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.
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
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.
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.
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.
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 building conversational chatbots using Dialogflow. It begins with defining what chatbots are and discussing their history. It then explains the types of chatbots and how Dialogflow uses artificial intelligence to enable chatbots that can learn from interactions. The document demonstrates how to create an agent and intents in Dialogflow to develop a basic chatbot. It also discusses entities, integration options, and using fulfillment for additional functionality. The presenter provides resources for learning more about Dialogflow and chatbot development.
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.
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.
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.
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:
- Defining what chatbots are and why they are important for app developers.
- Discussing different approaches for chatbots such as replacing apps, greeting users for apps/websites, and using conversation as a means or end.
- Covering best practices for conversational UX, platforms to build chatbots, and why the presenter likes the API.ai platform.
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.
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.
The document presents information about chatbots, including a background on early chatbots like ELIZA, the evolution of chatbots through 6 stages from simple character actors to companions, applications of chatbots in messaging platforms, websites, internal company platforms and toys, benefits like 24/7 availability and reducing costs, challenges like user acceptance and inability to perform complex tasks, and the future potential of chatbots integrated with artificial intelligence and the internet of things. Statistics are presented on industries that may benefit most from chatbots and whether chatbots will completely replace human counterparts. In conclusion, chatbots are seen as a new technology with great future potential that is still in the incubation phase.
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.
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.
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.
This presentation includes - History, Functions, Working, Advancement, Applications, Advantages, Disadvantages, Limitations & Contests Held - of Chatbot Technology.
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.
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.
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.
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.
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.)
An introduction to Dialogflow (API.AI) for the class of Pervasive Systems of University of Rome - La Sapienza, Master Degree in Computer Engineering.
Demo: https://github.com/lucamaiano/pervasive-agent
ChatGPT is an AI assistant created by OpenAI to have natural conversations. It was trained on a large text dataset to recognize patterns and generate responses in different styles. Since its release, ChatGPT has gained over 1 million users in its first week and demonstrated abilities like answering follow-up questions, admitting mistakes, and rejecting inappropriate requests. While ChatGPT shows promise for more human-like conversations, experts note it still has limitations like potential for incorrect answers and bias issues due to limitations in its training data.
ChatBot Based Solutions by hizliYOL TechnologyAydin Ozcekic
What is ChatBot? Benefits of ChatBots. ChatBot Development process. ChatBot methodology. ChatBot Strategy. Chatbot use cases. ChatBot Development Tools.
This document discusses chatbots, including their background, types, objectives, interface, working components, uses, needs, and advantages. It notes that chatbots use natural language interfaces and artificial intelligence to interact with users through chat. The objectives of developing chatbots are to create a system that can answer questions, reduce response times, and handle high workloads compared to humans. The main types of chatbots are rule-based and AI chatbots.
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.
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.
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.
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:
- Defining what chatbots are and why they are important for app developers.
- Discussing different approaches for chatbots such as replacing apps, greeting users for apps/websites, and using conversation as a means or end.
- Covering best practices for conversational UX, platforms to build chatbots, and why the presenter likes the API.ai platform.
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.
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.
The document presents information about chatbots, including a background on early chatbots like ELIZA, the evolution of chatbots through 6 stages from simple character actors to companions, applications of chatbots in messaging platforms, websites, internal company platforms and toys, benefits like 24/7 availability and reducing costs, challenges like user acceptance and inability to perform complex tasks, and the future potential of chatbots integrated with artificial intelligence and the internet of things. Statistics are presented on industries that may benefit most from chatbots and whether chatbots will completely replace human counterparts. In conclusion, chatbots are seen as a new technology with great future potential that is still in the incubation phase.
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.
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.
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.
This presentation includes - History, Functions, Working, Advancement, Applications, Advantages, Disadvantages, Limitations & Contests Held - of Chatbot Technology.
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.
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.
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.
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.
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.)
An introduction to Dialogflow (API.AI) for the class of Pervasive Systems of University of Rome - La Sapienza, Master Degree in Computer Engineering.
