Ziya
@TryingToUnderstand
What if not?
nullius in verba/memento mori/omnes una manet nox/sub specie aeternitatis
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yaşamak
CE, GTU
soluk mavi nokta
Eskişehir, 18 Nisan
9 kütüphaneci puanı
511 okur puanı
Haziran 2021 tarihinde katıldı
It’s not correct to say that the moon orbits the earth; rather, both the earth and the moon move in orbits around their common center of mass.
neden kemerinizi yukarı çekerek havalanamazsınız? çünkü:Fizik
When a body or a collection of particles is acted on by external forces, the center of mass moves as though all the mass were concentrated at that point and it were acted on by a net force equal to the sum of the external forces on the system.
This result is central to the whole subject of mechanics. In fact, we’ve been using this result all along; without it, we would not be able to represent an extended body as a point particle when we apply Newton’s laws. It explains why only external forces can affect the motion of an extended body. If you pull upward on your belt, your belt exerts an equal downward force on your hands; these are internal forces that cancel and have no effect on the overall motion of your body.
Generally speaking, artificial intelligence differs from artificial neural nets in the level of human intervention it requires. With an AI algorithm, all the information needed for a solution must be preprogrammed into a database, whereas artificial neural nets learn on their own. AI is based on the principles of deductive reasoning, whereas neural nets are inductive. This means that with Al, each new situation the system encounters may require another programmed rule. For example, when AI is used to program the behavior of a robot, all the desired behavior patterns must be worked out and programmed a priori-the robot can't adapt its behavior to changes in the environment. Consequently, AI programs can become quite large and unweildy in their attempt to address a wide range of different situations.
Artificial neural nets, on the other hand, automatically associations or relationships between parts of the network according to the results of known situations, adjusting to each new situation and eventually generalizing their behavior by correctly guessing the output for inputs never seen before. The disadvantage of artificial neural nets, however, is that they cannot be programmed to do a specific task, like adding numbers. The sets of examples or "training sets" of data the network must be fed in order to bring it closer to the desired solution must be chosen very carefully; otherwise, valuable time is wasted-or worse, the network doesn't do what it is supposed to do.
