The business communications landscape has changed dramatically in the last twenty years, thanks to Voice-Over-Internet-Protocol (VoIP) and the rise of the internet.
Copyright by jaxenter.com
Telephone networks are no longer tied to a wired landline network. Instead, your VoIP phone system can be operated from various IP addresses , providing flexibility for workers and devices. Machine learning is further transforming that landscape.
Gartner, in their report, Top 10 Strategic Technology Trends for 2020 , state that AI and machine learning are increasingly used to make decisions in place of humans. In this article, we dig into this trend to focus on how machine learning is changing business communications.
Microsoft’s vision for intelligent communications
Microsoft led the way in unified communications. “The company was UC before UC was UC” quipped Robert Ballecer at Enterprise Connect in Florida earlier this year when interviewing Scott van Vliet, Corporate Vice President for Microsoft Teams. Microsoft Teams has brought “together all the aspects of communications and collaboration, whether it is chat, calling, meetings, and the office suite of apps,” says Scott.
Over 500,000 organizations using Microsoft Teams. Microsoft themselves have 180,000 team members using the cloud-based software. Scott is a keen proponent of the innovations the team is making in video quality. Looking forward, they plan ‘intelligent’ video background replacements. Both features use machine learning.
Microsoft announced a vision for ‘intelligent communications’ on their blog back in September 2017. The idea was “to transform calling and meeting experiences for people and organizations around the world. To achieve our vision, we are bringing comprehensive calling and meeting capabilities into Teams, and infusing those experiences with intelligence.”
One of the significant features discussed in the keynote speech by Bob Davis, Corporate Vice President of Office 365 Engineering at Microsoft, at Enterprise Connect was the addition of Microsoft Graph to Teams. Microsoft describes Graph as “the gateway to data and intelligence in Microsoft 365”. GetVoIP cites Davis as calling it “a powerful brain that connects to data signals coming from every email, every file, every message sent within Office 365.”
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Examples of what Graph can do within a team include finding someone by name, and not just by finding a simple search match for a phrase. Graph will calculate which person with that name you most commonly deal with or which person with that name is in your team or channel.
Graph goes one step further. If you don’t know the name of the person you are looking for, but you need someone with expertise in, say, ‘chatbots’ Graph can calculate who in the organization you are most likely to need. The program bases its calculation on who posts, chats, or emails most frequently about ‘chatbots.’
These features scratch the surface of the possibilities. Graph can provide virtual assistance for meetings, recording, transcribing, and even filing meeting notes. You can also search for a particular keyword, or speaker and Graph will take you to that timestamp in the recording of the meeting.
There appears to be a common thread in the machine learning features list in the improvement of meetings. Diane Chaleff, Office of the CTO for Google Cloud Suite, also spoke at Enterprise Connect on Google’s plans for machine learning and their vision for future communications. […]
Read more – jaxenter.com
The business communications landscape has changed dramatically in the last twenty years, thanks to Voice-Over-Internet-Protocol (VoIP) and the rise of the internet.
Copyright by jaxenter.com
Gartner, in their report, Top 10 Strategic Technology Trends for 2020 , state that AI and machine learning are increasingly used to make decisions in place of humans. In this article, we dig into this trend to focus on how machine learning is changing business communications.
Microsoft’s vision for intelligent communications
Microsoft led the way in unified communications. “The company was UC before UC was UC” quipped Robert Ballecer at Enterprise Connect in Florida earlier this year when interviewing Scott van Vliet, Corporate Vice President for Microsoft Teams. Microsoft Teams has brought “together all the aspects of communications and collaboration, whether it is chat, calling, meetings, and the office suite of apps,” says Scott.
Over 500,000 organizations using Microsoft Teams. Microsoft themselves have 180,000 team members using the cloud-based software. Scott is a keen proponent of the innovations the team is making in video quality. Looking forward, they plan ‘intelligent’ video background replacements. Both features use machine learning.
Microsoft announced a vision for ‘intelligent communications’ on their blog back in September 2017. The idea was “to transform calling and meeting experiences for people and organizations around the world. To achieve our vision, we are bringing comprehensive calling and meeting capabilities into Teams, and infusing those experiences with intelligence.”
Thank you for reading this post, don't forget to subscribe to our AI NAVIGATOR!
Examples of what Graph can do within a team include finding someone by name, and not just by finding a simple search match for a phrase. Graph will calculate which person with that name you most commonly deal with or which person with that name is in your team or channel.
Graph goes one step further. If you don’t know the name of the person you are looking for, but you need someone with expertise in, say, ‘chatbots’ Graph can calculate who in the organization you are most likely to need. The program bases its calculation on who posts, chats, or emails most frequently about ‘chatbots.’
These features scratch the surface of the possibilities. Graph can provide virtual assistance for meetings, recording, transcribing, and even filing meeting notes. You can also search for a particular keyword, or speaker and Graph will take you to that timestamp in the recording of the meeting.
There appears to be a common thread in the machine learning features list in the improvement of meetings. Diane Chaleff, Office of the CTO for Google Cloud Suite, also spoke at Enterprise Connect on Google’s plans for machine learning and their vision for future communications. […]
Read more – jaxenter.com
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