At the start of the school week, we returned to the University of Nicosia for some lectures on blockchain, data science, and forecasting along with pharmaceutical demonstrations. I was most excited about this day because UNIC is one of the leading schools for blockchain technology.

We were lucky enough to hear from Mr. Antonis Polemitis, the CEO of UNIC, about a lecture on blockchain technology. Prior to the trip, I came in with a solid foundation of understanding of the topic. I have a few crypto assets and did research about blockchain technology in the supply chain. In his lecture, I was first shocked by his manner. One of the first things he said to us was to confirm that he was teaching blockchain technology. Along with the confirmation, he had no slides prepared and it seemed he was improvising. Honestly, he was narcissistic. Nonetheless, his lecture was one of my favorites of the trip. 

In speaking about blockchain, I thought he did an amazing job of describing the difference and the impact of entities that are centralized versus decentralized. He used examples such as Twitter, that have to make impossible decisions about censorship, and explained the impact of censorship if Twitter was decentralized. Only after outlining the issue of censorship with one person at a third-party server having final control over what is posted, he began to talk about blockchain technology in the supply chain.

Adding to his narcissistic nature, he frequently referenced the crypto “business model”, saying that almost all are wrong. This attitude was not just an opinion, but a matter of correct or incorrect. As he spoke about the crypto market and blockchain technology, he continued to make it clear that almost all people are using it and planning it wrong. This was surprising to me because he never explained or outlined what parts of these models were wrong. Instead, he used obscure examples such as the development of the internet to compare it to blockchain and crypto technology. The internet example was specifically interesting; he described the world to be for the development of the internet with little regulation. He continued to say that the technology today has more negative buzz and is more regulated but it would still develop similarly to the internet. He contradicted himself multiple times but ultimately had an engaging presentation from which I learned much. All in all, his analysis boiled down to a question of if there are multiple parties involved in the process, and if so, it should most likely be decentralized.  

Our next two lectures were forecasting in supply chain and data science with respect to supply chain analysis. Both presentations were very informative. I learned that forecasting with human judgment can be inaccurate because of innate human bias. Machine learning proves to be much more accurate. Machine learning is also extremely helpful when it comes to data science. In the supply chain, machine learning is a valuable tool to predict a more accurate demand model and therefore extract more accurate and better conclusions.