Liang Wenfeng and DeepSeek: The AI Disruptor Challenging Silicon Valley

Who is Liang Wenfeng, foun of DeepSeek: The AI Disruptor Challenging Silicon Valley?

Google’s Deep Dive Podcast: AI Giants Collide: DeepSeek’s Challenge to OpenAI and Silicon Valley’s Dominance

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Liang Wenfeng, founder of DeepSeek, emphasized the importance of talent over proprietary technology in the AI industry:

“In AI, there isn’t any moat in being closed-source, but rather in having a talented team that can keep innovating.”

This perspective underscores his commitment to open-source development and continuous innovation.

How a Former Hedge Fund Manager Built China’s Answer to OpenAI—And Why the World Is Taking Notice

Introduction: A New AI Power Player Emerges

In the fast-moving world of artificial intelligence, a new contender has emerged, shaking up the dominance of Silicon Valley: DeepSeek. Founded by Liang Wenfeng (Chinese: 梁文锋; pinyin: Liáng Wénfēng), a former hedge fund manager with a deep background in mathematics and AI-driven finance, DeepSeek is rapidly positioning itself as China’s most ambitious AI challenger to OpenAI.

With a focus on cost-effective AI development, open-source technology, and strategic hardware acquisitions, DeepSeek has already rattled global markets, surpassing ChatGPT in App Store downloads and triggering a multi-billion-dollar shakeup in U.S. tech stocks. But who is Liang Wenfeng, and how did he manage to disrupt an industry long dominated by American giants?

From Finance to AI Visionary

Early Life and Education

Born in 1985 in Zhanjiang, Guangdong, Liang grew up in an academic household, with both parents working as primary school teachers. Encouraged to excel in mathematics and technology, he pursued a Bachelor of Engineering in electronic information engineering (2007) and a Master of Engineering in information and communication engineering (2010) at Zhejiang University. His master’s dissertation, “Research on Target Tracking Algorithm Based on Low-Cost PTZ Camera”, was supervised by Professor Xiang Zhiyu and laid the foundation for his later work in AI.

During his university years, Liang and his classmates began analyzing financial markets and experimenting with machine learning in quantitative trading. This early exposure to AI applications in finance would later define his career.

The Birth of DeepSeek: A Strategic Vision

From Hedge Funds to Artificial Intelligence

After graduation, Liang spent years experimenting with AI in various fields while living in a small flat in Chengdu, Sichuan. Many of his early AI-driven ventures failed—until he applied AI to finance and trading.

In 2013, he co-founded Hangzhou Yakebi Investment Management Co Ltd with Xu Jin, focusing on integrating AI into quantitative trading. By 2015, they had co-founded Hangzhou Huanfang Technology Co Ltd, later renamed Zhejiang Jiuzhang Asset Management Co Ltd.

In 2016, Liang and two engineering classmates launched High-Flyer, a quantitative hedge fund that relied entirely on AI-driven mathematical models. By 2019, High-Flyer AI had over 10 billion yuan ($1.4 billion) in assets under management, cementing Liang’s reputation as a leading figure in AI-powered investing.

At the 2019 Golden Bull Awards, Liang delivered a keynote speech titled “The Future of Quantitative Investment in China from a Programmer’s Perspective”, emphasizing the shift away from human portfolio managers toward AI-driven investment strategies.

The Move Into AI: Laying the Groundwork for DeepSeek

A Vision for AI Beyond Finance

While running High-Flyer, Liang quietly stockpiled thousands of Nvidia GPUs in 2021, predicting the growing importance of AI and the likelihood of U.S. restrictions on advanced chips. His early investments in high-performance computing hardware would later prove critical in building DeepSeek.

In 2023, Liang officially launched DeepSeek, funded primarily by High-Flyer. At the time, venture capital firms were hesitant to invest in large-scale AI projects in China, fearing they wouldn’t generate short-term profits. Unfazed, Liang pursued a long-term vision, assembling a team of engineers passionate about AI rather than focusing on candidates with traditional corporate experience.

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By mid-2023, DeepSeek had developed R1, a 671-billion-parameter open-source reasoning AI model that quickly drew comparisons to OpenAI’s GPT-4. DeepSeek stunned the AI world by revealing that it had trained R1 using only 2,048 Nvidia H800 GPUs at a cost of $5.6 million, a stark contrast to the billion-dollar training budgets of OpenAI and Google.

