This presentation includes - History, Functions, Working, Advancement, Applications, Advantages, Disadvantages, Limitations & Contests Held - of Chatbot Technology.
Chatbots are services powered by rules and sometimes artificial intelligence that users interact with via chat interfaces. They are a big opportunity because people are using messaging apps more than social networks, so building services within messaging platforms positions them where users spend their time. Chatbots work either by following a set of predefined rules or using machine learning to be more flexible. While they seem simple, building good chatbot experiences requires overcoming challenges like analytics, optimization, and platform changes. Common steps to create a chatbot include determining its purpose, choosing a platform like Facebook Messenger or Slack, and selecting a development service to build it.
This document discusses different approaches for building chatbots, including retrieval-based and generative models. It describes recurrent neural networks like LSTMs and GRUs that are well-suited for natural language processing tasks. Word embedding techniques like Word2Vec are explained for representing words as vectors. Finally, sequence-to-sequence models using encoder-decoder architectures are presented as a promising approach for chatbots by using a context vector to generate responses.
The document discusses and compares three open source platforms for building chatbots: Dialogflow, Snatchbot, and Chatfuel. Dialogflow is highlighted as having powerful machine learning and natural language processing capabilities. Snatchbot's visual editor allows for pre-defined templates but has less robust NLP than Dialogflow. Chatfuel provides contact history, customization, and third party integrations, but has limited NLP and support for complex conversations. Overall, Dialogflow is positioned as best for natural conversations while the others have more limitations.
How do Chatbots Work? A Guide to Chatbot ArchitectureMaruti Techlabs
A chatbot is a program that can have conversations with humans without human assistance. There are two types of chatbots: rule-based chatbots that are limited to their programming, and AI-based chatbots that can understand open-ended queries using machine learning. Chatbots work through question and answering systems, natural language processing to understand context, and by adopting classification methods like pattern matching, algorithms, and artificial neural networks.
The document discusses implementing chatbots using deep learning. It begins by defining what a chatbot is and listing some popular existing chatbots. It then describes two types of chatbot models - retrieval-based models which use predefined responses and generative models which continuously learn from conversations. The document focuses on implementing a retrieval-based model using the Ubuntu Dialog Corpus dataset and a dual encoder LSTM network model in TensorFlow. It outlines the preprocessing, model architecture, creating input functions, training, evaluating, and making predictions with the trained model.
The Chatbots Are Coming: A Guide to Chatbots, AI and Conversational InterfacesTWG
2016 is the year of all things conversational. Chatbots, suddenly, are everywhere. Driven by the explosion in popularity of messaging apps like Kik, Slack and Facebook Messenger, chatbots are quickly becoming a core part of the software product mix.
So does your business need a chatbot? This deck will help you understand the massive opportunity for companies who are bold enough to start building chatbots of their own.
(Already au fait with chatbots and looking for a software team to help you with yours? Skip to slide 47 to see some of the chatbots we've built at TWG for our clients and ourselves.)
Chatbot and Virtual AI Assistant Implementation in Natural Language Processing Shrutika Oswal
In this presentation, I have given a short overview of hot recent topics of research in artificial intelligence. These topics include Gaming, Expert System, Vision System, Speech Recognition, Handwriting Recognition, Intelligent Robots, Machine Learning, Deep Learning, Robotics, Reinforcement Learning, Internet of Things, Neuromorphic Computing, Computer Vision and most important NLP (Natural language Processing). Here I have mentioned different fields and components of NLP along with the steps of implementation. In the further part of the presentation, I have described the general structure of chatbot in NLP along with its implementation algorithm in python language. Also, I have given some informative descriptions, technologies, usage, and working of virtual AI assistants along with this I implemented one virtual assistant for laptop who will able to perform some interesting tasks.
A chatterbot (also known as a talkbot, chatbot, Bot, chatterbox, Artificial Conversational Entity) is a computer program which conducts a conversation via auditory or textual methods.
To find more about it, checkout these slides. For more info, visit our website, www.appgalleryinc.com
This document outlines a project to design and develop a Sugar CRM bot using Artificial Intelligence Markup Language (AIML). The objective is to create a bot that can answer questions about Sugar CRM. It will be implemented as both a desktop and web application using programming languages like AIML, Python, and Adobe Flex. An automatic AIML generation tool will also be developed to ease the creation of AIML files. The source code for the project is available online for checkout and demonstration.
AI Revolution
AI Innovation Checkpoint
AI Innovative BM Development
AI Chatbot for Customer Experience
AI Chatbot Evolution
AI Chatbot Use Cases: Travel Industry
AI Chatbot Use Cases: Food & Beverage Industry
AI Chatbot Use Cases: Banking Industry
AI Chatbot Use Cases: Healthcare Industry
AI Chatbot for Retail Services Innovation
AI Chatbot Use Cases: Retail & Fashion Industry
Emotion AI
Replika: An Emotion AI Chatbot
Woebot: Robot Therapist
AI Chatbot Design
AI Chatbot Development
Emotion AI Chatbot Prototype Demo
AI Chatbot Sentiment Analysis + Big Data Analytics Demo
E-Commerce Integration Demo
The document introduces chat bots, which are computer programs that can converse with humans in natural language using artificial intelligence and predefined responses. Chat bots are useful for answering queries and replacing humans for repetitive tasks. They can operate based on artificial intelligence using machine learning or follow predefined rules to structure conversations.
