The distinction between human and machine intelligence


Welcome to Neural’s Beginner’s Guide to AI. This multi-part feature is designed to give you a basic understanding of what AI is, what it can do, and how it works. The guide contains articles on neural networks (published in order), Computer vision, Natural language processing, Algorithms, Artificial General Intelligence, and the Difference Between Video Game AI and Real AI.

According to legend, a reporter once asked Mahatma Ghandi what he thought of Western civilization. His answer was “I think it would be a good idea.”

The same feeling could be applied to artificial intelligence if you compare it directly to human intelligence. That said, the world’s most advanced AI systems (DeepMinds, GPT-3, etc.) pale in comparison to a human child’s intellect: artificial intelligence would be a good idea.

Fortunately for everyone in the industry, the rubrics we use to measure machine intelligence are completely different from those we apply to ourselves. It can be difficult to figure out what “AI” or even “intelligence” means from one source of information to another.

But the reality is not that complex. People experience reality through a theater of the mind. We naturally define our existence by the time, place, and sensations that we observe. It’s a fancy way of saying we have ideas.

We experience time as a user interface for memory, place is defined by where we think we are related to things outside of our observation (which we suspect still exist), and sensation is just one of the many languages ​​our brains speak. Our experience of reality, our foundation for intelligence, is like a movie that lasts as long as we live.

Computers experience intelligence as an exponentially developed sequence of ones and zeros. We can reverse engineer any current AI system (because we are the original engineers of all AI systems) and ultimately drill down on ones and zeros. (Cannot withstand quantum algorithms).

And while we still have not solved all the mysteries of the human brain, it is safe to say that we are not binary thinkers.

That’s the simple explanation. But it doesn’t teach much about what AI can and can’t do. Because, binary or not, it doesn’t seem too far-fetched to imagine that humanity might be a eureka or two away from inventing a sentient machine that does is able to imagine things and form a theater of the mind of its own.

To be very clear: no current AI system known to us can think or imagine. This theoretical idea for an artificial stream of consciousness is the closest we can find.

AI can’t do much right now. But what it can do it does very well. Deep learning – computer vision, natural language processing, and similar disciplines – is characterized by everyday tasks that would take humans too long to complete.

There was no way you or I could search 75 million images to see which ones looked like cats. Despite the fact that we would perform the task with far greater accuracy than any other algorithm, we wouldn’t live long enough to finish the job. An AI could do it in seconds.

So when you hear something like “AI can diagnose cancer with 97% accuracy,” the reality is this: You taught an AI to look at the pixels in a photo and tell us where Waldo is. And “Waldo” is exactly what oncologists look for in pictures when looking for signs of cancer.

But deep learning isn’t the only form of AI that exists. Thousands of researchers are developing new classes of algorithms, advanced neural networks, and hybrid learning technologies to better mimic the human brain.

In the meantime, human intelligence and machine intelligence just aren’t comparable. Anyway, meIn the future, technologies such as quantum AI, hybrid approaches with symbolic AI or new class calculations could make a major contribution to closing this gap.

Published December 11, 2020 – 20:00 UTC

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