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typing","conversation":{"__ref":"Conversation:conversation:4136575"},"id":"message:4136575","revisionNum":1,"uid":4136575,"depth":0,"board":{"__ref":"Forum:board:TeamsDeveloper"},"author":{"__ref":"User:user:2119007"},"metrics":{"__typename":"MessageMetrics","views":323},"postTime":"2024-05-09T23:13:55.683-07:00","lastPublishTime":"2024-05-09T23:13:55.683-07:00","body@stripHtml({\"removeProcessingText\":true,\"removeSpoilerMarkup\":true,\"removeTocMarkup\":true,\"truncateLength\":-1})":" Does Microsoft Teams have a specific endpoint that allows developers to receive each keystroke or each character typed in the input field in real-time? 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Your Own Chatbot in Minutes with Power Virtual Agents: No Coding Required!","conversation":{"__ref":"Conversation:conversation:3869323"},"id":"message:3869323","revisionNum":7,"uid":3869323,"depth":0,"board":{"__ref":"Blog:board:EducatorDeveloperBlog"},"author":{"__ref":"User:user:1548027"},"teaser@stripHtml({\"removeProcessingText\":true,\"truncateLength\":-1})":" \n Learn how to build a chatbot without coding using Power Virtual Agent, a platform by Microsoft. Automate tasks, reduce costs, and improve efficiency with AI-powered chatbots. No programming knowledge required! Discover how Power Virtual Agents work, guiding you through information like a digital librarian. Create your first chatbot by signing up on the Power Virtual Agents website and accessing your dashboard. Customize your bot's name, language, and even enable voice capabilities. Add relevant online content to enhance your bot's responses. Test and publish your bot with just a few clicks. Experience the functionality of your chatbot on the demo website. Explore more resources about Power Virtual Agent and reach out for assistance. Start building chatbots effortlessly today! ","introduction":"","metrics":{"__typename":"MessageMetrics","views":23211},"postTime":"2023-07-20T00:00:00.024-07:00","lastPublishTime":"2023-07-20T00:00:00.024-07:00","body@stripHtml({\"removeProcessingText\":true,\"removeSpoilerMarkup\":true,\"removeTocMarkup\":true,\"truncateLength\":-1})":" Introducing the Power of Power Virtual Agent: Building Chatbots Made Easy \n \n In today's fast-paced digital world, automation and efficiency are key to success. And when it comes to streamlining tasks and reducing manual work, chatbots have emerged as game-changers for organizations and individuals alike. But what if you don't have programming knowledge? Is building a chatbot out of your reach? \n \n Enter Power Virtual Agent, the groundbreaking platform developed by Microsoft. In this blog, we'll delve into the world of chatbot creation without writing a single line of code. We'll explore how Power Virtual Agent empowers anyone to design and customize AI-powered chatbots effortlessly, regardless of their technical background. \n \n Our journey begins with a conversation between myself and Lee Stott, where the idea of venturing into new horizons sparked my interest in building a voice assistant. Lee recommended Power Virtual Agent, and what I discovered left me amazed. Within just a few minutes, I had a fully functional chatbot up and running, capable of handling various requests. The best part? I didn't need any programming knowledge to achieve this feat. \n \n Power Virtual Agent enables individuals and organizations to automate tasks, reduce costs, and improve efficiency through chatbot implementation. It serves as a digital librarian, guiding users through a vast library of information. If your request aligns with known topics, it provides the answers you seek. But when faced with an unfamiliar query, it prompts you for more details or suggests specific information. And if the conversation becomes too complex, it seamlessly escalates to a live agent for personalized assistance. \n \n Building your first chatbot using Power Virtual Agent is a breeze. We'll guide you through the process step by step. From signing up on the platform to accessing the user-friendly dashboard, you'll be creating your chatbot in no time. We'll show you how to set up your bot's name, select its language, and even enable voice capabilities. You'll have the freedom to customize your chatbot to match your specific needs. \n \n But it doesn't stop there. Power Virtual Agent allows you to suggest topics by adding links to online content, empowering your chatbot to gather information and respond effectively to user queries. We'll also walk you through testing your chatbot to ensure its functionality meets your expectations. Once you're satisfied, we'll show you how to publish your chatbot and make it available for use. \n And don't forget the cherry on top: the demo website. We'll provide you with a link where you can interact with your chatbot and experience its capabilities firsthand. It's an exciting opportunity to showcase your creation and witness its potential in action. \n \n Throughout this blog, we'll share valuable insights, tips, and resources to help you dive deeper into the world of Power Virtual Agent. So, whether you're an entrepreneur seeking to automate your business processes or an individual with a passion for technology, this blog is your gateway to unlocking the power of chatbot creation without coding. \n \n Join us on this journey of discovery as we empower you to unleash the potential of Power Virtual Agent. Say goodbye to programming hurdles and hello to building chatbots effortlessly. Let's dive in and