Chatbots are computer programs designed to simulate conversation with humans over the Internet. Examples include Cortana, Siri, and Eliza, the first chatbot created by Joseph Weizenbaum. Chatbots provide information quickly and efficiently for productivity or entertainment, fueling conversations to avoid loneliness. They are trained using large datasets of conversation logs to understand language and connect questions to answers. While chatbots reduce costs and can handle many users at once, they have limitations in complex conversations and understanding intent. Future chatbots may become more specialized and useful in applications like e-commerce, travel, and events.
Daden Emerging Technology Seminars - Daden Limited is a Virtual Worlds and artificial intelligence solution provider.
Our focus is on using virtual worlds, and virtual personalities to deliver more efficient and effective enterprise systems, saving our clients money, time and carbon, and delivering better understanding and collaboration.
This document provides an overview of chatbots, including: definitions of chatbots, the history of chatbots beginning in the 1960s, problems with current chatbot scenarios, educational and system requirements for developing chatbots, how chatbots work, types of chatbots, principles of chatbot design, data flow diagrams and ER diagrams related to chatbots, chatbot architecture, advantages and disadvantages of chatbots compared to humans, examples of successful chatbots, applications and limitations of chatbots, and conclusions. It also includes an index of topics covered and references related to chatbot design.
An overview of some key concepts of chatbots, with some do's and don'ts.
We will happily present the high-resolution version of this presentation, extended with additional detailed slides, and a clear explanation at your offices. Contact us for that.
There are two main types of chatbots: decision tree and cognitive. Decision tree chatbots use flowcharts of possible questions and answers while cognitive chatbots use artificial intelligence to understand language. Examples of chatbots include DoNotPay which helps with legal issues, KiK and KLM for customer service, and bots that can order food or provide government information. A video is presented showing what might happen if two chatbots had a conversation with each other.
ChatGPT is a conversational AI model developed by OpenAI that is capable of generating human-like text responses. It is trained on a large dataset of human conversations which allows it to have natural, coherent conversations on a wide range of topics. Key features include generating long-form paragraphs, handling diverse inputs, and maintaining context across multiple conversation turns. While not designed for SEO, ChatGPT could potentially be used to generate website content, but may not optimize for search engines and could harm a site's rankings.
The document discusses artificial text chatting machines (chatbots). It provides an overview of chatbots, including their history starting with ELIZA from 1966. Common approaches to developing chatbots include pattern matching and using the Artificial Intelligence Markup Language (AIML). The document outlines some challenges in developing human-like intelligence for chatbots and possibilities for future work, before concluding with a demonstration.
Chatbot technologies allow for conversational interfaces using artificial intelligence. Chatbots have evolved from simple script-based assistants to more advanced bots that can understand context, maintain histories of conversations, and collaborate with users. Chatbots work using natural language processing and databases to match user inputs with responses. They are used in messaging platforms, apps, websites, and more to provide information and services with many benefits like 24/7 availability but also challenges like limited capabilities. The future of chatbots includes more personalized and integrated experiences using artificial intelligence and connections to other technologies.
AI Agent and Chatbot Trends For EnterprisesTeewee Ang
This document discusses the growing trend of chatbots and artificial intelligence assistants. It notes that major tech entrepreneurs like Mark Zuckerberg and Elon Musk have expressed interest in AI. While Musk sees AI as a potential threat, Zuckerberg wants to create an AI assistant for home use. The document outlines how chatbots use technologies like natural language processing and machine learning. It provides examples of chatbots being used in applications like customer service, human resources, and scheduling. In conclusion, the document predicts that AI assistant and chatbot applications will continue growing in both enterprise and consumer spaces.
This document provides an overview of chatbots including:
1. It defines chatbots as AI programs that simulate conversation through text or voice with humans.
2. It discusses the history of chatbots from early prototypes in the 1960s to modern implementations on platforms like Facebook Messenger.
3. It describes the main types of chatbots as flow-based, artificially intelligent, and hybrid models.
The document discusses chat bots and their potential future uses. It notes that apps have already created millions of jobs and bots may be the next step. Bots can perform automated tasks like answering questions or taking orders through messaging apps. Currently, people are using messaging apps more than social networks. The document outlines different types of bots including those that operate through rules-based programming and more advanced bots using machine learning that can understand language. It provides examples of potential bots and services to build bots. It concludes by recommending Cisco leverage chat bots for quick answers, analyzing Facebook messages, and developing future uses in tech support, sales, and communications between companies' bots.
Tech adoption for AI ML has been rapidly growing over the globe and ChatGPT is the game changer. Artificial intelligence and Machine learning are uplifting internet era with swift solutions for users. https://www.9series.com/blog/revolutionary-chatgpt/
This document describes the development of a chatbot application using Python to answer queries about a college. It discusses the existing system of students having to visit the college in person to ask questions, and the limitations thereof. The proposed chatbot system allows students to get college information by chatting with the bot through text. The document outlines the modules, design, and functioning of the chatbot, including its ability to understand natural language queries and provide relevant answers from its database. It concludes discussing the benefits of chatbots and potential for future improvements.
