This Presentation talks about:
-Introduction to AI
-Introduction to Chatbots
-Why do we need Conversational Agents
-Use Cases
-Watson Assistant
-Building Blocks
-Analytics
Webinar - Building a ChatBot using IBM Watson Conversation ServiceThirdEye Data
This webinar showcases step-by-step instructions to build a Chatbot from scratch using IBM Watson Conversation.
And there is no need to write long lines of code nor have any machine learning background!
The Ultimate Guide to Implementing Conversational AICeline Rayner
What exactly is conversational AI? How is it different than chatbots? How does it work, and why should you implement it?
In the most comprehensive guide ever written on this topic, we cover every single facet of successful, pain-free conversational AI implementation and maintenance in 2021.
inteliwise.com provides intelligent bot for Customer Service and e-Commerce, which answers FAQs on facebook Messenger without a live person, performing as an ultimate Conversational Customer Service
Webinar - Building a ChatBot using IBM Watson Conversation ServiceThirdEye Data
This webinar showcases step-by-step instructions to build a Chatbot from scratch using IBM Watson Conversation.
And there is no need to write long lines of code nor have any machine learning background!
The Ultimate Guide to Implementing Conversational AICeline Rayner
What exactly is conversational AI? How is it different than chatbots? How does it work, and why should you implement it?
In the most comprehensive guide ever written on this topic, we cover every single facet of successful, pain-free conversational AI implementation and maintenance in 2021.
inteliwise.com provides intelligent bot for Customer Service and e-Commerce, which answers FAQs on facebook Messenger without a live person, performing as an ultimate Conversational Customer Service
How to Build a Chatbot with Tom Martin, Founder of LawDroidThomas G. Martin
Thinking a chatbot can help your clients? Learn how the basics to building your own chatbot that can screen clients or complete documents, all while syncing with your Clio account. Tom Martin, creator of LawDroid corporate filings, shares his expertise in building your own chatbot in this hands-on session.
How do Chatbots Work? A Guide to Chatbot ArchitectureMaruti Techlabs
We’d all agree that chatbots have been around for some time now. The initial apprehension that people had towards the usability of chatbots has faded away. Chatbots have become more of a necessity now for companies big and small to scale their customer support and automate lead generation.
According to a Facebook survey, more than 50% of consumers choose to buy from a company they can contact via chat. Chatbots are rapidly gaining popularity with both brands and consumers due to their ease of use and reduced wait times.
Intelligent chatbots are already able to understand users’ questions from a given context and react appropriately. Combining immediate response and round-the-clock connectivity makes them an enticing way for brands to connect with their customers.
A chatbot can be defined as a developed program capable of having a discussion/conversation with a human. Any user might, for example, ask the bot a question or make a statement, and the bot would answer or perform an action as necessary. A chatbot communicates similarly to instant messaging.
Bots are made for a specific reason. A store would most likely want chatbot services that assists you in placing an order, while a telecom company will want to create a bot that can address customer service questions.
There are two categories of chatbots: one that works by following a series of rules, and another that uses artificial intelligence.
Chatbot architecture is the spine of the chatbot. The type of architecture for your chatbot depends on various factors like use-case, domain, chatbot type, etc. However, the basic conversation flow remains the same. Let us learn more about the critical components of chatbot architecture.
Here is the link for the entire article: https://marutitech.com/chatbots-work-guide-chatbot-architecture/
AI is key for transforming customer service and e-commerce. We are serving almost 200 great, global brands with Chatbots, Live Chat, Facebook, helping them to sell more to customers.
Intelligent Assistant with Microsoft BotFrameworkMarvin Heng
A sharing of how difference pieces of technologies can be put together to be great solution for small businesses.
Technologies involved: Microsoft BotFramework, SignalR and ASP.NET Core on Azure.
www.techconnect.io
Youtube: https://www.youtube.com/watch?v=nwGFZA0h9k8&feature=youtu.be
World's First Core Banking AI Bot, built on IBM Watson and IBM Core Banking Transaction technologies.
The first AI Bot designed for actual Banking Transactions.
Supports both commercial and business banking.
Azure as a Chatbot Service: From Purpose To Production With A Cloud Bot Archi...Paul Prae
The tooling for building chatbots has exploded. Putting chatbots into production is now easier than ever. In this presentation, I focus on how you can use Azure Bot Service, Azure Search, and Cosmos DB to create a scalable backend for your chatbot. By using a fully managed, serverless architecture with continuous deployment, you can get your chatbot up and running quickly. Check out this deck to learn how to combine cloud computing and artificial intelligence so you can help humans and machines achieve more together.
