Artificial Intelligence, or AI, is perhaps one of the most exciting emerging technologies of the year. The technology is so ground-shaking that the entire AI industry is expected to grow to $17 billion by 2020. As a result, many large companies are adapting to new technology. Most importantly, Google shifted its primary focus to “A.I. First.” While the announcement seems trivial, it introduced a massive wave of AI development kits for Android, making it easier than ever to develop high-quality applications that learn. The consequences of AI for app development will be huge. Let’s take a closer look at how AI is shaking up Android Development.
What is AI?
In order to understand how AI works, we need to break down how humans learn into the simplest parts. Let’s start with an example: you’re grilling some delicious brisket on a Green Mountain Grill when you accidentally touch the hot surface. Ouch! Your brain recognizes that when you touch the grill, you get burnt. As a result, it decides not to touch the grill anymore. That’s pretty straightforward, right? Human learning boils down to recognizing patterns.
Artificial intelligence works in a similar way, but on a larger scale. In the simplest terms, AI lets your apps learn and interact like humans do by recognizing and repeating patterns. Pretty cool, right?
All sorts of companies seem to think so. Enterprises in every industry from healthcare to tourism are realizing the limitless potential of apps that can learn.
AI In App Development
Any application can benefit from AI. However, some functions are improving so quickly that they cannot be ignored. Here are some of the features most strongly impacted by AI technology.
If an AI has collected a lot of data about what certain objects look like, it can find similar objects in the future. By recognizing particular points in an image, computers can detect and label things better than before. This landmark in AI technology promises to improve both mundane and specialized industry applications in a large variety of ways. While many facial ID programs use landmark detection for facial recognition, healthcare apps use the technology to automatically read radiology images. The only thing growing faster than the technology itself is the number of different ways people can use it.
You know those captchas that ask you to click on pictures of buses? Whenever you solve this captcha, you help train Google’s AI to recognize images. While you carry on logging into your account, Google compares all the images you clicked to figure out what a bus looks like. In order to accomplish this feat, the AI assigns each pixel to a class (bus, road, sign, human, etc). This process is called pixel semantic segmentation, and it is absolutely crucial for image-labeling AI.
While labeling parts of an image is easy for humans, it’s a major development for AI. A computer that can recognize images can also automate strategic and operational decisions. That’s why the image labeling feature is extremely useful for automated cars and medical technology.
AI in facial recognition systems generally works by comparing facial features from a video source with those in a database. However, the process requires a machine to detect the face, find facial landmarks, extract them, and compare them with existing data. AI and deep learning technology are making each step of the process simpler and more accurate.
Identifying a person from a video source has become a widespread and handy feature used for everything from unlocking your smartphone to labeling people in a Facebook post. And face detection will only grow more widespread as AI improves. Apps in the near future can possibly use face detection for types of surveillance, forensics, or person/object tracking.
Many applications like Google Translate can detect and recognize text in images thanks to advances in AI. The process for recognizing text is not too different from image recognition. This post from Facebook Engineering goes into great detail about how their AI recognizes and processes text in images.
Text can be recognized from any Latin-based languages, including French, German, Dutch, Spanish and more. That means that AI text recognition is extremely useful for translation software. However, the technology also works extremely well in retail applications.
What’s Next for AI?
The future of AI is hard to predict. Depending upon whom you ask about the future of AI, you will receive a different answer. In fact, the Pew Research Center surveyed nearly 1000 experts and received different predictions from each one. Since the technology is so versatile, anything can happen–especially in app development. Besides, no matter how AI technology may change, we will be ready to build the future. Reach out with our online contact form to chat about how AI can enhance your application, or call us at 844.526.2253.