DeepSeek Just Exposed The Rot At The Core Of The AI Industry
This new model has changed almost everything.

Every few decades, something comes along that obliterates the status quo. In the ’50s, it was Sputnik. In the ’90s, it was the internet. And in the modern ’20s, it appears to be DeepSeek, a Chinese AI aimed squarely at challenging OpenAI. So what makes DeepSeek so damn special? Well, it’s cheaper, more efficient, and generally higher quality than anything produced in the West. This model only cost $6 million to build, in comparison to OpenAI, which spent well over $3 billion on AI training last year alone and has required $13 billion in investment from Microsoft just to stay afloat. And it wasn’t just cheaper to build. The cost of actually running DeepSeek is over 96% cheaper than OpenAI’s o1 model! Unlike any OpenAI model, you can actually use DeepSeek for free. Yet, in third-party bench tests, DeepSeek outperformed every OpenAI model by some margin. Unsurprisingly, upon launch, DeepSeek became the top-rated free app on the App Store, and when news of this product broke, $1 trillion was wiped off the American tech stock market. In doing so, it has exposed the rotten ideology at the core of the AI industry. So, how has DeepSeek achieved this? What does it mean for the future of AI and the American tech industry? And, more importantly, what does this mean for you?
Let’s start with the technical stuff. How have they built such a capable model on such a small budget?
In this instance, necessity seemed to be the mother of innovation. The US has restricted the sale of high-end AI-optimised supercomputer GPUs to China for some time now. The idea was that these are essential infrastructures for developing AI, and this restriction would keep the US one step ahead of the game (so much for free market capitalism, hey?). As a result, DeepSeek was only able to use weaker, cheaper GPUs designed for gaming to develop their model. This forced them to be hyper-efficient.
Consequently, DeepSeek’s model is only 38% the size of OpenAI’s older ChatGPT-4 model, and it has been optimised to run efficiently on these less powerful chips. But this tiny size meant that if they took the same approach as OpenAI, their model would underperform dramatically! So, they made two critical changes.
Firstly, the architecture. OpenAI uses an AI architecture known as “fully dense.” This basically means that the architecture is comprised of a single, vast network that processes every request with all its parameters and data points. This is incredibly computationally dense, but the idea is that it can make it more capable in a broader application. DeepSeek is instead much more picky and uses a “mixture of experts” architecture. In this approach, the AI is split into many models designed to be better at answering certain queries, and there is a front-facing AI that can understand what kind of query it is being asked and triage it to the AI model best suited to answer it. This is a far more efficient model, as it only engages the parts of the AI needed to solve a problem and not the whole AI. It also means it requires less training, which is very costly, as these expert AIs are more focused and restricted in scope. However, as a trade-off, this approach, in theory, should make a model have a less broad application than those with fully dense architecture.
But we don’t see this application restriction when it comes to bench testing DeepSeek against its rivals or in the real world. How come?
Well, this is thanks to the second change DeepSeek made — ensuring the finished product is open-source and not closed-source like most Western AI models.
Closed-source AIs are developed in secret, and then use cases are found for the model once it is released, hence why OpenAI needs to use the costly “fully dense model” and why it seems like AI is being shoehorned into every possible corner of our lives, even if it doesn’t add any value. These closed-source models are expensive to build, and tech companies need to find applications to justify their astronomical expenditure on them. But open-source works the other way around. Users have specific use cases in mind and work with the developers to develop the AI to be usable in that specific application. This enables far more focused, efficient, and cheaper development that results in an AI that is more useful in areas that actually matter than in closed-source models.
So, why are most Western AI companies using a closed-sourced approach? Well, this creates a proprietary AI that is wholly owned by the AI company. This enables them to charge more for its use and also helps them raise more investment, as it creates a more secure asset. After all, a tech giant or investment bank isn’t going to bankroll an open-source model that they can’t have total power and control over or sell on for billions of dollars. More on this critical point in a minute.
I have seen a few rumours and articles claiming that DeepSeek’s dramatic efficiency is a vast leap forward for AI, and this will make human-like AI possible in the near future and resolve the technical issues in the AI world. This simply isn’t true. DeepSeek still suffers from the same scaling issues, lack of actual cognition, and query errors that all AIs suffer from. It is no better a tool than those from OpenAI, and its cheaper cost won’t open the door to far better tools. It is fundamentally the same technology with the same flaws; it’s just been managed and built in a non-moronic way. I have covered the limitations of AI extensively; to read more about it, read those articles here, here, and here.
So, the question has to be asked: why has the West gotten so caught up in wildly expensive and overly costly closed-source models?
Well, this is, I think, the main insight from DeepSeek. It’s not that China could dominate the AI race. It’s not that OpenAI isn’t that unique. Instead, it is that the US economy is no longer based on the real world and therefore doesn’t value genuine innovation. In short, it exposes how far America has fallen into late-stage capitalism.
OpenAI was originally meant to be open-source, but it changed to closed-source. Why? Well, Western venture capitalists see AI as a way for them to replace the human workforce with their own AI in basically every sector of the economy, enabling them to wield significant control and reap huge profits. This is the hype that has been pushed for years now, despite scientists and AI developers themselves saying that AI can’t, and might not ever be able, to do this. But these venture capitalists didn’t care; they knew that investing in AI and pushing this false narrative would increase the stocks and make them money, whether AI can achieve this feat or not. As such, OpenAI and almost every Western AI project switched to closed-source to enable such investment, as it enriches the investors and the executives of these AI companies.
In fact, this is the real reason why America restricted GPU sales to China — not to get ahead in the AI race but to protect American investment and hegemonic domination of the sector.
In short, they are making AI a worse and more expensive product than it needs to be, have removed any true free market economics for the sector at the cost of true innovation, while pushing misinformation about the technology all too specifically to enrich investors at the cost of the consumer. This isn’t so much late-stage capitalism and more akin to a messy, plutocratic, post-capitalist market intervention and all.
This is why DeepSeek wiped $1 trillion off the stock market despite not having proven itself in the real world and having some serious security issues. It represented real-world economics encroaching on the heavily protected and falsely inflated American bubble.
And this economic rot doesn’t just exist in the AI industry. It is now widespread across the entire Western economy. Indeed, this is why the middle class is being squeezed so hard, as the inbuilt laws and motions of capitalism that once protected them are being overridden to enrich the 1%.
So, yes, DeepSeek is a Sputnik or World Wide Web moment. Just not for AI. They haven’t actually changed the world of AI all that much, as all the horrific issues and fatal flaws of the technology still very much remain. But it exposes the economic rot at the heart of Western economies that is causing us so much pain, strife, and disenfranchisement. It is the wake-up call we need to move past the bullshit we are swimming in and get back to the real world. After all, if a quasi-Communist country can achieve market economics better than the US, something seriously wrong is afoot.
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Sources: Sky, The Independent, The Guardian, BI, Sky, TensorOps, Capacity Media, Al Jazeera, India Startup News, Reuters, Axios