Learn more at http://www.neona.chat
This was my presentation at the Xamarin Developer Summit: July 11th-12th 2019 in Houston, FL. The Xamarin Developer Summit is a premiere community-run, cross-platform, mobile developer conference.
This session helped attendees to build three things:
* A LUIS application capable of understand and process users' messages to get the intention and important entities within the message.
* A web application which contains all the bot logic. This is built by using Bot Framework and will be published in Azure.
* A cross-platform mobile app built with Xamarin which makes use of the bot application by sending requests (from users) and listening to replies (from the bot).
The business of writing, owning, licensing and monetizing code has become more complicated due to the evolution of SaaS and the move to mobile, meaning a proliferation of apps and APIs. Proper awareness of how to own your code (or not), how to license it, how to allow others to subscribe to it, how to protect it and how monetize it is critical for every developer.
May MarTech Madness - London MUG May 18thAdele Miller
John Grundy (Accenture) will share tips from a pro to stop you going mad (see what we did there? 😉) and help you organise your day/life/Marketo instance by streamlining the tasks that take up the bulk of your time, so you can focus on the thrilling Martech innovations that matter (there is never enough time for this, right?!)
Josh Arrington (Kapturall) is going to speak about one of the 🔥hottest topics🔥 taking over boardrooms & LinkedIn feeds everywhere: ChatGPT and how to unleash its power to drive your marketing effectiveness.
We will also have a brief interlude from our own co-leader, Courtny Edwards-Jones (Zuora), who is going to share her experience as a 2022 Adobe Champion, and how you can become one too, ahead of 2023 applications opening soon.
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.
John Grundy (Accenture) will share tips from a pro to stop you going mad (see what we did there? 😉) and help you organise your day/life/Marketo instance by streamlining the tasks that take up the bulk of your time, so you can focus on the thrilling Martech innovations that matter (there is never enough time for this, right?!)
Josh Arrington (Kapturall) is going to speak about one of the 🔥hottest topics🔥 taking over boardrooms & LinkedIn feeds everywhere: ChatGPT and how to unleash its power to drive your marketing effectiveness.
We will also have a brief interlude from our own co-leader, Courtny Edwards-Jones (Zuora), who is going to share her experience as a 2022 Adobe Champion, and how you can become one too, ahead of 2023 applications opening soon.
Chatbots Rule Based Vs. AI Powered Chatbots.pptxLovina Kapoor
In today’s digital era, chatbots are of significant prominence to effectively carry out businesses. They have revolutionized the customer support service and are playing the game-changing role of automatically interacting with the customers.
How to Build a Chatbot with Tom Martin, Founder of LawDroidThomas G. Martin
Thinking a chatbot can help your clients? Learn how the basics to building your own chatbot that can screen clients or complete documents, all while syncing with your Clio account. Tom Martin, creator of LawDroid corporate filings, shares his expertise in building your own chatbot in this hands-on session.
How do Chatbots Work? A Guide to Chatbot ArchitectureMaruti Techlabs
We’d all agree that chatbots have been around for some time now. The initial apprehension that people had towards the usability of chatbots has faded away. Chatbots have become more of a necessity now for companies big and small to scale their customer support and automate lead generation.
According to a Facebook survey, more than 50% of consumers choose to buy from a company they can contact via chat. Chatbots are rapidly gaining popularity with both brands and consumers due to their ease of use and reduced wait times.
Intelligent chatbots are already able to understand users’ questions from a given context and react appropriately. Combining immediate response and round-the-clock connectivity makes them an enticing way for brands to connect with their customers.
A chatbot can be defined as a developed program capable of having a discussion/conversation with a human. Any user might, for example, ask the bot a question or make a statement, and the bot would answer or perform an action as necessary. A chatbot communicates similarly to instant messaging.
Bots are made for a specific reason. A store would most likely want chatbot services that assists you in placing an order, while a telecom company will want to create a bot that can address customer service questions.
There are two categories of chatbots: one that works by following a series of rules, and another that uses artificial intelligence.
Chatbot architecture is the spine of the chatbot. The type of architecture for your chatbot depends on various factors like use-case, domain, chatbot type, etc. However, the basic conversation flow remains the same. Let us learn more about the critical components of chatbot architecture.
