The correct answer is: All of the mentioned.
Artificial Intelligence (AI) has evolved extremely in many fields, but there are still some areas where it has not been able to achieve human-level performance. These include:
- Web mining: AI systems are still not able to understand the meaning of web pages as well as humans can. This is a problem because it means that AI systems cannot extract the information they need from the web as effectively as humans can.
- Construction of plans in real time dynamic systems: AI systems are still not able to construct plans in real time dynamic systems as well as humans can. This is a problem because it means that AI systems cannot react to changes in the environment as quickly as humans can.
- Understanding natural language robustly: AI systems are still not able to understand natural language as well as humans can. This is a problem because it means that AI systems cannot communicate with humans as effectively as humans can.
These are just a few of the areas where AI has not yet achieved human-level performance. However, AI research is constantly evolving, and it is likely that AI systems will eventually be able to outperform humans in all of these areas.
Here are some additional details about each of the three options:
- Web mining: Web mining is the process of extracting useful information from the web. This can be done for a variety of purposes, such as market research, product development, and fraud detection. AI systems have been used for web mining for many years, but they have not been able to achieve human-level performance. This is because web pages are often written in a way that is difficult for AI systems to understand. Additionally, the web is constantly changing, which makes it difficult for AI systems to keep up.
- Construction of plans in real time dynamic systems: A real time dynamic system is a system that is constantly changing. This can be due to changes in the environment, changes in the system itself, or changes in the goals of the system. AI systems are often used to control real time dynamic systems, but they have not been able to achieve human-level performance. This is because it is difficult for AI systems to understand the complex interactions that occur in real time dynamic systems. Additionally, it is difficult for AI systems to make decisions quickly enough in real time dynamic systems.
- Understanding natural language robustly: Natural language is the language that humans use to communicate with each other. AI systems have been used to understand natural language for many years, but they have not been able to achieve human-level performance. This is because natural language is a complex and ambiguous language. Additionally, natural language is constantly changing, which makes it difficult for AI systems to keep up.