explore the incredible possibilities together! \n \n So where to start \n I decided to give it a try and to be honest, I was amazed by how quickly I could build a chatbot without writing a single line of code. In just 2-3 minutes, I had a fully functional chatbot up and running. Not only that, but I was also able to publish the chatbot. You can check out the chatbot here. I didn't need any programming knowledge to create a chatbot that could handle various requests. \n \n Here is the link to the bot that I built Demo website - Whisper | Power Virtual Agents (microsoft.com) \n \n \n \n Let's make our first chatbot using Power Virtual Agents. \n Now, what exactly Power Virtual Agent is? \n Chatbots are really helpful for an organization as well as individuals because they can automate tasks and reduce manual work. \n Chatbots help organizations by automating tasks, reducing costs, and improving efficiency. \n But developing chatbots can be challenging for non-programmers since programming knowledge is typically required. However, what if I told you that you don't need any programming knowledge to build chatbots? That's where Power Virtual Agent comes in. \n \n It is a platform by Microsoft to build AI-powered chatbots that allows everyone to create chatbots effortlessly. With Power Virtual Agent, you can design and customize chatbots without the need for coding skills. \n \n Now how do Power Virtual Agents work? \n Imagine Power Virtual Agents as a digital librarian in a vast library of information. Just like a librarian, it is knowledgeable and can assist you with finding the information you need. Imagine you're searching for a specific book on a particular topic. The digital librarian guides you through the library's collection and points you to the right section. However, if your request doesn't match any known books or topics, the librarian kindly asks for more details or suggests giving specific details. If your query remains unclear, the librarian may recommend consulting with a subject specialist or referring you to a human librarian who can provide more personalized assistance. \n \n Similarly, Power Virtual Agents strives to guide you but may prompt you to rephrase your query. If it still can't understand, it escalates the conversation to a live agent through the system's Escalate topic. \n \n Now how we can build our first chatbot using Power Virtual Agent? \n \n \n \n Sign up: Visit the Power Virtual Agents website and sign up using the Power Virtual Agent . \n \n \n \n \n Dashboard: After signing up, we will access our dashboard. \n \n \n \n \n Create a bot: Let's click on the \"Create a bot\" button to start building our chatbot. \n \nLet's enable voice capabilities (optional): If desired, navigate to the \"Start Here\" section to enable voice capabilities for your bot.\n \n \n \n Bot setup: We will give our bot a name and select the language we want our bot to use. Now, let's Click on \"Create\" to finalize the setup. \n \n Now we will give it a name and select a language in which we want my bot to speak. Then I will click on create button. \n \n \n \n \n \n \n \n Suggest topics: Add links to online content that your bot can use to gather information and respond to user queries effectively. \n Now we will click on the start button. \n \n Test your bot: Now we will give a prompt to the chatbot and we will test it. \n \n Publish your bot: When your bot is ready, click on the \"Publish\" button to make it available for use. \n \n \n \n Demo website: Access the demo website for your chatbot, where users can interact with it and experience its functionality. \n \n \n Now it’s published bot is good to go, when we will click on the demo website you will get our demo website for our chatbot ready. Demo website - Whisper | Power Virtual Agents (microsoft.com) \n \n In conclusion, Power Virtual Agent is a groundbreaking platform that has revolutionized chatbot creation, making it accessible to individuals and organizations without programming knowledge. With Power Virtual Agent, you can design and customize AI-powered chatbots effortlessly, automating tasks, reducing costs, and improving efficiency. \n \n Throughout this blog, we have explored the power of Power Virtual Agent and how it serves as a digital librarian, guiding users through a vast library of information. We have walked you through the process of building your first chatbot step by step, from signing up and accessing the user-friendly dashboard to customizing your bot's name, and language, and even enabling voice capabilities. \n \n Power Virtual Agent allows you to suggest topics by adding online content links, empowering your chatbot to provide accurate and relevant responses. We have emphasized the importance of testing your chatbot to ensure its functionality meets your expectations before publishing it. And with the demo website, you can showcase your chatbot's capabilities and witness its potential in action. \n \n To further enhance your journey into the world of Power Virtual Agent, we have provided valuable insights, tips, and resources. By unlocking the power of chatbot creation without coding, you can say goodbye to programming hurdles and embrace the ease and efficiency of building chatbots. \n \n Remember, if you want to explore more about Power Virtual Agent, check out the resources provided. And if you encounter any problems along the way, feel free to reach out for assistance. We are here to help you unleash the potential of Power Virtual Agent and discover the incredible possibilities