Here is the link for the entire article: https://marutitech.com/chatbots-work-guide-chatbot-architecture/
AI is key for transforming customer service and e-commerce. We are serving almost 200 great, global brands with Chatbots, Live Chat, Facebook, helping them to sell more to customers.
Intelligent Assistant with Microsoft BotFrameworkMarvin Heng
A sharing of how difference pieces of technologies can be put together to be great solution for small businesses.
Technologies involved: Microsoft BotFramework, SignalR and ASP.NET Core on Azure.
www.techconnect.io
Youtube: https://www.youtube.com/watch?v=nwGFZA0h9k8&feature=youtu.be
World's First Core Banking AI Bot, built on IBM Watson and IBM Core Banking Transaction technologies.
The first AI Bot designed for actual Banking Transactions.
Supports both commercial and business banking.
Azure as a Chatbot Service: From Purpose To Production With A Cloud Bot Archi...Paul Prae
The tooling for building chatbots has exploded. Putting chatbots into production is now easier than ever. In this presentation, I focus on how you can use Azure Bot Service, Azure Search, and Cosmos DB to create a scalable backend for your chatbot. By using a fully managed, serverless architecture with continuous deployment, you can get your chatbot up and running quickly. Check out this deck to learn how to combine cloud computing and artificial intelligence so you can help humans and machines achieve more together.
Learn more at http://www.neona.chat
This was my presentation at the Xamarin Developer Summit: July 11th-12th 2019 in Houston, FL. The Xamarin Developer Summit is a premiere community-run, cross-platform, mobile developer conference.
This session helped attendees to build three things:
* A LUIS application capable of understand and process users' messages to get the intention and important entities within the message.
* A web application which contains all the bot logic. This is built by using Bot Framework and will be published in Azure.
* A cross-platform mobile app built with Xamarin which makes use of the bot application by sending requests (from users) and listening to replies (from the bot).
The business of writing, owning, licensing and monetizing code has become more complicated due to the evolution of SaaS and the move to mobile, meaning a proliferation of apps and APIs. Proper awareness of how to own your code (or not), how to license it, how to allow others to subscribe to it, how to protect it and how monetize it is critical for every developer.
May MarTech Madness - London MUG May 18thAdele Miller
John Grundy (Accenture) will share tips from a pro to stop you going mad (see what we did there? 😉) and help you organise your day/life/Marketo instance by streamlining the tasks that take up the bulk of your time, so you can focus on the thrilling Martech innovations that matter (there is never enough time for this, right?!)
Josh Arrington (Kapturall) is going to speak about one of the 🔥hottest topics🔥 taking over boardrooms & LinkedIn feeds everywhere: ChatGPT and how to unleash its power to drive your marketing effectiveness.
We will also have a brief interlude from our own co-leader, Courtny Edwards-Jones (Zuora), who is going to share her experience as a 2022 Adobe Champion, and how you can become one too, ahead of 2023 applications opening soon.
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.
John Grundy (Accenture) will share tips from a pro to stop you going mad (see what we did there? 😉) and help you organise your day/life/Marketo instance by streamlining the tasks that take up the bulk of your time, so you can focus on the thrilling Martech innovations that matter (there is never enough time for this, right?!)
Josh Arrington (Kapturall) is going to speak about one of the 🔥hottest topics🔥 taking over boardrooms & LinkedIn feeds everywhere: ChatGPT and how to unleash its power to drive your marketing effectiveness.
We will also have a brief interlude from our own co-leader, Courtny Edwards-Jones (Zuora), who is going to share her experience as a 2022 Adobe Champion, and how you can become one too, ahead of 2023 applications opening soon.
Chatbots Rule Based Vs. AI Powered Chatbots.pptxLovina Kapoor
In today’s digital era, chatbots are of significant prominence to effectively carry out businesses. They have revolutionized the customer support service and are playing the game-changing role of automatically interacting with the customers.
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.
Entering the Conversational Era with Chatbots for the EnterpriseAleisha McKeeby
Free on-demand webinar recording: https://kore.com/entering-conversational-era-webinar/
Turning hype into action for emerging technologies like conversational AI, chatbots, machine learning, and natural language can be confusing and intimidating, but it doesn’t have to be. We will tell you what other vendors won’t to help you break through the noise and get you on your way to successfully leading your company into the conversational era.
SAP Inside track - SAP Conversational AI - Lecture.
45minutes lecture on the architecture, technical components, roadmap, lessons learned and an extensive demo of the platform.
