How do artificial intelligence work?
AI uses machine learning to provide machine the ability to learn and respond. AI works with a combination of large amounts of data and intelligent algorithms with a fundamental and well-defined iterative process. AI is a field of study that includes various methods, theories, technology and includes several subbies such as machine learning (ML), neural networks, deep learning, cognitive computing, computer vision (NLP).
The concept of artificial intelligence is classified into two types based on its ability and functionality.
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Classification based on AI capabilities:
1. Artificial intelligence is narrow: This is one stream in AI, which stands out to do a single task with intelligence. Because it has a defined limit, it cannot surpass its limitations. This makes intelligence also known as a weak AI.
2. General artificial intelligence: General AI is a type of intelligence that can do any task with the same intellectual efficiency as humans. The idea behind General AI is having a system that will be able to think and react as humans.
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3. Super artificial intelligence: Super AI is a superior level of intelligence that can exceed human intelligence. Has been reduced from General AI and able to carry out a much better task than human intelligence.
Classification based on the AI function:
1. Reactive machine: This type of machine is the basic type of AI engine. This does not store memory or previous actions or action in the future. The type of machine only works by considering the current scenario and reacts to them with possible actions.
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2. Limited memory: This type of machine stores memory and previous experience for a shorter period of time because they have limited time to store data.
3. AI self-awareness: These machines are expected to be very intelligent and have a decision-making function. Although this does not yet exist, the hypothetical concept makes AI self-awareness that can be seen as the future of AI.
All types and methodologies the AI mentioned above can be effectively utilized to ensure effective software testing. Some significant benefits of AI in testing are given below.
Benefits of Artificial Intelligence in Qa Testing
Ai powered test
Write tests - faster, better and cheaper
Developing a pattern and test case to test how performing applications takes time if done by humans. AI-based tools can automatically write tests for applications or systems with spiderering, i.e., collect data, catch the screenship and do more. Therefore, AI-based testing cut costs and save time.
Questions requirements - better than the best human
The challenges we usually see in the process of developing and testing software are our human inability to fully understand and review the requirements. Intelligent assistants understand the software requirements and limitations of complex systems, which will support meetings that are better than humans in many cases. AI also helps define testing requirements based on the latest trends and marketing competitiveness.
Example: To develop ecommerce sites, AI can help collect and review the requirements based on competition.
Exploration testing is easy
Because AI-based testing is trained in all the collective knowledge of all people working on the team, it helps to easily identify various scenarios. Smart assistants are not only used to do testing, but also used as a background tool that captures test data, user behavior by navigating through applications or systems and records the default test cases.
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