Machines have already received superhuman strength, speed and endurance – and one day they will have superhuman intelligence. The only reason that this can not happen – it’s when we first kill themselves by some ultra-hazardous technology, well, or become victims of some global catastrophe. If we assume that technological progress will continue, machine intelligence human level, is likely to be developed. Then comes the turn of superintelligence.

To predict how long it would take to develop such a machine, it is extremely difficult. In this regard, there is no black and white answers, they say, “machines are stupid and will never become human beings” and “machines will be smarter than we are very soon, out – artificial intelligence is born and ready to kill.”

Poll of the leading researchers of artificial intelligence suggests that there is a 50 percent probability that machine intelligence will reach the level in 2050 (meant is the one that is able to perform most of the actions of the common man and will replace most of the human workers). This opinion does not seem absolutely insane. But there are a lot of uncertainties on both sides of the issue: whether it will happen soon, or much later.

Similarly, the question shrouded in mystery, as we get to this point. There are several ways to develop that will help us get there in the end, but we do not know which one to shoot first.

We have a concrete example of the intellectual system – the human brain – and one obvious idea is to figure out how it works. From a complete understanding of the brain we are still very far away, but it may happen that we derive a number of basic computing principles, which uses the brain, and programmers will be able to adapt them to the computers unnecessarily study biological nuances .

We already know a few things about how the human brain works: a neural network, it learns through repetition, it has a hierarchical structure, it is based on perception, and so on. Perhaps there are a few basic principles that we have to open, and all this will develop into a “neuromorphic AI”: the basic principles of biological will, but they will be wrapped certainly not in biology.

Another way – a more mathematical approach of “top-down”, which is a little that borrows from biology, and just trying to get to work basic principles. This is a more desirable way of development than neuromorphic artificial intelligence, because programmers will be well understand what is happening at a deep level. Compare it possible that take exams on their own better than to write off a classmate or a classmate.

In short, we need the developers of artificial intelligence that will grow it from seed to the size of superintelligence who understand what they do. Parallel to this, we could check mathematical theorems about the system and how it behaves, rising through the ranks of intelligence.

One can also imagine a way which will no longer rely on brute force computation, for example, by the use of genetic algorithms. This development would be undesirable for the same reason as the neuromorphic AI because it can lead to success and without a full understanding of what it was made. The presence of a large array of hardware to a certain extent could replace deep mathematical understanding.

We are already familiar with the code, which would have a sufficient number of processing power become sverhintellektualnym agent. Model AIXI, for example. At best, it will destroy the world. Fortunately, the necessary amounts of computing power is physically impossible.

Path of the complete emulation of the brain will logically lead to a complete digital copy of the specific human mind. The idea is to freeze or vitrified brain, cut it into thin slices and slices to feed these microscopes. Automated image recognition system and then re-create the original map of the neural connections of the brain. Three-dimensional map will be combined with neyrovychislitelnoy model functionality of different types of neurons, and the whole structure of the computer will operate at a sufficiently capacious supercomputer. This approach looks very complicated, but guarantees certain theoretical breakthroughs.

In principle, we can assume that there is enough quality to emulate the digital brain, retaining all the beliefs, desires and personality of the individual loaded. But before the technology will reach a level of perfection, emulation will be extremely rude. And before emulating the brain will lead to some success, but rather result in neuromorphic AI.

Perhaps the most attractive way to machine superintelligence will be indirect, during which we have been well studied own biological structure. This can be achieved by, for example, genetic engineering and institutional innovations that improve our collective intelligence.

Can not say that one way or another it will “keep up with the machines” – the finite limits of information processing in the brains of the machine is much higher than that of the biological brain. But the cognitive development of humanity is closely linked with the development of machines: it brings the day when machines surpass us in development, because smart people contribute to progress in the field of computer science.


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