This document provides an overview of chatbots and the growing chatbot ecosystem. It discusses why natural language interfaces are important, defines what a chatbot is, explores where chatbots are being used, outlines what capabilities chatbots have, and describes the growing platform and tools available for building chatbots. It emphasizes that while building basic chatbots is easy, creating truly useful chatbots requires serious thought and work.
This document provides an overview of chatbot technology. It discusses that a chatbot is a software application that conducts online conversations through text to simulate human interactions. The document then covers what a chatbot is, how it responds using pattern matching and predefined responses, examples of popular chatbots like Google Home and Amazon Echo, common usage areas of chatbots, and limitations such as inability to handle complex conversations. In summary, the document defines chatbots, describes how they operate through examples, and discusses their applications and limitations.
Artificial Intelligence Virtual Assistants & ChatbotsaNumak & Company
Artificial Intelligence transforms different interfaces into interactive systems that can be interacted with using Natural Language Processing technology. Thus, businesses can offer voice-integrated smart self-service solutions to their customers with Natural Dialogue Solutions, which can be positioned in different areas ranging from IVR systems to virtual assistants, from chatbots to smart systems.
A chatterbot (also known as a talkbot, chatbot, Bot, chatterbox, Artificial Conversational Entity) is a computer program which conducts a conversation via auditory or textual methods.
To find more about it, checkout these slides. For more info, visit our website, www.appgalleryinc.com
This document outlines a project to design and develop a Sugar CRM bot using Artificial Intelligence Markup Language (AIML). The objective is to create a bot that can answer questions about Sugar CRM. It will be implemented as both a desktop and web application using programming languages like AIML, Python, and Adobe Flex. An automatic AIML generation tool will also be developed to ease the creation of AIML files. The source code for the project is available online for checkout and demonstration.
AI Revolution
AI Innovation Checkpoint
AI Innovative BM Development
AI Chatbot for Customer Experience
AI Chatbot Evolution
AI Chatbot Use Cases: Travel Industry
AI Chatbot Use Cases: Food & Beverage Industry
AI Chatbot Use Cases: Banking Industry
AI Chatbot Use Cases: Healthcare Industry
AI Chatbot for Retail Services Innovation
AI Chatbot Use Cases: Retail & Fashion Industry
Emotion AI
Replika: An Emotion AI Chatbot
Woebot: Robot Therapist
AI Chatbot Design
AI Chatbot Development
Emotion AI Chatbot Prototype Demo
AI Chatbot Sentiment Analysis + Big Data Analytics Demo
E-Commerce Integration Demo
The document introduces chat bots, which are computer programs that can converse with humans in natural language using artificial intelligence and predefined responses. Chat bots are useful for answering queries and replacing humans for repetitive tasks. They can operate based on artificial intelligence using machine learning or follow predefined rules to structure conversations.
Chatbots are computer programs designed to simulate conversation with humans over the Internet. Examples include Cortana, Siri, and Eliza, the first chatbot created by Joseph Weizenbaum. Chatbots provide information quickly and efficiently for productivity or entertainment, fueling conversations to avoid loneliness. They are trained using large datasets of conversation logs to understand language and connect questions to answers. While chatbots reduce costs and can handle many users at once, they have limitations in complex conversations and understanding intent. Future chatbots may become more specialized and useful in applications like e-commerce, travel, and events.
Daden Emerging Technology Seminars - Daden Limited is a Virtual Worlds and artificial intelligence solution provider.
Our focus is on using virtual worlds, and virtual personalities to deliver more efficient and effective enterprise systems, saving our clients money, time and carbon, and delivering better understanding and collaboration.
This document provides an overview of chatbots, including: definitions of chatbots, the history of chatbots beginning in the 1960s, problems with current chatbot scenarios, educational and system requirements for developing chatbots, how chatbots work, types of chatbots, principles of chatbot design, data flow diagrams and ER diagrams related to chatbots, chatbot architecture, advantages and disadvantages of chatbots compared to humans, examples of successful chatbots, applications and limitations of chatbots, and conclusions. It also includes an index of topics covered and references related to chatbot design.
An overview of some key concepts of chatbots, with some do's and don'ts.
We will happily present the high-resolution version of this presentation, extended with additional detailed slides, and a clear explanation at your offices. Contact us for that.
There are two main types of chatbots: decision tree and cognitive. Decision tree chatbots use flowcharts of possible questions and answers while cognitive chatbots use artificial intelligence to understand language. Examples of chatbots include DoNotPay which helps with legal issues, KiK and KLM for customer service, and bots that can order food or provide government information. A video is presented showing what might happen if two chatbots had a conversation with each other.
ChatGPT is a conversational AI model developed by OpenAI that is capable of generating human-like text responses. It is trained on a large dataset of human conversations which allows it to have natural, coherent conversations on a wide range of topics. Key features include generating long-form paragraphs, handling diverse inputs, and maintaining context across multiple conversation turns. While not designed for SEO, ChatGPT could potentially be used to generate website content, but may not optimize for search engines and could harm a site's rankings.
The document discusses artificial text chatting machines (chatbots). It provides an overview of chatbots, including their history starting with ELIZA from 1966. Common approaches to developing chatbots include pattern matching and using the Artificial Intelligence Markup Language (AIML). The document outlines some challenges in developing human-like intelligence for chatbots and possibilities for future work, before concluding with a demonstration.
