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  • Peter McAllister

Background: What is AI?


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Artificial Intelligence is a branch of computer science that endeavours to replicate or simulate human intelligence in a machine, so machines can perform tasks that typically require human intelligence.


Artificial intelligence systems are powered by algorithms, using techniques such as machine learning, deep learning and rules. Machine learning algorithms feed computer data to AI systems, using statistical techniques to enable AI systems to learn. Through machine learning, AI systems get progressively better at tasks, without having to be specifically programmed to do so.


There are 3 types of artificial intelligence (AI): narrow or weak AI, general or strong AI, and artificial superintelligence.


Artificial Narrow Intelligence (ANI)


Artificial narrow intelligence (ANI), or weak/narrow AI, is the only type of artificial intelligence we have successfully made to date. It is goal-oriented, designed to perform singular tasks - i.e. facial recognition, or speech recognition - and is very intelligent at completing the specific task it is programmed to do.


While these machines may seem intelligent, they operate under a narrow set of constraints and limitations( hence weak). Narrow AI doesn’t mimic or replicate human intelligence, it merely simulates human behaviour based on inputs and a narrow range of parameters and contexts. This simulation of human behaviour has lead to the issue unconscious bias in weak AI – where an unwanted behaviour has been reproduced in the computer.


A couple of examples: Siri, the google search algorithm, facial recognition tools, and spam filters.


Artificial General Intelligence (AGI)


Artificial general intelligence (AGI), is the concept of a machine that mimics human intelligence, with the ability to learn and apply its intelligence to solve any problem. AGI can think, understand, and act in a way that is indistinguishable from that of a human in any given situation.


AI researchers and scientists have not yet achieved strong AI.


Strong AI uses a theory of mind AI framework, which refers to the ability to discern needs, emotions, beliefs and thought processes of other intelligent entitles. Theory of mind level AI is not about replication or simulation, it’s about training machines to truly understand humans.


We don’t truly understand human being ourselves – we don’t know what consciousness is, how it works, where it lives – so that makes it that much harder.


And we have such a wide range of functioning humans – meek and mild to full blown psychopaths and everything in between. Our society works with a mixture so what do you put into 1?


Fujitsu-built K, one of the fastest supercomputers, is one of the most notable attempts at achieving strong AI, but considering it took 40 minutes to simulate a single second of neural activity, it is difficult to determine whether or not strong AI will be achieved in our foreseeable future.


But for contaxt, the first airplane flight at Kitty Hawk in 1903 was only for 12 seconds, and we made it to the moon in 1969 – so we have history in successfully solving the scale issue.

So I think this one is well on the way to reality..


Artificial Superintelligence (ASI)


Artificial super intelligence (ASI), is the hypothetical AI where machines become self-aware and surpass the intellectual capacity of human.


ASI would theoretically be better at everything we do. ASI would have a greater memory and a faster ability to process and analyse data and stimuli. Consequently, the decision-making and problem solving capabilities of super intelligent beings would be far superior than those of human beings.


Could that be the next apex species on the planet?


Credit - Adapted from a Codebots article

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