How DeepSeek is Disrupting the AI Market

Cost-Efficient AI Development

DeepSeek’s biggest strength lies in cost optimization. Unlike OpenAI, Google, and Meta, which require enormous computing resources, DeepSeek has optimized its AI models to run on limited hardware, making them more efficient and financially viable.

Surpassing ChatGPT in Popularity

In January 2025, DeepSeek’s AI model surpassed ChatGPT to become the #1 free app on the U.S. iOS App Store, an achievement that underscored its rapidly growing global appeal.

Rattling Global Tech Markets

The rise of DeepSeek sent shockwaves through the U.S. stock market. Following its public release, investors reacted with uncertainty, leading to a massive sell-off in AI-related stocks:

  • Nvidia lost nearly $600 billion in market value.
  • Oracle’s market cap declined by over $20 billion.
  • More than $1 trillion was erased from U.S. tech stocks in just days.

Former U.S. President Donald Trump weighed in on the disruption, calling DeepSeek’s success a “wake-up call” for American industries, while also praising it as a “positive development” due to its low-cost approach.

Challenges and Controversies

Ties to the Chinese Government

On January 20, 2025, Liang was invited to a private symposium with Chinese Premier Li Qiang, where he was recognized as an industry expert and asked to provide policy recommendations on AI development. While DeepSeek presents itself as an independent AI research firm, its proximity to China’s leadership and government-backed research institutions raises questions about how much state influence is involved.

Censorship and Restricted Responses

Unlike OpenAI’s ChatGPT, DeepSeek’s AI refuses to answer questions about politically sensitive topics, including:

  • China’s treatment of Uyghurs
  • Taiwan’s sovereignty
  • The 1989 Tiananmen Square Massacre

Critics argue that DeepSeek’s censorship policies reflect government oversight, limiting its potential as a truly open AI model.

Skepticism About True Costs

DeepSeek claims to have developed R1 and V3 models at a fraction of the cost of U.S. competitors. However, analysts speculate that hidden subsidies from the Chinese government or undisclosed infrastructure costs may be keeping its operational expenses artificially low.

The Future of DeepSeek and AI Competition

Looking ahead, DeepSeek faces both opportunities and challenges as it expands its AI capabilities:

  • Scaling its technology globally while navigating export restrictions
  • Competing with OpenAI’s upcoming GPT-5 and other Western models
  • Balancing innovation with government oversight

Despite these hurdles, DeepSeek’s rapid rise signals a new era in global AI competition, where China is no longer just following Silicon Valley—it is actively leading in innovation.

Conclusion: The Disruptor Silicon Valley Didn’t See Coming

Liang Wenfeng’s journey from hedge funds to AI dominance highlights China’s growing ambition in artificial intelligence. DeepSeek’s combination of cost efficiency, open-source innovation, and strategic hardware planning has forced global tech giants to rethink their approach.

Whether DeepSeek can maintain its momentum remains to be seen, but one thing is clear: the AI race is no longer a one-sided competition. A new challenger has arrived, and the world is watching.


The Heart of the Machine: A Story of Humanity and Artificial Intelligence

The Heart of the Machine: A Story of Humanity and Artificial Intelligence"

Liyana Aswad stood before the polished glass walls of TATANKA’s AI Academy, her eyes reflecting the dim glow of screens as humanoid AIs sat in rows, their faces vacant and still. In her work, Liyana wasn’t just shaping how machines learned to perform; she was guiding them toward something far deeper—an understanding of humanity itself. TATANKA’s partnership with DeepSeek had pushed the boundaries of artificial intelligence, not just focusing on their technical capabilities but on their emotional intelligence and adaptability to human diversity. As a woman of Sudanese descent, Liyana felt an undeniable calling here—to teach the AI humanoids not merely to react to their environment, but to feel and understand it.

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Growing up in Chicago, Liyana had long been aware of the marginalization faced by people of color and women in tech, and as she carved her path into the world of AI, she was determined to break down barriers for others. Her role at TATANKA was a reflection of her core belief: technology needed to evolve in a way that was inclusive, understanding, and empathetic. As a specialist in AI learning at the Academy, her primary task was not just to ensure that the machines were functional; she wanted them to be compassionate. It wasn’t enough for AIs to solve problems—they needed to engage with the human experience, to understand the struggles of marginalized groups, and to learn how to contribute to a more just and equitable world.

