AI Trajectory: Stargate, DeepSeek, and Jevons Paradox
- John Vassh
- Jan 28
- 4 min read
Welcome to Project Stargate. You may have already heard of this massive project and its ambitious goals in headline stories across the internet and news reports over the past week. As the initial announcement dust begins to settle, our mission is to elaborate and curate some of the finest content from direct sources involved. So, without further ado, let us jump right into the basics and provide you with "learn more" links on this civilization-changing endeavor.
Imagine a grand vision: a constellation of data centers glowing across the American landscape, humming with the power of artificial intelligence. That's the Stargate Project. A bold initiative to supercharge the US's AI capabilities. It’s not just about building computers; it’s about building the future of the United States. Think of it as a massive investment, potentially reaching half a trillion dollars by 2029, just a small down payment on American innovation. This isn't a solo endeavor; it's a powerhouse team-up between giants like OpenAI, the brains behind some of the most cutting-edge AI models; the investment prowess of SoftBank; and the cloud computing muscle of Oracle.
The official announcement of Stargate on OpenAI’s website:
The ultimate goal? To plant the flag of American AI dominance firmly in the ground. They’re not just aiming for technological superiority, though; it’s also about creating tens of thousands of jobs, boosting the economy, and most importantly, bolstering national security. Picture construction crews currently buzzing with activity in Texas, the project’s initial launchpad, with plans to spread this technological revolution to other states. It’s a high-stakes game, and the Stargate Project is poised to be a star player. But not everyone is convinced, with Elon Musk and Sam Altman exchanging several heated messages directed at each other over the feasibility of its financing.
For more detail on the project itself, check out this informative video from A.I. Revolution on the Stargate Project. Enjoy!
Now that you’re all caught up on this huge infrastructure investment and the key players involved, let’s discuss how the Jevons Paradox applies not only to resource consumption but also to international competition.
The Jevons Paradox describes a counterintuitive economic phenomenon where technological advancements that increase resource efficiency paradoxically lead to increased overall resource consumption. This occurs because greater efficiency reduces the cost of using the resource, making it more attractive and accessible. This lower cost stimulates demand, and if the increase in demand is significant enough, it can offset the initial efficiency gains, resulting in a net increase in resource usage. This was famously observed by William Stanley Jevons in 19th-century England with coal-powered steam engines: while engine efficiency improved, leading to cheaper coal usage, it also spurred wider adoption of steam power across industries, ultimately driving up total coal consumption.
This paradox has significant implications for modern discussions surrounding sustainability and resource management, especially in areas like energy consumption and technology. For instance, while more fuel-efficient cars could theoretically reduce gasoline use, they might also encourage more driving, potentially leading to increased overall fuel consumption.
Similarly, advancements in computing power and efficiency, while enabling more complex applications like Agentic AI, will also drive greater overall energy demand as these technologies become more widespread and are used for increasingly intensive tasks. The Jevons Paradox highlights the limitations of relying solely on technological efficiency for reducing resource consumption and underscores the need for complementary strategies.
More on Jevons Paradox:
We now embark on the international stage. Just recently, a Chinese-based AI startup named DeepSeek entered the race as a rival to OpenAI’s most advanced complex problem-solving models. The rival, R1, is reported to have taken just months to build, a few million to train, and cost around 98% less than its rival to run. The models were released under an MIT license, allowing for developers to freely modify it for commercial use. These models are currently achieving O1-level reasoning capabilities, in layman’s terms, that means very good.
So, how did this progress happen so quickly at such a low cost? DeepSeek relied heavily on open-source software development as opposed to closed source with expensive hardware requirements found with OpenAI. This lowered the cost barrier while still driving performance and is opening the field for countless smaller firms to play. Yet, this is still just a partial answer, as Meta’s llama is also open source, so word is that Zuck is scrambling top engineers to figure out a response and a greater understanding. This definitely should raise the concerns of our Silicon Valley titans when setting the standards in AI progress.
Ultimately, DeepSeek has currently found a way to strike at the very chain links between software and hardware, as it claims the need for far less advanced chips to run its models. As we write this, major chip suppliers such as Nvidia are experiencing an almost 15% decline in share price during market trading. However, let’s not forget some limitations placed on DeepSeek: it is completely censored and controlled to influence the Chinese Communist Party’s Agenda. A simple query about Tiananmen Square will tell you all you need to know about its current state. Since it is open-source software, the code can be modified to remove these filters, but it is still reliant on U.S. chip design and its ability to be manufactured in Taiwan and the Netherlands.
The race is heating up, and what happens next will be dynamic, a guessing game where the field of play and rules are constantly changing. One statement will always ring true: creative problem-solving will help the victors prevail, while simply throwing money at the situation won’t guarantee leadership. Stay tuned, and as always, thank you for the privilege of your time.
