How AI Will Destroy The Earth

And Why We Need To Severely Limit It's Growth

AI as we know it today

Since 500 billion dollars just got implemented towards AI, it’s best to spend some time discussing it and what it will do to the earth.

For comparison, only $10 billion was funded towards the mRNA vaccines, so we’re going to hear as much propaganda about AI as we heard about the mRNA vaccines, only 50x more.

In this article, we’ll discuss:

1. What exactly is AI

2. What are the costs of AI

3. Why we need to limit our AI use severely

Without further ado, let’s dive right in.

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What Exactly Is AI

I’ve discussed AI a few times on Unorthodoxy. For example, in the article Why AI is nothing more than Advanced Computing, I equate AI to the next level of processing like Excel and macros. I’ve also explored my relationship with AI in the podcast To AI or not AI and in the article Is ChatGPT thinking for me?

In the article Why AI is nothing more than Advanced Computing, I precisely touch on what AI is. Since it’s been eight months since that article, and I’ve grown in my experience of the world and the topic, I can expand upon this subject more clearly. To start:

#1 — The term “Artificial Intelligence” is a metaphysical narrative designed to imbue computing with humanistic characteristics. The attribute of intelligence should be given only to living things. To view a computer as learning and, therefore, intelligent is a misnomer as we’re romanticizing advanced computing.

The reality is that the processing we see when we use AI services is not intelligence but rather the next stage of computing, thereby the phrase “advanced computing.” The term artificial intelligence is nothing more than a marketing scheme for users to personalize and fantasize about the next level of computing.

A true example of artificial intelligence can be seen with the brain, as discussed in the article How to Use Your Brain and the series How to Train Your Mind.

#2 — The allure of AI is due to how the advanced computing processes and responds to information via its LLM and NLP. AI¹ systems are distinct in processing information due to their NLP (Natural Language Processing). What we simply have here occurring is that you are asking Google a question — as you would a person — and Google provides you a response in a humanistic manner. That’s it.

This humanistic response, the ability to understand what a human may be asking and to respond in a way that pleases the human, is due to AI’s LLM (Large Language Model). Understanding the question that the human asked and responding in a human-like manner takes an incredible amount of computing data; this is where LLMs and NPs come into place. Again, this is simply advanced computing.

Note: As we’ll see, it takes enormous amounts of processing data for machines to understand the question, use context clues, respond to it, etc. — what we humans do instantaneously. It makes you marvel at the intelligence of the human and their Creator.

These two concepts 1) How AI is simply the next step in computing and 2) this advanced computing requires large amounts of data to respond human-like) is critical in understanding whenever we hear the term “AI.”

Now that we have this firm understanding of the topic let’s discuss just how much energy it takes to run this next level of computing.

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The Cost To Run Advanced Computing

The LLMs process the information asked and respond in NLP, which takes a large amount of processing data. Here is where data centers come into play to process all this data. Data centers are spaces within buildings that house computer systems.

An image of a data center - a space for computing processing to occur

This point here is where we need to talk about the large amounts of energy required to feed these data centers and the primary energy sources we are going to use are going to be:

1. Land resources,

2. Electricity,

3. Water.

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Let’s start with the land.

To quickly touch on the amount of land needed for these data centers, let’s read from our UK brethren on how much land they use for their AI data centers. From Reuters², we read:

The real-world manifestation of the AI scramble is evident in the northern English county of Northumberland. That is where Blackstone, the world’s largest commercial real estate owner, in May bought, opens new tab 95 hectares of land with plans to spend 10 billion pounds ($13 billion) building one of Europe’s largest data centre campuses.

• For reference, 95 hectares of land equals 234 acres.

• 234 acres equals 176 football fields³ from end zone to end zone.

That’s just Europe. Thanks to Trump and Project Stargate, 875 acres⁴ in Texas have been set aside for these data centers.

• For reference, 875 acres equals 661 football fields from end zone to end zone.

• For more reference, that’s as big as Central Park in New York City.

Central Park in New York City is only 843 acres

Note: Whenever you hear that the world is overpopulated, remember this. This reason is why we have an “overpopulation narrative” — so they can squeeze us into small spaces so the rest of the land can be used for their investments.