Demo: https://github.com/lucamaiano/pervasive-agent
ChatGPT is an AI assistant created by OpenAI to have natural conversations. It was trained on a large text dataset to recognize patterns and generate responses in different styles. Since its release, ChatGPT has gained over 1 million users in its first week and demonstrated abilities like answering follow-up questions, admitting mistakes, and rejecting inappropriate requests. While ChatGPT shows promise for more human-like conversations, experts note it still has limitations like potential for incorrect answers and bias issues due to limitations in its training data.
ChatBot Based Solutions by hizliYOL TechnologyAydin Ozcekic
What is ChatBot? Benefits of ChatBots. ChatBot Development process. ChatBot methodology. ChatBot Strategy. Chatbot use cases. ChatBot Development Tools.
This document discusses chatbots, including their background, types, objectives, interface, working components, uses, needs, and advantages. It notes that chatbots use natural language interfaces and artificial intelligence to interact with users through chat. The objectives of developing chatbots are to create a system that can answer questions, reduce response times, and handle high workloads compared to humans. The main types of chatbots are rule-based and AI chatbots.
A Comprehensive Overview of Chatbot Development_ Tools and Best Practices.docxDaniel Jack
In today’s digital landscape, chatbots have become essential tools for businesses aiming to automate customer interactions and improve service delivery. Whether you’re building a simple FAQ bot or an advanced conversational assistant, chatbot development involves multiple stages and the use of specific tools to ensure efficiency and effectiveness. Visit us! https://richestsoft.com/ai-chatbot-development-services
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.
This document provides an overview of chatbots, including their concept and market potential. It discusses what chatbots are, where they can be applied, and how the market for chatbots is growing. It also covers natural language processing (NLP) and common AI tools used for chatbots. Popular bot platforms and frameworks are described along with messaging platforms like Facebook Messenger that chatbots can integrate with. The document concludes by noting how chatbots are becoming more advanced with capabilities beyond just text.
Few Chatbots Expert Interview Questions & Answer For FreshersRobert Smith
Chatbots — automated conversation systems — have become increasingly sophisticated. Should you design and deploy one that can interact with your customers? If you’re an executive making that decision right now, you may feel caught between A.I. hype on the one hand and the fear that machines might not treat your customers right on the other.
This document discusses chatbots and how to build them. It defines a chatbot as a computer program designed to simulate conversation with humans through text or audio. Chatbots can be rule-based or AI-based, and standalone or web-based. The document outlines different components of chatbots and methods for building them, including using APIs, scripting languages, machine learning, and traditional programming. It encourages attendees to practice using bot builders and contact the presenters with any questions.
How AI is going to change the world _M.Mujeeb Riaz.pdfMujeeb Riaz
How AI is going to change the world?
"AI: The Future of Our World“
"AI and its Transformative Impact on the World: Understanding the Potential of Chatbots and Conversational AI"
What is Artificial Intelligence and how it works?
What are Chatbots?
What Is ChatGPT?
Difference between chatGPT 3 and chatGPT 4?
Is Jasper artificial intelligence?
What is Character AI and how it works?
How chatGPT is going to change the world?
Why we are calling ChatGPT the future?
This slide is dedicated to OpenAI's Chatbot ChatGPT. This Chatbot was first released to the public on November 30,2022. Since from its launch it has gained huge popularity among the Internet users. Users were astonished by the responses generated by the ChatGPT Artificial Intelligence based Chatbot. There are several other information related to Chatbot ChatGPT if you want further detailed reading on this topic you can easily follow link of the website in profile page of slideshare. Thanks.
OK Google, it's time to bot! - Hadar Franco & Stav LeviHadar Franco
This document discusses building chatbots using Actions on Google. It begins with introductions from the presenters and an overview of what will be covered, including what a chatbot is, why you should build one, and how the presenters built their first bot. It then discusses key aspects of designing a bot like persona, voice, and tools. It provides a demo of building a recipe recommendation bot using Dialogflow for natural language understanding and fulfillment through APIs. It concludes with information on testing, analytics, and additional Actions on Google capabilities.
