AI, the abbreviation of artificial intelligence, is the name of the revolution of the digital beings to having the capability to do tasks that are only carried out by intelligent beings so far. This term is usually used in relevance to computers being able to reason, discover meaning, generalize and learn from experience and being able to make decisions based on this information.
The concept of artificial intelligence was first brought forward half a decade after the second world war when Mathematician Alan Turing raised a simple question: “Can machines think?”. The research and development on this concept laid the foundation of artificial intelligence and realized its goals and visions to fruition.
Artificial intelligence is currently broken down into four major segments, which are as follows:
- Self-awareness
- Theory of mind
- Limited memory
- Reactive Machines
AI and machine learning are one the fastest growing technology bringing unbelievable innovations providing advantages to different fields globally. And to create such automated applications or machines, a huge amount of training data sets is required. The image annotation technique makes the objects recognizable to computer vision for machine learning. And this annotation process benefits not only the AI field but also provides advantages to other stakeholders.
AI Data Annotation labels the data available in various formats like text, video, or images. For supervised machine learning, labeled data sets are required to easily and clearly understand the input patterns, and to train the computer vision-based machine learning model; data need to be precisely annotated using the right tools and techniques.
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Examples of AI Features in mobile applications
Speech Recognition
The voice control system is speech recognition is the most popular Artificial intelligence technology used in mobile applications. Take the example of Siri and Cortana; they decode and convert human speech into a format that a computer understands.
Chatbots
Chatbots are the virtual assistant for the company answering users’ questions. Various renowned companies having virtual assistants include Apple, Amazon, Artificial solutions, Google, IBM, creative virtual, Microsoft, satisfy, and many more.
The Machine Learning (ML) Feature
This is a very prevalent AI technology integrated into most mobile applications. For corporal purposes, having an app with machine learning is very important. Machine Learning is used for classification and forecast.
Natural Language
This AI technology is used in apps for reporting and market reviews needed in their mobile apps. Natural language is the appropriate AI technology to integrate and is used to develop an app for customer service on mobile phones
Emotional Recognition
Artificial Intelligence provides another facet to technology by reading human emotions. The technology uses advanced image processing and audio data for emotion recognition, capturing human feelings with voice intonation and subtle speech signals.
Biometrics
Biometrics is used to identify, analyze, and measures human behavior. It can recognize the physical aspects, shape, structure, and size of the human body.
Image Recognition
Image recognition is based on recognizing all objects in a digital image or video. These features can also identify license plates, analyzes clients to check users’ faces, and diagnose diseases.
Text Annotation
This is also known as natural language processing and allows the user to search all the information required in the news, search engines, and structure solid texts.
