DeepSeek: Chinese AI Disrupts Crypto Market

January 31, 2025 9 min
Daniel Bennett Twitter
Daniel Bennett
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DeepSeek: Chinese AI Disrupts Crypto Market
Table of contents
  • Reasons Behind the Hype Surrounding DeepSeek AI
    • The Architect of DeepSeek: Liang Wenfeng and China's AGI Ambitions
  • DeepSeek's AI Arsenal: A Focus on Efficiency 
  • DeepSeek's Stock Market Shockwave: A Tech Sell-Off and Rebound
  • DeepSeek's Geopolitical Tremors: National Security and the AI Arms Race
Table of contents
  • Reasons Behind the Hype Surrounding DeepSeek AI
    • The Architect of DeepSeek: Liang Wenfeng and China's AGI Ambitions
  • DeepSeek's AI Arsenal: A Focus on Efficiency 
  • DeepSeek's Stock Market Shockwave: A Tech Sell-Off and Rebound
  • DeepSeek's Geopolitical Tremors: National Security and the AI Arms Race
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DeepSeek, a Hangzhou-based startup founded in 2023, has rapidly emerged as a significant player in the AI landscape, challenging the dominance of established US firms like OpenAI and Google. This article explores the reasons behind DeepSeek's sudden rise, its impact on the market, and the controversies surrounding its development and deployment.

Reasons Behind the Hype Surrounding DeepSeek AI

DeepSeek's sudden rise to prominence in the AI industry can be attributed to a combination of factors, leading to both excitement and controversy. The company's claim of developing high-performing models for only $6 million has sparked interest and skepticism. Some experts argue that, while this figure may reflect training costs, it fails to account for significant expenses such as data acquisition and research. 

Although DeepSeek reportedly used less powerful GPUs available in China, its success is also due to advanced post-training techniques. This cost-effectiveness, however, has alarmed investors, resulting in a "DeepSeek selloff" and raising concerns about the future demand for high-end GPUs. 

Additionally, DeepSeek's open-source approach and the growing desire for alternatives to US-based AI providers enhance its attractiveness. However, the model's strict censorship raises concerns about information control, while its demonstrated weaknesses in AI safety have drawn scrutiny. 

Moreover, claims about DeepSeek's superior energy efficiency are disputed, with some studies suggesting that its performance in this area may be exaggerated. Finally, DeepSeek's emergence has geopolitical implications, igniting discussions about US competitiveness in AI and potential government responses, including possible bans similar to those imposed on other Chinese tech companies. 

DeepSeek has captured the attention of the tech world for several reasons:

  • Competitive Performance: DeepSeek's AI model, DeepSeek-V3, reportedly surpasses the performance of leading US models in various benchmarks. This has surprised many, considering the company's relatively small size and the significantly lower development cost compared to its competitors.
  • Cost-Effectiveness: DeepSeek claims to have developed its model for just $6 million, a fraction of the billions invested by OpenAI and Google. This has sparked both excitement and skepticism, with some experts questioning the accuracy of the reported cost.
  • Open-Source Approach: Unlike many proprietary AI models, DeepSeek has adopted an open-source approach, making its technology more accessible to developers and researchers. This fosters transparency and encourages wider adoption of AI technologies.
  • Desire for Alternatives: The AI landscape is evolving rapidly, and businesses are increasingly seeking alternatives to US-based AI providers. DeepSeek offers a compelling option, for those seeking greater transparency, flexibility, and lower costs.

