Artificial intelligence has been breaking into the mobile app development industry and becoming part of more developers’ tools in their wheelhouse. This is because AI and machine learning are able to provide many benefits to not only the team building the application but to the end user as well.
But how is AI used to develop mobile applications and what role is it set to play in the future?
Why AI Is Perfect For Mobile Apps
As a heuristic, the best technologies are those that subtract the most from our daily chores.
Artificial Intelligence (AI) is able to subtract the ‘chores’ that humans do the most during the course of their lives. It does this by extracting the quintessence of a lot of data and trying to become an instrumental substitute for that chore.
With AI, what you can create, you can ultimately recognize. This is why AI can generate and recognize content alike.
The emergence of the smartphone changed how many of us approach our relationship with computers. Humans start their pocket computers in the morning and keep them turned on during their work day and during their personal time. From going to the post office to opening a desktop email application to swiping a few times with their fingers. When you introduce machine learning to these processes, the equation becomes ever more simpler. How? Because humans are able to talk a lot -- another chore -- there is sufficient data to train an AI model to be able to generate speech and recognize it with sufficient probability. From a user perspective, the next frontier is always the same. It is to facilitate ever less friction between a human and a machine.
Because humans are able to talk a lot, there is sufficient data to train an AI model to be able to generate speech or recognize it with equal quality. Because humans have a face, there is sufficient data to train an AI model to generate or recognize faces for example.
The next frontier is always to facilitate ever less friction between a human and a machine. AI and mobile devices are one and the same thing from the ultimate perspective of how humans use technology. This is why AI and mobile apps are adjacent technologies from a user perspective and integrate extraordinarily well.
Use Cases For AI In Mobile Apps
If you are a mobile app developer, you may try to merge the following AI features with your next project or recognize them in existing SaaS applications.
Face recognition works by recognizing if a picture contains a human face or not. It does not matter if that face is of the owner of the device or any particular face. How will this be used in applications? The answer is security. Facial recognition can be used for surveillance purposes or to monitor emotional or general activity. Say a CCTV camera in the area has filmed a robbery - facial recognition could help identify the perpetrator.
A superset of face recognition is facial identification. It means identifying the face and granting permissions to particular content or the phone software itself. This can be used for content restriction, unlocking your phone, or accessibility purposes. The most common example is being able to unlock your smartphone by looking at it.
Voice recognition usually recognizes sounds as human voices. It does not matter if that voice is of the owner of the device or a particular voice. As with facial recognition, it can be used for surveillance purposes or to monitor emotional or general activity. Text-to-speech falls under this category too, as do accessibility tools for the differently-abled.
As a superset of voice recognition voice identification means identifying the face and granting permissions to content or the phone software itself.
Recommendations For Using AI in Mobile Development
Based on user input, mobile AI can recommend ever better content to the user. Customers save time on finding the products they truly desire. Unknown products that might enhance the individual’s life can pop up on the screen with a higher probability.
Do Artificial Intelligence and mobile app development fit together? Yes, they do. The two technologies converge in terms of human accessibility, portability, and usability of computational devices. AI for mobile devices improves how humans use technology magnitudes stronger than AI for desktop devices does.
About the Author
Dennis Bosch, is a writer at Passivebasics: a Technical Newsletter for non-technical Founders. Learn the top-down basics of Web Apps, APIs, Git, Docker, ML/AI, et al. without the usual hassle. You can also follow them on Twitter @passivebasics.