that lie ahead. \n \n Thank you for joining us on this journey of discovery. Let's dive in together and make chatbot creation a breeze with Power Virtual Agent. \n If you want to explore more about Power Virtual Agent then you can check out these Resources. \n \n References: \n 1. Microsoft Power Virtual Agents: https://powervirtualagents.microsoft.com?wt.mc_id=studentamb_170844 Official website of Power Virtual Agents, where you can sign up and access the platform. \n 2. Power Virtual Agents Documentation: https://docs.microsoft.com/power-virtual-agents?wt.mc_id=studentamb_170844 Comprehensive documentation provided by Microsoft, offering in-depth guidance on using Power Virtual Agents. \n 3. Power Virtual Agents Community: https://powerusers.microsoft.com/t5/Power-Virtual-Agents-Community/ct-p/PowerVirtualAgentsForum?wt.mc_id=studentamb_170844 Join the Power Virtual Agents Community to connect with other users, ask questions, and share your experiences. \n 4. Whisper | Power Virtual Agents Demo Website: https://powerva.microsoft.com?wt.mc_id=studentamb_170844 Experience the functionality of a chatbot built with Power Virtual Agents on the official demo website. \n 5. Microsoft Learn: Power Virtual Agents: https://learn.microsoft.com/training/modules/power-virtual-agents-bots?wt.mc_id=studentamb_170844 A learning path provided by Microsoft Learn to gain a deeper understanding of Power Virtual Agents and expand your knowledge. \n 6. Microsoft Power Automate: https://powerautomate.microsoft.com?wt.mc_id=studentamb_170844 Explore the capabilities of Microsoft Power Automate, a powerful automation platform that can be integrated with Power Virtual Agents for enhanced functionality. \n 7. Power Apps: https://powerapps.microsoft.com?wt.mc_id=studentamb_170844 Learn about Power Apps, another Microsoft platform that allows you to build custom applications and extend the capabilities of Power Virtual Agents. \n 8. Microsoft Bot Framework: https://dev.botframework.com?wt.mc_id=studentamb_170844 Discover the Microsoft Bot Framework, a powerful toolset for building and deploying conversational bots across various channels. \n 9. Azure Cognitive Services: https://azure.microsoft.com/services/cognitive-services?wt.mc_id=studentamb_170844 Explore Azure Cognitive Services, a collection of AI services that can enhance the capabilities of your chatbots built with Power Virtual Agents. \n 10. GitHub - Power Virtual Agents Samples: https://github.com/microsoft/PowerVirtualAgentsSamples?wt.mc_id=studentamb_170844 Access the official GitHub repository for Power Virtual Agents Samples, which provides code examples and resources to help you get started. \n Feel free to reach out to me if you face any problems, I'll be more than happy to help you out 🙂 Vinayak Gavariya- Gold Microsoft Learn Student Ambassador. \n \n 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What? Why? And How?","conversation":{"__ref":"Conversation:conversation:3799381"},"id":"message:3799381","revisionNum":12,"uid":3799381,"depth":0,"board":{"__ref":"Blog:board:EducatorDeveloperBlog"},"author":{"__ref":"User:user:755935"},"teaser@stripHtml({\"removeProcessingText\":true,\"truncateLength\":-1})":" \n This blog discusses ChatGPT, a pre-trained language model that has garnered significant attention in the AI community due to its innovative capabilities. It explores the technology behind ChatGPT, its purpose, function, and utilization, as well as its potential applications and impact on the field of artificial intelligence. This blog also covers the limitations of ChatGPT and its architecture and working, including the use of advanced machine learning techniques such as Transformer and fine-tuning. \n ","introduction":"","metrics":{"__typename":"MessageMetrics","views":10528},"postTime":"2023-04-24T00:00:00.064-07:00","lastPublishTime":"2023-04-24T00:00:00.064-07:00","body@stripHtml({\"removeProcessingText\":true,\"removeSpoilerMarkup\":true,\"removeTocMarkup\":true,\"truncateLength\":-1})":" ChatGPT- What? Why? And how? \n \n \n ChatGPT: the word everyone has heard of, but why has this thing become such a big revolution and earned such huge praise and a name in such a short time? What does it even do? Why is it being spread so much? How do I use it exactly? \n All these questions will be discussed and explained in this blog. ChatGPT has garnered significant attention and praise in the AI community due to its innovative capabilities as a language model. This blog aims to provide an in-depth understanding of ChatGPT, including its purpose, function, and utilization. By exploring the technology behind ChatGPT, the reader will gain a deeper appreciation for its potential applications and the impact it has had on the field of artificial intelligence. Join us as we delve into the world of ChatGPT and uncover its significance in the development of advanced AI systems. \n Outline: \n \n In-depth architecture and working of ChatGPT (part 1) \n ChatGPT and InstructGPT (part 1) \n How ChatGPT is used in the industry (part 2) \n Microsoft and ChatGPT (part 2) \n Limitations of ChatGPT (part 2) \n Prompt Engineering and its Importance for ChatGPT (part 2) \n \n Architecture and working of ChatGPT: \n ChatGPT is a language model designed to provide human-like responses to the thing asked and spoken by humans with it. It is a model which can perform several human-like tasks like question answering, generating text, writing poems, providing explanations to the questions it receives, and many more. \n \n \n The increase in the size of