YOURSTORY Journal posted an article discussing how important it has become for businesses to understand and properly use their ‘dark data’ to make informed decisions. Below is the section where onQ was mentioned in this article in relation to the deep-learning based methods around training data:

From data to insights and value

There are various ways for businesses to leverage the power of dark data and data black holes using new and emerging technologies.Deep-learning based methodsin particular, are popular today, and have demonstrated the ability to extract insights from vast amounts of training data.

These methods are driving a new wave of computer vision innovation that could one day be the eyes through which a blind person sees the world. Today, these technologies are able to automatically process an image and identify it, including a frisbee being thrown in a park. This means, we may not be too far from a time when robots may be able to scan a swimming pool and jump in immediately to save a person who may have fallen in.

For example, US-based onQ, an innovative startup that we are working with, has a video tagging platform that allows users to post a comment or an emoji on the timeline while watching the video. Based on the exact moments of user engagement, the system can identify and provide specific and related insights. In contrast to heavily algorithmic approaches, onQ’s approach is intuitive and design-oriented. Their tool provides an overlay on top of any video that captures interactions with the content; this, in turn, creates new structured data that can be leveraged further to add significant value from otherwise dark data.

Deep-learning based models, however, need to be trained, and often, quite extensively, to ensure it’s useful. This does favor larger incumbents with access to the kind of labeled data that can help build models to unlock dark data. It is not surprising, therefore, to see technology giants such as Google, Baidu, Microsoft, Alibaba or Facebook pushing the envelope when it comes to deep-learning based models.


To read the full article by Sunil Mithas & Balaji Padmanabhan visit YOURSTORY.