The Architect of DeepSeek: Liang Wenfeng and China's AGI Ambitions

Liang Wenfeng, the 39-year-old founder of DeepSeek, has rapidly become a prominent figure in China's tech landscape, embodying the nation's aspirations to overcome US export controls and achieve leadership in artificial intelligence. Maintaining a low profile until recently, Liang's presence at a closed-door symposium hosted by Premier Li Qiang signaled Beijing's recognition of DeepSeek's potential to reshape the global AI order. While DeepSeek's recent launch of a cost-effective AI assistant has garnered global attention, Liang's vision extends far beyond commercial applications. Unlike other Chinese tech leaders who have focused on scaling existing innovations, Liang has prioritized fundamental research and development, specifically targeting the creation of Artificial General Intelligence (AGI). This commitment to originality, a departure from China's traditionally imitative approach, reflects Liang's belief that the nation's tech industry must embrace fundamental breakthroughs to truly compete on the world stage. DeepSeek's open-source strategy, mirroring a practice previously championed by US tech insiders, further underscores Liang's commitment to fostering innovation and building "soft power" within the AI community. His background, spanning from academic pursuits at Zhejiang University to co-founding a successful quantitative hedge fund, demonstrates a blend of intellectual curiosity and business acumen. The hedge fund's eventual pivot towards AI research, culminating in the creation of DeepSeek, underscores Liang's dedication to tackling the "world's hardest problems" and attracting top talent who share his ambition to achieve AGI. Liang's journey reflects a broader shift in China's tech industry, moving beyond imitation towards original innovation and a long-term vision for AI dominance.

DeepSeek's AI Arsenal: A Focus on Efficiency 

Source: panewslab

DeepSeek has rapidly emerged as a competitor to OpenAI, albeit with a distinct approach. While OpenAI, founded in 2015, has focused on broad AI capabilities and a range of specialized models (like DALL-E and Whisper), DeepSeek, established in 2023, prioritizes efficient, open-source models with a strong emphasis on reasoning. This difference is reflected in their flagship models: OpenAI's GPT-4 and o1 versus DeepSeek's V3 and R1. DeepSeek's training approach diverges significantly from OpenAI's supervised and instruction-based fine-tuning. DeepSeek leverages reinforcement learning, a sophisticated reward engineering system, knowledge distillation for model compression, and an "emergent behavior network" where complex reasoning arises organically. These innovations have allowed DeepSeek to achieve comparable performance to OpenAI's o1, particularly in reasoning tasks, but at a dramatically lower cost. DeepSeek claims its R1 model cost less than $6 million to develop, a stark contrast to the hundreds of millions estimated for OpenAI's o1. This cost advantage stems partly from DeepSeek's efficient training methods and partly from its use of less expensive hardware. DeepSeek's model development has been rapid, with a series of releases since its inception. These include DeepSeek Coder for coding tasks, the general-purpose DeepSeek LLM, and increasingly powerful versions like DeepSeek-V2 and DeepSeek-Coder-V2. The current flagship models, DeepSeek-V3 and the reasoning-focused DeepSeek-R1, both boast 671 billion parameters and a 128,000 token context window. DeepSeek has also branched out into vision with Janus-Pro-7B, demonstrating its ambition to compete across various AI domains. 

Janus and Janus-Pro-7B: Expanding DeepSeek's Capabilities

DeepSeek continues to expand its offerings with the release of Janus-Pro-7B, an open-source AI model designed for text-to-image generation. This move signals DeepSeek's ambition to compete across multiple AI disciplines, further challenging the dominance of established players.

DeepSeek's commitment to open-source models and its focus on efficient training and advanced reasoning capabilities position it as a significant disruptor in the AI landscape.

DeepSeek's Key Features and Applications

DeepSeek offers a range of features and capabilities that make it a versatile AI tool for various applications:

  • Natural Language Processing (NLP): DeepSeek excels in handling complex language tasks, including multi-step reasoning and structured data interpretation.
  • Technical Focus: The model is reportedly more reliable for coding, math, and structured data processing, making it well-suited for tasks requiring precision.
  • Efficiency: DeepSeek's MoE architecture allows for efficient processing by activating only the necessary parts of the model for each request.