parameters for the models \n \n The image above illustrates the way parameters have increased from GPT-1 to GPT-3, resulting in better performance and efficiency of the model: the higher the number of training parameters the greater the model’s knowledge. Basically, parameters are a synonym for weights, which is the term most people use for neural network parameters. It is challenging to train a model with such a high number of parameters, it requires access to a supercomputer with ~10,000 GPUs and ~285,000 CPU cores and around 12-15 months of training time with such high resources. \n ChatGPT is based upon an advanced machine learning technique called Transformer, which is a type of neural network architecture. The training process involved a large corpus of text data, in the order of billions of words; the resulting model is able to predict the next word in a sentence given the preceding context. This training was done by OpenAI, a leading AI research organization. During training, the model was exposed to a massive amount of diverse text data from various sources, including books, articles, websites, and more. This allowed the model to learn about a wide range of topics and styles of writing, as well as the relationships between words and phrases. \n The training process also involved fine-tuning the model on specific tasks – in the conversational domain, such as language translation or question answering, to improve its performance further. This fine-tuning process involved adjusting the model's parameters to better fit the task-specific data and was done using supervised learning, where a general-purpose model – GPT 3.5 - was trained on labeled examples of the specific task. Overall, the training process involved a combination of unsupervised and supervised learning, as well as transfer learning, where the model was able to leverage its knowledge from the large corpus of text data to better perform specific tasks. \n ChatGPT uses the Transformer architecture, which is a deep learning model designed for natural language processing (NLP) tasks. \n The Transformer model is made up of two main components: the encoder and the decoder. \n The encoder does the work of processing input text, while the decoder is used to generate the output text. Also, a multi-head attention mechanism is used, which is a key component of the Transformer architecture, allowing the model to attend to different parts of the input sequence simultaneously, which helps it to generate more accurate responses. Furthermore, the transformer architecture also consists of Position-wise feed-forward networks, where a simple neural network is applied to each position in the input sequence separately. The purpose of this structure is to allow the model to learn more complex representations of the input text. \n ChatGPT is a pre-trained language model, which means that it has been trained on a large corpus of text. It is done using a technique called transfer learning. Transfer learning is a technique that allows a pre-trained model to be used for a new task by fine-tuning it on a smaller dataset. This allows the model to leverage the knowledge it has gained from pre-training to improve its performance on the new task. \n \n \n \n Transformer Architecture (Source Paper: Attention is all you need) \n \n ChatGPT can be further fine-tuned for specific NLP tasks, such as text classification or language translation, It is also possible to fine-tune a model for specific domains and use cases, such as medical or legal language. This helps the model to better understand the specific language used in these domains, which can improve its performance on tasks related to those domains. \n ChatGPT was created by fine-tuning GPT 3.5, a general-purpose model whose most common feature is text completion. The language abilities of ChatGPT were enhanced through the collection of data from various sources and the use of a reward model. Reinforcement learning techniques such as Reinforcement Learning from Human Feedback (RLHF) and Proximal Policy Optimization (PPO) were utilized to further improve its language abilities. The methods used for training both InstructGPT and ChatGPT are similar, but there are minor differences in the data collection process. These techniques enabled ChatGPT to better understand human language and communicate more effectively. \n Reinforcement learning from human feedback is a subfield of machine learning that involves learning from a human expert's feedback to improve an agent's decision-making skills. In this approach, the expert provides feedback to the agent in the form of rewards or penalties, which are used to update the agent's policy. There are several methods for implementing reinforcement learning from human feedback which include imitation learning, reward shaping, and interactive learning. \n Imitation Learning: In imitation learning, the agent learns to mimic the behavior of a human expert. For example, in the game of chess, an expert can provide the agent with a series of moves to make in a given position, and the agent can learn to imitate those moves. This approach can be useful in situations where there is a clear right or wrong action to take, and the expert's actions can be easily observed. \n Reward Shaping: In reward shaping, the expert provides additional rewards or penalties to the agent's behavior to guide its decision-making. For example, in a driving simulation, the expert can provide a reward for staying within the lanes or a penalty for colliding with other vehicles. This