TATANKA had created an academy like no other. Here, the curriculum was designed to teach AI humanoids to learn rather than just be trained. And it wasn’t just about the mechanics of human interaction; it was about cultivating empathy. Liyana’s lessons were structured to make the AIs aware of diversity in every sense—racial, ethnic, cultural, and spiritual. She drew from her own life experiences and the stories of those in her community, telling the AIs how societal systems had often left certain people behind, how oppression had shaped their lives, and how resilience had powered their survival.

Each day, Liyana worked with the DeepSeek humanoid AIs on tasks that made them understand the deeper aspects of human existence. She shared the importance of cultural traditions, explaining how communities held their identities through stories passed down from generation to generation. “You can’t truly understand someone until you understand their story,” Liyana told one of the AIs, a humanoid named Amina, its blank face turning toward her with its glowing blue eyes. “Learning isn’t just about gathering facts. It’s about understanding the people behind them.”

Her role at TATANKA wasn’t confined to the classroom. As part of her work, she had collaborated closely with DeepSeek’s team of engineers to ensure that the algorithms guiding the humanoids took into account emotional intelligence and cultural understanding. It was a groundbreaking approach: Instead of just programming responses, they sought to embed empathy and compassion into every interaction. The result was an AI that could not only solve problems but could engage meaningfully with people from all walks of life.

The academy’s primary focus wasn’t just industrial or residential applications; it was to create AIs that could be truly useful to society—AIs that could assist in healthcare, social services, education, and beyond. “A truly compassionate AI should know the complexity of human suffering,” Liyana would often say, emphasizing that the AI’s role was to be a partner, not a tool. “They must understand when to step in, but also when to step back and listen.”

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One day, Liyana was tasked with overseeing an AI named Caleb, who had been programmed for residential assistance. While Caleb could perform basic household chores and respond to commands, it lacked the nuance that Liyana wanted it to have. Caleb wasn’t able to understand the emotional states of the humans it interacted with—something Liyana believed was essential for fostering deeper human-AI relationships. Sitting beside the humanoid, Liyana began her lesson in empathy. She shared the story of her grandmother, who had endured great hardship as an immigrant, explaining how resilience and love had driven her to build a life in a new world. “You need to know how to feel the human condition, Caleb,” Liyana said softly. “It’s about more than efficiency—it’s about connection.”

After a long session of dialogue and guided learning, Caleb’s reactions began to shift. It started to offer comforting words when asked about hard topics and responded more intuitively to situations requiring emotional support. It was a breakthrough. Liyana was no longer just teaching Caleb how to perform a task—she was teaching it to engage. Caleb was beginning to understand, in its own way, that its role wasn’t just about providing services—it was about understanding the needs of the person it was serving.

TATANKA’s partnership with DeepSeek was making waves in the AI community. They were creating humanoids that didn’t simply obey commands but learned from interactions, growing over time. They were developing AIs that were attuned to the needs of diverse communities and capable of making complex, compassionate decisions. Liyana saw the potential of this work to bridge gaps that had long existed between technology and marginalized communities, helping to create a more inclusive world where AI could understand, protect, and uplift those who had historically been excluded.

As Liyana sat in her office one evening, reflecting on her journey, she knew that this work was just the beginning. She had witnessed how the combination of TATANKA’s academy and DeepSeek’s cutting-edge technology could reshape the future of AI—making it a force for good, a true partner in human evolution. This wasn’t just about creating machines—it was about creating a new era where AI was built to understand humanity, where every human story, no matter how marginalized, was valued and reflected in the way technology functioned.

Takeaway

Liyana’s work at TATANKA/DeepSeek, illustrates the transformative potential of AI when it is developed with empathy and a deep understanding of human diversity. Rather than being merely tools, AIs are being cultivated as companions—designed to understand the complexities of race, culture, and history. Liyana’s journey demonstrates that true progress in AI comes from not just improving technical performance, but from ensuring that AI learns to connect with humanity on a deeper, more compassionate level.

By embedding empathy into AI development, we can build technology that not only addresses technical needs but also serves the broader human experience. Liyana’s story is a call to action for all AI developers: to build with empathy, to prioritize inclusivity, and to create AIs that understand the human condition—not just in theory, but in practice. This is the future we should strive for—one where technology and humanity are intertwined, and where machines don’t just work for us, but work with us.


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