Today we visited the University of Nicosia again for a couple of lectures from their professors. The university is ranked the highest for blockchain research we got to talk to the CEO of the of the university Mr. Polemitis. Mr. Polemitis is also the key coordinator of the blockchain and cryptocurrency program. He gave us a lecture on each of these departments.  These were both very interesting dissections for me because I knew very little about both of these topics. What I learned is that there are two types of information databases the first is centralized and the second is decentralized. Your centralized databases include Google, Twitter, grade books for schools, and libraries. What all of these databases have in common is the fact they have one person who can decide what can or cannot be published. However decentralized database there is not a singular person in charge and the information is available to everybody who has the code.

Moving on to cryptocurrencies the definition of this is a virtual currency that people can transfer money immediately without any counties exchange rates. However, the amount each currency costs can fluctuate with the market just as the exchange rate between each country can fluctuate. One of the benefits of cryptocurrencies is that the money can be transferred immediately. Also, the transfers cannot be canceled once sent and they are very easily trackable.

After our lectures about blockchain and crypto, we discussed machine learning and how you can teach a machine to take in data and make a decision on what to do. An important fact to know about machine learning is it is not memorization so there are going to be some errors. The general goal of machine learning is not to have everyone be an expert in it. The goal is to have some companies be very good at the synthesis of data and forecasting. Other companies are able to use the companies that are good with machine learning to forecast data for their company. Then the experts in a business can make decisions on how their company can operate based on minimal bias forecasting derived from machine learning.