Vocal assistants, have to be afraid
Market shares
The two most used voice assistants in the world are Siri and Google Assistant, according to a market study conducted by Microsoft, Amazon Alexa and Cortana from Microsoft just after, this study is based on statistics on the use of voice assistants by more than 2000 people residing in the United States, United Kingdom, India, and Canada.
Google's assistant is used by 36% of the respondents, as is Siri, this domination is due to the integration of their intelligent assistant with Android and iOS, just after Alexa from Amazon, with 25% market share, and Cortana from Microsoft with, 19% share. And in the last place in Bixby, Samsung's assistant with 1%.
Voice search tends to be more mobile and locally targeted as it is integrated into many mobile applications and devices. However, many PDAs are integrated into products that are part of your everyday life, at work and at home.
Google's assistant is used by 36% of the respondents, as is Siri, this domination is due to the integration of their intelligent assistant with Android and iOS, just after Alexa from Amazon, with 25% market share, and Cortana from Microsoft with, 19% share. And in the last place in Bixby, Samsung's assistant with 1%.
Voice search tends to be more mobile and locally targeted as it is integrated into many mobile applications and devices. However, many PDAs are integrated into products that are part of your everyday life, at work and at home.
For personal use, it's all about saving time and simplifying life
The artificial intelligence behind voice search becomes smarter with each interaction and provides a better understanding of the user's intent as the search becomes more conversational. Artificial intelligence develops a conversational language-based model that understands intent and context, builds on previous queries, can consider multiple steps and queries, and is action-, task-, and transaction-oriented.
Speech search engines and PDAs focus on new ways to use machine learning and artificial intelligence to analyze all available data signals - not only from their own products and available search knowledge graphs - but also a current query is about previous queries, geolocation signals, and your own connected data as intention signals.
As more and more devices and the Internet of Things provide data signals to artificial intelligence platforms that optimize voice search, it can understand who you are, what you are doing, and where you need to understand the context of what you want, based on your behavior. patterns and preferences.
This makes voice search somewhat predictive in nature, with the ability to understand the intent and anticipate the researcher's future needs.
Speech search engines and PDAs focus on new ways to use machine learning and artificial intelligence to analyze all available data signals - not only from their own products and available search knowledge graphs - but also a current query is about previous queries, geolocation signals, and your own connected data as intention signals.
As more and more devices and the Internet of Things provide data signals to artificial intelligence platforms that optimize voice search, it can understand who you are, what you are doing, and where you need to understand the context of what you want, based on your behavior. patterns and preferences.
This makes voice search somewhat predictive in nature, with the ability to understand the intent and anticipate the researcher's future needs.
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