How Green Can We Get: The Subtle Roles of AI in Decarbonizing Crypto Operations
At first glance, one is inclined to dismiss the possible correlation between AI and cryptocurrencies. Of course, it only makes sense. Each field appears to be so uniquely distinct, massive enough to pride itself in the vastness of its scope- so much that trying to fit them both in a sentence would be synonymous with trying to fit two planets into a cookie jar. However, to the advanced eye, while it is easy to see each field in its independent grandness, it is still possible to have them exist within the same universe, revolving around the same solar system and drifting towards a fixed goal - the underlying desire to advance the world as a whole.
To attain this objective, there is one fundamental question we must ask: How do we achieve geometric progress in these fields? In more precise terms, how do we integrate AI and cryptocurrency to make our planet greener and, consequently, safer and more convenient for the coming generations?
A Date with the Crypto Energy Crisis
As measured in 2017, Sweden's 10.1 million population jointly produced about 419TWh of energy. About this same amount of energy is consumed by Bitcoin every year, and Bitcoin is only one of the many assets within the cryptocurrency space. A Bloomberg report reveals that the global power needed to create cryptocurrencies in the next few years could rival Argentina's yearly energy consumption levels. This means that cryptocurrencies are bound to use up a developed country's one year's worth of power supply on average. Pretty massive!
Little wonder cryptocurrencies have gained quite a reputation for being the bad boy of the energy consumption world, snacking on a full bag of some of the world's largest energy sources and tossing its carbon footprints all over the place.
The rising demand for blockchain technology as a store for cryptocurrency transactions does very little to help the matter. It only indicates that before 2030, crypto-energy consumption might become one of the world's most critical issues to address. Those that speak the lingo know the translation - a much larger brunt on the world's climate. By all means, they want to move to find a solution to it as soon as possible.
On April 8, 2021, a private group called the Crypto Climate Accord was established to specifically address the persistently growing energy implications of crypto mining on the ecosystem. The Crypto Climate Accord is essentially a partnership of many independent communities- the RMI, Energy Web, and the Alliance for Innovative Regulation (AIR). Within these communities are some other notable independent bodies and NGOs like the Web 3 Foundation, ConsenSys, CoinShares, EDF, Energy Piece Partners, Ripple, and the United Nations. This union aims to decarbonize crypto operations and make cryptocurrency energy 100% renewable and green by 2025.
The CCA, though only a few days old, has their work cut out for them. It is not an easy task: creating an alternative source of energy that will power the world's blockchain ledger system. Hopefully, the conglomeration has enough firepower to see the project through in record time. 2025 is, after all, just around the corner.
The private group is at liberty to take whatever path most appeals to them. What percentage of this energy supply will come from a hydroelectric power system?
What percentage will stem from wind farms, solar systems, or geothermal energy? We'll discover in time.
It is clear how these energy systems make for worthy sources of renewable energy, but can the CCA capitalize on more subtle intelligence to increase the efficiency of renewable energy in the long run?
The interaction of AI and Cryptocurrency in today's world
No one has enjoyed the impact of AI in the cryptocurrency world as much as investors. On that personalized scale, we see the use of Artificial Intelligence in Automated Trading. High-Frequency Trading utilizes AI to analyze specific technical tools to predict price movements across multiple trading platforms and hence take advantage of intraday price spikes in both trading directions.
Humans are not best suited for making decisions when it comes to a high influx of data. AI, on the other hand, is perfectly suited for this duty.
Hence, Hedge Funds turn to in-house programmers and full-stack developers with AI and Machine Learning knowledge to create cryptocurrency bots that can take in loads of historical data and make decisions with the highest probability outcomes.
On August 16, 2020, the Forecast Foundation developed a decentralized platform for peer-to-peer prediction markets called Augur. Augur relied on the experience of network participants to make predictions on various cryptocurrencies.
While Augur is fairly accurate, another system, NeuroBot, which relies on neural networks instead of network participants, is viewed to be more accurate than Augur.
