Present day AI can detect cancers better than human doctors, build better AI algorithms than human developers, and beat the world champions at games like chess and Go. Instances like these may lead us to believe that perhaps, there’s not a whole lot that artificial intelligence can not do better than humans.
The internet abounds with stories of stunning applications that exist today, culminating from years of artificial intelligence research. With such developments, the gap between human intelligence and artificial intelligence seems to be diminishing at a rapid rate. This might give you the impression that powerful artificial intelligence systems or artificial general intelligence systems may not be too far out in the future. However, it is vital to understand that it takes more than just performing specific tasks better than humans to qualify as artificial general intelligence.
Our definition of AGI is the ability of a machine to perform any task that a human can.
While an AI has to be trained in any function it needs to perform with massive volumes of training data, humans can learn with significantly fewer learning experiences. Although it might be theoretically possible to replicate the functioning of a human brain, it is not practicable as of now. Thus, capability-wise, we are leaps and bounds away from achieving artificial general intelligence.
AGI is Inevitable
Human intelligence is fixed unless we somehow merge our cognitive capabilities with machines. Elon Musk’s Neuralink aims to do this but research is in the early stages.
Machine intelligence depends on algorithms, processing power, and memory. Processing power and memory have been growing at an exponential rate. As for algorithms, until now we have been good at supplying machines with the necessary algorithms to use their processing power and memory effectively.
Considering that our intelligence is fixed and machine intelligence is growing, it is only a matter of time before machines surpass us unless there’s some hard limit to their intelligence. We haven’t encountered such a limit yet.
This is a good analogy for understanding exponential growth. While machines can seem dumb right now, they can grow quite smart, quite soon.
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