AI capabilities in Power Virtual Agents
AI models in Power Virtual Agents - background
Power Virtual Agents hosts multiple AI models and AI capabilities on a single service, the core of which is a transformer-based natural language understanding (NLU) model.
Traditionally, intent triggering (how an AI model determines the intent of a question posed to it, by using NLU to understand what a user is asking) is formalized as a multi-class classification problem, in which the model is highly associated with known categories; any change to these categories will result in the need to build a new AI model.
Power Virtual Agents, however, employs a language understanding model that uses an example-based approach, powered by a deep neural model. This type of large-scale model only needs to be trained once with large amounts of data using AI supercomputing, and can then be used for specific tasks with few examples without further training. The use of this model is part of the AI at Scale initiative by Microsoft, and means the way AI is developed and used is changing. Specifically for Power Virtual Agents, the use of this model allows for an intuitive way for bot makers to work on their bot content confidently, without having to involve AI experts.
The use of this type of model means that in Power Virtual Agents, when you craft trigger phrases for a topic, you only need to provide a few examples, usually in the range of five to 10 phrases for a single topic. Shorter trigger phrases are better, and you should aim for two to 10 words. You just need to make sure trigger phrases are semantically different: changing a single verb or noun could be enough to expand a topic's coverage. Adding things like new articles (changing or adding 'the' or 'a' or 'an'), changing capitalization, adding contractions (you're or don't), or adding plurals won't improve the triggering because contractions are already accounted for in the AI model.
These tips for creating tooltips are described in the tooltip associated with the Trigger phrases section on a topic's Details page.
There are some specific features that further improve how the AI in Power Virtual Agents understands what your bot users are asking, and how the AI provides answers.
Advanced AI features in Power Virtual Agents
Note
The AI capabilities listed in this topic are in preview, available to bots created with English as the set language.
Automatic triggering improvements (Preview)
The automatic triggering feature improves intent triggering by using AI to automatically generate new trigger phrases by analyzing previous bot traffic.
With the continuous learning in Power Virtual Agents provided by this feature, each conversation will make the next one better - using reinforcement learning and signals from responses to "Did you mean" questions: when the bot is unsure of the bot user's response it will ask a clarifying question. The bot then learns automatically from the bot user's responses and will not have to ask again.
Over time, as users interact and talk to the bot, it will get better and better.
In the following screenshot, the first time the bot comes across a question it doesn't understand, it asks for clarification.
On the left side of the image, a bot user asks "I'd like to purchase somethign", to which the bot says "Sorry, I didn't get that. Did you mean:" and then provides a few options such as "Buy items" and "Buy service". In this case, the bot user selected "Buy items".
The next time someone asks the same question, the bot doesn't ask for clarification – it knows from previous interactions what the bot user is likely asking to buy items, so it goes straight into the purchasing topic, replying to the question "I'd like to purchase somethign" with "I am happy to help you place your order. To what state will you be shipping?". In this example, it also understands the misspelling of "somethign" to mean "something", so it's able to carry over the improved intent triggering even though the bot user's question is spelled differently.
Conversation personalization (Preview)
When this feature is enabled, the bot will reuse information from Microsoft Graph and Azure Active Directory (Azure AD) throughout the course of a conversation. This feature allows the bot to use already existing information to enhance and personalize future conversations. For example, if a user mentions a name, email, or zip code these properties are stored and used in later conversations without having to reprompt the user.
Specifically, with this feature enabled, when the bot asks questions such as those in the following table, the corresponding user information will be pulled from Microsoft Graph and Azure AD (for authenticated users) and provided as prompts for the user to choose as an option.
| Sample bot questions | User property automatically filled from Microsoft Graph or Azure AD |
|---|---|
|
Address |
|
Annual income |
|
Date of birth |
|
Business phone number |
|
City of residence |
|
Country of residence |
|
Email address |
|
Fax number |
|
First name |
|
Gender |
|
Home phone number |
|
Job title |
|
Last name |
|
Manager's name |
|
Marital status |
|
Middle name |
|
Mobile phone number |
|
Nick name |
|
Number of children |
|
Spouse/partner name |
|
State/province of residence |
|
Zip code |
Enable or disable AI capabilities
To use these advanced AI capabilities in Power Virtual Agents:
Open a bot you want to enable or disable the features for.
Expand Manage on the side navigation pane, then go to the AI capabilities tab.
For each feature, select the checkbox to turn the feature on or off.
Select Save at the top of the tab.
Note
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