Next, the electricity.

In July 2024, when Trump accepted the Republican nomination, he touched on the energy AI would need. Ironically, no one seemed to mention that, or I must have missed it.From his transcript⁵, we read:

America’s on the cusp of a new golden age, but we will have the courage to seize it. We’re going to take it, we’re going to make it a current — I mean, we’re going to bring this into a golden age like never seen before. Remember this: China wants to do it, Japan wants to do it. All of these countries want to do it.

We have to produce massive amounts of energy. If we’re going to produce the new — if you look at some of the things that have been done, and some of the things that we’re going to do. But A.I. needs tremendous — literally, twice the electricity that’s available now in our country, can you imagine? But instead we’re spending places where they recharge electric cars.

Staying with Reuters and back to the UK, we read:

The arrival of GenAI⁶ means greater processing power which requires more electricity. A ChatGPT text search consumes, 10 times the power of a Google search, per Goldman Sachs analysts, while generating an image using a GenAI model could take as much energy as half a smartphone charge, according to a study, by researchers at the AI startup Hugging Face and Carnegie Mellon University. Data centre operators are now planning and constructing facilities with capacity of 200 to 500 MW. Morgan Stanley analysts estimate the cost of building a campus at $10 million per megawatt.

These plans are testing energy infrastructure. Data centres, including those used to mine cryptocurrencies, sucked up about 460 terawatt hours (TWh), or 2% of global electricity demand in 2022, according to the International Energy Agency. In Europe, Morgan Stanley analysts estimate they will account for 4% of power demand by 2035, up from 1% today.

In some areas, however, the figure is much higher. Ireland, which is home to many large tech companies, has seen the proportion of its electricity consumed by data centres rise from 5% in 2015 to 18% in 2022. The figure is projected by EirGrid to hit 28% by 2031, prompting the state utility to place a moratorium on new data centres until 2028. By 2033, Goldman analysts expect AI data centres to add 370 TWh of power demand globally, equivalent to the combined power consumption of the United Kingdom and the Netherlands in 2023.

The next level of advanced computing won’t feed itself. It’s going to require large amounts of human resources to do so. We’ve touched on the land and the electricity; now it’s time to touch on the following valuable resource — water.

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The Water Needed To Fund AI

The most startling need of the data centers is the cooling aspect. Think about this: even with our laptops, as we use them, even when they get hot, there are systems designed to cool them down internally. It’s the same methodology for these data centers.

When these computers start processing all that information, they get really hot — like a furnace. So water is needed to cool them down.

From The Times⁷, we read:

Data centres have always needed cooling because computers are essentially like radiators, with most of their energy converted into heat. However, the servers that are built for AI are processing huge amounts of data and have more power density and greater cooling demands.

Staying with the times, let’s find out how much more cooling demands are needed. Back to the Times, we read:

Many data centres use water-based systems to cool the plant with towers evaporating the heat, like a huge perspiration system, which means that the water is lost. It also has to be drinking quality because impurities can damage the servers. [The machines needed drinking water more than you do]

The United States is the world’s biggest location for data centres, with more than 5,000, compared with about 600 in the UK.

New data centres built in Britain over the next five years could require the same amount of water as a city the size of Liverpool, according to estimates by the water industry.

The latest Big Tech sustainability reports show double-digit increases in water consumption by Google (17 per cent), Microsoft (22.5 per cent) and Meta (17 per cent).

“The expansion of AI products and services is leading to an increase in data centre workloads and the associated water footprint required to cool them efficiently,” Google said.

Here are some more images on the impact of the water being consumed by Artificial Intelligence:

Next time you use water, think of how much of that water is needed for AI

I hope everyone can see how Project Stargate is about to destroy the United States.

PS: I wanted to make this article a paid article due to the amount of research that went into this article. However, this information is so important that I want everyone to read it. If you gained some insights from this article, consider supporting more work like this and become a paid subscriber.