Chatbot technologies allow for conversational interfaces using artificial intelligence. Chatbots have evolved from simple script-based assistants to more advanced bots that can understand context, maintain histories of conversations, and collaborate with users. Chatbots work using natural language processing and databases to match user inputs with responses. They are used in messaging platforms, apps, websites, and more to provide information and services with many benefits like 24/7 availability but also challenges like limited capabilities. The future of chatbots includes more personalized and integrated experiences using artificial intelligence and connections to other technologies.
AI Agent and Chatbot Trends For EnterprisesTeewee Ang
This document discusses the growing trend of chatbots and artificial intelligence assistants. It notes that major tech entrepreneurs like Mark Zuckerberg and Elon Musk have expressed interest in AI. While Musk sees AI as a potential threat, Zuckerberg wants to create an AI assistant for home use. The document outlines how chatbots use technologies like natural language processing and machine learning. It provides examples of chatbots being used in applications like customer service, human resources, and scheduling. In conclusion, the document predicts that AI assistant and chatbot applications will continue growing in both enterprise and consumer spaces.
This document provides an overview of chatbots including:
1. It defines chatbots as AI programs that simulate conversation through text or voice with humans.
2. It discusses the history of chatbots from early prototypes in the 1960s to modern implementations on platforms like Facebook Messenger.
3. It describes the main types of chatbots as flow-based, artificially intelligent, and hybrid models.
The document discusses chat bots and their potential future uses. It notes that apps have already created millions of jobs and bots may be the next step. Bots can perform automated tasks like answering questions or taking orders through messaging apps. Currently, people are using messaging apps more than social networks. The document outlines different types of bots including those that operate through rules-based programming and more advanced bots using machine learning that can understand language. It provides examples of potential bots and services to build bots. It concludes by recommending Cisco leverage chat bots for quick answers, analyzing Facebook messages, and developing future uses in tech support, sales, and communications between companies' bots.
Tech adoption for AI ML has been rapidly growing over the globe and ChatGPT is the game changer. Artificial intelligence and Machine learning are uplifting internet era with swift solutions for users. https://www.9series.com/blog/revolutionary-chatgpt/
This document describes the development of a chatbot application using Python to answer queries about a college. It discusses the existing system of students having to visit the college in person to ask questions, and the limitations thereof. The proposed chatbot system allows students to get college information by chatting with the bot through text. The document outlines the modules, design, and functioning of the chatbot, including its ability to understand natural language queries and provide relevant answers from its database. It concludes discussing the benefits of chatbots and potential for future improvements.
This document provides an overview of chatbots and the growing chatbot ecosystem. It discusses why natural language interfaces are important, defines what a chatbot is, explores where chatbots are being used, outlines what capabilities chatbots have, and describes the growing platform and tools available for building chatbots. It emphasizes that while building basic chatbots is easy, creating truly useful chatbots requires serious thought and work.
This document provides an overview of chatbot technology. It discusses that a chatbot is a software application that conducts online conversations through text to simulate human interactions. The document then covers what a chatbot is, how it responds using pattern matching and predefined responses, examples of popular chatbots like Google Home and Amazon Echo, common usage areas of chatbots, and limitations such as inability to handle complex conversations. In summary, the document defines chatbots, describes how they operate through examples, and discusses their applications and limitations.
Artificial Intelligence Virtual Assistants & ChatbotsaNumak & Company
Artificial Intelligence transforms different interfaces into interactive systems that can be interacted with using Natural Language Processing technology. Thus, businesses can offer voice-integrated smart self-service solutions to their customers with Natural Dialogue Solutions, which can be positioned in different areas ranging from IVR systems to virtual assistants, from chatbots to smart systems.
A study states that people are now spending more time in messaging apps than social networking applications. Messaging apps are in trend and chatbots are the future. Learn everything about the chatbots from history to types to working, right here.
With lower budgets and staff available, chatbots may be the future of Extension support. Learn how we built our own Extension chatbot called "veggiebot" to help answer questions from the public.
Chatbots, and how will Microsoft help us with this?PVS-Studio
This overview article is devoted to the study of a trend which is growing rapidly in popularity in the IT industry - chatbots, and the role of Microsoft in their development process. The article will cover the history of chatbots, peculiar properties of bots, the main, and also some unexpected spheres of their application, perspectives and technology limits.
We have deliberately chosen Microsoft as the main platform for comparative research. The company does a lot of work in the field of promotion and development of intelligent bots. One of the main steps in this direction is a framework for creation of custom bots Microsoft Bot Framework platform - independent and open source; Microsoft presented it at the Build 2016 exhibition.
Chatbots have grown business by drawing in a greater number of customers, investigating customer data, providing personalized support and thus increasing sales. This has made an evident feature in app development
The chat bots which are Artificial Intelligent and are fully functional on how they learn and what they learn with respect to the inputs, how they find patterns and respond accordingly.
Fundamental Difference between an AI Powered Chat Bots and Normal Chat Bots.
This presentation will cover all the fundamentals related to AI Chat bot with examples. You will also learn about working of chatbots at the back end using NLP i.e. Natural Language Processing.
Do you use the internet? Do you use websites with customer support live chat? If you answered yes to any of the questions I asked above, then chances are you have the first-hand experience of interacting with a chatbot. With digital interaction reaching new heights, chatbots have become quite the new buzz. And over the time chatbots have evolved too. When chatbots were conceived, they sounded entirely robotic, but today with the advancements in machine learning, these chatbots have improved in analysing the legions of data provided to them. They almost feel human when talking to.
