Digital media Intelligence powered by Machine Learning and Artificial Intelligence

Do you wish you had a friend at home who could do everything? Hear you even while music was on, answered all your questions, read the news, reported traffic and weather conditions, gave information on local businesses and most important controlled all the lights, fans and switches.  You got it right we are talking about Amazon Echo.

Welcome to the world of digital media intelligence powered by Artificial Intelligence.

As per Mary Meeker of KPCB by 2020, nearly 50% of web searches will use image or voice search rather than text. “More efficient and often more convenient than typing, voice-based interfaces are ramping quickly and creating a new paradigm for human-computer interaction,” she says

While Artificial Intelligence has been around for long, there, Machine Learning is a current application of AI.

Machine learning analyzes deep consumer insights through multitude of data and via statistical readings creates self-learning to make better decisions and optimize user experiences.

Machine learning can be used in many ways. Automated categorization is widely used in digital media to build categories automatically. As an example, ‘Google Keep’, an application used for making notes on your phone uses this feature pretty well. Make few notes next time while on vacation you will see those features under the location tab.
A great example of AI and machine learning in action today is Netflix. The media analyzes your behavior and predicts what you would like to watch next. It understands you better the more time you spend with the media. In Netflix’s case they can tell you with 85 to 90% confidence your choice after you have been a member for long. In case of e-commerce sites too lots of data mining is used with machine learning to predict your next purchase, which appears as product recommendations.  (2- Forbes) Recommendations on digital media platforms are another great example of Machine learning. Pinterest’s recent acquisition of Kosei- that provides recommendations for users- then is no surprise.

Another natural application of machine learning is in analytics and predictions; for example in graph based machine learning at an advanced level its application in social media analytics is used for social relational inference. So, next time when you post on facebook beware that facebook is watching you closely. Another example is facial recognition within Facebook. From framing and tagging feature initially we have reached a phase where facebook is able to automatically detect the face. With a DeepFace approach it is as close to as a real human recognizing the picture. Huge volume of photos on facebook and sophisticated machine learning has made this possible.

So then is the future all bright?

Looks like there is another view though, while machine learning algorithms have become powerful with deep and sophisticated math to come up with a magical solution there, we run the risk of moving towards general problem solving rather than focusing on a specific issue.

As per Alessandro Zolla, Machine Learning Program Lead at Nielsen “Machine intelligence will never be 100% reliable—there are always edge cases, exceptions and incomplete data, where the smart machine is not able to carry out a task to a high degree of accuracy. For these cases, humans are a vital part of any solution as the guardians of quality control and the intelligence of last resort; humans have the ability to make good decisions based on limited information and possess that elusive quality, common sense.”

Reliability of machine is also extremely important. The decision really is to know when to rely on machine results versus when not to.  Human interventions become critical for low confidence recommendations while for high confidence machines will be as close to reality as will humans be. Hence looks like that the best solution is for humans and machines to collaborate to achieve a winning outcome. For only then when you enter your favorite hotel you are greeted by your name with your preferred arrangements in the room.

Future of Digital Media and Machine Learning

Digital realities will continue to steam forward empowered by Machine Learning and AI. These digital realities will help customers and businesses alike in numerous new ways, making them a highly relevant tool to explore. Who knows next time when you are watching a video it is created itself through machine learning and has self learnt how to fix and evolve itself to give you a better experience!

 

https://cogswell.edu/blog/chatbots-virtual-reality-machine-learning-new-applications-future/

http://www.thedrum.com/news/2016/09/10/how-data-machine-learning-and-ai-will-perform-magic-consumers

http://www.thedrum.com/news/2016/09/10/how-data-machine-learning-and-ai-will-perform-magic-consumers

https://www.forbes.com/sites/rachelarthur/2016/12/19/8-tech-trends-that-will-shape-the-future-of-fashion-and-luxury-retail-in-2017/#3ed347a07615

https://www.forbes.com/sites/bernardmarr/2016/12/06/what-is-the-difference-between-artificial-intelligence-and-machine-learning/#67a6e7f92742

https://www.digitaltrends.com/mobile/google-keep-automatic-categorization/

https://www.forbes.com/sites/unicefusa/2017/03/29/yemens-war-leaves-10-million-young-lives-falling-through-the-cracks/#157567fd736a

http://www.nielsen.com/in/en/insights/news/2016/uncommon-sense-humans-in-the-smart-machine-age.html

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