Ok google, it's time to bot! - Hadar Franco, Albert + Stav Levi, MondayDroidConTLV
This document discusses building chatbots using Actions on Google. It begins with introductions from the presenters and an overview of what will be covered, including what a chatbot is, why you should build one, and how the presenters built their first bot. It then discusses key aspects of designing a bot like persona, voice, and tools. It provides a demo of building a recipe recommendation bot using Dialogflow for natural language understanding and fulfillment through APIs. It concludes with information on testing, analytics, and additional Actions on Google capabilities.
How ChatBot Work? | What Is Chatbot? | List Of Chatbot | Complete Chatbot Guide Harikrishna Kundariya
In 2019, more than 1.4 Billion businesspeople Use Messaging Apps like chatbots. And now we all know The chatbot represents the business if it's communicating with the customer; consequently, from an advertising viewpoint, it is an ideal embodiment of new construction. Thus do you one of the people who want to grow your business with chatbot development or need to know about what is chatbot? How does chatbot work? Then read this guide about complete chatbot development.
This document discusses chatbots and provides information about RIKAI Labs, a company that builds chatbots. It describes their MicroEnglish product, which allows users to learn English by chatting with AI teachers within WeChat. It also outlines David Collier and Edaan Getzel's backgrounds, provides an overview of their chatbot platform and scripting engine, and discusses structural, visual, conversational and personality considerations for building chatbots.
The Best AI Chatbots of 2024 (Apart from ChatGPT)NdimensionLabs1
Artificial Intelligence (AI) chatbots have revolutionized the way we interact with technology. By simulating human conversation, these chatbots enhance customer service, provide mental health support, assist in education, and much more. As we progress into 2024, the evolution of AI chatbots continues to break new ground, providing more sophisticated and human-like interactions.
A presentation on chatbots is summarized as follows:
1) A chatbot is a computer program that uses artificial intelligence and natural language processing to understand customer questions and provide automated responses, simulating human conversation.
2) Chatbots can provide users with information by responding to questions and requests through text or audio without human intervention.
3) To become a chatbot developer requires a degree in computer science or related field as well as skills in artificial intelligence, machine learning, and programming languages.
UiPath Community Berlin: Orchestrator API, Swagger, and Test Manager APIUiPathCommunity
Join this UiPath Community Berlin meetup to explore the Orchestrator API, Swagger interface, and the Test Manager API. Learn how to leverage these tools to streamline automation, enhance testing, and integrate more efficiently with UiPath. Perfect for developers, testers, and automation enthusiasts!
📕 Agenda
Welcome & Introductions
Orchestrator API Overview
Exploring the Swagger Interface
Test Manager API Highlights
Streamlining Automation & Testing with APIs (Demo)
Q&A and Open Discussion
Perfect for developers, testers, and automation enthusiasts!
👉 Join our UiPath Community Berlin chapter: https://community.uipath.com/berlin/
This session streamed live on April 29, 2025, 18:00 CET.
Check out all our upcoming UiPath Community sessions at https://community.uipath.com/events/.
Learn the Basics of Agile Development: Your Step-by-Step GuideMarcel David
New to Agile? This step-by-step guide is your perfect starting point. "Learn the Basics of Agile Development" simplifies complex concepts, providing you with a clear understanding of how Agile can improve software development and project management. Discover the benefits of iterative work, team collaboration, and flexible planning.
Rock, Paper, Scissors: An Apex Map Learning JourneyLynda Kane
Slide Deck from Presentations to WITDevs (April 2021) and Cleveland Developer Group (6/28/2023) on using Rock, Paper, Scissors to learn the Map construct in Salesforce Apex development.
Procurement Insights Cost To Value Guide.pptxJon Hansen
Procurement Insights integrated Historic Procurement Industry Archives, serves as a powerful complement — not a competitor — to other procurement industry firms. It fills critical gaps in depth, agility, and contextual insight that most traditional analyst and association models overlook.
Learn more about this value- driven proprietary service offering here.
Semantic Cultivators : The Critical Future Role to Enable AIartmondano
By 2026, AI agents will consume 10x more enterprise data than humans, but with none of the contextual understanding that prevents catastrophic misinterpretations.