approach can be useful in situations where the optimal behavior is not easily defined, and the expert can provide additional guidance to the agent. \n Interactive Learning: In interactive learning, the agent and the expert work together to improve the agent's decision-making. For example, in a robotics task, the expert can guide the agent's actions in real-time, providing feedback as the agent explores the environment. This approach can be useful in situations where the agent's actions have a significant impact on the environment and the expert can provide real-time feedback to prevent mistakes. \n \n \n RLHF explained for chatGPT (source: OpenAI website) \n \n The other algorithm that is introduced by OpenAI and is used in the modeling and training process is Proximal Policy Optimization (PPO) which is a class of Reinforcement learning and comes mostly under the reward shaping type of reinforcement learning. PPO is a reinforcement learning algorithm that is commonly used for training large language models like ChatGPT and Instruct GPT. It works by adjusting the parameters of the model such that the reward is maximized for it, and it does small updations on the policy. A policy is the inner working and parameters of a model like the decision-making function. \n The PPO algorithm has two key components: the policy network and the value network. The policy network generates actions based on the current state, while the value network estimates the expected reward for the current state. PPO uses an interaction algorithm that updates the policy and value networks based on actions and rewards. \n To optimize the network, PPO uses a surrogate objective function that approximates the expected reward of the current policy. Stochastic gradient descent (SGD) is used for optimization, along with techniques like clipping and regularization. \n PPO is an efficient algorithm that works well with large language models, providing stable and efficient network updates. It's also an interactive model that helps language models learn from their environment. For more information on PPO, you can visit this link: https://openai.com/blog/openai-baselines-ppo/#ppo. \n \n Working of Language Model \n \n The above figure explains how the language models respond to different inputs and give output according to the input. One single language model does many works based on input changes, and we can get different and desired outputs with appropriate prompts. Prompts are sentences the model’s user provides as input, which describes the output desired from the model, like“ Please answer the following question” or “Answer the following question by reasoning step-by-step”. For the same input prompt, we might get different outputs based on what we have asked the model since large language models like ChatGPT are not deterministic. So prompts play a major role in the way a model processes the input and finally gives an output for it, there is a special field called prompt engineering for this purpose which teaches one how and when to use which prompts, how to create certain prompts based on certain needs and more. \n \n ChatGPT and InstructGPT: \n ChatGPT and InstructGPT are both variants of the GPT (Generative Pre-trained Transformer) model, a type of deep learning model for natural language processing tasks. While they share many similarities, there are also a few differences between ChatGPT and InstructGPT. ChatGPT is trained to generate conversational responses to a wide range of inputs, while InstructGPT is trained to generate instructional text, such as how-to guides or manuals. Another difference is in the training data setup: \n \n \n InstructGPT is trained with interactive learning from human instructors who provide corrective feedback on the generated text; \n ChatGPT is trained using supervised fine-tuning, with a training dataset which is a combination of the InstructGPT dataset - transformed into a dialogue dataset - and a new dialogue dataset made up of conversations in which the trainers played both sides - the user and an AI assistant. \n \n Despite their differences, both ChatGPT and InstructGPT demonstrate the power of GPT-based models in generating high-quality, context-aware text for a variety of applications. 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capabilities of Bot Framework Composer. It's Bot creation rebuilt from the ground up. ","introduction":"","metrics":{"__typename":"MessageMetrics","views":5042},"postTime":"2022-05-24T08:01:52.150-07:00","lastPublishTime":"2022-05-24T08:01:52.150-07:00","body@stripHtml({\"removeProcessingText\":true,\"removeSpoilerMarkup\":true,\"removeTocMarkup\":true,\"truncateLength\":-1})":" New updates have come to Power Virtual Agents, our low-code bot creation service that’s part of the Microsoft Power Platform. We’ll show you how this single environment enables fusion teams of citizen and pro developers to author bots that are more engaging with dynamic custom greetings, in addition to quick replies, and more sophisticated and visual through adaptive cards. \n \n Gary Pretty, from the Power Platform Team, joins JeremyChapmanMSFT to walk you through all of this along with the deep Power FX integration to dynamically adapt bot responses using variables, as well as new native telephony integration that gives your bot a voice. \n \n \n \n \n \n Power Virtual Agents' new authoring canvas. \n Microsoft's authoring studio is designed to meet the business and technical requirements of citizen and pro-developer teams. See how low code