DeepSeek's Stock Market Shockwave: A Tech Sell-Off and Rebound

DeepSeek's arrival has not only disrupted the AI landscape but also sent shockwaves through the stock market, particularly impacting tech giants. The initial reaction to DeepSeek's launch was a dramatic sell-off, with the Nasdaq plunging and Nvidia experiencing a record one-day loss of approximately $600 billion in market capitalization. This drastic decline was fueled by concerns over DeepSeek's potential to undercut US AI companies with its lower development costs and cheaper, open-source models. The sell-off extended beyond Nvidia, impacting semiconductor, power, and infrastructure companies exposed to AI, collectively losing over $1 trillion in value.

However, this initial panic subsided as investors reassessed the situation. Bargain hunters saw an opportunity, leading to a partial recovery in tech stocks. Nvidia rebounded with an 8.9% gain, while the broader tech sector rallied by 3.6%. This rebound suggests that while DeepSeek's emergence is a significant development, investors recognize the continued demand for high-performance AI solutions, regardless of the availability of lower-cost alternatives.

The DeepSeek episode has highlighted several key aspects of the current market:

  • AI-related stock valuations: The sell-off has prompted a reassessment of AI-related stock valuations, with investors likely to exercise more caution moving forward.
  • Demand for both high-performance and cost-effective AI: The market is expected to accommodate both high-performance AI solutions, like those offered by Nvidia, and more economically viable offerings like DeepSeek.
  • Investor Confidence: Despite the initial shock, the rebound demonstrates a degree of resilience and confidence in the long-term growth prospects of the AI industry.

DeepSeek's impact on the stock market underscores the significant influence that AI advancements can have on investor sentiment and market dynamics. As the AI landscape continues to evolve, we will likely see further fluctuations and adjustments as the market adapts to innovations and competitive pressures.

DeepSeek's Geopolitical Tremors: National Security and the AI Arms Race

DeepSeek's rapid ascent has triggered significant geopolitical concerns, particularly within the US, where its potential impact on national security and the broader AI arms race is being intensely scrutinized. The company's Chinese origins and the capabilities of its AI models have sparked fears of espionage, influence campaigns, and a shift in the balance of power in the global AI landscape.

National Security Concerns:

  • Data Security and Privacy: DeepSeek's data collection practices and the location of its servers in China have raised alarms about the potential misuse of user data. Concerns center on the possibility of the Chinese government accessing sensitive information shared with DeepSeek, as well as the company's ability to comply with US data privacy regulations.
  • Espionage and Influence Campaigns: The US Navy's ban on DeepSeek reflects concerns that the Chinese government could leverage DeepSeek's AI models to conduct espionage, influence operations, and steal proprietary secrets from American citizens.
  • AI Arms Race: DeepSeek's rapid progress has intensified concerns about the AI arms race between the US and China. The company's achievements challenge the notion of US dominance in AI and highlight the need for continued investment and innovation to maintain a competitive edge.
     

Differing Perspectives on DeepSeek's Risks:

While some experts emphasize the unique risks posed by DeepSeek, others argue that its data collection practices are comparable to those of its American counterparts. They caution against using DeepSeek's rise as a pretext for deregulation, drawing parallels to the ongoing debate surrounding TikTok and its data security implications.

Calls for Action and Industry Safeguards:

DeepSeek's emergence has prompted calls for various actions, including:

  • Increased scrutiny and potential bans: The US government is considering stricter measures, such as export controls on technologies underpinning DeepSeek's infrastructure or even an outright ban on the company itself.
  • Investment in American AI: Industry leaders and policymakers are advocating for increased investment in the American AI sector to maintain competitiveness and counter the perceived threat from China.
  • Industry safeguards: AI ethicists emphasize the need for robust industry safeguards and regulations to protect user data and mitigate the potential harms of AI, regardless of its origin.

DeepSeek's rise has ignited a complex debate about the intersection of AI, national security, and geopolitical competition. As the company continues to evolve and its impact becomes clearer, navigating these challenges will require a nuanced approach that balances innovation, security, and ethical considerations.

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