OpenAI invested over $100 million to train GPT-4. DeepSeek AI achieved similar capabilities at a fraction of the cost, just $6 million. This money-saving idea helped DeepSeek beat ChatGPT. It became the most downloaded free app on Apple’s App Store in the U.S.
DeepSeek has become a game-changer since its launch in July 2023. The company’s impact was so substantial that it caused Nvidia to lose $600 billion in market value. The company’s R1 model is very cheap. It costs 20 to 50 times less than other AI models. Still, it works just as well as the top ones.
This article will talk about DeepSeek’s amazing story. It will show its smart technology. It will also explain why big tech companies like Amazon are watching it closely. Their rise has sparked intense discussions about artificial intelligence’s future.
The Rise of DeepSeek: A New AI Challenger:
Liang Wenfeng, a 40-year-old entrepreneur, leads DeepSeek’s remarkable growth. His special journey from finance to AI changed the tech world. He mixes money skills with tech knowledge. This makes him unlike most Silicon Valley founders. It also helps DeepSeek grow very quickly.
Who is Liang Wenfeng, the mind behind DeepSeek?
Teacher’s parents raised Liang in China’s southern Guangdong province in 1985. He was known as a “top student” because he was very good at math. His strong grades took him to Zhejiang University. There, he got his bachelor’s and master’s degrees. He studied information and communication engineering. He completed both by 2010.
Liang stands out in the AI world through his analytical mindset and ambitious vision. People call him the “Sam Altman of China.” He supports AI growth and research investment. In his few public talks, he says China should lead in AI, not just follow others. “Chinese AI cannot always stay behind,” Liang said in a November interview. The main challenge is the difference between being original and copying others” from hedge fund to AI powerhouse.
How Lian Built DeepSeek:
Liang’s journey with DeepSeek began in 2015. That year, he co-founded a hedge fund called High-Flyer. It was a quantitative fund that focused on data and algorithms. The fund used mathematical models to guide investment choices. Success followed quickly – High-Flyer grew to manage about $14 billion in assets by 2021..
A breakthrough came when High-Flyer launched its first AI model in October 2016. The model enabled stock position decisions based on AI predictions. By 2017, AI models managed nearly all the fund’s stock positions. This showed Liang’s early interest in using artificial intelligence.
Liang made a smart move in 2021. He bought thousands of Nvidia graphics cards. This was before the US government banned its export to China. This strategic decision laid the foundation for DeepSeek’s future innovations.
DeepSeek officially started in July 2023 with a modest $1.4 million as the original capital. The company proved its worth quickly. In November 2023, DeepSeek released DeepSeek Coder. Later that month, the company also launched the DeepSeek-LLM series.
How DeepSeek Disrupted the AI Market:
In December 2023, DeepSeek shocked the global tech world. The company announced a powerful new AI model that gained worldwide attention. Their statement was simple yet extraordinary.
The $6 million claim that shook Silicon Valley:
DeepSeek made a bold claim. It said its large language model could match or even beat top industry leaders. The cost? A mere $5.60 million was spent over two months. This amount was small compared to OpenAI’s GPT-4. Reports say GPT-4 costs between $80 million and $100 million to train. On top of that, the Chinese startup’s DeepSeek-R1 model runs at 20-50 times lower cost than OpenAI’s O1 model.
The success was even more impressive because DeepSeek used Nvidia’s basic H800 chips. Most top AI systems run on the more powerful H100 GPUs. Meta’s Llama 3 needed 16,000 GPUs, yet DeepSeek claimed success with just 2,000.
Impact on tech stocks and Nvidia:
Stock markets reacted swiftly and harshly. Tech stocks dropped sharply. Investors began to question the huge spending by major US tech companies. The numbers tell the story:
- Nvidia lost a record-breaking $600 billion in market value within a day.
- Nvidia and Broadcom saw their stocks plunge 17%.
- VanEck Semiconductor ETF dropped 9.8%.
- Oracle’s shares fell 13.8%.
One analyst put it plainly: “DeepSeek’s rise could be bad news for the Magnificent 7,” experts said. These big tech companies had planned to control the AI market with their costly AI services.
Why investors and competitors are paying attention:
DeepSeek’s rise signals a major transformation in the AI landscape. Marc Andreessen compared DeepSeek-R1 to “AI’s Sputnik moment.” He said it was similar to the space race between the US and the Soviet Union. Microsoft CEO Satya Nadella described it as “very impressive.” Skepticism remains about the complete picture. Some experts say the $6 million figure is misleading. It doesn’t include the years of research and infrastructure costs behind it. They believe it might only reflect the final training costs. Even so, DeepSeek made big tech companies rethink their AI costs and strategies. It forced the industry to look for smarter and cheaper ways to build AI.
DeepSeek vs ChatGPT: A Practical Comparison
DeepSeek and ChatGPT both call themselves top AI chatbots. However, they work very differently in daily use. Let’s explore what makes each one unique and where it really counts.
User experience differences:
DeepSeek keeps things simple compared to ChatGPT’s feature-packed interface. Right now, DeepSeek lacks many features that ChatGPT users rely on. For example, DeepSeek can’t analyze images. This is a major drawback for users who rely on ChatGPT’s image tools. DeepSeek also lacks ChatGPT’s many interface options and voice features.
