While this is something of an exaggeration as the CPU does not think the way you do, there are some real similarities between it and the human brain.
While a supercomputer like the Sequoia can analyze problems and reach a solution faster than humans, it can't adapt and learn the way humans can. Our brains are capable of analyzing new and unfamiliar situations in a way that computers can't.
We can draw upon our past experiences and make inferences about the new situation. We can experiment with different approaches until we find the best way to move forward. Computers aren't capable of doing that -- you have to tell a computer what to do. Humans are also very good at recognizing patterns.
While we're making progress in machine pattern recognition, it's mostly on a superficial level. For example, some digital cameras can recognize specific faces and automatically tag photos of those people as you take pictures. But humans can recognize complex patterns and adapt to them -- computers still have trouble doing that.
Could computer scientists build a machine that simulates the way humans think? It's not as easy as it sounds.
The human brain is incredibly complex. We still don't have a full understanding of how the brain works. Without this understanding, it's challenging to create a meaningful simulation of the brain.
One of the features computers would need to be more intelligent than humans is the ability to draw conclusions from observations. In a study published incomputer engineers at Cornell University designed a program that could do this on a limited scale. The program gave the computer a basic set of tools it could use to observe and analyze the movements of a pendulum.
Using this foundation, the software was able to extrapolate basic laws of physics from the pendulum's motions. It took about a day for the computer to arrive at the same conclusions it took humans thousands of years to grasp [source: While the Cornell project was a remarkable achievement in computer engineering, we're still years away from computers that can make conclusions from general observations.
The Cornell software gave the computer the tools it needed to draw conclusions -- the computer was unable to create or refine these tools for itself. As long as computers rely on sets of pre-installed instructions to perform tasks, they can't be said to be more intelligent than humans.
Even IBM's Watson can only respond to input -- it can't spontaneously pull up information or think in the way we humans do. Only when computers can adapt and perform tasks outside their initial programming will they be truly intelligent.A Comparison of Human and Computer Information Processing phones, the Internet, e-mail, chat, bulletin boards, etc.) all use computers to support rather than supplan t human.
Mar 02, · Computers are extremely fast, so when a task can be translated (by a human!) into an algorithm (a set of step-by-step instructions), a computer will typically accomplish it . The Human Brain versus Computers In the past few decades we have seen how computers are becoming more and more advance, challenging the abilities of the human brain.
By contrast to computers, the richness of human faculties is accomplished by activating huge numbers of neural connections and structures in a highly organized manner. Unlike in a digital computer, the signals do not need to be coded in a central location, the microprocessor.
Two of the examples were the human’s ability to make decisions and algorithms. While for the most part I agree with your stance on humans being more emotional and thoughtful than computers, I feel the brain-computer comparison is effective.
First, I agree that without humans there would be no computers. The human mind has those restrictions, the human brain seems to and no counter-example has ever been found.
From this, we can conclude the human brain is Turing Complete and therefore a computer. The obvious next step is to ask how the brain compares with regular computers.