What is Machine Learning?

    Machine learning is a term that is often thrown around in the modern day of technology. But what does it actually mean? How does machine learning relate to data? And how does it benefit all of our lives?

    Machine learning put simply, is the analysis of data to achieve a result. We are now in the modern era where data is abundant. That is where machine learning comes into play. It allows us to gain new insights from data that we might not have picked up without machine learning. There is naturally a lot of information in today's world, due to the ability we have to store it digitally. A supermarket stores information on its customer's purchases, a bank stores the history of its transactions, and a school stores the performance of its students.

    This abundance of data can be analyzed by machine learning algorithms to create valuable and useful insights. For example, the data from the supermarket store can be analyzed to determine which customers will buy which products, and therefore allow for more efficient advertising. How does the computer analyze the data you might ask? There are many ways the computer can analyze the data in the form of machine learning algorithms. Some algorithms are better suited for certain tasks than others. Some require more time to run while others are more efficient. In the example of a supermarket store, an algorithm commonly used is called Basket Analysis. In basket analysis, we calculate the probability that an event will happen given another event has happened based on past data. Lets say past data shows that 70% of people who buy chips also buy beer. A new customer named Mark buys a bag of chips, then it can be concluded that Mark has a 70% likelihood that he will buy a beer. The supermarket can now recommend a beer to Mark and will be likely to sell it. Of course, this concept is implemented in a computer to be autonomously done.

    Other applications of machine learning include the diagnosis of diseases. Machine learning can help doctors identify diseases much quicker through analysis of past patient's data. Self-driving cars use reinforcement learning to learn how to drive and adapt to their situations. Weather forecasts use past information on the weather to predict what the weather might look like in the future.

    As I mentioned earlier, there are different kinds of machine learning algorithms. They can be classified into three main categories: supervised learning, unsupervised learning, and reinforcement learning. Supervised learning has a supervisor, aka the programmer, who tells the algorithm what is right and what is wrong. Unsupervised learning algorithms only have the data to work with and they find regularities or irregularities within the data. Reinforcement learning is similar to unsupervised learning in that it does not need a supervisor. However, it differs because a reinforcement learning algorithm learns from a sequence of actions, like a chess bot.

    In conclusion, there is a lot of data now and machine learning takes advantage of that fact. It can be used to benefit businesses, medicine, and other sciences. Machine learning is used globally and has improved our quality of life and will likely continue to do so in the foreseeable future.

Analysis of "Cogito, ergo sum"

        "Cogito, ergo sum" translates to, "I think, therefore I am". It is a quote from Descartes' book titled Meditations. After doubting everything's existence, he realised that the only thing he can be sure exists is himself. Because, he is doubting whether he exists or not, and one cannot doubt without existing. How did Descartes get to this conclusion? Is the conclusion valid? Do thoughts prove the existence of an "I"?

    Firstly, let us take a closer look at what "I think, therefore I am." means. Descartes put forward an idea of the possibility of an "Evil Demon". A being that feeds him with all his thoughts and actions, giving the illusion of free will. This possibility frightened Descartes because it could be that nothing truly exists. He eventually came up with the following argument: There exists a doubt, and doubt cannot exist without the existence of a doubter, therefore I exist. Hence, I think. therefore I am. Descartes had proven his own existence within a sea of doubt.

    But did Descartes truly prove his existence? Another philosopher named Lichtenberg argued as such, we can say "it thinks" just as we say "it thunders". There does not have to be a "thinker", just as there does not have to be a "thunderer". But is this true? Can thoughts and doubts simply exist in a box without being used by someone? Even thunder has a "user", lightning. The thinker can act as the lightning for thoughts and doubts as it does with thunder.

    However, there is another problem within Descartes' argument which is the existence of doubt. Considering we are working within Descartes' framework, there exists a possibility of an "Evil Demon" feeding Descartes with all his thoughts and actions including his doubts. How can Descartes throw out the possibility of the demon simply creating the illusion of the existence of a doubter? Descartes solved this through his finding of God. He argued as such: There exists the idea of a perfect being in his mind, since the idea exists in his mind, it has to be given by something as perfect or more perfect than the idea itself, God is the only perfect being, therefore God exists. There are counterarguments to this. For example, does a perfect idea require a source that is as perfect? I can say that I have an idea of a person who is always right in my mind, but that doesn't mean that a person who is always right puts that idea in my head. The existence of the idea did not come from something with qualities of the idea. Without the usage of God, it seems "Cogito, ergo sum" cannot truly rule out the possibility of an "Evil Demon".

    In conclusion, "Cogito, ergo sum" is an attempt at proving the existence of oneself within a sea of doubt. In reality, it actually only proves that we cannot doubt our own existence, it doesn't actually prove we exist. However, I believe it is still valuable, because it doesn't matter whether we exist or not as long as we cannot tell the difference.