http://www.wired.com/2015/12/elon-musks-billion-dollar-ai-plan-is-about-far-more-than-saving-the-world/
WhatsApp, Facebook Messenger, WeChat, and Viber have 2.125 billion monthly active users globally (users who accessed the apps at least once in a 30-day period). And these are all mobile users
2.125 billion, users of Facebook, Twitter, LinkedIn, and Instagram combined. But these numbers also include millions of computer-only users!
WhatsApp, Facebook Messenger, WeChat, and Viber have 2.125 billion monthly active users globally (users who accessed the apps at least once in a 30-day period). And these are all mobile users
2.125 billion, users of Facebook, Twitter, LinkedIn, and Instagram combined. But these numbers also include millions of computer-only users!
during their interaction with online users by taking inputs and matching it with data base to output a sentence and continue the conversation
during their interaction with online users by taking inputs and matching it with data base to output a sentence and continue the conversation
WhatsApp, Facebook Messenger, WeChat, and Viber have 2.125 billion monthly active users globally (users who accessed the apps at least once in a 30-day period). And these are all mobile users
2.125 billion, users of Facebook, Twitter, LinkedIn, and Instagram combined. But these numbers also include millions of computer-only users!
Retrieval models, which use predefined responses or Generative models which generate new responses from scratch. - retrieval models don’t make grammatical mistakes, as they have a database of responses to choose from; they are unable to handle cases for which no appropriate predefined response exists. On the other hand, Generative models are hard to train and are more likely to make grammatical mistakes, even though they are ‘smarter’ as they use machine translation techniques to translate from an input to output.
Facebook Messenger bot engine will be following the retrieval model for most companies as the starting point of a bot would be a set of interaction rules defined by the developer as some basic guidelines on handling inquiries.
http://analyticsindiamag.com/rise-chatbots-analytics-behind/
Retrieval models, which use predefined responses or Generative models which generate new responses from scratch. - retrieval models don’t make grammatical mistakes, as they have a database of responses to choose from; they are unable to handle cases for which no appropriate predefined response exists. On the other hand, Generative models are hard to train and are more likely to make grammatical mistakes, even though they are ‘smarter’ as they use machine translation techniques to translate from an input to output.
Facebook Messenger bot engine will be following the retrieval model for most companies as the starting point of a bot would be a set of interaction rules defined by the developer as some basic guidelines on handling inquiries.
http://analyticsindiamag.com/rise-chatbots-analytics-behind/
Retrieval models, which use predefined responses or Generative models which generate new responses from scratch. - retrieval models don’t make grammatical mistakes, as they have a database of responses to choose from; they are unable to handle cases for which no appropriate predefined response exists. On the other hand, Generative models are hard to train and are more likely to make grammatical mistakes, even though they are ‘smarter’ as they use machine translation techniques to translate from an input to output.
Facebook Messenger bot engine will be following the retrieval model for most companies as the starting point of a bot would be a set of interaction rules defined by the developer as some basic guidelines on handling inquiries.
http://analyticsindiamag.com/rise-chatbots-analytics-behind/
Retrieval models, which use predefined responses or Generative models which generate new responses from scratch. - retrieval models don’t make grammatical mistakes, as they have a database of responses to choose from; they are unable to handle cases for which no appropriate predefined response exists. On the other hand, Generative models are hard to train and are more likely to make grammatical mistakes, even though they are ‘smarter’ as they use machine translation techniques to translate from an input to output.
Facebook Messenger bot engine will be following the retrieval model for most companies as the starting point of a bot would be a set of interaction rules defined by the developer as some basic guidelines on handling inquiries.
http://analyticsindiamag.com/rise-chatbots-analytics-behind/
Retrieval models, which use predefined responses or Generative models which generate new responses from scratch. - retrieval models don’t make grammatical mistakes, as they have a database of responses to choose from; they are unable to handle cases for which no appropriate predefined response exists. On the other hand, Generative models are hard to train and are more likely to make grammatical mistakes, even though they are ‘smarter’ as they use machine translation techniques to translate from an input to output.
Facebook Messenger bot engine will be following the retrieval model for most companies as the starting point of a bot would be a set of interaction rules defined by the developer as some basic guidelines on handling inquiries.
http://analyticsindiamag.com/rise-chatbots-analytics-behind/
A human-like language processing
Two components
Natural Language Understanding (NLU)
Natural Language Generation (NLG)
Information extraction and classification
Translation
Question Answering
Information Retrieval
While chatbots may not replace the app experience entirely, they can offer a new and flexible way for brands to create new experiences for mobile users. So for example, instead of having to download and register for an additional dedicated app to access a new service, mobile messaging users will simply send a text to their bot of choice to do a variety of activities such as purchasing cinema tickets, calling a taxi, ordering a take-away or simply to catch up on the latest news stories."
A human-like language processing
Two components
Natural Language Understanding (NLU)
Natural Language Generation (NLG)
Information extraction and classification
Translation
Question Answering
Information Retrieval
While chatbots may not replace the app experience entirely, they can offer a new and flexible way for brands to create new experiences for mobile users. So for example, instead of having to download and register for an additional dedicated app to access a new service, mobile messaging users will simply send a text to their bot of choice to do a variety of activities such as purchasing cinema tickets, calling a taxi, ordering a take-away or simply to catch up on the latest news stories."
A human-like language processing
Two components
Natural Language Understanding (NLU)
Natural Language Generation (NLG)
Information extraction and classification
Translation
Question Answering
Information Retrieval
While chatbots may not replace the app experience entirely, they can offer a new and flexible way for brands to create new experiences for mobile users. So for example, instead of having to download and register for an additional dedicated app to access a new service, mobile messaging users will simply send a text to their bot of choice to do a variety of activities such as purchasing cinema tickets, calling a taxi, ordering a take-away or simply to catch up on the latest news stories."
A human-like language processing
Two components
Natural Language Understanding (NLU)
Natural Language Generation (NLG)
Information extraction and classification
Translation
Question Answering
Information Retrieval
While chatbots may not replace the app experience entirely, they can offer a new and flexible way for brands to create new experiences for mobile users. So for example, instead of having to download and register for an additional dedicated app to access a new service, mobile messaging users will simply send a text to their bot of choice to do a variety of activities such as purchasing cinema tickets, calling a taxi, ordering a take-away or simply to catch up on the latest news stories."
eliminate the password jujitsu associated with accessing dozens of workplace apps.
53% Better performance thanks to enterprise apps
240 hours Per year saved from mobile working
61% Of workers working outside office
3+ Devices daily for working activities
eliminate the password jujitsu associated with accessing dozens of workplace apps.
53% Better performance thanks to enterprise apps
240 hours Per year saved from mobile working
61% Of workers working outside office
3+ Devices daily for working activities
facilitate data-driven decision making in all areas of businesses.
http://www.cio.com/article/3027442/collaboration/how-messaging-bots-will-change-workplace-productivity.html
facilitate data-driven decision making in all areas of businesses.
http://www.cio.com/article/3027442/collaboration/how-messaging-bots-will-change-workplace-productivity.html