What are artificial intelligence systems?
Artificial intelligence (AI) makes humans fascinated. There are so many dreams of scientists in terms of AI to achieve. For achieving pure AI, the scientists have designed and developed various artificial intelligence systems. These artificial intelligence systems consist of both hardware and software.
Designing and development of artificial intelligence systems is not an easy, straightforward task. It takes years of research, decades of experience, and millions of dollars. In addition to that, these artificial intelligence systems needs to achieve the success as planned, or otherwise, these projects are threatened by the financial sponsors.
Artificial intelligence systems are an integration of many tiny components that interwork successfully with the others. These components can be programmed in different AI languages, using different technologies. As long as they have a common platform to communicate, there is no question about the interoperability. When it comes to the components in artificial intelligence systems, they have a better interoperability than in conventional software systems. This is something the conventional software systems can learn from artificial intelligence systems.
From predicting the next stock boost to predicting the next big tornado, the artificial intelligence systems are used. Most of these systems perform in back office, doing bulk of the computation work.
When it comes to computer hardware, artificial intelligence systems require more resources such as computer processing power for successful operations. When artificial intelligence systems at work, there are millions of calculations taking place in the computer processor. Therefore, ordinary von Neumann computers lack some of the properties required by artificial intelligence systems. To address this, there are custom made computers.
The AI problems represented by artificial intelligence systems
In most cases, artificial intelligence systems are developed separately to address specific issues in AI problem domains. Reasoning and knowledge representation are two main AI problems that have been in research for more than four decades. These areas of AI can be considered as most fascination problems as they aim to resemble human capabilities.
Natural language processing and machine learning are two of the areas where the most of the research has been conducted. These two AI problems have achieved significant progress over time. There are commercial applications already in the real world catering the multimillion dollar businesses.
Artificial intelligence systems integration
It is now a common agreement that the integration of artificial intelligence systems is a much better approach than designing and developing a general, monolithic AI system from the scratch. Therefore, research has been conducted successfully integrating the artificial intelligence systems developed for different AI problems.