The Chatbot Imperative: Intelligence, Personalization and Utilitarian DesignCognizant
To boost business outcomes and deliver superior experiences, chatbots must quickly deliver responses that speak directly to individual human needs and apply meaningful responses to evolving requirements over time.
The Software Challenges of Building Smart Chatbots - ICSE'21Jordi Cabot
Chatbots are popular solutions assisting humans in multiple fields, such as customer support or e-learning. However, building such applications has become a complex task requiring a high-level of expertise in a variety of technical domains. Chatbots need to integrate (AI-based) NLU components, but also connect to internal/external services, deploy on various platforms, etc.
The briefing will first cover the current landscape of chatbot frameworks. Then, we’ll get our hands dirty and create a few bots of increasing difficulty playing with aspects like entity recognition, sentiment analysis, event processing, or testing. By the end of the session, attendees will have all the keys to understand the main steps and obstacles to building a good chatbot.
Mark Swaine UX Guy Designing Bot ExperiencesMark N Swaine
The document discusses the rise of messaging platforms and chatbots. It notes that messaging apps are increasingly used for both personal and business communication, replacing voice calls and emails. As messaging grows, companies are exploring using chatbots for customer service and marketing through platforms like Facebook Messenger, WhatsApp, and Slack. The document provides an overview of some popular tools for developing chatbots and outlines important considerations for designing the user experience of a chatbot, such as ensuring the core services can be represented through natural language conversations and testing the dialogue flows.
This document provides an overview of chatbots from Deloitte Artificial Intelligence. It discusses the rise of chatbots and how they are becoming more sophisticated through advances in AI. It describes different types of chatbots from simple FAQ chatbots to more advanced virtual agents. It also outlines factors to consider when architecting a chatbot such as natural language processing capabilities and training approaches. Finally, it discusses Deloitte's approach to assisting clients with chatbot implementations.
This document provides an overview of chatbots from Deloitte AI. It discusses the rise of chatbots and how they are becoming more sophisticated through advances in AI. It describes different types of chatbots from basic FAQ chatbots to more advanced virtual agents. It also discusses how to architect chatbots, including the need for natural language processing, machine learning, intent recognition and other capabilities. The document then provides an overview of Deloitte's approach to assisting clients with chatbot implementation, from the initial exploration phase to building prototypes and integrating solutions.
Fabrice Lacroix - Connecting a Chatbot to Your Technical Content: Myth and Re...LavaConConference
Analysts predict that chatbots will be your customers’ preferred interface. How can you transition from carefully staged demos to real-life customers?
In this session attendees will learn:
How rules-based chatbots work and why those simple demos are so impressive
Why chatbots so often fail as soon as they enter the real world
Why current technologies are inadequate and give unsatisfactory experiences
The difficulties in fueling a chatbot with text-based content
Technological approaches which will permit you to go to the next level with a chatbot that can take you to a higher degree of functionality
Here we have shared little cheat sheet with an essential checklist for you, so you don’t have to wonder where to start. Take a look, and happy building!
A chatbot is an artificial intelligence software that can simulate conversations with users through messaging apps, websites, or phone calls. There are two main types - AI based chatbots that can learn from interactions, and rule based chatbots with fixed information. Chatbots work by analyzing user requests to understand intent, then returning an appropriate response. While chatbots provide round-the-clock assistance and instant responses, limitations include an inability to understand new queries or remember past conversations.
The document discusses the growing use and capabilities of chatbots and virtual assistants. It notes that chatbots are becoming a key access channel for customer service, with Gartner predicting 25% of customer service will be via bots by 2020. The document then draws parallels to the rise of websites in the 1990s, and how chatbot development skills are becoming more widespread. It emphasizes that chatbots should be designed with user needs and expectations in mind. The remainder discusses tools for developing more advanced chatbots with capabilities like disambiguation, digressions, and integrating images and backend data.
This is my presentation for Global Azure Verona 2021, where I talked about Azure Functions and how this technology can be used to process messages that come from WhatsApp in a chatbot environment.
While the idea of talking to a robot might seem silly or like something from a science fiction novel, the truth is, you probably already spend time talking to robots. The development and integration of artificial intelligence (AI) into our everyday lives and the technology we use means robots are all around us. Chatbots are just one common example. Here, we will talk about the evolution of chatbots and the features of the chatbots that we interact with often today.
This paper proposes a shoulder inverse kinematics (IK) technique. Shoulder complex is comprised of the sternum, clavicle, ribs, scapula, humerus, and four joints.
Building Security Systems in Architecture.pdfrabiaatif2
Building security systems are essential for protecting people, property, and assets within a structure. These systems include a range of technologies and strategies such as surveillance cameras (CCTV), access control systems, alarm systems, security lighting, and motion detectors. Modern security solutions often integrate smart technology, allowing remote monitoring and real-time alerts through mobile devices. Access control systems, like key cards or biometric scanners, ensure that only authorized individuals can enter certain areas, enhancing both safety and privacy. Alarm systems, whether triggered by unauthorized entry, fire, or environmental hazards, play a critical role in emergency response. Additionally, video surveillance acts as both a deterrent and a tool for investigating incidents. An effective building security system is carefully planned during the design phase, taking into account the building's size, purpose, and potential risks. Ultimately, robust security systems are vital for ensuring peace of mind, protecting lives, and preserving valuable assets.
