CS3216 Application Critique
Group 8 brought us a very interesting app called Photomath tonight.
As the name suggested, it is an app that help you solve math problems with your phone’s camera. They have a slick UI design and a super easy to user interface. Just turn on the app, open your math textbook, point the camera to the math problem, and done.
In the presentation, there are three points group 8 made that interest me: the OCR technology behind it, the idea of adaptive learning, and the comparison with traditional calculator.
First of all, the OCR technology. The team mentioned that Photomath is a very good example usage of Optical Character Recognition (OCR), and they should make use of the technology in many more interesting areas. I totally agree with their opinion, and in fact that’s what the company behind Photomath, microblink, is doing right now. I think the most important technology involved in the math equation recognition is OCR, and microblink company actually has developed their own OCR engine, blinkOCR. Personally, I felt the performance of their recognition is pretty good. Given a not so complex math equation, they could still recognize the pattern within 1 seconds with a high accuracy, and it could recognize linear equation as well! (Be alert! MA1101R student :P). However, math is a complex thing, as there are tons of patterns and transformation. Name card, bank statement, resume, documents and ID card are much easier to work with using OCR instead. I remembered in US, there is a bank that supports depositing checks by just taking a picture of it using their banking application. It saves you a lot of trouble for walking our of your house and try finding a check deposit place (I have to take a bus to the bank in order to deposit my check in Singapore). Therefore, their OCR engine will have a large potential customer groups in financial, travel (scan ticket), and public service (filling annoying forms) sectors. However, OCR these days is already a hot thing in the industry. Universities are researching on it, big companies is working on it, how to make it stands out from the crowd? This is something the microblink must think about.
Secondly, adaptive learning. During their presentation about the app’s commercial potential and improvement, the team gave an example using User Persona and User Story (side note: good use of what we have learnt in week 3’s guest lecture!). Imagine a secondary school student, Jason, who use this app to do their homework (let’s not discuss the “cheating” act first…). After he finished the work from school, he wants to learn more but don’t know where he can find similar exercises. Here is where Photomath comes in. While he is scanning on different question, Photomath could show some suggested similar problem sets on the screen, and by testing identical concepts can reinforce Jason’s learning. That’s the key idea of adaptive learning. At first, you use it as a tool like calculator, but then, you use it as your private math coach, and a library full of problem sets. I personally like this idea very much as when I was in secondary school, I also wanted to find more questions to try out apart from my homework. But then I have to either buy more textbooks or go to math classes, which costs more money. But if I have such app, I could benefit from just taking pictures of one question and then more questions are coming up. I felt this could also be a business potential of Photomath, that they can partner and integrate their technology in many K12 education applications to help children learn better.
Last but not list, comparison with traditional calculator. In their introduction, group 8 believed that traditional calculator may be tedious, and using Photomath is a much easier and more pleasant experience. I agree. If we think about the word “calculation”, most likely things come to our mind is about tedious and messy writing on paper, or typing a long expression on your calculator or computer. However, Photomath is a totally different user experience. It saves you time and efforts to take our pen and paper, calculator and laptop. What you have to do is just take your phone and snap. That’s it. Although it is not perfect for now, it does refresh people’s opinion toward calculation. I wish it could continue its development and keep improving itself.
Imagine you are a 14-year-old kid again. You need to do this really difficult math exercise for tomorrow, but have no idea how to do it. What if you could just open an app on your phone, point your camera at your textbook, snap a picture and get the detailed instructions to solve your equation? That’s the Photomath in my mind. It conquer our nightmare when we were still kid: solving hard math problems. I guess as an CS students, Photomath may seem to be useless to us, because of its wrong recognition and cannot be applied on hard questions. But from the aspect of K12 educators and parents, this is definitely a very useful app that will help their kids and students to learn better. The technology involved is also promising, as OCR could also apply to english text, chemical elements and structure, and even…computer codes? That’s just an example usage in education, the company could easily find more to do in other industries as well.
(Try to OCR this one with your phone?)
I think the immediate improvements the company could do to make Photomath better, is to make use and incorporate more advanced technology, such as machine learning and pattern recognition, and improve the accuracy of their recognition rate. Moreover, they could also experiment more complex math by partnering up with Wolfram Alpha. They can recognize what the equation is, and Wolfram Alpha is professional in math calculation. In addition, as a tech company, they could be more active in open source industry, and attract more developers to try out their OCR SDK, so they could gain more users, and also, money :P