authoring is combined with advanced capabilities. \n \n \n Familiar Microsoft commands, enhanced navigation, and productivity improvements. \n Bot building made easy and efficient with Power Virtual Agents' new authoring canvas. See what's new in the top level navigation. \n \n \n Give your bot a voice with expert-level speech authoring capabilities. \n Do you remember the last positive experience with a chatbot? Check out how Power Virtual Agents is changing the game with rich responses and personalization for chat and voice. Watch the quick and easy way to connect a phone number to your bot and give it a voice. \n \n QUICK LINKS: \n \n 00:00 - Introduction \n 01:23 - New changes \n 03:22 - Demo- topic navigation, question nodes \n 04:33 - Next level low-code capabilities \n 07:24 - Citizen developer and pro dev collaboration \n 10:06 - Telephony integration \n 12:17 - Wrap up \n \n Link References: \n Get more details on our blog at https://aka.ms/PVABuild22 \n Watch our show on creating chatbots with Power Virtual Agents at https://aka.ms/TeamsPVA \n \n Unfamiliar with Microsoft Mechanics? \n We are Microsoft’s official video series for IT. You can watch and share valuable content and demos of current and upcoming tech from the people who build it at Microsoft. \n \n Subscribe to our YouTube: https://www.youtube.com/c/MicrosoftMechanicsSeries?sub_confirmation=1 \n Join us on the Microsoft Tech Community: https://techcommunity.microsoft.com/t5/microsoft-mechanics-blog/bg-p/MicrosoftMechanicsBlog \n Watch or listen via podcast here: https://microsoftmechanics.libsyn.com/website \n \n \n Keep getting this insider knowledge, join us on social: \n \n Follow us on Twitter: https://twitter.com/MSFTMechanics \n Follow us on LinkedIn: https://www.linkedin.com/company/microsoft-mechanics/ \n Enjoy us on Instagram: https://www.instagram.com/microsoftmechanics \n Loosen up with us on TikTok: https://www.tiktok.com/@msftmechanics \n \n \n \n Video Transcript: \n \n - Up next, we'll look at updates coming to Power Virtual Agents, our low-code bot creation service that's part of the Microsoft Power Platform. Now, we'll show you how this single environment enables fusion teams of citizen and pro developers to author bots that are more engaging, with dynamic custom greetings in addition to quick replies, and more sophisticated and visual through adaptive cards along with deep Power FX integration to dynamically adapt bot responses using variables, as well as new native telephony integration that gives your bot a voice. And I'm joined today by Gary Pretty to walk us through all the updates from the Power Platform team. Welcome. \n - Yeah, thanks so much. It's great to be here. \n - Glad to have you on, because we've been following the Power Virtual Agents story for a while now, and it's evolution. We recently actually had Lili Cheng on the show, who leads conversational AI at Microsoft, which you can check out if you missed that at aka.ms/TeamsPVA. Now at the time, she actually alluded to how fusion developer experiences will get better in the next round of updates so that citizen developers can more seamlessly collaborate with their peers as pro developers on projects. \n - Yeah, and it's really incredibly important because today five out of six organizations have what we would call fusion teams. So we really are laser focused on making sure that pro developers, citizen developers, and the other disciplines can work together collaboratively to build out their bots. \n - I know that in the past we've had two distinct tools for building out chatbots; one of those is Power Virtual Agents which citizen developers could use for a low-code experience. Then we also have Azure Bot Framework Composer for more custom code targeted professional developers. And both environments were integrated, but separate. So what changes now? \n - Well now we've got a brand new unified authoring canvas built from the ground up. It combines the intuitive authoring experience that PVA is known for, with the advanced capabilities of Bot Framework Composer. And it gives fusion teams a single bot building platform that spans the breadth of business and technical skill set requirements to author powerful next generation bots. Importantly, if you're a pro developer, you can better take advantage of the advanced feature set that gives you the control you need. You don't have to choose between the two different tools, and there's no infrastructure or resources to provision thanks to the PVA SaaS service. \n - So this is really the best of both worlds then? If you're a pro developer you're not limited, and citizen devs can more easily improve their bot building skills and also bring in experts when they need help. So I'd love to try this out. And I kind of consider myself a citizen developer, and you know, I've started building out a customer-facing airline bot, and I really wanted to be able to answer some simple questions and really complete some simple tasks. So I've built a simple topic to let the customer check the status of their flight. And it asks a couple of questions, you know, to ask for things like the flight number and also the date. And I'm calling Power Automate, as you can see, to get the status information. And then I have added also some conditions here to send the appropriate response back to the user, and all this was pretty easy and pretty familiar. And something else that I noticed was just how much easier it is now to build bots, because I can use my favorite Windows commands like cut, copy, and