AI in Video will Enhance Work in the Modern-Day Work Environment

AI in Video will Enhance Work in the Modern-Day Work Environment

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by Richard Gall — 2 weeks ago in Business Ideas 6 min. read
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Remote work has emerged as a hot topic in the employment world, despite being the longest year ever recorded. Remote work is gaining popularity because of its many benefits and its difficulties.

Remote work is becoming more common among employees, with many actually preferring it to work in the office. A FlexJobs survey found that 65% of employees want to work remotely after the pandemic. 31% also desire a hybrid environment for remote work — 96% of respondents wanted some type of remote work.

These numbers will inevitably indicate that the methods we used during the pandemic (primarily via video calls and screen) will be able to last.


There has been an overwhelming amount of unintentional or accidental content creation over the last year via various digital platforms. There are huge amounts of information that can be gleaned from this massive amount of data.

Your business can work smarter and not harder with the right tools. This valuable knowledge is derived from worker’s day-to-day interactions. This knowledge can give your company the competitive edge it needs to move forward in the technological age. AI in video enhances many aspects of modern-day work life.
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How AI Has Changed Video Streaming Experience

The key to video streaming in modern work environments is how you navigate it. There will be more online meetings and content creation in 2021. Video can bring content to life but, more importantly, it allows you to quickly and intuitively access the video.

Let’s think about it like this: Would you buy a book without a table of contents, index, and chapters? You wouldn’t. Although it would be absurd to try to navigate through unstructured text pages, that is exactly what we do for video.

You can customize and access all contexts in the video by implementing AI.

AI can perform all the work required to deduce data using Machine Learning and Natural Language Processing. This will help reduce search time and fatigue.

AI uses audio and visual data to extract all the information from video and tags content. Keywords, concepts, important and relevant topics are some of the other ways Artificial Intelligent can assist you.

The ML and NLP create a transcript and then the AI creates an intuitive Index–creating transcriptions and chapters and title pages, and finally a Table of Contents. This makes it easier to search for content and allows for more efficiency for each user.
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Video in the present is significantly different from video in past.

It has been a meticulous process to utilize the power of video until now. Rather than manually tagging video media with editor tool applications–crafting tags one-by-one or creating a time-sliced video by tagging minute intervals–AI can do the work for you.

A single label, title, or tag at “minute six”, is meaningless for searching. This is because the keyword is restricted to the publisher’s interpretation.

You will often know what you want when you search for something, whether it is in a grocery store or Google’s search engine. AI is a new type of video tagging that can draw relevance to a variety of keywords and topics.

This improves the accessibility and ease of use for video organization. AI can save companies time, money, and resources by allowing them to apply these techniques to existing video content.
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OCR: How it is changing videoconferencing

Optical Character Recognition is a new video technology that can read stills from your video and determine if any text lines can be drawn.

This technology can be used to read PowerPoint presentations or words written on whiteboards behind speakers in videos. AI can combine both audio and text elements derived by OCR to create a complete transcript of the video.

This AI-driven translation allows for media contextualization. This simply refers to the ability to view a video and extract all the relevant information.

NLP and ML combine their abilities to create a knowledge base to which all relevant information can be centralized. The deep-learning process will then be able to analyze the text and organize it into a systemized database. This allows for understanding changes in context.

The AI-driven technology then decides when to create a new chapter. It outputs a blurb or phrase that best describes the content. The entire table of contents for each video recording is created. It contains all the information logically and efficiently.

The AI can go beyond the video and interpret all data points. This technology can be used to help spread relevant information between departments in a company.

This is especially important given the increase in conference recordings in modern workplaces. There are many potential insights in recorded business video calls. However, it is important to understand them in a context that is meaningful to the individual.

OCR is used in AI-driven technology. This allows for contextual connections to be made throughout the information. It also creates a user-friendly structure. This creates a more intuitive video-user experience that allows users to easily find and share what they need.

Connecting Context through Ontology and DBpedia

AI can innovate further by using an ontology, which is a system that allows for a centralized, organized, and informed knowledge base. Ontology refers to a collection of concepts and categories within a subject or domain that show common properties and their relationships.

One of my clients is Ziotag. They use proprietary AI ontology technology for creating tags in video media. To start this process, you first need to assign all the terms people might use when discussing a topic.
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Using this insight, the AI can create ontology tags that can procure more than 50k concepts. It will also find the best ways for them to relate.

This creates a multi-faceted and dynamic foundation of data points that could almost represent a human brain–using concepts, keywords, and context-understanding to deduce what a user might be looking for in the knowledge base.

The possibilities of the internet are limitless when this local fear is applied to the larger picture. DBpedia is a Wikipedia project that extracts structured data from 111 language editions to help users find out more about the Semantic Web or Linked Data technologies.

To give you an idea of the scale, the largest DBpedia knowledge database in English is over 400 million facts. It describes 3.7 million items. These maps were created through a global crowd-sourcing effort to allow knowledge from all Wikipedia editions to be combined and put into context.

Ziotag’s Ontology Approach mirrors this Data Connection Strategy, allowing the AI to recognize concepts from a variety of resources.

AI can understand the context and transform video to give immeasurable insight to the people who use it.

This insight can be gleaned from searching for words with very similar names, but different meanings. Let’s take for example the word “salt”. When you searched the word, did you want to find the scientific compound sodium chloride? Or table salt? Perhaps you were searching for the name of the local restaurant or the history behind mining it.

The Ontology AI technology can distinguish what you are looking for by linking meaning vectors. This allows you to tailor the organization of concepts in your video to meet your specific needs.

Automating Business Processes

Combining all these AI innovations can drastically improve the efficiency and interconnectivity of modern companies.
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The AI-driven technology extracts MetaData from interactions between employees and team meetings. This makes expertise visible across all departments.

This allows employees to have the information they need instantly, regardless of any silos in their business infrastructure. AI can then be proactive and create delightfully personal experiences once the knowledge is centralized.

AI can begin to build a dialog for personal workflows by gleaning context from employees’ interactions both via video and through other applications like Slack or email.

This can be particularly important in large companies that have a distributed workforce. It allows for the integration of different communication channels and compiling all information as a diligent librarian. The AI can also be able to access data about the individual’s daily work schedule and their role in the company.

This could help people get up to speed quickly, for instance, if they are unable to attend meetings or are away for a while because of vacation. The best thing about this is that you can absorb the information in your own way.

The information can be translated back to the worker in a way that’s most convenient for them, whether it be expanding chapters, searching topics with ease, or reading and listening at their leisure.


Automation will change the way AI is implemented in business. This will make it easier to manage and improve the digital workplace. This will enable a new way to work across multiple industries. Computer science and AI are a complex structure that was built upon a wide range of innovations.
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Many relevant innovations can be made if the greater goal is emphasized.

AI in the next generation will be capable of doing even more. Each floor of the computer science structure is defined by the level below it and there is no limit to its height. The construction of this structure will make AI in video a multiplier, allowing remote workers to take control of their work.

Richard Gall

Richard is senior editor of The Next Tech. He studied International Communication Management at the Hague University of Applied Sciences.

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