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What Are The Main Differences Between Strong and Weak AI?
From the song we instruct Amazon’s Alexa to play when we wake up in the morning to the chatbots, we converse with frequently- our modern lives are wholly immersed in machines that learn for us, think for us, and help us make better decisions.
Regardless of the deep-rooted impact that AI and Machine Learning have had on the life, the primary goal that Artificial Intelligence seeks out to fulfill is this: to create a machine powerful and smart enough to handle any level of cognitive difficulty, in a variety of different settings- quite similar to how human brains function.
Just like a human brain works, it’s hard to tell how a strong AI would respond to specific keywords- only that it’d make an independent decision based on how it evaluates and reacts to the data provided to it.
With the ‘basic’ definitions out of the way, we must analyze how these definitions hold up in the current age of technology, particularly when we take into account the burgeoning influence that AI has had on modern-day cybersecurity solutions.
As we’ve mentioned above, the conventional definition of strong AI states that the term refers to a form of artificial intelligence that is meant to replicate human intelligence, or cognitive functions- which refers to the ability to think and decide.
The ability to analyze and come up with solutions for intelligent components can be broken down into the following parts: In addition to the components mentioned, some back-hand aspects of a strong, or general AI include the abilities to solve complex puzzles, reason, along with the capacity to display intelligence and common sense.
With that said, several specialists, and researchers tend to disagree with the somewhat ‘limiting’ definition of Strong AI, stating their doubts in classifying Strong AI as intelligent, simply because it can mimic the cognitive abilities of the human brain, such as the ability to communicate.
The dilemma surrounding the age-old question of what classifies as intelligence only gets more challenging to answer when you take into account the Chinese Room test, which aims to check whether a machine understands Chinese, or simulates the ability to understand Chinese.
Jay Richards at COSM Talks Kurzweil and Strong AI
On this episode of ID the Future, Andrew McDiarmid catches up with philosopher Jay Richards at the recent COSM conference in greater Seattle.
Then he argues the other side, namely that human beings possess something beyond the purely material, something even the most powerful computers will never possess.
Rethinking Weak Vs. Strong AI
Artificial intelligence has a broad range of ways in which it can be applied - from chatbots to predictive analytics, from recognition systems to autonomous vehicles, and many other patterns.
The general AI ecosystem classifies these AI efforts into two major buckets: weak (narrow) AI that is focused on one particular problem or task domain, and strong (general) AI that focuses on building intelligence that can handle any task or problem in any domain.
From the perspectives of researchers, the more an AI system approaches the abilities of a human, with all the intelligence, emotion, and broad applicability of knowledge of humans, the “stronger” that AI is.
Additionally, there are ancillary aspects that come with these main requirements, such as the ability to reason, solve puzzles, represent knowledge and common sense, and the ability to plan.
Some have argued that the above definition for strong AI is not enough to be classified as truly intelligent because just being able to perform tasks and communicate like a human is not really strong AI.
Searle believes that there is no difference between the roles of the computer and the person in the experiment because each follow a program with step by step instructions and produce a behavior that is deemed intelligent.
However weak AI isn’t a particularly useful term, because weak implies that these AI systems aren’t powerful or able to perform useful tasks which isn’t the case.
The meaning will change over time and continues to evolve, and doesn’t even really give us any measurable specificity as to how intelligence a system is since there is a disagreement as to how strong a system should be.
After all, if narrow and general AI are just relative terms, it may be better to define the intelligence of systems in terms of a spectrum of maturity of how intelligent it is against the sort of tasks or range of tasks to be done.
Given the ambiguity of the above terms we should rather look at the capabilities of what these AI systems can do and map them across the spectrum while keeping in mind the ever pushing boundaries of AI technologies.
- On 28. januar 2021
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