Your Next App Might Just Be a Bot: Building Conversational Bots with PythonDavid Asamu
Thanks to advancements in ML, bots are becoming the main interface between humans and machines. 25% of installed apps are never used. The average Android app loses 77% of its daily active users within the first 3 days. The amount of time people spend on social media is constantly increasing. Certainly, the next user interface won't be based on fancy design, it will be based on simple conversation.
Openbar Kontich // How to create intelligent & personal conversational AI - W...Openbar
With his team, Wouter has been building chat- and voicebots for almost 3 years. In this session, you will learn about the pitfalls of a conversational AI implementation. Wouter will tell you about common mistakes and share best practices about how you can create intelligent and personal virtual agents based on a number of previous projects.
06-04-2024 - NYC Tech Week - Discussion on Vector Databases, Unstructured Data and AI
Round table discussion of vector databases, unstructured data, ai, big data, real-time, robots and Milvus.
A lively discussion with NJ Gen AI Meetup Lead, Prasad and Procure.FYI's Co-Found
Opendatabay - Open Data Marketplace.pptxOpendatabay
Opendatabay.com unlocks the power of data for everyone. Open Data Marketplace fosters a collaborative hub for data enthusiasts to explore, share, and contribute to a vast collection of datasets.
First ever open hub for data enthusiasts to collaborate and innovate. A platform to explore, share, and contribute to a vast collection of datasets. Through robust quality control and innovative technologies like blockchain verification, opendatabay ensures the authenticity and reliability of datasets, empowering users to make data-driven decisions with confidence. Leverage cutting-edge AI technologies to enhance the data exploration, analysis, and discovery experience.
From intelligent search and recommendations to automated data productisation and quotation, Opendatabay AI-driven features streamline the data workflow. Finding the data you need shouldn't be a complex. Opendatabay simplifies the data acquisition process with an intuitive interface and robust search tools. Effortlessly explore, discover, and access the data you need, allowing you to focus on extracting valuable insights. Opendatabay breaks new ground with a dedicated, AI-generated, synthetic datasets.
Leverage these privacy-preserving datasets for training and testing AI models without compromising sensitive information. Opendatabay prioritizes transparency by providing detailed metadata, provenance information, and usage guidelines for each dataset, ensuring users have a comprehensive understanding of the data they're working with. By leveraging a powerful combination of distributed ledger technology and rigorous third-party audits Opendatabay ensures the authenticity and reliability of every dataset. Security is at the core of Opendatabay. Marketplace implements stringent security measures, including encryption, access controls, and regular vulnerability assessments, to safeguard your data and protect your privacy.
06-04-2024 - NYC Tech Week - Discussion on Vector Databases, Unstructured Data and AI
Discussion on Vector Databases, Unstructured Data and AI
https://www.meetup.com/unstructured-data-meetup-new-york/
This meetup is for people working in unstructured data. Speakers will come present about related topics such as vector databases, LLMs, and managing data at scale. The intended audience of this group includes roles like machine learning engineers, data scientists, data engineers, software engineers, and PMs.This meetup was formerly Milvus Meetup, and is sponsored by Zilliz maintainers of Milvus.
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Empowering the Data Analytics Ecosystem: A Laser Focus on Value
The data analytics ecosystem thrives when every component functions at its peak, unlocking the true potential of data. Here's a laser focus on key areas for an empowered ecosystem:
1. Democratize Access, Not Data:
Granular Access Controls: Provide users with self-service tools tailored to their specific needs, preventing data overload and misuse.
Data Catalogs: Implement robust data catalogs for easy discovery and understanding of available data sources.
2. Foster Collaboration with Clear Roles:
Data Mesh Architecture: Break down data silos by creating a distributed data ownership model with clear ownership and responsibilities.
Collaborative Workspaces: Utilize interactive platforms where data scientists, analysts, and domain experts can work seamlessly together.
3. Leverage Advanced Analytics Strategically:
AI-powered Automation: Automate repetitive tasks like data cleaning and feature engineering, freeing up data talent for higher-level analysis.
Right-Tool Selection: Strategically choose the most effective advanced analytics techniques (e.g., AI, ML) based on specific business problems.
4. Prioritize Data Quality with Automation:
Automated Data Validation: Implement automated data quality checks to identify and rectify errors at the source, minimizing downstream issues.
Data Lineage Tracking: Track the flow of data throughout the ecosystem, ensuring transparency and facilitating root cause analysis for errors.
5. Cultivate a Data-Driven Mindset:
Metrics-Driven Performance Management: Align KPIs and performance metrics with data-driven insights to ensure actionable decision making.