Spark is a powerhouse for large datasets, but when it comes to smaller data workloads, its overhead can sometimes slow things down. What if you could achieve high performance and efficiency without the need for Spark?
At S&P Global Commodity Insights, having a complete view of global energy and commodities markets enables customers to make data-driven decisions with confidence and create long-term, sustainable value. 🌍
Explore delta-rs + CDC and how these open-source innovations power lightweight, high-performance data applications beyond Spark! 🚀
The Evolution of Meme Coins A New Era for Digital Currency ppt.pdfAbi john
Analyze the growth of meme coins from mere online jokes to potential assets in the digital economy. Explore the community, culture, and utility as they elevate themselves to a new era in cryptocurrency.
Hands On: Create a Lightning Aura Component with force:RecordDataLynda Kane
Slide Deck from the 3/26/2020 virtual meeting of the Cleveland Developer Group presentation on creating a Lightning Aura Component using force:RecordData.
AI and Data Privacy in 2025: Global TrendsInData Labs
In this infographic, we explore how businesses can implement effective governance frameworks to address AI data privacy. Understanding it is crucial for developing effective strategies that ensure compliance, safeguard customer trust, and leverage AI responsibly. Equip yourself with insights that can drive informed decision-making and position your organization for success in the future of data privacy.
This infographic contains:
-AI and data privacy: Key findings
-Statistics on AI data privacy in the today’s world
-Tips on how to overcome data privacy challenges
-Benefits of AI data security investments.
Keep up-to-date on how AI is reshaping privacy standards and what this entails for both individuals and organizations.
This is the keynote of the Into the Box conference, highlighting the release of the BoxLang JVM language, its key enhancements, and its vision for the future.
Leading AI Innovation As A Product Manager - Michael JidaelMichael Jidael
Unlike traditional product management, AI product leadership requires new mental models, collaborative approaches, and new measurement frameworks. This presentation breaks down how Product Managers can successfully lead AI Innovation in today's rapidly evolving technology landscape. Drawing from practical experience and industry best practices, I shared frameworks, approaches, and mindset shifts essential for product leaders navigating the unique challenges of AI product development.
In this deck, you'll discover:
- What AI leadership means for product managers
- The fundamental paradigm shift required for AI product development.
- A framework for identifying high-value AI opportunities for your products.
- How to transition from user stories to AI learning loops and hypothesis-driven development.
- The essential AI product management framework for defining, developing, and deploying intelligence.
- Technical and business metrics that matter in AI product development.
- Strategies for effective collaboration with data science and engineering teams.
- Framework for handling AI's probabilistic nature and setting stakeholder expectations.
- A real-world case study demonstrating these principles in action.
- Practical next steps to begin your AI product leadership journey.
This presentation is essential for Product Managers, aspiring PMs, product leaders, innovators, and anyone interested in understanding how to successfully build and manage AI-powered products from idea to impact. The key takeaway is that leading AI products is about creating capabilities (intelligence) that continuously improve and deliver increasing value over time.
2. WHAT IS A CHATBOT??
Chatbot is a AI program. chatbot can
process a conversation with a user in
natural way using AI & ML. Chatbot
uses NLP to understand query asked by
human. A chatbot can also be called as
Smartbot, Talkbot, Chatterbot or
conversational AI.
4. How to build a chatbot??
Identify the Opportunities For an AI-
Based Chatbot
Understanding the Goals of Customers
Designing a Chatbot Conversation
Building a Chatbot Using Frameworks or
Development (Non-Coding) Platforms
5. What are Available chatbot Platforms(OPEN SOURCE)??
Dialogflow
Sntachbot
Chatfuel
Botkit
Botpress
Rasa
6. Is programming necessary to build a chatbot
No , you do not need to be a
programmer to build a basic chatbot
.But for complex chat bots we must
know some of programming
languages as python.
7. Which language are used while developing a chatbot
JAVA
C++
RUBY
Python etc…
Python is the most popular language for
natural language processing and machine
learning