As CS3216 Students, we are interested in leveraging on existing technologies to bring innovative application ideas alive. Hence, the most interesting points that I gathered out of Group 8’s presentation on PhotoMath are lessons learnt, which I can apply to other future ideas.
Lesson #1: Applying OCR Technology to other contexts
Group 8 mentioned innovative ways to leverage on Optical Character Recognition (OCR) technology, most pertinently how it can be applied to replacing manual data entry roles. A quick search on job portals in Singapore would show the prevalence of data entry jobs today, and this is a pain point faced across even developed societies. A well implemented data entry OCR application could have the potential to disrupt and replace the data entry market.
Lesson #2: Make PhotoMath “Smart”
Group 8 mentioned how adaptive learning could be applied to PhotoMath to deliver math content to the user that is most relevant to him, based on the questions that he scans. This could potentially be used to deliver targeted math syllabus to students, and help users reinforce their learning. With all the buzz in “smart” applications, we learn how to appropriately leverage technologies to create smart applications that is targeted at specific pain points, like how “smart” PhotoMath proposes to help students learn better.
Lesson #3: How to manage unintended negative effects of PhotoMath
PhotoMath’s main target audience of students who use their application regularly are now empowered to cheat easily. Given the prevalence of mobile devices amongst students, it is easy for students to use PhotoMath to cheat, resulting in detrimental effects to these student’s education. PhotoMath could face controls by regulatory bodies to limit its use among people who abuse it. This leads us to remember to consider how to address some of the repercussions of our proposed application.
Final thoughts: Feasibility of OCR based apps in solving manual Data Entry
OCR technology is now actually very prevalent, with many new and existing players in the market. Some of these players like Microsoft Office focus on alternative problems like utility applications for consumers to convert PDF documents to word documents.
However, I feel that the data entry pain point mentioned is a real issue that many companies face, and with enough research and analysis in this, there lies a potential to develop a targeted application which could eliminate this pain point. Other enterprise solutions like trapeze exist , but they have not gained enough traction. Even large and commercially successful companies like Apple did not have first mover advantage in most of their products, but still managed to capture a huge market share, because of the fact that they are able to make user friendly products that address specific and huge pain points . If anyone can somehow make use of OCR algorithms to do this, it could potentially reap huge benefits.