Data Storytelling Workshops: Equip stakeholders with the skills to translate complex data findings into compelling narratives that drive action.
Benefits of a Precise Ecosystem:
Sharpened Focus: Precise access and clear roles ensure everyone works with the most relevant data, maximizing efficiency.
Actionable Insights: Strategic analytics and automated quality checks lead to more reliable and actionable data insights.
Continuous Improvement: Data-driven performance management fosters a culture of learning and continuous improvement.
Sustainable Growth: Empowered by data, organizations can make informed decisions to drive sustainable growth and innovation.
By focusing on these precise actions, organizations can create an empowered data analytics ecosystem that delivers real value by driving data-driven decisions and maximizing the return on their data investment.
3. • Introduction to AI
• Introduction to Chatbots
o Why do we need Conversational Agents
o Use Cases
• Watson Assistant
o Building Blocks
o Analytics
• Demo
Get started at: https://ibm.biz/assistantchatbot
Agenda
5. Artificial Intelligence (AI) refers to
the ability of computer systems to
perform tasks commonly
with intelligent beings.
These processes include learning,
reasoning, and self-correction.
7. What is a Chatbot?
An Artificial Intelligence tool that can
human conversation, with the objective of
providing some value to the end user.
Using chatbots you can get information,
pay bills, provide feedback, the
are endless...
10. IBM Watson Assistant
10
Create an application that understands natural-language and responds to customers in human-
like conversation –in multiple languages.
Seamlessly connect to messaging channels, web environments and social networks to make
scaling easy.
Easily configure a workspace and develop your application to suit your needs.
• Expose your conversation as APIs
• Supports multiple languages (including Arabic)
• Can understand context
• Doesn’t require coding skills to develop*
* However requires coding to integrate
12. Components of Assistant
Intents: An Intent is the purpose behind a statement.
Entities: Entities are like the nouns in a sentence.They are
used to clarify a user’s intent
Dialog: The Dialog is the flow of the conversation.
13. Components of Assistant
13
INTENTS
Identifies the purpose behind the user’s query
1. Where is the office ?
2. How can I get to the swimming pool?
3. Is there a bank here?
4. I want to book a room for 2.
Intent 1, 2, 3: #place
Intent 4: #booking
16. Components of Assistant
16
ENTITIES
Identifies the object of the user’s query
1. Where is the office?
2. How can I get to swimming pool?
3. Is there a bank here?
4. I want to book a room for 2.
Entity 1: @location: office
Entity 2: @location: swimming pool
Entity 3: @location: bank
Entity 4: @room: room, @number: 2
18. 18
DIALOG
Defines the flow of the conversation.
Used to identify what conditions trigger what
response. Built using a combination of intents,
entities, and context variables.
• Conditional
• Folders – Group similar content, handle digression
• Prebuilt Content
Avoid having a tree more than 20 nodes deep.
Components of Assistant
19. Analytics
• Metrics Overview
• Improve your skill
• Empower your skill to learn automatically
• Defining what's irrelevant
20. Demo
Sign-up or Sign-in at IBM Cloud: https://ibm.biz/assistantchatbot
21. • Artificial Intelligence (AI) refers to the ability of computer systems to perform tasks commonly
associated with intelligent beings.
• A Chatbot is an Artificial Intelligence tool that can imitate human conversation, with the
objective of providing some value to the end user.
• Why do we need chatbots and why are they important for businesses.
• Siri and Bixbi as real-life use cases for chatbots that everyone is using for different purposes.
• Watson Assistant service on IBM Cloud, its building blocks (Intents, Entities and Dialogs). We
have also covered the analytics part of the service.
• Lastly, we have concluded the presentation with a demo for deploying a Watson Assistant
service to IBM Cloud.
Wrap Up
So what is AI ?
AI refers to the ability of a computer system to act like a human being by performing tasks that you would normally associate with humans, so tasks like learning communicating, self correction etc.
A common misconception about AI is that, it is supposed to replace humans. However, that’s not exactly accurate. AI as I see it is supposed to augment or enhance our abilities as humans, to allow us to solve even more complex problems.
So building on that point, some of the applications of AI include sifting large amounts of data and deriving insights from that data which can then help us make better decisions, these decisions can include predicting weather patterns, predicting the stock market trends etc. AI can also be used to create tools like chatbots which can interact with 100’s of people at the same time. So so you all these applications of AI, they are used to augment human abilities. And you will see and example of one such use-case of AI in today’s demo
So now that you have an overview of what AI is, let me tell you alittle bit more about chatbots
let me explain to you guys what a chatbot is, so a chatbot is an AI tool that can imitate human conversation. So what happens is when you are chatting with a chatbot and you send your message, the chatbot uses AI to identify the user’s intent behind that message, it tried to determine what is user is looking for or what the user wants to know. And then once the chatbot has figured that out, it provides the most appropriate response to the users query.