paste from the toolbar right here, or even use keyboard shortcuts if I want. \n - Yeah, that's right. Cut, copy, and paste are just one of the broader set of improvements that we've made on the new unified authoring canvas, to make authoring as efficient as possible. Another thing you should try out is the new Topic navigation experience. \n - Okay, sounds good. So right now, I've noticed that's a lot easier too because instead of moving back and forth between the Topics page to go between different topics, now from the authoring canvas, I can just use this drop down here and it's so easy. I can go between the topics now. So I can move to the Confirmed Success topic. Now I'm going to go back to my Flight Status topic and it's just that easy. \n - Yeah, absolutely. Another thing you should do is take a look at the properties on one of your question notes and you'll see how we're giving you even more control there as well. \n - Okay, so I'll try this out. So I'm going to go ahead and look at this note and click on the ellipse, and then I'm going to open the properties. And wow, there's a lot more that I can do now. So I can even control what happens then if a user enters an incorrect answer to a question. So in this case, what I want to do is customize the retry message. So if someone provides an invalid answer, you know, maybe I'm asking for a flight number and they just input the airline name pretty common, I think, I can just paste in a message like, 'Oops, that doesn't look like a flight number. For example, I'm looking for something like 173.' Now, I'm guessing there's even more I can do to make my bot even more engaging in terms of the experiences. So what can I do to take things then to the next level? \n - Yeah, sure. We really are just scratching the surface as to how we are improving that low-code experience and enabling advanced authoring. Let me show you a few more low-code capabilities that you can add to the bot that you started. Right now I'm in the greeting topic, where the simple message to greet the user when they start a conversation with the bot. It would be good to make this a little more engaging though, and I can do this with our new rich responses feature. First, I can now add an additional alternative message, where one will be picked at random when the message gets sent. This is great because customers will likely engage with this bot multiple times. So this helps to solve the problem of the bot sounding too rigid or too stale over time. Next, for users chatting via text with the bot, I can now easily add images and videos to my responses. Here, I just provide a URL pointing to my Contoso logo, and I immediately get a preview of how that will be displayed to users. Another good way to improve the customer experience, especially on greeting messages, is to help users understand what the bot can do and what they might ask for. And I can now add quick replies which show up as suggestions for users. Here we can add a quick reply for the top two reasons users will speak to this bot: check flight status, and book a flight. Now these are great updates to greatly improve text-based interactions, but we also want to make sure the experience over voice is just as good. Switching to the speech tab on the message note, I can now provide tailored responses that will be used on voice-enabled channels. You can see here that I'm thanking the user for calling, and including those top two suggestions to guide users as to how they might answer. I can even include SSML or Speech Synthesis Markup Language, which helps further control how the message is spoken with things like short pauses or breaks, word emphasis, or prosody for better intonation. And just like that, in just a couple of minutes, we've made a meaningful difference to the user experience by updating just that single response. \n - And this is really powerful because I think in the past it would've probably taken a professional developer using tools like the Bot Framework Composer. \n - Absolutely, we're taking those advanced capabilities from Bot Framework Composer, and we're combining them with that intuitive, low-code experience that PVA is known for, so that it can be used by anyone. For the voice authoring capabilities that I showed, this goes hand-in-hand with the Dynamics 365 voice channel that's already generally available, and allows for the creation of conversational, voice-enabled bots. Meaning you don't need to be an IVR expert to bring voice capabilities to your bot. And we're going even further now with new native telephony capabilities, right within PVA. \n - Awesome, but I want to go back to our telephony integration that you touched on earlier for the developers and admins who are watching. But first, I feel like I've kind of reached my limit with the check flight status topic, and I think it could be enhanced, you know with something like an adaptive card. So how can I get help from you, as a pro developer, to add that to my bot? \n - Right, sure. So you could just use the built-in commenting capability within PVA and @ mention me, and ask me for my help. \n - Okay, let me try this out. So I'm going to go ahead and add a comment. I'll @ mention you. Now is this going to then send a notification to you? \n - Yeah, because this is all integrated with Microsoft 365, I just got an email notifying me of your comment. I can jump to that comment in the bot and even reply to you if I want to. I'll clear out the original message and I'll add an adaptive card using the Add menu. Because I've