The media industry is already full of data, but creating data sets such as metadata for images and video can be a daunting, and time consuming task. Metadata is necessary for archiving and creating media libraries so we can easily reference content in the future based on what’s in the footage (people, places, objects, names, etc). Sifting through footage and manually having to tag it with this data is no fun task, it can take a very long time, it’s subject to human error and differences in the way people think, and badly tagged footage can be hard or even impossible to find. But AI systems can make our lives easier by being able to categorise footage intelligently, quickly, and clearly. AI platforms can tag media with vast amounts of data like file information, objects, faces, locations, on-screen text, audio and much, much more – all of this done quickly, freeing up your time and making the future of your job easier.
Inclusivity and meeting the needs of all your users should be a part of every business’ approach to modern video content. Transcription and speech to text has a multitude of use cases, particularly in the media industry. Whether it be captioning existing business footage, reducing editing time by the alignment of audio media monitoring or the live transcription of a broadcast. Using the Google Cloud API, IBM Watson AI, Truis can work with you and your team’s needs to build personalised solutions to enhance your customer’s experience while creating efficiencies within your own operations.
News and journalism can use machine learning in a unique way, to write topical and of the moment stories to publish based on data and existing trends. You may be thinking “why what about me [as a journalist] won’t it push me out of a job?!” Well actually, no, it won’t. While machine learning can take structured data, distil it and develop a piece of written content highly relevant to that piece of data, it cannot replicate ‘the human voice’, the personality and opinion of a journalist. What it can do it help creators publish more niche articles that, while relevant to only some, cannot be written by journalists everyday as it isn’t cost effective for a business. It gives the users and the readers of news more consumable content rather than the writers reaching a maximum due to, for example, the number of employees a business has and time to spend on a piece of content.
Where there is rich media content, images, photography, video etc. there is opportunity for AI and automation. Whether it is personalising content for the user enhancing their experience with your media, to driving the predictive capabilities of your resources and limit disruptions, we’ve only scratched the surface of what AI can offer to the media industry. Get in touch with Truis today, let’s discuss how we can make your work life easier through machine learning.
Join us next month where we deep dive into AI and machine learning for the retail sector.