The Fluke 925 is a vane anemometer, a handheld device designed to measure wind speed, air flow (volume), and temperature. It features a separate sensor and display unit, allowing greater flexibility and ease of use in tight or hard-to-reach spaces. The Fluke 925 is particularly suitable for HVAC (heating, ventilation, and air conditioning) maintenance in both residential and commercial buildings, offering a durable and cost-effective solution for routine airflow diagnostics.
ADVXAI IN MALWARE ANALYSIS FRAMEWORK: BALANCING EXPLAINABILITY WITH SECURITYijscai
With the increased use of Artificial Intelligence (AI) in malware analysis there is also an increased need to
understand the decisions models make when identifying malicious artifacts. Explainable AI (XAI) becomes
the answer to interpreting the decision-making process that AI malware analysis models use to determine
malicious benign samples to gain trust that in a production environment, the system is able to catch
malware. With any cyber innovation brings a new set of challenges and literature soon came out about XAI
as a new attack vector. Adversarial XAI (AdvXAI) is a relatively new concept but with AI applications in
many sectors, it is crucial to quickly respond to the attack surface that it creates. This paper seeks to
conceptualize a theoretical framework focused on addressing AdvXAI in malware analysis in an effort to
balance explainability with security. Following this framework, designing a machine with an AI malware
detection and analysis model will ensure that it can effectively analyze malware, explain how it came to its
decision, and be built securely to avoid adversarial attacks and manipulations. The framework focuses on
choosing malware datasets to train the model, choosing the AI model, choosing an XAI technique,
implementing AdvXAI defensive measures, and continually evaluating the model. This framework will
significantly contribute to automated malware detection and XAI efforts allowing for secure systems that
are resilient to adversarial attacks.
Taking AI Welfare Seriously, In this report, we argue that there is a realist...MiguelMarques372250
In this report, we argue that there is a realistic possibility that some AI systems
will be conscious and/or robustly agentic in the near future. That means that the
prospect of AI welfare and moral patienthood — of AI systems with their own
interests and moral significance — is no longer an issue only for sci-fi or the
distant future. It is an issue for the near future, and AI companies and other actors
have a responsibility to start taking it seriously. We also recommend three early
steps that AI companies and other actors can take: They can (1) acknowledge that
AI welfare is an important and difficult issue (and ensure that language model
outputs do the same), (2) start assessing AI systems for evidence of consciousness
and robust agency, and (3) prepare policies and procedures for treating AI systems
with an appropriate level of moral concern. To be clear, our argument in this
report is not that AI systems definitely are — or will be — conscious, robustly
agentic, or otherwise morally significant. Instead, our argument is that there is
substantial uncertainty about these possibilities, and so we need to improve our
understanding of AI welfare and our ability to make wise decisions about this
issue. Otherwise there is a significant risk that we will mishandle decisions about
AI welfare, mistakenly harming AI systems that matter morally and/or mistakenly
caring for AI systems that do not.
Passenger car unit (PCU) of a vehicle type depends on vehicular characteristics, stream characteristics, roadway characteristics, environmental factors, climate conditions and control conditions. Keeping in view various factors affecting PCU, a model was developed taking a volume to capacity ratio and percentage share of particular vehicle type as independent parameters. A microscopic traffic simulation model VISSIM has been used in present study for generating traffic flow data which some time very difficult to obtain from field survey. A comparison study was carried out with the purpose of verifying when the adaptive neuro-fuzzy inference system (ANFIS), artificial neural network (ANN) and multiple linear regression (MLR) models are appropriate for prediction of PCUs of different vehicle types. From the results observed that ANFIS model estimates were closer to the corresponding simulated PCU values compared to MLR and ANN models. It is concluded that the ANFIS model showed greater potential in predicting PCUs from v/c ratio and proportional share for all type of vehicles whereas MLR and ANN models did not perform well.
ELectronics Boards & Product Testing_Shiju.pdfShiju Jacob
This presentation provides a high level insight about DFT analysis and test coverage calculation, finalizing test strategy, and types of tests at different levels of the product.
Dust Suppressants: A Sustainable Approach to Dust Pollution ControlJanapriya Roy
This journal explores the growing field of bio-organic dust suppressants as a sustainable solution to dust pollution. It reviews the working principles of dust suppression, key performance indicators, and the latest research on using natural materials like polysaccharides, lignin, proteins, and agricultural wastes. It also highlights current challenges and future directions to enhance the durability, cost-effectiveness, and environmental safety of bio-based dust control technologies. A valuable reference for researchers, environmental engineers, and industry professionals seeking eco-friendly dust management solutions.
Dust pollution, whether natural or anthropogenic, poses significant threats to both the environment and public health. Effective dust suppression technologies are essential in mitigating airborne particulate matter, especially in industrial, mining, and construction settings. Recently, bio-organic materials have emerged as promising raw materials for eco-friendly dust suppressants. This paper explores the working principles of dust suppressants, key performance evaluation indices, and the current progress in developing bio-based dust control agents using polysaccharides, lignin, proteins, microorganisms, and agricultural or forestry waste. It also discusses existing challenges and future research directions for enhancing the efficiency and applicability of bio-organic dust suppressants.