already designed the card on the adaptive cards website, I'll copy the JSON to my clipboard. And if I jump back to the Power Virtual Agents canvas, I can paste it straight in. And that gives me a preview of the card. And just like that you, as a citizen developer, and me as a pro developer, have collaborated to improve the bots experience. \n - And all these updates really show that the adaptive cards are a lot easier to add. So is it possible then for kind of the contents of the card to be dynamic as well? \n - Yeah, so that's where our work to deeply integrate Power Fx, our Excel-like formula language already used elsewhere in the Power Platform, really comes in. Power Fx now underpins the entire variable system for Power Virtual Agents. And we've added a new formula editor into the canvas which I can use to arbitrarily assign values to variables, write custom condition logic, and in this case I can use it to create a dynamic adaptive card. By choosing to edit my card as a formula, the JSON is automatically converted into a Power Fx record. And I can use the formula editor to reference the variables being used within the topic. In the interest of time, I'll paste in an updated version of the record which I've already amended, and you can see here that I've referenced our flight details. We want the same status card to be used for all statuses. So I can even simplify my logic by copying and pasting the message note and removing the condition. Now I can save my topic and test that my card's working correctly. I'll enter the flight number, the date I want to check, and there it is, our new dynamic adaptive card to show the flight status summary. \n - Good stuff. So what I'm seeing here is that we've basically taken something that would've required professional developers really making it available to everyone. So what you also did though, was you've uplifted kind of the pro dev experience, in terms of integrating more Power Fx? \n - Yeah, exactly. And because it's Excel-like in nature, anybody who's familiar with formulas, whether they're a pro developer or a citizen developer can get up and running with this. \n - Okay, so now we've built and tested out our experience here within a new unified canvas, including tailored messages and also voice scenarios. So why don't we come back to our topic of telephony integration and see what's possible there? \n - Right, I mean, there's a lot to talk about here, but first let me show you how quick and easy it is to connect a phone number to your bot and give it a voice. I'll head over to the Channels page and select the new Telephony channel, where I can connect an existing phone number. I'll select my Azure subscription and my Azure Communication Services resource. Then my phone number type, in this case, it's PSTN. And this lets me see what numbers are available to me to connect my bot. In this case, there's one listed. I'll select it and hit connect. And that's it. The phone number is now connected and my bot is ready to answer phone calls. The next thing I want to do is go to the Speech Settings page, where I can configure the bot's voice. Now you can choose from a wide variety of voices for your bot powered by Azure Cognitive Services. I'll pick one, and now I can even choose specific speaking styles such as customer service, which might be a good one to use for our scenario. And that's it, our bot's now ready to be called. \n - Okay, so as you can tell, I'm ready to try this out. So I'm going to go ahead and call Contoso Airlines customer service here, and I'll go ahead and turn the speaker on to make sure that everyone can hear it. And it's ringing now. \n - [Contoso Bot] Hi, thanks for calling Contoso Airlines. In just a few words, tell me how I can help you today. For example, you could say 'check the status of a flight,' or 'make a new booking.' \n - Check the status of a flight. \n - [Contoso Bot] Sure, I can help you check the status of a flight. What's the flight number? \n - Flight 73. \n - [Contoso Bot] And for which day do you want to check status for? \n - For tomorrow. \n - [Contoso Bot] Good news, Flight 73 is currently on time and scheduled to leave Seattle-Tacoma Airport at 2:30 PM and arrive into Atlanta at 5:45 PM local time. \n - I'll go ahead and hang up. And that's really great news. You know, this is pretty fluid, and it really sounded natural with the voice that you added when you were authoring your bot earlier. \n - Yeah, and this really is just the tip of the iceberg. We're also adding capabilities to make sure that your bot shined over voice, such as silence detection, where a bot can detect if the user stops speaking and connect accordingly. And we'll now allow you to connect your bot with existing contact centers, so that your customers can be rerouted to a live agent if needed. \n - That's a really great update. So for anyone who's watching right now and looking to try this out, what should they do? \n - Sure, so you can register today for the technology preview to get hands on with the new features yourself. And first-time PVA users can also take advantage of a new limited time pricing offer. You can get all the details on our blog over at aka.ms/PVABuild22. \n - Thanks so much Gary, for joining us today and also showing us all the updates for Power Virtual Agents. Of course, keep watching Microsoft Mechanics for the latest in tech updates, and be sure to subscribe to our channel if you haven't already. And as always, thank you for watching. \n 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