What is the difference between Strong AI and Weak AI?


The word "Artificial Intelligence" is sometimes misinterpreted, yet the technology is more beneficial than harmful. Although past developments in the field of AI may no longer be relevant, the method has evolved significantly over time. Despite the fact that AI is one of the newest branches of intellectual inquiry its roots may be traced back thousands of years.

Strong AI is a speculative form of machine intelligence that argues that machines can develop human consciousness on par with humans. Strong AI refers to computers or programs that have their own mind and can think and complete complicated tasks without the need for human intervention. Strong AI uses complicated algorithms to assist systems operate in a variety of scenarios and strong AI-powered robots can make judgments without the need for human intervention.

Artificial intelligence with restricted capability is known as weak AI or narrow AI. Weak AI is the application of advanced algorithms to specific problem-solving or reasoning activities that do not require the entire spectrum of human cognitive powers. Voice-based personal assistants like Siri and Alexa could be called weak AI systems because they work within a limited pre-defined set of functions, implying that their responses are often pre-programmed.


WEAK AI   vs  STRONG AI
Comparison chart

WEAK AI

STRONG AI

The belief that intelligent behavior may be described and exploited by computers to solve complex issues is known as weak AI.

A hypothetical machine with strong AI capabilities is referred to as a strong AI machine.

Weak AI refers to systems that are programmed to solve a wide variety of issues yet only perform a limited set of tasks.

Strong AI refers to machines that have their own minds and can think and complete complex tasks independently.

Weak AI-powered machines are incapable of thinking for themselves.

Human-like cognitive abilities can be demonstrated by AI-powered devices.

Alexa and Siri are the best instances of AI programs that aren't very good.

Strong AI is a hypothetical idea that has yet to be realised in its entirety.




 

Comments

Post a Comment

Popular posts from this blog

EXPLAIN HOW DEEP LEARNING WORKS?

Image
  Deep learning networks gain knowledge by identifying complex patterns in the data they process. The networks can develop several degrees of abstraction to describe the data by constructing computational models that are made up of many processing layers. For instance, a convolutional neural network, a type of deep learning model, can be trained using a lot (like, millions) of photos, such as ones with cats. This kind of neural network often picks up information from the pixels in the photographs it collects. It has the ability to categorise sets of pixels that are typical of cat traits, with sets like claws, ears, and eyes indicating the presence of a cat in a picture. The fundamental building block of the brain is a brain cell, often known as a neuron. An artificial neuron or perceptron was created after being inspired by a neuron. Dendrites are employed by biological neurons to receive inputs. A perceptron operates similarly, taking in a variety of inputs, applying a variety of tr
Read more

WHY IS DATA SCIENCE IMPORTANT?

Image
In general, data science can be defined as the process of extracting information and insights from data. It is a combination of several tools, algorithms and machine learning techniques that uncover hidden patterns in raw data. With the introduction of Artificial Intelligence and Deep Learning, the notions of Data Science have reached a pinnacle in recent years. The basic cornerstone of Data Science is the ability to extract significant insights from unstructured and raw data. We will present you with in-depth knowledge about Data Science and its importance in this blog. Because data science can help transform raw data into actionable insights, it has become a must-have for businesses. A Data Scientist is an expert in the fields of statistics and computer science and he employs his analytical skills to address a variety of business challenges. Role of Data Scientist Each firm uses data in a unique way, and the way data is used also differs from one organization to the next.
Read more