Machine learning By Virtual Assistants

Machine learning By Virtual Assistants

A Virtual Assistant or Digital Assistant is an application program that understands natural language voice commands and completes tasks for the user. They use Natural Language Processing(NLP) to match user text or voice input to run commands. Virtual assistants are basically cloud-based programs that require internet-connected devices or applications to work with their capabilities. Every time a command is given to the assistant, they tend to provide a better experience to the user based on past experiences using Machine Learning algorithms and learning. Some of the popular virtual assistants include Amazon Alexa, Cortana (Microsoft), Siri (Apple), and Google Assistant.

Here are a few of the ways you can expect to use a virtual assistant on a day to day basis:

  • Daily news and weather update,
  • Reviewing schedule for the day,
  • Booking meetings and scheduling appointments in the calendar,
  • Taking notes in a meeting and sharing those notes for follow-up,
  • Getting directions to enable you to go from one meeting to the next,
  • Finding recipe’s that you can make for dinner with the ingredients you have or what you need to get,
  • Bookings for travel, for both personal or for business,
  • Optimizing your week by aggregating chores together in dedicated timely blocks.

Machine Learning By Virtual Assistants!
How Does It Work?

Machine learning by virtual assistants!
The accuracy, speed, and contextual abilities of Alexa, Google Assistant, and Siri are all because of  Machine Learning algorithms and servers owned by their developing companies. They all work in a similar manner, the only difference arises in their protocols and data privacy intricacies. When a user makes a request, the request is immediately packaged up and is sent to the server of their respective companies for a response i.e. why internet connectivity is one of the basic requirements for Virtual Assistants to function properly. After the package is sent to the server the words and tone of your request are analyzed by a set of algorithms, which are then matched with a command that it thinks you asked. Not all the information is processed with the help of the server, only the complicated ones.

The complexity is in relation to the speed of task fulfillment and understanding of what the user wants in the first try. Once it knows what it needs to do, that’s a basic process of tapping into a server, third-party computer, or any other electronic device. Here are the two most successful Voice Assistants:


Amazon has designed the Alexa Voice Service (AVS), Amazon’s cloud-based voice service, to mimic real conversations, using intuitive voice commands to get this service to perform specific tasks. Alexa acts as a “wake up” word for the Alexa supported devices that alert the service to start listening to the user commands. Its AVS has intelligent voice recognition and natural language understanding services. It is able to play music, provide information, deliver news and sports scores, weather reports, controls smart home services, and even allow Prime members to buy order products from Amazon. In order to use Alexa, the user will need a device that integrates voice technology. This typically means an Amazon device, such as an Echo Dot or Fire TV Stick.


Siri is Apple’s virtual/digital assistant for iOS, macOS, tvOS, and watchOS devices that use voice recognition. It is based on the fields of Artificial Intelligence, Machine Learning, and Natural Language Processing. And it is based on three basic components: a conversational interface, personal context awareness, and service delegation. It enables the user to operate the mobile device and its apps using natural voice commands. Moreover, Siri is not all business, though. Users can have some fun and ask it more obscure questions if users like. Siri can help you when the user is out and about, with sports and entertainment information, phone calls and messages, getting organized, tips and tricks, read your last email, text your friends and family, shuffle playlist, even finding a table for three in a restaurant and much more stuff like this.

All you need to know about Machine Learning

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Future of Machine LearningRole of Machine Learning in Business Growth
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