Artificial intelligence, or AI, is perhaps one of the most exciting new technologies of the year. The technology is so terrifying 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 moved its primary focus to “A.I. First. “While the announcement seems trivial, it introduced a massive wave of AI development kit for Android, making it easier than ever to develop high-quality learning apps. The consequences of AI for app development will be enormous. Let’s see how AI is shaking during Android development.
What is AI?
To understand how AI works, we need to divide how people learn in the simplest parts. Let’s start with an example: you grill a delicious brisket on a Green Mountain Grill when you accidentally touch the hot surface. Ouch! Your brain realizes that when you touch the grill, you get burned. As a result, it decides not to touch the grill anymore. It’s pretty simple, right? Human learning is based on recognizing patterns. AI works in a similar way, but on a huge scale.
In the simplest terms, AI lets your apps learn and interact as humans do by recognizing and repeating patterns.
All kinds of companies seem to think so. Companies in every industry, from healthcare to tourism, realize the boundless potential of apps that can learn.
AI in app development
Any application can benefit from AI. However, some features are improved so quickly that they cannot be ignored. Here are some of the features that are heavily influenced by AI technology.
If an AI has collected a lot of data on how certain objects look like, it can find similar objects in the future. By recognizing specific points in an image, computers can detect and sense things better than before. This landmark in AI technology promises to improve both everyday and specialized industry applications in many different ways. While many facial ID programs use detection of face recognition landmarks, healthcare apps use the technology to automatically read radiology images. The only thing that is growing faster than the technology itself is the number of different ways people can use it.
Do you know those captchas that ask you to click on the photos of the buses? Every time you solve this captcha, you help train Google AI to recognize the images. While continuing to sign in to your account, Google compares all the images you clicked to discover what a bus looks like. To accomplish this feat, the AI assigns each pixel to a class (bus, road, signal, human, etc.). This process is called semantic pixel segmentation and is absolutely crucial for AI image labeling AI.
While labeling parts of an image is easy for humans, it is an important development for AI. A computer that can recognize images can also operational decisions and automate strategically. That is why the image labeling function is extremely useful for medical technology and automated cars.
AI in facial recognition systems generally works by comparing the facial characteristics of a video source with those of a database. However, the process requires a machine to find facial marks, extract them, detect the face, and compare them with existing data.
Artificial intelligence and deep learning technology are making every step of the process simpler and more precise.
Identifying a person from a video source has become a widespread and useful feature that is used for everything from unlocking your smartphone to labeling people in a Facebook post. And face detection will only generalize as AI improves. Applications in the near future may possibly use face detection for types of surveillance, forensic analysis or tracking of people/objects.
Many applications such as Google Translate can detect and recognize text in images thanks to advances in AI. The process for recognizing text is not very different from image recognition. This Facebook Engineering publication details in detail how your AI recognizes and processes text in images.
The text can be recognized from any Latin-based languages, including French, German, Dutch, Spanish and more. This means that Artificial Intelligence text recognition is enormously useful for translation software. However, the technology also works very well in retail applications.
What’s Next for AI?
The future of AI is hard to predict. Depending on whom you ask about the future of AI, you will receive a different response. In fact, the Pew Research Center surveyed almost 1000 experts and received different predictions from each. Since technology is so versatile, anything can happen, especially in application development. Also, no matter how AI technology changes, we will be ready to build the future. Reach out with our online contact form to discuss how AI can improve your application, or call us at 844.526.2253.
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