movingimage is among the global pioneers of enterprise video technology. As such, the company is taking an active interest in Artificial Intelligence (AI) in conjunction with video technology and is experimenting with different features that will automate video procedures in the near future, making users’ lives that much easier.

AI is booming. According to an Aragon research, by the year 2023 cognitive interfaces with emotion detection for text, voice, and facial analysis will be integrated into 50% of new enterprise applications and available on 75% of all legacy enterprise apps. Meanwhile, Google and Facebook are conducting thorough research and exploring the subject from different angles. Everyone’s preparing for what’s to come, trying to evaluate the long-term effects of machine learning on our lives. When it concerns enterprises, the aim of AI is to eliminate tedious and repetitive tasks, allow employees to spend more time on creative endeavors, and improve customer interactions, operational productivity, and digitally-enabled business models.

Coupled with the growing video trend, AI is expected to create enhanced video automation and a plethora of new, exciting features. Once implemented into video management platforms such as movingimage, they will affect all video processes: from creation, through management, to distribution. Some video AI features are already available, while others are being developed at full speed. Either way, most will be introduced to the market in the upcoming years. Here are a few of them divided into three categories: available technologies, beta technologies, and future technologies:


Available AI-Video Technologies:

Visual metadata generation- computer vision is – in short – the area of machine learning that tries to replicate the human visual system. It can be used to recognize familiar faces, detect emotions, identify objects, etc. Once a computer vision is in use, users will be able to search for specific data shown in the video, including people appearing in it, their actions, specific events, etc.

Audio metadata generation- advanced, innovative software tools can create metadata not only from visual content but also from audio. Such metadata includes spoken topics, named entities, general themes, and explicit content.

Auto-generated subtitles- advanced software tools can also convert speech to text by employing various types of artificial intelligence technologies that are designed to recognize patterns. These technologies can make probable guesses at words and people from audio, and even feature a learning curve that allows them to improve their performance on the fly!

Text-to-speech- text to speech is a veteran feature you are probably familiar with from Google translate. However, it’s rapidly evolving and is becoming more sophisticated by the year. Not only can today’s technology generate audio from scratch, but it can even analyze the waveforms from a huge database of human speech and re-create them. The end result includes voices with subtleties like lip smacks and accents, which include customizable factors like pitch and speed.

Beta AI-Video Technologies:

Video summary- video summary is a powerful application that can reduce a long, archived video into a short video summary by editing redundant footage out of the video. Removing static background data while retaining the relevant data allows quick reviews of archived video in a fraction of the original video time.

Auto-editing- similarly to the video summary, the auto-editing application is meant to select the best scenes and then piece them together to create the final video. It does that by spotting redundant scenes and cutting them out of a video. Auto-editing diminishes the time it takes for a human editor to edit video footage from hours to mere minutes.

Natural Language Generation- Natural Language Generation, or NLG, is the natural language processing task from a machine representation system such as a knowledge base. NLG allows media outlets to publish stories online almost immediately while relying on accumulated data.

Video description- recent advances in “deep” machine learning have led to the creation of new models that can extract data from videos and automatically generate descriptions for various events featured in them.

Language translator-
translating from one language to another is a complex task that depends a lot on context, subtext, and cultural differences. However, AI-powered translation tools have improved a lot over the past few years. In March 2018, for example, Microsoft announced that it “Hit human parity in a machine translation task“ from Chinese to English, and even the Google Translate basic tool has significantly improved over the last few years, which warrants a bright future for AI-powered translation.

Future AI-Video Technologies:

Voice command-
The next step in AI is the well-known voice command, powered by AI technologies. Just like today’s mobile devices provide voice command capabilities, tomorrow’s sophisticated platforms will draw on AI to reach a more precise, better, faster results.

 “AI is the most talked about technology at the moment. Every company wants to use it or even create its own AI projects,” summarizes Christin Löhr, Chief Product Owner at movingimage and an avid AI enthusiast. “Quite often decision makers at a company realize too late how time-consuming and expensive the process is, especially if they don’t have a valid use case for it. That’s why it’s important to find a partner that you can trust, who can handle data securely and still provide you with the best AI experience, tailored to your specific use case. Speech-to-text services can be trained on specific vocabularies used in different industries, like healthcare or finance. Including these services in our platform helps our clients to automate their workflows considering the individual nature of their video content. Sparing them the AI-training hassle is a bonus.”