DeepSeek brings a big disruption in artificial intelligence models and rewrites the rules of the game.
When you think of seismic shifts in tech, your mind might jump from the Dot-Com bust to the 2008 financial meltdown. But in 2025, the tech world witnessed a disruption that dwarfed both in sheer audacity: the rise of DeepSeek. This scrappy newcomer didn’t just disrupt the market, it rewrote the manual on artificial intelligence (AI).
Imagine a day when U.S. stocks lost a trillion dollars in value. That’s exactly what happened when DeepSeek burst onto the scene, triggering a jaw-dropping USD 600 billion drop for NVIDIA alone – the worst single-day loss in history. Overnight, Silicon Valley’s once-untouchable giants scrambled to understand how a two-year-old company with no venture capital hype, no billionaire backers, and a team of PhD students – not traditional engineers – could upend the AI status quo.
The Player
History loves an underdog story, and DeepSeek has become the poster child for a modern-day David taking on industry Goliaths. In early January 2025, DeepSeek released its chatbot based on the DeepSeek R1 model, quickly climbing to the top of app stores and trending lists worldwide. Founded by Liang Wenfeng, a reclusive academic driven by scientific curiosity rather than commercial gains, DeepSeek rapidly surpassed ChatGPT in engagement and performance.
DeepSeek harnesses the power of a chain-of-thought model, an innovation previously missing from earlier ChatGPT versions. This advancement mirrors OpenAI’s o1 but with even stronger reasoning capabilities, allowing for more human-like critical thinking.
China’s AI Gambit
The backdrop to DeepSeek’s emergence is as dramatic as its technology. The United States and China have been locked in a technological cold war for years, with AI emerging as a key battleground. To curb China’s progress, the U.S. halted the export of advanced chips in 2022, including NVIDIA’s specialised AI chips.
Many assumed that China’s AI ambitions would stall under the weight of these export restrictions. Instead, the limitations sparked an unprecedented surge of ingenuity. In every arena of this technological cold war – from the moon race and quantum computing to advanced military technologies – innovations emerged out of necessity, proving that even with scarce resources, breakthrough progress was possible. In the realm of AI, this creative push led to transformative advances.
While industry giant OpenAI employs over 3,500 individuals, DeepSeek achieved groundbreaking results with only a fraction of that workforce. More astonishingly, it managed to train its models on 100 times less budget than its Silicon Valley rivals.
The 100x Advantage
Forced to rely on older hardware and imported chips, the DeepSeek team transformed these constraints into a formidable asset, propelling their rapid rise on the global stage. Rather than assembling a conventional team of engineers, founder Wenfeng took a radically grassroots approach by recruiting top PhD students from leading universities. While industry giant OpenAI employs over 3,500 individuals, DeepSeek achieved groundbreaking results with only a fraction of that workforce. More astonishingly, it managed to train its models on 100 times less budget than its Silicon Valley rivals.
This strategic pivot not only defied expectations but also paved the way for a new era of AI innovation, one forged in the crucible of international tension and technological scarcity.
Rethinking AI’s Core Architecture
DeepSeek’s technological breakthroughs extend far beyond its origins. Traditional models like ChatGPT function as monolithic ‘jacks-of-all-trades’, deploying 1.8 trillion parameters for every query, whether drafting an email or analysing complex code. DeepSeek, however, employs a sophisticated ‘specialist’ architecture, partitioning 671 billion parameters into dedicated subnetworks that serve as on-call experts for legal, medical, or technical tasks. At any given moment, only about 37 billion parameters are active, dramatically reducing computational costs. It’s guided by the principle: “Why light up a stadium when you only need a desk lamp?”
Breaking the Billion-Dollar Barrier
A few years ago, OpenAI’s Sam Altman claimed that competing in AI was hopeless without massive investment, high-end chips, crazy powerful servers, and an enormous power supply. That was the playbook followed by tech giants like Google, Meta, and OpenAI, placing them at the mercy of NVIDIA’s specialised AI chips.
However, by making its code fully open-source, DeepSeek ignited an innovation wildfire. Whereas companies like OpenAI and Google have guarded their models like crown jewels, DeepSeek’s transparent approach has empowered developers worldwide – from startup founders in emerging markets to research labs in top universities – to build and customise powerful AI without the need for billion-dollar data centres or the latest high-end chips.
This is exactly what led to the NVIDIA reckoning. The long undisputed king of AI chips saw its stock plummet as demand for its premium hardware wavered. If cheaper, older chips could train state-of-the-art models, what was the point of chasing exascale computing?
Founded by Liang Wenfeng, a reclusive academic driven by scientific curiosity rather than commercial gains, DeepSeek rapidly surpassed ChatGPT in engagement and performance.
The Roadblocks Ahead
Despite its groundbreaking approach, DeepSeek is not without its hurdles. The model’s reliance on deeper, more thoughtful processing sometimes leads to latency issues, with responses taking longer as the system deliberates through its intricate reasoning pathways. This trade-off between depth and speed presents a significant challenge in a market where rapid responses are often prized.
Additionally, DeepSeek has stirred controversy with its built-in censorship policies. By refusing to address questions about China or its government, the platform has faced accusations of promoting a biased narrative, a stance that has sparked both public debate and boycotts. However, the open-source nature of DeepSeek means that users have the option to remove or modify these restrictions, leaving the debate over neutrality open to community-driven solutions.
There’s also an ongoing distillation debate reminiscent of earlier critiques aimed at OpenAI. Concerns have been raised regarding the origins of DeepSeek’s training data, including its reliance on data from OpenAI itself. As the discourse intensifies, DeepSeek must navigate these legal and ethical challenges while maintaining the trust of a global user base. Regardless, there seems to be a general sense of trust in DeepSeek despite its Chinese origin.
DeepSeek’s Breakthrough: A Warning Shot
DeepSeek’s meteoric rise is more than a technical marvel. It’s a harbinger of a new era in AI. By proving that high-performance AI can be built on lean budgets and shared openly with the world, DeepSeek has fundamentally challenged the entrenched monopolies of Silicon Valley. The emerging tech war is no longer a battle of who has the deepest pockets, but who uses their resources with the most ingenuity and efficiency. DeepSeek is doing exactly what its name suggests – digging deeper, seeking smarter. For an industry dominated by colossal players, the lesson is clear: underestimate the underdog at your own peril.
And this is just the beginning.