Working Principles of Dust Suppressants
Dust suppressants operate primarily through three interrelated mechanisms: wetting, coagulation, and consolidation.
Wetting: This mechanism involves the application of dust suppressants to reduce the surface tension of water, allowing it to penetrate and coat dust particles. This increases the weight and cohesion of the particles, causing them to settle quickly. Surfactants and hygroscopic agents are commonly used in this approach.
Coagulation: Dust particles are brought together to form larger aggregates through electrostatic interactions or binding agents, which helps in accelerating their settling.
Consolidation: A more long-term effect where the suppressant forms a crust or mesh-like structure over the dust-prone surface, physically stabilizing it and preventing re-entrainment of particles by wind or vehicle movement.
Bio-Organic Materials in Dust Suppressants
The shift toward natural, renewable, and biodegradable components has led to extensive research on the use of various bio-organic substances, including:
Polysaccharides: Starch, cellulose derivatives, and chitosan can form gels or films that stabilize surfaces.
Lignin: A byproduct of the paper industry, lignin offers strong binding capacity and is naturally water-resistant.
Proteins: Derived from agricultural waste, proteins like casein and soy protein can enhance binding and wetting.
Microorganisms: Certain bacteria and fungi can produce biofilms or exopolysaccharides that trap dust particles.
Agricultural and Forestry Wastes: Residues su
its all about Artificial Intelligence(Ai) and Machine Learning and not on advanced level you can study before the exam or can check for some information on Ai for project
3. ABSTRACT
• A chatbot is a computer program that simulates human
conversation through voice commands or text chats or
both. Chatbot, short for chatterbot, is an Artificial
Intelligence (AI) feature that can be embedded and used
through any major messaging applications. There are a
number of synonyms for chatbot, including "talk-bot,"
"bot," "interactive agent" or "artificial conversation
entity."
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4. TABLE OF CONTENTS
INTRODUCTION:CHATBOT…………………………………….. 5
AI & NLP…………………………………………………………….. 6
TYPES OF CHATBOTS……………………………………………. 7
HISTORY……………………………………………………………. 8
FUNCTIONS………………………………………………………... 11
WORKING: CHATBOTS………………………………………….. 12
ADVANES: CHATBOT TECHNOLOGY………………………… 13
APPLICATIONS……………………………………………………. 16
ADVANTAGES OF CHATBOTS………………………………….. 17
DISADVANTAGES OF CHATBOTS……………………………... 19
LIMITATIONS OF CHATBOTS………………………………….. 20
CHATBOT DEVELPOMENT SITES…………………………….. 21
CONTESTS HELD………………………………………………… 25
CONCLUSION…………………………………………………… 26
REFERENCES…………………………………………………… 27 4
5. TABLE OF FIGURES
• Fig.1 Working Of Chatbots…………………………… 13
• Fig.2 Chatbot Usage In Different Domains…………………. 24
• Fig.3 Predicted Use Cases For Chatbots …..……………. 25
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6. INTRODUCTION: CHATBOT
• A chatbot is an artificial intelligence (AI) software that
can simulate a conversation (or a chat) with a user in
natural language through messaging applications,
websites, mobile apps or through the telephone.
• A chatbot is often described as one of the most advanced
and promising expressions of interaction between humans
and machines.
• However, from a technological point of view, a chatbot
only represents the natural evolution of a Question
Answering system leveraging Natural Language
Processing (NLP). 6
7. ARTIFICIAL INTELLIGENCE (AI):-
• A branch of computer science dealing with the simulation of
intelligent behaviour in computers.
• The capability of a machine to imitate intelligent human
behaviour.
NATURAL LANGUAGE PROCESSING (NLP):-
Natural language processing (NLP) is the ability of a computer
program to understand human language as it is spoken. NLP is
a component of artificial intelligence (AI).
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8. TYPES OF CHATBOTS
• Chatbots based on Artificial Intelligence (AI):
These chatbots learn dynamically, and are constantly being updated
through interactions with customers. They are intelligent, with an
advanced design and offer a very positive UX.
• Fixed Chatbots:
These are programs with fixed information, which offer limited help.
They are used for customers with limited access to Customer
Service, or to solve repetitive questions. They are not as popular, as
they are unable to understand human behaviour. In addition, if any
questions arise beyond those they have established, you will not be
able to answer them.
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9. HISTORY
• The term "ChatterBot" was originally coined by Michael Mauldin
(creator of the first Verbot, Julia) in 1994 to describe these
conversational programs.
• Though chatbots are still in their relative infancy technologically,
they have existed for decades. One of the first chatbots, ELIZA,
was developed in 1966 by computer scientist Joseph Weizenbaum
at the MIT Artificial Intelligence Laboratory.
• Joseph designed ELIZA to mimic human interaction through
pattern recognition; ELIZA could not, however, react to queries in
their full context. Instead, ELIZA had built-in scripts that allowed
it to display the illusion of intelligence in answering questions on
a given subject, such as those related to psychological evaluation.
9
10. • PARRY was an early example of a chatterbot, implemented in
1972 by psychiatrist Kenneth Colby.
• While ELIZA and PARRY were used exclusively to simulate
typed conversation, many chatbots now include functional
features such as games and web searching abilities.
