business Systems [CSBS] TECHNICAL SEMINAR Title : CHATBOTS Presented by, KARTHIKEYAN 2nd YEAR CSBS
  • 2. Presentation Overview • What is Chatbots • Working of chatbots • Use Cases • Real time usage • Case study • Popular development • limitations
  • 3. CHATBOTS What is chatbots ? o A chatbot or chatterbot is a software application used to conduct an online chat conversation via text or text-to-speech, in lieu of providing direct contact with a live human being o A chatbot is digital text or voice-based applications. They help different groups of people or individuals to put their inquiries via text or voice o They are used to reproduce powerful interactions with users, to aid business processes, to gain information from large groups, as a personal assistant among others
  • 4. WORKING OF CHATBOTS • A chatbot performs routine automated tasks based on specific triggers and algorithms, simulating human conversation. A bot is designed to interact with a human via a chat interface or voice messaging in a web or mobile application, the same way a user would communicate with another person. Like virtual assistants, chatbots are a form of conversational AI • The Artificial Intelligence-Powered Virtual Assistant uses advanced Artificial Intelligence (AI), RPA, natural language processing, and machine learning to extract information and complex data from conversations to understand them and process them accordingly • To perform its functions, It relies on artificial intelligence (AI) technologies such as NLP and ML to understand what the user is saying and to make suggestions or act on that language input.
  • 5. Chatbots are software that simulates conversations with human users • Deep learning is used in virtual assistants such as Alexa and Siri, which use Natural Language Processing (NLP). NLP analyses and understands unstructured data, such as forms of human language (written and verbal). It also analyses factors such as language recognition, sentiment analysis and text classification and then creates the appropriate response to your input. When using NLP, it’s recommended to use deep learning as it better understands unstructured data, such as written and verbal language, which helps in scenarios of recognizing sentiment analysis.
  • 6. Chatbots Use cases • 24/7 support • Internal help desk • FAQs responses • Customer engagement • Voice assistance • Customer feedback collection • Chatbot marketing • Product recommendations • Medication reminder • Appointment scheduling • Collect patient data • Financial advice and insights
  • 7. 1. Chatbots are Now Based on Natural Language Processing(NLP) Businesses are researching Natural Language Processing (NLP) to be able to send accurate responses to users' inquiries. The goal is to allow users and Artificial Intelligence to communicate naturally and understand complex requests. This would mean that customer service agents would be able to focus on other tasks while the AI takes care of customers' queries. 2. Bots for Internal Business Communications Chatbots can be used for various purposes, including addressing common problems, answering customer queries, communicating with employees, and finishing HR-related tasks and transactional functions. Chatbot for website has become increasingly common in the modern workplace, taking on several roles such as acting as a guide to new employees through company protocols, recording answers for screen questions, and assisting with the onboarding process for new employees. Chatbots can save time for IT desk agents and help with more complicated issues. REAL TIME USAGE
  • 8. 3. Voice-Bots are also Set to Help Businesses Enhance Customer Service As customers' attention spans decrease and demand faster methods of consuming information, companies are increasingly turning to voice search and text-based messaging platforms to connect with their target audiences. 4. Live Chatbots to Bring a Human Touch Chatbots are increasingly used in different sectors. They can communicate with your target market by speaking with them in complete sentences with a natural and easy-going conversational flow. Some markets that these bots serve include customer service and retail, amongst others.
  • 9. CASE STUDY 1- HelloFresh Freddy { Customer service chatbots } • HelloFresh launched its bot to manage its surveys and quizzes. When Facebook users correctly responded to quizzes, Freddy sent them automated deals. • Even though bot does not seem impressive in its conversational capabilities, it was able to: • Reduce response time by 76%. This is not surprising as bot Immediately responded to numerous queries, bringing the Average response time down. • Boost incoming messages by 47%
  • 10. 2 .Healthcare chatbots • During the Covid-19 outbreak, the government of India collaborated with conversational AI company Haptik to develop a WhatsApp chatbot to counteract misinformation, quickly address people’s questions, and educate them. Within five days, Haptik created a chatbot that can react in both Hindi and English. • The chatbot assisted the government in managing the pandemic and answered 110 million queries. Users can access information about the virus, symptoms, safety precautions, and other topics of interest using chatbots.
  • 11. 3. Dr. A.I.? already makes recommendations like a Doctor Developed by the healthcare app, HealthTap, Dr. A.I.? Reads patients’ symptoms, asks follow-up questions, and analyzes their data stored in the HealthTap app to connect patients with a specialized doctor in the vicinity. Dr. A.I.? uses HealthTap’s database of answers written by medical doctors to make the right recommendations regarding what next steps the patient should take. The latter can range from reading doctor recommendations to scheduling a virtual or in-person doctor visit or seeking urgent care.
  • 12. POPULAR CHATBOTS DEVELOPMENT ELIZA the first ever chatbot was developed by MIT professor Joseph Weizenbaum in the 1960s The Chatbot ELIZA worked by passing the words that users entered into a computer and then pairing them to a list of possible scripted responses.  PARRY-1972  Jabberwacky-1988  Dr. Sbaitso-1992  A.L.I.C.E-1995  SmarterChild-2001  Siri-2010  Google Assistant-2012  Cortana-2014  Alexa-2014  ChatGPT-2021
  • 13. • As the database, used for output generation, is fixed and limited, chatbots can fail while dealing with an unsaved query. • A chatbot's efficiency highly depends on language processing and is limited because of irregularities, such as accents and mistakes • Chatbots are unable to deal with multiple questions at the same time and so conversation opportunities are limited • Chatbots require a large amount of conversational data to train. Generative models, which are based on deep learning algorithms to generate new responses word by word based on user input, are usually trained on a large dataset of natural-language phrases • chatbots have difficulty managing non-linear conversations • uncomfortable with chatbots due to their limited understanding Limitations of chatbots