Recent research reveals that video conference adoption is set to grow by more than 20% by the year 2022, taking its overall market value to around $41 billion. If those numbers come to pass, then video communication is going to be second only to voice as the most widely used channel. It’s no surprise that demand for video collaboration has increased rapidly while traditional video conferencing has been left in the shadows. The days of video conferences being held in boardrooms with formal meetings and presentations are well and truly over.
Businesses today are more focused on shifting towards flexible work environments, where video devices are equipped in multi-purpose breakout areas and huddle rooms. The number of employees working remotely has also grown, which is why video-enabled communication is becoming so important. Not only does it boost productivity, but it also ensures greater convenience for team communications.
The Transformation of Video Conferencing By AI
It’s no surprise that AI is dramatically driving efficiencies and improving user experience by automating collaboration tasks that are time-consuming. Advancements in AI is pushing innovation in computer vision, natural language processing, and meeting room analytics. Let’s break them down individually:
Natural Language Processing – Everyone Has a Voice
Video conferencing can be improved with natural language processing in various ways, including:
- Translating conversation into different languages
- Sharing notes and actions
- Automating transcriptions of meetings
When AI is combined with natural language processing it enables chatbots and virtual assistants to leave, start, and join meetings with voice commands. Other advantages include better audio quality that minimizes background noise and suppresses echoes.
For instance, if an individual is eating chips in the meeting, the new technology muffles this distracting noise. When you combine this with evolving techniques like beamforming and automatic leveling, everyone in the meeting understands and hears everything clearly.
Computer Vision – Taking User Experience to the Next Level
Advancements in computer vision have elevated video conferencing to an entirely new level with drastic improvements in video meetings, where cameras can recognize the voice of the individual speaking and zoom in on them. It also helps in tracking and tagging the number of people in a meeting. Other advancements include controlling the background environment and gaze correction, both of which enhance the user experience.
When you combine AI with computer vision you get intelligent light and color correction, which optimizes light balance to make faces visible even in backlit or dim conditions. More interactive meetings are possible with smart camera control, as video cameras track individuals in the meeting room and shift to the person speaking and engaging the room.
Meeting Room Analytics – Driving Productivity with AI
In the future, AI will be utilized to interact with users outside and inside the meeting room, which also helps productivity. Conference rooms will be smarter and meetings will be more efficient with AI-driven devices incorporated into video conferencing. This will allow businesses to increase efficiency and manage meetings more effectively by automating tasks like sending notifications and rescheduling calls. It will also include the ability to book rooms, notify participants of schedule changes, and enable screen sharing.
Data insights generated by AI will also allow businesses to optimize the management of facilities. For example, using predictive analysis, AI will help businesses understand the way meeting rooms are being used so that occupancy levels can be increased, as needed. AI and data analytics will track engagement in video conferencing calls, the mood of the participants, and the voice of participants.
Enter EtherMeet: A Game Changer for Slack Users
For years, Slack users have relied on the app to seamlessly communicate with other team members and facilitate video conference systems. The ease of sharing information with other teams has positively impacted businesses, as it allows them to act quickly and deal with important issues before they major problems arise. However, with technology continuing to grow and develop at such a rapid pace, an even better solution has become imperative.
That was delivered by EtherLabs in the form of EtherMeet, a Slack-integrated system that uses artificial intelligence and promises to completely transform video calls. The mission of EtherLabs is to positively improve team productivity by finding solutions to the challenges experienced with distributed teams. EtherMeet is designed to not only make meetings more efficient but also eliminate the problems associated with asynchronous communication.
EtherMeet uses next level artificial intelligence and media analytics to help capture, summarize, and route crucial parts of a video conference back into Slack. During the call, participants can take important call snippets reroute them to other team members in Slack, who can then join the active call, watch, or reply without ever being a part of the meeting.
The idea behind EtherMeet is to resolve the problems experienced by businesses when they’re leading multiple distributed teams across different time zones. The result is better collaboration and communication sharing. It enables team members who are not attending the virtual meeting to stay informed. Snippets can be saved and sent to them for later review.
That means the context is never lost.
Breaking Down EtherMeet
With a foundation in artificial intelligence and media analytics, EtherMeet starts by enabling a smart call on top of Slack. EtherMeet captures and analyzes the call as the call happens and summarizes the important moments. It then routes those important parts back to the chat channel from which the call started so that others can read, watch, or listen. Participants during the call can even manually route call parts back into the channel with an @mention directed to specific users.
Additionally, EtherMeet learns who is in the meeting. It discovers what topics and words are important at the Org, Channel, and Individual level to drive greater relevance over time, and it automatically summarizes discussions and distributes those important parts. The system learns from the temporal context of the discussion and leverages the interactions captured from the team – dialogue, chat, documents shared, call parts routed, watched, and commented on. It even identifies relationships and behaviors. Calls are then summarized intelligently so that distributed teams can now collaborate not only across distance but also time zones.