NANDKUMAR M. KAMAT
This article analyses the impact of a new disruptive AI chatbot, DeepSeek, which has yet to be probed for originality and needs to undergo thorough probing because the Chinese are masters of intellectual and industrial piracy and capable of smart reverse
engineering.
Mobile and tablet versions of DeepSeek are freely available on GPlay in India, and in less than two weeks since its launch, it has astounded the world. Indians hope the Government of India will not ban it because a Chinese company has developed it.
The emergence of DeepSeek, a Chinese AI chatbot, has sent shockwaves through the global artificial intelligence landscape. With its innovative design, cost-effective development, and strategic market penetration, DeepSeek is challenging the long-standing dominance of Western AI developers. The rapid rise of this chatbot has led to significant economic and technological repercussions, forcing major players such as OpenAI, Google DeepMind, and Microsoft to reconsider
their strategies.
As DeepSeek continues to gain traction, the AI race between China and the West is intensifying, raising critical questions about competition, regulation, and the future of artificial intelligence. DeepSeek has quickly gained global attention, surpassing even OpenAI’s ChatGPT to become the top free AI chatbot app in multiple countries, including the United States, the United Kingdom, and China. Unlike other AI models that require massive computational resources and financial investment, DeepSeek has adopted a more cost-effective and efficient approach to AI development. One of the most striking aspects of DeepSeek’s rise is its low development cost. According to reports, DeepSeek’s R1 model was built for approximately $5.6 million, a fraction of the cost incurred by OpenAI to develop GPT-4, which is estimated to have required over $100 million. The affordability of DeepSeek’s model has demonstrated that high-performance AI does not necessarily require enormous financial or computational resources, disrupting conventional thinking in AI development.
At the core of DeepSeek’s success is its sparse mixture-of-experts (MoE) architecture. This approach allows the model to activate only a fraction of its neurons during processing, making it more efficient and faster while still delivering high-quality results. Additionally, DeepSeek employs test-time computing techniques, which enable it to handle complex reasoning tasks with increased precision. These innovations allow DeepSeek to achieve performance levels comparable to leading AI models from OpenAI and Google despite using significantly fewer resources.
The efficiency and cost-effectiveness of DeepSeek raise important questions about the future of AI research. Traditionally, AI models have required massive datasets, extensive computing power, and well-funded research teams to develop cutting-edge capabilities. However, DeepSeek’s breakthrough suggests that alternative approaches, which emphasise optimisation over brute-force scaling, may be just as viable, if not more so.
DeepSeek’s sudden entry into the AI space has had profound economic consequences, particularly for major Western technology firms. Within days of its launch, global stock markets witnessed a significant downturn, as investors reacted to fears that China’s AI capabilities were advancing more rapidly than expected. One of the biggest losers was Nvidia, the dominant supplier of AI chips, which saw its stock plummet by nearly 17%, wiping out approximately $593 billion in market value in a single day—marking the most significant one-day loss for any company on Wall Street. Other major tech giants, including Microsoft, Alphabet (Google’s parent company), and Meta (Facebook’s parent company), suffered major losses as investors reassessed the competitive landscape. The sudden market shakeup reflects growing concerns that China is poised to challenge Western dominance in AI development. Historically, companies like OpenAI, Google DeepMind, and Microsoft have led the field with cutting-edge research, massive investments, and superior infrastructure. However, DeepSeek’s success highlights that China is rapidly closing the gap—and doing so at a fraction of the cost. Investors are now questioning whether Western firms overestimated the importance of massive investment in AI infrastructure. If high-performance AI models can be developed with relatively minimal financial input, this could reshape the entire industry. Venture capitalists and tech analysts are now debating whether companies like OpenAI need to revise their spending strategies to remain competitive. OpenAI CEO Sam Altman acknowledged DeepSeek’s success and described it as an invigorating challenge that would push AI developers worldwide to improve their models even faster.
One of the biggest concerns for OpenAI, Google, and other Western tech giants is that DeepSeek’s open-source model could undermine their dominance. OpenAI and Google DeepMind have traditionally relied on proprietary models, keeping their most advanced AI systems behind paywalls or within closed platforms. DeepSeek’s decision to embrace open-source AI development could democratise AI research, making it accessible to a broader range of developers and start-ups. Additionally, DeepSeek’s efficiency-driven model has led to renewed discussions about the balance between proprietary and open-source AI development. While OpenAI and Google DeepMind have long emphasised massive computational power as a prerequisite for advanced AI, DeepSeek’s approach suggests that leaner, more efficient models can achieve comparable results. This realisation is prompting Western firms to re-evaluate their AI architectures, focusing more on optimisation and efficiency than brute computational power.
In response to the threat posed by DeepSeek, Western AI firms are adopting several strategic initiatives to maintain their competitive edge. Companies like OpenAI, Google DeepMind, and Microsoft are now exploring ways to optimise their AI models to deliver high performance while using fewer computational resources. The focus is shifting from scaling up models to making them more efficient and cost-effective. DeepSeek’s open-source model has reignited discussions about collaboration in AI development. Some Western AI firms are considering releasing more research papers and models to the public to accelerate innovation. Western AI firms are lobbying policymakers to introduce regulations maintaining transparency and accountability in AI development.
Concerns about data privacy, national security, and algorithmic bias are now being taken more seriously, particularly in response to DeepSeek’s rise. OpenAI has announced plans to release newer, more powerful AI models at a faster pace to stay ahead of DeepSeek and other Chinese competitors. This strategy includes frequent updates and enhanced AI capabilities tailored to specific industries. As competition intensifies, Western AI firms also focus on ethics and safety. They aim to distinguish themselves by emphasising responsible AI development, ensuring that AI systems are transparent, fair, and free from harmful biases.
DeepSeek’s emergence has marked a turning point in the global AI race, challenging the notion that Western companies alone can dictate the future of AI development. The next few years will likely see a wave of innovation, with companies focusing on efficiency, transparency, and ethical AI governance to maintain their edge. Ultimately, DeepSeek’s rise may accelerate global AI development, benefiting the broader industry by lowering costs, increasing accessibility, and diversifying the AI
research landscape.
Whether DeepSeek will permanently alter the AI market remains to be seen. Still, one thing is clear: the AI landscape is no longer a Western-dominated arena, and the competition is only just beginning. Donald Trump stated that DeepSeek is a wake-up call for the U.S.A., but India should also worry about our failure to develop such ‘Made in India’ applications. We need to wait till experts make critical scrutiny and clear it as an original innovation.
