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Answers to the Top 7 Questions about AI Featured

Artificial intelligence (AI) is one of the technologies that is changing the world for the better. Although people talk about it in different places, a majority do not fully understand what this technology is all about and its impact on businesses and everyday life. It is also an area where organizations seek knowledgeable people to help drive their plans and goals. Here are answers to the top seven questions about AI that you may want to know as an enthusiast.

  1. What is artificial intelligence?

Artificial intelligence (AI) is a subfield of computer science whose emphasis is the creation of machines that are intelligent and works or react in a human-like manner. The machines created mimic human-like behaviour. They can behave, think and make decisions like humans. With AI, machines do not need human interventions to make decisions. Rather, they rely on algorithms to perform tasks on their own.  

  1. What are AI neural networks?

AI neural networks are algorithms that mimic the human nervous system in how the brain functions. These networks allow machines to think and learn like humans, just like the human brain operates. They are systems of neurons like that of humans but are artificial. In artificial intelligence, neural networks help machines learn through data and develop to become better.

  1. What is the difference between strong AI and Weak AI?

Strong Artificial intelligence is a type of AI that constructs mental abilities, functions and thought processes similar to the human brain. On the other hand, weak AI predicts features that resemble human intelligence and can be added to a computer to improve the tools. Unlike strong AI, which is broad, weak AI is limited to a narrow area. It simulates the cognition of humans. It has the benefit of automating time-consuming activities and analyzing data in a manner that humans cannot manage.

  1. What is the difference between classical and statistical AI?

While statistical AI deals with complex domains that involve various entities connected by unique relationships, classical AI is concerned with logic and language processing. Classical AI deals with deductive thought to deduce a conclusion, unlike statistical AI, which focuses on complex domains and relationships, as explained above.

  1. What is reinforcement learning?

Reinforcement learning is a machine learning subset where an agent interacts with its environment by producing action and learning through feedback. Feedback is given to the agent as a reward, which is always a positive reward for each good action and a negative one for a bad action. In reinforcement learning, the agent performs actions, changes state and receives feedback as it explores the environment.

  1. What are frames and scripts in AI?

Frames are a type of semantic network that allows the presentation of non-cultural knowledge in an AI system. It is an artificial data structure used to divide knowledge by representing stereotypical situations. On the other hand, scripts are similar to frames, the only difference being that the values filling slots need to be ordered. They are used in natural language to understand systems and to organize bases with regard to the situation that the system should understand.

  1. What is a Bayesian network, and how important is it in AI?

 Bayesian networks are models used to show the relationship existing between variables. It is a graphical model that contains edges where each of these edges represents a dependency. The network is probabilistic because they are established from a probability distribution. It uses probability theory to predict and detect an anomaly. The Bayesian network is important in AI because it can be used to answer probabilistic questions.

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Scott Koegler

Scott Koegler is Executive Editor for PMG360. He is a technology writer and editor with 20+ years experience delivering high value content to readers and publishers. 

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