Artificial intelligence has become a topic of discussion, but in the end, many professionals and business managers still do not know what is the consensus about it and the applications of AI in the business world. The purpose of this article is to provide you with a better understanding of artificial intelligence and its various levels.
3 levels of artificial intelligence
Artificial intelligence can take different forms from a computer programmed to play chess to Sirius voice assistants. Experts agree on the classification of AI programs into three categories. These are based on how you can see and classify the algorithms used in your business and the ones you are looking around you:
1. Weak AI
Artificial intelligence technology is said to be weak when it is designed to handle a single task. An example? Deep Blue Software, developed by IBM, defeated Gary Kasparov in chess in 1996. This form of artificial intelligence is within our reach today. While weak AI can be very powerful in specific applications, its functions are very limited. This is level 1 of artificial intelligence. Machine learning is often associated with weak AI.
2. Artificial General Intelligence
Artificial General Intelligence is an artificial intelligence that comes from its capabilities, human intelligence. An AGI is flexible and can perform many tasks and solve a wide variety of problems, reason, think abstractly, understand complex ideas, learn quickly, and learn from experience. Creating artificial common intelligence is an ambitious project, but we are not yet close to realizing it. We are still in the research phase. For some experts, it would be decades before the first artificial intelligence was born. This is level 2 of artificial intelligence.
3. Artificial Super Intelligence
With ASI, we take another step forward. An artificial super-intelligence is an intelligence that is more sophisticated, more powerful, more complex than human intelligence – intelligence capable of scientific and artistic creativity, social skills, and even a form rich “Intelligence”. For some people, ASI will save humanity. For others, they are great crises that will drive us to extinction.
Opinions on ASIs are very different. ASI has been subject to a lot of speculation, and we already see it in the sci fi section, in Hollywood, and elsewhere. For most experts, general artificial intelligence is only one step, a springboard for artificial super-intelligence. There is a continuity between the two forms.
Difference Between Artificial Intelligence and Machine Learning
Before learning the uses and applications of AI, it is important to distinguish between AI and machine learning and to learn the differences and similarities between them. The two concepts are often related, if not confused with each other.
In fact, machine learning is a subset of artificial intelligence. In machine learning, the goal is not to program a machine capable of performing a specific task for completeness. Machine learning, in contrast, is based on the idea that we should give machines only access to data and let them learn it by themselves – without explicit human programming about the specific steps needed to solve the problem. Access to data allows machines to experiment and progress through these experiments. Machine learning is therefore a special form of artificial intelligence.
Machine learning is currently the most promising tool for AI application in marketing, predicting customer behavior, Automating repetitive tasks, and almost everything related to the business world in general. Algorithms with capability allow machines to learn from data, identify data patterns, and perform forecast analysis. With machine learning, the machine improves on its own and eventually succeeds in doing much more than its initial coding.