Each year, Microsoft Build is like Christmas for developers, especially those focused on the Microsoft stack. It's when they make the most exciting announcements, release the best new software, and start to solidify the roadmap of innovation for the next year. While we don't get to enjoy the conference in person this year, we do get the same great collection of announcements. This year's highlight for engineers and developers interested in machine learning is the Azure Applied AI Services. Microsoft has been Democratizing AI since 2016. Applied AI Services takes this ideal another step forward. Microsoft has already made machine learning accessible to developers through their outstanding Cognitive Services, and this offering will make certain scenarios even more accessible.

Most chatbot architectures consist of four pillars, these are typically intents, entities, the dialog flow (State Machine), and scripts. The dialog contains the blocks or states a user navigates between. Each dialog is associated with one or more intents and or entities. Session variables can also be employed the decide on which states or nodes must be visited. The intents and entities constitute the condition on which that dialog is accessed.

Over the past few years, we have seen many examples of organizations applying conversational AI in meaningful ways. Accenture and Caesars Entertainment are making their employees more productive with enterprise bots. UPS and Asiana Airlines are using bots to deliver better customer service. And finally, BMW and LaLiga have built their own branded voice assistants, taking control of how customers experience their brand. These are just a few of the organizations that have built conversational AI solutions with Azure AI. This week at Microsoft Ignite, we announced updates to our products to make it easier for organizations to build robust conversational solutions, and to deploy them wherever their customers are.

Automated machine learning has been drawing lots of attention lately, and is software that automatically selects and trains ML models. Some think it replaces the job of a data scientist however there are limitations as to what it can do. Presently, Microsoft's AutoML is able to build a set of ML models automatically, intelligently select models for training, then recommend the best one for you based on the ML problem and data type. Typically a data scientist with their domain expertise would manually produce and compare dozens of models. In a nutshell, it selects the right algorithm and helps to tune hyperparameters.

Robotic process automation (RPA) company UiPath may debut its own platform for creating AI agents or bots both for customer-facing services and to carry out backend processes, chief product officer Param Kahlon told VentureBeat in a recent interview in San Francisco. UiPath, a company that raised $225 million last fall at a valuation of $3 billion, added Microsoft Bot Framework functionality as well as an integration with Google's Enterprise Dialogflow last summer. Microsoft Bot Framework and Dialogflow bots are available alongside hundreds of industry-specific automated workflows and machine learning integrations in the UiPath Marketplace. UiPath is currently evaluating customer feedback and its own assessments about bots currently available on its platform before making a choice. "Initially our point of view was that we don't want to go create our own sort of conversational experience, because there's enough that exist out there. Some of our customers have said that, 'Hey we don't have our own and we want to get an end-to-end solution from you,' so we may decide to build some things that can own the end-to-end experience as well," Kahlon said.

AI, data and cloud are ushering the next wave of transformative innovations across industries. With Azure AI, our goal is to empower organizations to apply AI across the spectrum of their business to engage customers, empower employees, optimize operations and transform products. We see customers using Azure AI to derive tangible benefits across three key solution areas. Today, at Microsoft Ignite, we are excited to announce a range of innovations across these areas to make Azure the best place for AI. Let me walk you through them.

Recently, Google announced "Google Duplex", a new Assistant feature powered by AI for conducting natural conversations to carry out real-world tasks over the phone. Google Duplex can help you schedule an appointment at a hair salon or make a reservation at your favorite restaurant. The Assistant uses AI and Machine Learning to process and respond to human beings. The system makes conversational experiences as natural as possible. This smart bot-calling service may find its entry into the call centers soon.

More and more companies are opting for chatbots to provide top-notch support to their customers and clients. Chatbots can engage in a conversation with customers at any time of the day with fewer errors and consistent results. So here's looking at the 7 best chatbot tools your business can use to build bots of the highest degree. Its primary aim is to level up marketing & sales for businesses. Lets you create a Facebook Messenger bot – easy to use and free.

There are plenty of easy-to-use bot building frameworks developed by big companies. I had a chance to take a close look at Dialogflow (formerly known as API.AI; developed by Google) and Bot Framework (developed by Microsoft). Both Dialogflow and Bot Framework have pre-built custom language understanding modes. These frameworks seem to be great tools to get you started quickly, especially if you don't have existing chat logs that you can use as a training data. However, there are circumstances in which you may want to avoid using a closed-source framework that processes user inputs on servers owned by Google or Microsoft.

Cognitive Services--a collection of powerful cognitive AI APIs for vision, speech, language understanding, knowledge and search, which enables developers to easily add AI to their apps and services. Bot Framework makes it easy for developers to build and connect intelligent conversational AI to their customer experiences, and deploy these in their own custom UI as well as embedded in Skype, Microsoft Teams, Cortana, Bing as well as Facebook, Slack, etc. It's pretty clear that Cheng is a source of knowledge for all things AI and bot related so get ready to dive deep into her domain expertise in this insightful interview. Rosenthal: There are a number of bot frameworks in market, what's Microsoft's special sauce as it relates to their bot framework? What makes the Microsoft Bot framework unique? Cheng The Bot Framework is one component of Azure Bot Service, which includes the Bot Framework and BotBuilder software development kit.