His trilemma (as described on page one) brings logic and abstract proof to the proposition that us living in a simulation is likely true. Brian Weatherson, another philosophy doctorate, argues Bostrom’s proposition in a lengthy response (“Are You a Sim?”). Starting off Weatherson says that even if we were simulated, and simulations could produce more simulations, if selected at random, any one’s reality has more than an infinitesimal chance of being base reality, as the number of simulations only approaches infinity as linear time encroaches eternity—which Weatherson argues we won’t be simulated for that
He doesn’t focus on explaining why we do it this way, he automatically assumes that humans understand this concept. However, he cannot prove that his theories of associations are accurate. He tries to explain that this is how our mind works. When it comes to other types of association of ideas, I think of constant conjunction where something repetitive will happen. An example of this could be the law of gravity since most of the times objects fall to the floor by the effect of this law.
The common objection states the Newtonian physics is not incorrect, rather it is simply a special case of the Einstein’s newer theory. Under certain constraints, Newton’s equations can still accurately predict experimental results. Kuhn’s opponents would say this invalidates paradigm shift, since a theory cannot reject one of its special cases. They would go further to say that the two models only disagreed in the first place because of scientific malpractice by Newtonians. Newtonians overextended their theory by claiming that it was precise at high velocities, despite not having evidence for the claim.
In fact, the value of the constant is so precise, that if changed at all, conditions would not be suitable for life on Earth. Second, Susskind describes how our universe contains a constant that was needed to create the universe. This cosmological constant, or sort of "dark energy," is the major determining factor on whether or not the Earth will survive or end. Since fine tuning is unlikely to occur by the product of chance, we must explore other options. The only possible explanation for this constant being such a necessity is due of the chance of a multiverse.
Quantum entanglement is a scientific phenomenon that is changing how scientists view well-known existing physical laws. Although the interactions of entangled particles are mysterious, they could turn out to be the key to secure communications. Though it may be disappointing that we cannot travel faster than light using entanglement at the moment, physicists are discovering more and more new, strange physical laws and it is still possible that Einstein’s theory of relativity is ultimately wrong. So, who knows? Maybe we will be able to travel superluminally one day or even have our very own personal Dokodemo
Laibson and Gabaix (2008) found out that many successful economic models have several of the seven properties they define. The seven properties are: 1. Parsimony A parsimonious model is a simple model which rely on several specific assumptions which provides little degree of freedom to the researchers. The purpose of this characteristics is to prevent the researchers to manipulate the model so that it would work well in the situation. If such manipulation occurs, there will be over-fitting model which cannot work in out-of-sample condition.
What if getting two things done at once was a bad thing? Although completely unbelievable at first, multitasking is indeed unhealthy and doesn’t allow one’s self to accomplish more. When multitaskers spend time on multiple things and not just one, they allocate time to multiple things instead of focusing on one. The end result is producing several average things in comparison to one great thing. This is exactly what S. Craig Watkins, author of “Fast Entertainment and Multitasking in an Always-On World”, discusses when he outlines why multitasking is hurtful.
Complexity Thinking Complexity theory is, as the name implies, a way of understanding complex systems; it is difficult to understand. Complexity theory has evolved from studies in physics, mathematics, computer sciences, and biology, and is related to (and includes aspects of) chaos theory. A descriptive way in which we can conceptualise complexity theory is provided by Kevin Kelly, author of New Rules for the New Economy, who says complexity is, “to think like nature.” Another description he uses is, “You can’t make a plant grow.” (You can, however, provide the necessary ingredients for optimal growth, but, even then, it may not thrive, for who knows what the weather, or other random events, will be?). Complex systems are non-linear – they do not follow a simple, additive “straight line” form of change. Elements within complex systems interact with each other in a variety of non-linear ways – a single change in one element may result in several changes elsewhere in the system, and multiple changes in other elements may result in only a single change in a crucial aspect of the system, for example – and frequently involve feedback mechanisms – change in one element impacts another element, which in turn (through
Physicists theorize that reverse time travel could be impossible, but think that it could be very possible to travel forward. The reason that reverse time travel would be challenging is because scientists would have to find something traveling faster than the speed of light. Some theories say things like wormholes could throw you into the future, or possibly the past, but technology isn 't developed enough to truly
Chaos theory isn't something to be exploited for application. It doesn't represent some mathematical or scientific discovery that can be used in novel ways. Instead, it represents a set of techniques for analyzing dynamical systems that are deterministic (i.e., they follow apparently simple rules that lead to behaviors which depend only upon their initial conditions) and yet very sensitive to perturbations of input. Consequently, advances in understanding certain classes of these systems lead to advances in either understanding the physical world or designing technology that interfaces with such