• More recent notable programs include A.L.I.C.E., Jabberwacky
and D.U.D.E (Agence Nationale de la Recherche and CNRS
2006).
• A.L.I.C.E. is still purely based on pattern matching techniques
without any reasoning capabilities, the same technique ELIZA
was using back in 1966.
10
11. • Jabberwacky learns new responses and context based on
real-time user interactions, rather than being driven from a
static database.
• Today, most chatbots are accessed via virtual assistants such
as Google Assistant and Amazon Alexa, via messaging apps
such as Facebook Messenger or WeChat, or via individual
organizations' apps and websites.
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12. “One should not look at a chatbot as a simple
messaging service.
Chatbots today are designed to not only perform natural
language understanding but are also able to perform
cognitive service functions such as:
• Speech to Text
• Computer Vision
• Language Recognition and Translation
• Content Moderation
• Speaker Recognition
• Text Analytics
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14. Advances In Chatbot Technology
• Microsoft has recently demonstrated one of their more advanced
ChatBots over in China, Xiaolce, which is said to have more
natural interaction with humans demonstrating Microsoft’s
determination to get ahead in the ChatBot world.
• The knowledge which has been implemented in these new and
more advanced ChatBots is called ‘Full Duplex Voice Sense’,
which means two-way communication can be had. In other
words, the Microsoft Xiaolce is a telephone whereas the Alexa
is a walkie-talkie.
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15. • Automated Call Centers with AI technology
With the advancement done in NLO as mentioned above-automated
call centers will soon come into existence. Combining NLO, AI
voice generation and ‘server-less’ technology will allow automated
call centers. Automated call centers will have deep domain
knowledge and this will help to have a conversation with the
customers.
• Deep Customer Insights
Chatbots easily store customer data as per request which can be
easily retrieved to make a proper analysis.
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16. Chatbots assure
• Logical,
• Transparent, and
• Clear Communications.
You will have them directly inside your applications, and
regardless of what you speak will get recorded. In this way,
there’s no possibility of ambiguities or disarray.
• As per the latest analysis, just 20 percent of the web
clients have followed the chatbot usage in their daily
subsistence which is estimated to raise in the future up to
93 percent till 2021.
16
17. APPLICATIONS:-
• Messaging apps
• As part of company apps and websites
• Chatbot sequences
• Company internal platforms
• Banking
• Politics
• Toys
17
18. Advantages: Chatbot Technology
• Save Time
For instance, when used on your website they can provide fast,
automated answers to most questions. Their use prevents customers
from waiting a day or longer to receive responses as they would have
in the past.
• Save Money
Chatbot use can be cheaper than hiring more workers. Costs to have a
chatbot built can range from 2K to 10K or more depending on the
complexity needed.
• Provide Greater Customer Satisfaction
Chatbots don’t work 8 hour days and don’t need sleep which means they are
always available. Frustrated customers who don’t get quick answers, on the
other hand, may leave your website and never return. Chatbots can eliminate
that scenario and help you keep your customers.
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19. • Increase Customer Base
They may help you reach more people which can increase your
customer base. Since chatbots can be used in many applications you
can take advantage of that to help your business grow.
• Cut Down on Errors
Unfortunately, humans handling customer service questions and other
issues can make errors. They can forget things, transpose numbers, and
make other types of mistakes. Not so with chatbots.
• Add Good Humor
You never have to worry about a chatbot being in a bad mood. They
will never turn away customers with an angry response, attitude, or
glance. They can be programed to have a bit of humor which can make
them seem more humanlike.
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20. Disadvantages: Chatbot Technology
• Complex interface
• They don’t get you right
• Time-consuming
• Installation cost
• Null decision making
• Bad memory
• Your personnel information is being stored & can be
misused.
• People will become dependent and will be vulnerable.
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21. LIMITATIONS OF CHATBOTS
It have some important limitations in terms of functionalities
and use cases:-
• 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 that can create an important barrier for international
and multi-cultural organisations.
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22. Chatbot Development Sites
The process of building, testing and deploying chatbots can be done on
cloud-based chatbot development platforms offered by cloud Platform
as a Service (PaaS) providers such as:-
• Oracle Cloud Platform
• SnatchBot
• IBM Watson
• These cloud platforms provide Natural Language Processing,
Artificial Intelligence and Mobile Backend as a Service for chatbot
development.
• Some Companies like Microsoft Azure and AARC are currently
providing their Bot Engines through which chatbot Platforms or
Software can be developed.
22
23. • Chatbots are unable to deal with multiple questions at the
same time and so conversation opportunities are limited.
• As it happens usually with technology-led changes in
existing services, some consumers, more often than not
from the old generation, are uncomfortable with chatbots
due to their limited understanding, making it obvious that
their requests are being dealt machines.
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26. CONTESTS HELD
Two such annual contests are:-
• The Loebner Prize
• The Chatterbox Challenge (the latter has been offline
since 2015, however materials can still be found from
web archives).
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27. CONCLUSION
Chatbots for business will definitely evolve in the following
years – the design and architecture can possibly improve to a
point where interactive bots become the standard for
customer service. Still, there are different apps for Chatbots
across a variety of sectors.
In the end, the adaptation of a new technology largely
depends on these factors:
• - Lower costs
• - Growing demand
• - Improved technology
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