Artificial intelligence (AI) has been currently used as a problem solver in the development of technology and science. It is implemented in many fields, such as industry, healthcare, and finance. In daily life, we have witnessed the real applications of AI developed by several companies, i.e., often found in life around, the use of Google Assistant for smart home, or SIRI on iPhone, and signal analyzer in GeNose C19.
To find out how AI works in helping humans answer some problems, the first things that need s to be known are AI working principles and methods, in which the machines or robots can then understand the existing problems.
So, what exactly is AI? How does it work, and how can AI become a promising problem solution in various areas of life?
What is Artificial Intelligence?
Artificial intelligence (AI) is a constellation of many different technologies that work together to enable machines to sense, comprehend, act, learn, and make decisions with human-like levels of intelligence. Maybe this is the reason why the definition of artificial intelligence is different: AI has a broad meaning.
In a nutshell, AI can be interpreted as:
- the broad science that mimics human abilities
- the thing that leverages computers and machines to mimic the human mind for problem-solving and decision-making capabilities
- What is Machine Learning? Difference between Machine Learning and Artificial Intelligence
- Development of AI models in response to industry challenges
- GeNose C19 as a Covid-19 detection, is it a solution or just a research product?
How Does Artificial Intelligence Work?
Artificial intelligence (AI) in its simplest form is a field, which combines computer science and powerful data sets, to enable problem-solving. It also includes the sub-fields of machine learning and deep learning, which are often mentioned along with artificial intelligence. This discipline consists of AI algorithms that seek to create expert systems that make predictions or classifications based on big data input. Quick big data collection, iterative processing, and intelligent algorithms enable the system to learn automatically from patterns or features in the data. The processes that occur in AI itself include learning, reasoning, and self-correction. This process mimics the humans doing analysis before making a decision.
Learning process. This aspect focuses on collecting data and establishing rules on how to turn data into information that can be acted upon or interpreted as a result of the analysis. Rules called algorithms, provide computing devices with step-by-step instructions on how to complete a particular task.
Reasoning process. This aspect focuses on selecting and determining the right algorithm related to labeling or categorizing data to achieve the desired results.
Self-correction process. This aspect is designed to continuously refine the algorithm and ensure that it gives the most accurate results possible through a continuous learning process from the initial input data.
AI is not developed to replace humans. AI enhances capabilities and makes them better at what humans do. AI algorithms can see relationships and patterns that might otherwise be missed from a human’s point of view. Since AI algorithms learn differently from humans, and AI sees things in a different way.
What Are the Application of Artificial Intelligence?
There are many real-world applications of AI systems that are hitting a wide variety of markets. Here are some of the most common examples:
AI services to detect sensor-related problems or fault detection of a decision-making plan from technical problems.
AI services can be used to determine the estimated purchase of materials, goods and stock for the warehouse to be in optimal condition.
AI services are used in white blood cell classification, cell type ratio calculations and comparisons with normal blood cells to determine the diagnosis of leukemia.
AI services are used as sentiment analysis from social media to see the image of political figures.
AI provides quality control that can determine a product that is good and not good based on the label classification that has been determined during the selection process.
AI services can predict weather and climate change over the next few years.
AI services can determine the credit score that can be given to clients by looking at the classification and determining the potential of the client.
AI services can see what features need to be improved and updated, or provide similar recommendations when someone is looking for an object
The application of AI can be used in any high-demand industry – especially question answering systems that can be used for political assistance, risk notification, business analysis, and medical research. This really depends on the quality of the data from the AI system itself.
Challenges of Artificial Intelligence in the Future
Artificial intelligence (AI) will change every industry, but we must understand its limitations because each field will require different models and labels for processing its data.
The limitation of AI is that it learns from data. There is no other way to import knowledge to the system. That means quality and quantity data input will represent the results. Accurate data with small amounts of data, or large data with inaccurate data, will provide less reliable analysis in AI systems
Current AI systems start to perform clearly defined tasks. The system used to count numbers cannot be used to read letters or tell stories. In other words, these systems are highly specialized. They focus on one task, can not be used for other tasks so it is far from behaving like a human.