Chatbots have many applications, chatbots can be integrated with websites to make it easier for the users to browse through the website, they can also be used in applications to answers some questions that are very frequently asked by the users, or to get feedback from the users etc. so you see there are a lot of applications and uses that chatbots can have.
So let me actually tell you about some of the commons applications of chatbots that you guys might have interacted with.
For any industry type, if you take account the user base, there are some basic questions that users generally ask. And for these specific question, same specific answers are required to be answered every time the customer makes the similar query. Well, for such purposes, chatbot is the best engaging way to answer these common questions.
Many businesses use chatbots to make sure their internal business processes are more efficient. Chatbots can manage calendars, hunt down documentation, and even make it easier to manage assets, such as social media. HR departments are also using chatbots to handle internal requests. Managers can use bots to send out messages and oversee the team.
One of the great advantages of chatbot is, it requires less development cost in comparison to application development. Well, making an investment into a quality product like chatbot is worth as it can offer a better experience to your customers.
The best example of a chatbot is SIRI, which is present in the iphone. For those of you who have used an iphone would know that you can se siri to do various tasks on your iphone. You can use it to make phone calls, set reminders, set alarms, and so on. And it is as simple as having a conversation, you can ask siri to make a phone call to someone in your contacts and it will do that.
Similar to Siri, for Samsung users. Samsung phone also have their own chabot which is called bixby.
So these are some of the examples of chatbots that you guys might have interacted it.
IBM Watson™ Assistant is used to build your own branded live chatbot into any device, application, or channel. Your chatbot, which is also known as an assistant, connects to the customer engagement resources you already use to deliver an engaging, unified problem-solving experience to your customers.
With Watson conversation, you can add a built-in channel integration to deploy the configured assistant directly to a social media or messaging channel, such as Facebook Messenger, Slack, Voice Agent ..
Build your own client application as the user interface for the assistant. Or add the built-in web chat integration to your company website. From the web chat you can transfer customers who ask to speak to someone to your existing service desk personnel.Supports up to 12 languages
And now lets look into the major components of a chabot.
The three main components of a chatbot are intents, entities and dialogs. Its as simple as that, you put all these three components together and you have a chatbot. So I want you all to remember these three components because we will be using these in our demo. And not lets look into what these components actually are and what is their function in a chatbot.
Intent, as the name suggests is the purpose of the users statement, it is basically what the user intends when they communicate something to the chatbot. So if I say to a chabot, set reminder, my intention behind that statement is that I want to set a reminder. Simple right ? But its very important for the Chabot to categorize your statements according to the right intents because it is only then that the chatbot will be able to guide you correctly or provide you with accurate information etc.
Entities, are used to further clarify the users intent. So e.g. in the previous example like I mentioned if I say to the Chabot “set a reminder” my intention is to set a reminder. But the chatbot needs more information about my intent in order to help me appropriately. E.g. the chatbot needs to know what time the reminder is for and what date the reminder is for. So all this additional information needed to further explain the users intent, comes under entities.
Lastly, the dialog. Dialog is the flow of the conversation. It is basically how the chatbot will actually respond to the users queries. And for that we use the intents and entities to. So now building on our earlier example: once I say to a chatbot, “set a reminder” it will categorize my intent is to set a reminder and it will ask me a question such as “What is the time and date of the reminder” etc. So this whole flow of the conversation…me asking the chatbot to set a reminder and then the chatbot asking me additional questions is referred to as the dialog.
A vey important aspect of Watson assistant for all businesses is the analytics. With the analytics, you can gain insights on how your assistant is
The Overview page provides a summary of the interactions between users and your assistant. You can view the amount of traffic for a given time period, as well as the intents and entities that were recognized most often in user conversations.
The Analytics page of Watson Assistant provides a history of conversations between users and a deployed assistant. You can use this history to improve how your assistants understand and respond to user requests.
When customers interact with your assistant, they often make choices. If your underlying dialog skill pays attention, it can learn from these user decisions over time.
Teach your dialog skill to recognize when a user asks about topics that it is not designed to answer. And training your assistant on how to ignore specific subjects.