The subject of interest is not the corresponding, debatable accuracies, but the fact that the world is gradually leaning more and more towards using Artificial Intelligence to further evolve accuracy concerning the multi-billion dollar investment world.
Why AI is important in trading
Humans make mistakes. Humans intend to do something and change their minds at the last minute for emotional and sentimental reasons. Humans hesitate. Humans need sleep to function; hence they might not always be able to trade round the clock. Artificial Intelligence doesn't have to deal with any of these.
Renewable Energy Solutions to Crypto Problems
Today's blockchain system functions primarily to power cryptocurrencies. However, within a few years, its application will extend to other areas of our everyday lives- the internet of things, for example, where more everyday operations will take on a smooth decentralized and anonymous approach. Each year, the blockchain ecosystem will only require more energy than it does today. It will only make sense if the energy directed to this process is entirely renewable and clean.
So far, hydroelectricity has been at the frontlines of The Green Battle, with wind and solar sources following closely behind. Sadly, there are seasons when the champion of war loses a solid grip of its sword, and crypto miners revert to using coal-powered systems. In periods of low water supply, miners resort to coal-powered systems. But the goal is not to reduce the number of fossil fuels burnt. The goal is to go completely green.
Private firms like Soluna have taken the initiative to acquire a 37,000-acre farm site in a part of Western Sahara controlled by Morocco, to build a world-grade power-generating plant. Like other committed plants, Soluna is dedicated to powering the crypto sphere with clean, low-cost renewable energy. This specific plant in Western Sahara is being structured to produce more than 900 megawatts of power. While this does not even cover half of the energy requirements for Bitcoin, it's a major step in the right direction.
With Crypto Climate Accord in the mix, we can only be more confident of attaining the 100% renewable energy objective before 2025.
Through embracing renewable energy supplies, the cryptocurrency world stands a chance to create an example for other industries and show, in the clearest light, how a completely decarbonized system will look like.
Hydroelectric systems account for 16% of the world's energy supply. It towers above other renewable energy sources. as Wind Energy Systems and Solar systems account for 5.3% and 2%, respectively. However, dams require intricate engineering across specific topography. Constructing dams in certain areas might lead to the displacement of the locals in such areas. While it is a minor price to pay for such a drastic energy problem, it is worth keeping in mind that the CCA might have to compromise on issues such as this.
Solving Crypto Energy Problems with AI
The limitations around renewable energy supplies put a cap on the amount of energy produced per time. But what if there was a way to do more with less? AI provides such answers.
Artificial Intelligence can optimize the most important sectors of power generation and consumption. Offshore wind farms are a classic example. Presently, turbine inspection requires human factors and highly trained personnel to go out in helicopters to access the situations. However, AI and Machine Learning techniques, i.e. deep learning methods, can assist scientists and researchers in studying sequences and predicting those wind farms' possible failures and successes. With a vast amount of historical data on key elements like voltage, temperature, humidity, wind speeds, models can be trained to pull information simultaneously from all these individual elements and accurately access and predict issues on the wind farms before they happen. The same models can be created to effectively analyze other energy sources like solar systems and optimize the production and consumption of energy from these sources.
This could help to prevent some significant breakdowns and to scale down the cost of maintaining these facilities.
While AI has apparent uses in creating efficient energy systems, it can also aid our faster arrival at our destination, attaining sustainable energy solutions in other fields, and reducing the global carbon footprint.
On April 18, 2021, the United States and China pledged their commitment to climate change. With such hopes, both global giants will take unified actions towards reducing emissions and hasten the Green movement.
Ultimately, we aim to create a completely green world with no threat to the ecology and climate. We will learn to coexist in a complex organic way that factors in our progress without causing harm to our home. The safety of our planet is a priority. Not everyone might be able to afford a trip to Mars eventually. Our best bet is to use all the tools we have to continually steer ourselves towards Utopia. After all, a safe world translates to a space more conducive for dreams, and a world where people can dream translates to one where humans can experience a richer, fuller life.
You might be interested in reading this article which looks at some of the more sustainable crypto currencies.
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