Why We Need To Stop AI

In the 2012 movie The Lorax, the antagonist is a billionaire who got wealthy from selling oxygen to the population. The reason he’s able to sell oxygen is because there are no trees to provide oxygen naturally. There are no trees because the billionaire before him got rich by destroying all the trees to give the population a “thneed” — a trendy product that the people just had to have.

To give the population their ask, removing all the trees is required.

Ladies and gentlemen, if we do not say no to AI, we find ourselves asking for the same fate: asking for AI at destroying our world.

AI is being referred to as the savior of the world and the narrative of this presidential campaign, but as we saw with these narratives, they are simply money grabs. Lest we forget, mRNA vaccines were a $10 billion investment that yielded billions in ROI for the companies but no tangible ROI for the population. AI is slated to do the same.

The narrative that is to follow AI is that of Quantum computing, but just as mRNA was built upon the narrative fallacy of viruses, the same strategy will be built towards Quantum Computing (QC) and a sentient being. This angle is a topic I will be diving into, but this QC narrative itself is also a fallacy — however, be warned: demons and spiritual entities are most certainly real.

Sam Altman has stated that nuclear fusion will be needed to power AI. If you’ve read my article on Lies Not Discussed In The Truth Community, then we see that nuclear weapons — as in the sense of the Atomic bomb — were also a fallacy.

This context is why many of the narratives we’re being told are nothing but fallacies. As I mentioned in my article on Stargate and mRNA, actual dollars are funneled into corporate pockets while we’re told all these narratives are built on fallacies. After four years, these companies will roll in billions at our expense.

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Conclusion

The great Rudolf Steiner talked about this technocratic force known as Ahriman and how it reveals itself throughout humanity. I’ve touched on Steiner’s prophecies on vaccination before, so I must familiarize myself more with his work on this topic before expanding on it more deeply. However, what we see shows how clearly we worship this technocratic beast at the expense of our natural resources.

This perspective is why I state that we should look at the Bible from a Historicist lens vs. a Futrisitic lens because symbolically, we can see Trump playing the Antichrist role as he ushers in the rise of this technocratic Beast of Ahriman—more to come on this topic, but a fascinating perspective.

Technology is not inherently wrong; it is a natural development, as writing has been in our history. To grow, we must tame it rather than letting it run wild as it is. From the French newsletter Le Monde⁸, we read:

“Between technosolutionism (the myth of technology that will save us) and decay, there is a third possible path,” says Mr. Babinet. In his view, the useful uses of AI should be encouraged, which often did not require generative AI, and “deter” futile and computationally-intensive uses, such as social media image generation.

We must limit our use of AI and technology or give up our humanity.

AI can be seen as the apple in a sense: convenience. Instead of putting in the work, doing the research, and spending the time, we ask for the query and get the response. Yet what occurs is: 1) the ability for humanity to think in multiple aspects decreases. What’s worse is that 2) if we continue down this path, all systems will soon come together, and even more data centers will be required—no more thinking in multiple areas, only one — the path of the AI.

What’s the solution to all of this?

1. We must share the harms of advanced computing and the resources it takes to run.

2. We must be intentional with our technological use. It should always help us strengthen our humanity, not take away from it.

To close, thank you for your time reading this work, and I look forward to your thoughts in the comments and the chat! Have a wonderful day!

Ashe,

Franklin O’Kanu

PS: No AI was used in the writing of this article.

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Notes and References

1. If we could get the world to start calling AI AC (advanced computing), that would be a win on so many levels.

2. https://www.reuters.com/breakingviews/data-centre-boom-reveals-ai-hypes-physical-limits-2024-07-04/

3. https://www.amortization.org/acres/875

4. https://www.wdsu.com/article/trump-stargate-project-ai-initiative/63545806

5. https://archive.ph/77Zww#selection-5861.299-5861.367

6. GenAI is another fancy term they look to come up. It’s literally the AI that we use now when we use ChatGPT

7. https://www.thetimes.com/uk/technology-uk/article/thirsty-chatgpt-uses-four-times-more-water-than-previously-thought-bc0pqswdr?region=global

8. https://archive.ph/w0kWc#selection-2377.47-2379.1