A few days ago I read that Constantinos Daskalakis got the Rolf Nevanlinna Prize for For transforming our understanding of the computational complexity of fundamental problems in markets, auctions, equilibria, and other economic structures. His work provides both efficient algorithms and limits on what can be performed efficiently in these domains. Thus, according to this, we now can somehow compute economies. However, even economists have started to realize that economies cannot be described with mathematics only. In fact, Why economists need to expand their knowledge to include the humanities is a recent article that discusses exactly this problem. Daskalakis's approach is based on the assumption that humans are Turing machines. Unfortunately, they are not and this is the reason why economists fail so miserably in their predictions. Furthermore, there are some other things that people who work in computational economics "fail" to realize. For example, ev
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Recently I read an article that presented a novel idea by Nicolas Gisin . In a nutshell, Gisin says that only a certain number of digits of real numbers have physical meaning. After some number of digits, for example, the thousandth digit, or maybe even the billionth digit, their values are essentially random. This is very interesting because it means that there are no noncomputable numbers. Provided this idea is correct, we can easily decide if for example there are three 4s in the decimal expansion of π! The real problem of course is to agree on the number of significant digits. Once this problem is settled, then we can answer any question about physical real numbers. Another consequence of this idea would be that real numbers might be directly representable in even present computer hardware. What is left is to examine deeply this idea and see if it is actually valid.