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Industry Disrupting Technologies

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Prompt for this entry:

Turning your attention to the related concept of emerging, disruptive, or game-changing technologies. Think about the paradigms that were broken in the industry when personal computing became the norm or when over six billion people had cell phones that broke the barriers to reaching people across the globe. Identify at least two more game changers or disruptive technologies that created a new trend. Explain how these game changers or technologies have impacted the industry.



Part One:

Introduction:

I was born in the early 1990s within a country in the imperial core. I consider myself to be incredibly lucky to be privileged with the quality of life that I have lived. I have lived through a number of incredible, rapid, advancements in technology. Advances such as the explosion of public internet access, of cloud-based computing, and of general availability to the majority of known knowledge in the world. In this journal entry, I am going to cover what I believe to be the two most impactful, current, and emerging technological advancements that are being made in Computer Science. I will also cover how I think they may impact both the field of Computer Science, and myself personally in my career.

Identification and description of the first technology:

The first of the two technological advancements that I am going to cover, is into the field of quantum computing. This technology is perhaps one of the most impactful technology advancements that will be made in my lifetime. It wasn’t until recently that I began to understand that a quantum computer is not just a computer that has more processing power than a standard computer. “Quantum physics describes the behavior of atoms and subatomic particles, like electrons and photons. A quantum computer operates by controlling the behavior of these particles in a way that is completely different from regular computers,” (Quantum Computing: The Future of Quantum Chemistry | Merck KGaA, Darmstadt, Germany, n.d.). It is an entirely new approach to computing, vastly different from standard computers. I won’t speak too much on its applications, as my understanding of their usage is still quite limited, but I do know that they have the potential to drastically change and improve on fields of science that rely on quantum mechanical principles.

Standard computers rely on bits, 0s and 1s, open or closed, off or on states, to perform calculations. These states are typically implemented using transistors, and they are used to create the fundamental logic gates that are used to perform computations. At least with standard computers, these transistor states, off or on, are definite, they are either on they are off, 0 or 1. Quantum computers change this approach, and they allow for a quantum mechanical effect known as superposition to be held. That is, where the state of the qubit is neither on or off, but is in a state of quantum superposition until the point where the qubit is measured (an interaction/observation occurs). At the point when the qubit is measured, the state collapses into a definite value, similar to the definite values that are held by standard bits.

In my previous journal entries I mention an interest in using machine learning models to calculate interatomic potentials for various particle reactions / interactions. These states can be utilized for these types of computations because, “a quantum computer with several qubits in superposition can crunch through a vast number of potential outcomes simultaneously. The final result of a calculation emerges only once the qubits are measured, which immediately causes their quantum state to ‘collapse’ to either 0 or 1,” (Quantum Computing: The Future of Quantum Chemistry | Merck KGaA, Darmstadt, Germany, n.d.). This is the same effect that we would see from any other attempts to measure the state of a particle, as any intervention, such as through direct measurement, causes the state of the particle to collapse into a definite state. Where as, before measurement we cannot truly know the state of the particle, as it is in a super-position, we can only say probabilistically what its attributes are. The area of quantum computing is still in its infancy, and methods for performing meaningful calculations are likewise still being developed. These approaches to computation are generally performed through highly specialized quantum algorithms.

From the first technology, what are the likely impacts on computer science or your career?

If I have the opportunity to continue my education, I would like to end up working as a computational scientist / chemist. I have an enormous passion for both programming, and chemistry. I would love to find a way to end up working with both in my daily life. The evolution of quantum computing I think has the greatest potential to impact and provide material sciences with highly advanced approaches to studying interactions between particles that until very recently had been limited to measuring physical interactions. Quantum computing has the potential to allow us to drastically improve the types of computational work we can perform, as they can better represent the real quantum mechanical properties of interactions in ways that computations with standard computers are unable. I feel that learning to adapt and represent the material world through quantum computational algorithms will provide us with approaches to solving a multitude of problems that we have yet to even formulate. It will provide us with the means by which to accelerate physics and chemistry based research in remarkable ways. And I foresee it providing a number of enhancements in both medicinal research, and general materials research.

Identification and description of the second technology:

The second technology that is currently emerging, and largely disrupting the field of Computer Science is machine learning. Machine learning is an important component of the larger field of artificial intelligence. Machine learning models have the potential to fundamentally transform the field of Computer and Data Science, as they are capable of accurately, and independently creating generalizations, and recognizing patterns in complex data sets. Machine learning models use existing data-sets as examples, and especially with newer models, they are capable of very successfully recognizing patterns within pools of data. There are a multitude of different approaches and algorithms that can be applied to solve different problems. One such approach is with deep learning, which utilizes a series of neural network layers, and can be used to create solutions to very complex problems. This can allow a machine learning model to determine the importance of values within a data-set without ever being directly instructed as to the “weight” or importance of specific types of values. We are currently seeing an interdisciplinary application of these types of models, that is, across a number of different fields they are proving to be incredibly useful. They are capable of accurately refining and adapting themselves through additionally provided data, and excel in situations that have vast pools of data from which to generalize and “learn”. Machine learning approaches to solving problems are changing the way the world views data science, and put great emphasis on the necessity to collect and store large data-sets.

From the second technology, what are the likely impacts on computer science or your career?

I do think that there will be profound ways in which machine learning can be applied to the field of Computer Science as we continue to learn and improve our implementations. I think that machine learning will be a powerful tool in the arsenal of methods which computer scientists, or computational scientists approach solving challenging problems. My personal opinion is that the greatest impacts felt will be in specialized fields of scientific research. I think that it will be an incredible tool for advancing scientific research, as it is capable of processing vast amounts of experimental data in ways that we have previously been hindered. I am very hopeful of a future in which the field can be applied towards medicinal and material based research.

How might the two technologies impact humans, communities, or the world?

I think that both of the discussed technologies have a great deal of potential to positively impact the world. As I previously mentioned, I do feel that the greatest impacts of these technologies will be felt by researchers, such as computational scientists who focus on adapting the way that traditional or quantum mechanical problems are solved to utilize these technologies. I do believe that there is a significant amount of over-hype in AI related technologies at the moment, I don’t think we are as close to achieving generalized intelligent models as some seem to believe. That being said, I do still believe that machine learning models have the potential to advance our ability to make progress scientifically in ways that we have not since since the initial creation of digital computational systems. I am very hopeful for physics based material and medicinal research, using both quantum computing, and machine learning. I think that through both of these approaches, and perhaps through a combination of the two technologies, we will see the initial burden of researching and discovering new materials greatly reduced.

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