Block Chain decrypted by Quantum Computers?

5

October

2019

5/5 (3)

While Block Chain is a technology that has found its way into modern economy partially through the proliferation of Bitcoins, Quantum Computers are less prominent. I will later explain what these two technologies are and why they might be competing with each other.

Starting with Block Chain and what it actually is. Bankrate (2019) defines it as a “digital, public ledger that records online transactions” and Investopedia (2019) describes it as a chain of information blocks. So, from that one can understand that block chain consists out of digital information blocks tied together in a chain, that are publicly available and look very similar to a bank’s ledger containing past online transactions. On a brief note, block chains are not always public (“permission-less”), they can also have a restricted access (“permissioned”). In the latter case not only, the access for actors is restricted, but also the type of transactions (Massessi, 2018). However, let us not dive too deep into the also very complex governance structure of block chains.

Now what is so special about block chains? Basically, this technology enables different parties to agree on the outcome of a transaction. It is secured and recorded through a “one way” mathematical function that turns information into a long string of numbers and letters (Fedorov, Kiktenko & Lvovsky, 2018). It is very difficult for a computer to reverse engineer this function and hence it is also very complex to alter its outcome. Fedorov et al. (2018) provide this example: a mathematical operation in which you multiply two very large prime number is very straight forward, but finding the factors ex post is very difficult and needs great amounts of processing power. This is great for record keeping and could be used to store very sensitive information of companies or to securely make large sum transactions online.

On that note, quantum computers come in to play. However, lets first explain what this technology actually is first. Techopedia (2019) defines it as follows: “a computer that operates on and/or incorporates aspects of quantum theory”, IBM Q (2019) define computers as a computer that “leverage the quantum, mechanical phenomena of superposition and entanglement to create states that scale exponentially with number of qubits, or quantum bits”. These definitions are very technical, so in other words quantum computers are supercomputers that can work with three states namely: 0,1, or both at the same time (Rouse, 2005).

So what effect does this one extra state have on computing in general? One could compare the quantum computer to the Enigma machine used in the WWII. Quantum computers allow to solve very complex tasks in a very timely manner. To illustrate this, let us take the breakthrough made by Googles quantum computer earlier this year. It performed a task in just three minutes which would take 10,000 years to be computed by a modern and very powerful supercomputer (Pollock, 2019).

Its ability to raise the bar of computational power, not only brings efficiency purposes but also may make encryption as we know it a very difficult discipline. Moreover, the way quantum computers work make data transfer safer than ever before (Fedorov et al., 2018). The use of photons (particles of light), makes altering information without anyone recognizing almost impossible. As such, block chains as a mean to encrypt data, may become obsolete in the future.

However, it is also important to note that quantum computers are not likely to be marketable any time soon, and for now block chains are an effective way to keep information safe. Quantum computers are expensive to build and are at the moment also less powerful than their conventional brothers (Fedorov et al., 2018). Furthermore, its way of computing may also be combined with block chain solutions, but it is not yet evident whether these two technologies will coexist. As such, quantum computers may not be the end of block chains after all.

References:

https://www.bankrate.com/glossary/b/blockchain/
https://www.investopedia.com/terms/b/blockchain.asp
View at Medium.com
https://www.nature.com/articles/d41586-018-07449-z
https://www.techopedia.com/definition/5735/quantum-computer
https://www.ibm.com/quantum-computing/learn/what-is-quantum-computing/
https://whatis.techtarget.com/definition/qubit

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Artificial Intelligence and Big Data

20

September

2019

5/5 (1)

How will these prominent two developments in information technology and their interplay change socio-economical world? Maybe to start this discussion, there is need to define what Artificial Intelligence and Big Data actually is. Artificial Intelligence or often just abbreviated as AI, comes in two forms. Most people when thinking about AI, have the movie “Transcendence” starring Johnny Depp in their mind. The film shows an unsupervised system. That is a system that does neither need labels nor any classification to learn. As such it learns in a very similar fashion than we humans do. One could imagine how complex it is to make a computer duplicate the workings of a human brain, considering that we do not even know our own abstract thinking process. Instead, there has been made more progress in the area of supervised learning systems. One could think of voice and image recognition where a computer learns by going through thousands of “right and wrong” scenarios (Brynjolfsson & Mcaffe, 2017).

So now that we have broadly defined what artificial intelligence is, let us talk about Big Data. According to Gartner’s definition Big Data is defined as follows: “Big data is data that contains greater variety arriving in increasing volumes and with ever-higher velocity “(oracle.com, 2019). This definition brings us to the often cited “three V’s”: Volume, Velocity, and Variety. The amount of data, the speed in which we receive data, as well as the types and variant of data we can collect, has grown exorbitantly over the last decades. Developments such as the Internet of Things, or the internet itself which tracks billions of interactions, are just two contributors to this trend of piling data.

It becomes clear, that analyzing these enormous data sets can be very valuable for various actors such as companies, Governments, and even individuals. However, one also needs to recognize the challenge on how to deal with these data sets both effectively and efficiently. One of the solutions to this is using AI. MIT Sloan Management Review puts it nicely by rating this interplay as the “(…) single most important development that is shaping the future of how firms drive business value from their data and analytics capabilities” (Bean, 2017).

So, what can this power couple do? Let us look at some examples together:

Tempus, is an AI developer in in the Healthtech industry. Their AI, uses large data sets of medical records, to assist doctors to diagnose and provide suggestions for individualized treatment. Moreover, it heavily engages in cancer research, an area many hope for faster progress.

Nutonomy, on the other hand is an AI developer within the automotive industry. Their AI technology consolidates various disciplines such as “mapping, perception, motion planning, control and decision making” to enable safe autonomous driving (Schroer, 2019).

Lastly, Blue River Tech, a company that works within the agriculture industry. They employ an AI that can distinguish between plants and then only applies herbicides to weeds. This incentive, reduces the risk of herbicide- resistant weeds and at the same time “reduces 90% of the chemicals currently sprayed” (Schroer, 2019).

These are just a few examples, but there are many more. Coming back to the question of how AI and Big data influence the socioeconomical world. AI is fed by large amounts of data on which it learns. It becomes so effective that most of the times it is more accurate in detecting and analyzing than us humans. For example, in diagnosing child diseases, some AI actually outperformed many doctors in that they were not only faster but more often correct than their human counter parts (Whyte, 2019). Moreover, AI make the future of autonomous transportation not only possible, but also safer (Wiggers, 2029). Lastly, the example of an AI just like the one by Blue River Tech, opens new ways for us to reduce the negative impact we have on our environment. And who knows, maybe AI will also safe the world from us humans one day.

Sources:

https://hbr.org/cover-story/2017/07/the-business-of-artificial-intelligence
https://www.oracle.com/big-data/guide/what-is-big-data.html
https://sloanreview.mit.edu/article/how-big-data-is-empowering-ai-and-machine-learning-at-scale/
https://builtin.com/artificial-intelligence/ai-companies-roundup
https://www.newscientist.com/article/2193361-ai-can-diagnose-childhood-illnesses-better-than-some-doctors/

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