DeepSeek’s strength lies in showing how it thinks. Users love how it breaks down problem-solving into clear steps. The AI uses a step-by-step method. It shows how it reached each conclusion. This helps users learn how the AI reasons.
Performance in everyday tasks:
Both AI models handle common tasks well. DeepSeek really shines with math problems and systematic problem-solving. Both write well. However, users say DeepSeek organizes information in a clearer and easier way.
DeepSeek often performs better with technical questions. It understands context well and explains its logic clearly. The platform works best with specialized questions and technical problems. ChatGPT, on the other hand, excels at creative writing and handles topics of all types with ease.
Pricing and accessibility:
The biggest difference between these platforms comes down to cost. DeepSeek gives users free access with about 50 R1 messages daily. ChatGPT’s free version has many limits, and users need to pay $20 monthly to unlock better features.
Businesses and developers using the API see an even bigger price gap:
DeepSeek: DeepSeek costs $0.55 per million input tokens and $2.19 per million output tokens.
In comparison, OpenAI’s GPT-4.1 costs about $15 per million input tokens and $60 per million output tokens. These low prices are possible because DeepSeek is designed smartly. It only uses the parameters needed for each task instead of using them all every time.
In the end, both platforms serve different users. DeepSeek is great for those on a budget who need technical support. ChatGPT is better for people who want creative freedom and advanced features.
Security and Privacy Considerations:
Privacy issues surround DeepSeek AI. Users need to understand this complex security situation before they start using it. Let’s get into what really happens when you interact with this powerful Chinese AI model.
Data handling practices:
DeepSeek gathers a vast amount of user information. The company’s privacy policy shows they record almost everything. This includes your typing patterns, IP address, device model, and system language. The company doesn’t stop at simple device data. They also gather personal details such as your birth date, email, phone number, and password. The AI saves everything you share, including text, voice prompts, and uploaded files.
Security experts have raised red flags about data handling methods. The Security Scorecard’s STRIKE team found several problems. They discovered weak encryption, possible SQL injection flaws, and hidden data sharing. The app uses outdated encryption with fixed keys. This makes it easier for hackers to steal sensitive user data.
Regulatory concerns in different countries:
Governments have been quick to react to DeepSeek’s privacy practices. Italy’s data protection agency blocked the app. Officials said DeepSeek’s privacy policy was “totally insufficient.” France, Belgium, Ireland, and South Korea are now investigating possible data privacy problems.
U.S. Congress members have told their staff not to use the app. The U.S. Navy has banned its members from using the chatbot due to security risks. Australia and Taiwan don’t allow the app on any government devices.
What happens to your data when using DeepSeek?
The biggest concern is that DeepSeek sends all collected data to servers in China. Chinese law requires companies to share user data if the government asks for it. No public reports show that officials have used DeepSeek to collect personal data. Still, privacy experts remain worried.
Experts suggest these safety measures:
- Don’t sign up with Gmail or Apple accounts.
- Don’t share personal information in your questions.
- Use a VPN to mask your location.
The Future of DeepSeek and Chinese AI:
DeepSeek’s fast growth is still shaping the AI world. The company is already working on even more advanced models.
Upcoming models and features, DeepSeek has fast-tracked the release of its R2 model. The launch was originally scheduled for May 2025, but now has an earlier priority. This next-generation model promises improved coding capabilities and multilingual reasoning beyond English. The company launched its first consumer-facing app in January 2025. They also launched the DeepSeek-Janus-Pro model. It can both understand and create visual content.
The company plans to release five code repositories in February 2025. These will include their open-source R1 reasoning model. DeepSeek also introduced a new algorithm called Native Sparse Attention (NSA). The algorithm makes long-context training and inference quicker.
How DeepSeek is changing the AI world:
DeepSeek’s open-source approach differs from its competitors’ proprietary systems. The company shares its code and technical documents for free. The company shares its code and technical guides for free. This is different from OpenAI’s ChatGPT and Anthropic’s Claude. By removing license fees, DeepSeek makes advanced AI tools available to more people. It also helps reduce the power of big AI companies.
DeepSeek also breaks the idea that AI needs huge computer power to grow. Their smart and simple models show that good software and hardware can do better than raw power. They made big tech companies rethink whether billion-dollar GPU clusters are really needed. DeepSeek shows that top AI models can be trained simply and efficiently.
What this means for the US-China tech competition:
DeepSeek’s achievements highlight China’s growing technological self-reliance. The company’s success validates China’s Innovation 2.0 era within the country. The U.S. national security group is worried. They think DeepSeek’s strong results may hurt their competitiveness
Still, DeepSeek’s new ideas may help U.S. companies more than Chinese ones. American firms can use these smart methods with their big computer power. This can help them make better AI for more people. Both countries should also share ideas safely to keep AI development secure.
Conclusion:
DeepSeek’s fast progress shows that new AI methods can quickly beat old industry rules. Their success has changed how we see AI growth and use. Still, some people doubt their claim of spending only $6 million.
DeepSeek’s future faces security concerns and regulatory hurdles. Their new way of building AI and sharing it openly helps people learn more about the industry. It’s especially useful when training methods are low-cost and efficient.
Smart optimization and fast algorithms may lead to the next big change in AI. Massive computer power might not be needed anymore. This change can help both Chinese and American companies. But strong safety rules are important for global cooperation.
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