Artificial Intelligence

Artificial intelligence that uses limited memory occurs when a model is continually trained to analyze and utilize new data or when an AI environment is created to train and retrain models automatically.

How Does Artificial Intelligence Work?

Towards and Concepts of Artificial Intelligence

The mathematician Alan Turing changed history a second time with his simple question: “Can machines think?” less than a decade after breaking the Nazi encryption machine Enigma and helping the Allied forces win World War II. 

Previously, Turing’s “Computing Machine and Intelligence” (1950) and its associated Turing Test had established artificial intelligence as its fundamental goal.   

At its heart, artificial intelligence addresses Turing’s question positively. Machine learning is the attempt to replicate or simulate human intelligence.

Various questions and debates have arisen from artificial intelligence’s expansive goal. It is so vast that there is not a single universally accepted definition for the field.  

Artificial Intelligence: The Four Types

Reactive machines

Based on the most basic AI principles, a reactive machine can only interpret and react to what is in front of it, as its name implies. In such a machine, past experiences cannot be accessed in real-time, so the past cannot inform decision-making.

Since reactive machines perceive the world directly, they can only carry out a limited set of specialized tasks. Intentionally narrowing a reactive machine’s view of the world is not a cost-saving measure. Still, instead, a way to make this kind of artificial intelligence more trustworthy and reliable will always react the same reactive machine say to the same stimuli. 

Reactive machine artificial intelligence offers reliability when designed to accomplish repeatable tasks, despite restrictions in scope and the inability to change the system.

Memory limitation

When gathering information and weighing potential decisions, artificial intelligence with limited memory can keep previous data and predictions in mind to track what may happen. Compared to reactive machines, artificial intelligence with few memories is much more complex.

Little memory AI in machine learning involves six steps: creating training data, creating a machine learning model, making predictions, having the model receive human or environmental feedback, storing that feedback, and then repeating these steps.

Theories of Mind

Theories of Mind are merely theoretical. Artificial intelligence has not yet reached the next level of technological and scientific capability. 

Psychologist understands that one’s behavior can be influenced by the thoughts and emotions of other living things. It would mean that AI machines could comprehend how humans, animals, and other machines feel, make decisions through reflection and determination, and then use that information to make their own decisions. Ideally, devices would be able to comprehend and process the concept of “mind,” the fluctuation of emotions in decision-making, and a plethora of other psychological ideas in real-time, creating a two-way relationship between humans and machines.

 Awareness of oneself

After it can establish a Theory of Mind, self-aware AI will be the final step sometime in the future. A system with this type of artificial intelligence has a human-level consciousness and understands its existence in the world and the presence of others and their emotional states. Based on what they convey to them and how they convey it, it would understand what others may need. 

Reactive machines are essential for human researchers to learn to replicate consciousness through simulations to build self-aware robots.

Also Read:

LEAVE A REPLY

Please enter your comment!
Please enter your name here