By now, you’ve probably heard about DeepSeek—the AI model that not only dominated headlines this past week but also managed to shake up the stock market, climb to the top of the App Store charts, and even surpass ChatGPT in search volume. But what exactly is DeepSeek, and why did it cause such a massive disruption?
Let’s break it all down and separate the facts from the hype.
The David vs. Goliath Story That Captivated the Internet
The reason DeepSeek’s rise grabbed so much attention is simple: it’s the perfect underdog story. A small Chinese hedge fund—yes, not even a tech giant—took on AI powerhouses like OpenAI, Google, and Anthropic and delivered a model that competes with (and in some cases beats) the best AI models available.
For context, DeepSeek wasn’t even their main focus. The company primarily worked on quantitative trading and just happened to have a bunch of GPUs lying around. So, they decided to experiment with training an AI model. That “side project” turned into DeepSeek, a model that now rivals OpenAI’s most powerful AI.
Now, let’s put this into perspective:
- DeepSeek has fewer than 200 employees (compared to OpenAI’s 5,000+ employees).
- They didn’t have access to top-tier NVIDIA GPUs due to U.S. restrictions.
- They had a training budget of just $5–6 million, which is less than some U.S. CEOs’ yearly salaries.
And yet, against all odds, they created an AI model that competes with OpenAI’s GPT-4-level models. That’s unheard of!
Why DeepSeek Is So Disruptive
So how did they do it? It all comes down to a smarter design rather than brute force compute power.
One of DeepSeek’s standout features is its “thinking process” visibility—a capability that allows users to see step-by-step reasoning behind responses. Here’s an example:
- When asked a simple question like “Give me a random number between 1 and 100,” DeepSeek doesn’t just spit out a number. Instead, it walks through different logical steps, considering how randomness works, debating different approaches, and weighing past responses before settling on a final number. It’s like peeking into the mind of a human problem-solver!
Another mind-blowing example? Medical diagnosis.
- Given a scenario of a child with cough, fever, congestion, and severe calf pain, DeepSeek systematically considered different possible illnesses before concluding the most likely diagnosis: acute viral myositis.
- The accuracy and thoughtfulness in its approach make it feel eerily human.
And here’s the kicker: OpenAI’s GPT-4-level models also have this “thinking” feature, but it’s only available to paid users. Meanwhile, DeepSeek offers it for free to everyone.
DeepSeek’s Open-Source Advantage
Another game-changer? DeepSeek is open source (technically, “open weights”).
Unlike OpenAI, which keeps its most powerful models closed off, DeepSeek allows anyone to download and run it on their own servers—even offline. That means developers, researchers, and companies worldwide can freely experiment with and improve upon it.
This has massive implications:
- AI is no longer in the hands of just a few corporations.
- Innovation is no longer bottlenecked by restrictive closed-source models.
- Open-source AI may now outpace proprietary models in development speed.
Even Meta’s Chief AI Scientist, Yann LeCun, praised this shift, emphasizing how open research fuels rapid progress.
The Stock Market Chaos
DeepSeek’s rise didn’t just shake the AI world—it sent shockwaves through the stock market.
- NASDAQ dropped nearly 3%.
- Google’s stock fell over 4%.
- NVIDIA plunged almost 20%—a $600 BILLION loss in one day.
Why? Because DeepSeek proved that you don’t need the most expensive GPUs or billions of dollars to create top-tier AI models. Investors freaked out, thinking that NVIDIA’s dominance in AI hardware might not be as critical as once thought.
The Path to AGI Just Got Shorter
Beyond the market chaos, DeepSeek’s breakthroughs hint at something even bigger: a faster path to Artificial General Intelligence (AGI).
Here’s why:
- DeepSeek used reinforcement learning to train itself—meaning it learned by figuring things out on its own rather than just copying human examples.
- It then used its own knowledge to train an even smarter version of itself.
- If this process is repeated over and over, AI models could improve exponentially without human intervention.
This self-learning approach could accelerate AGI’s arrival much sooner than expected. In fact, big tech companies are likely already cloning DeepSeek and scaling it up with even more compute power.
Final Thoughts: The AI Race Just Got Interesting
DeepSeek isn’t just another AI model—it’s a symbol of what’s possible without massive resources. It challenges the narrative that only trillion-dollar companies can dominate AI and pushes the entire industry toward more accessible, open AI development.
Even OpenAI’s Sam Altman acknowledged DeepSeek’s impressive achievement, saying it’s “invigorating” to have a new competitor.
And as for DeepSeek’s CEO, Liang Wenfeng? He’s not concerned about money, competition, or even being copied. His goal? Achieving AGI.
So, buckle up. AI is evolving faster than ever—and the race to AGI just got a whole lot more interesting.
