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Four Ways DeepSeek Could Change Everything

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The release of DeepSeek’s highly effective and cost-efficient large language model has made waves in the AI industry, promising far-reaching implications for technology, trade, and U.S.-China economic relations. While the immediate market impact may have been brief, the long-term effects could be profound. Here are four predictions on how DeepSeek might shape the future:

  1. Artificial Intelligence Costs Will Continue to Plummet
    Innovations typically aim to achieve more with less, and AI is no different. Before DeepSeek’s release, the costs of leading AI models had already fallen by about 80% annually over the past two years. DeepSeek has accelerated this trend by making AI models 30 times cheaper compared to market leader OpenAI, through algorithmic advancements and aggressive pricing strategies. This deflationary trend is expected to persist as more research and competition in the AI field drive costs lower.

  2. The AI Economic Pie Will Get Bigger and Be Sliced Differently
    As AI becomes more affordable and accessible, demand is expected to grow, following the concept of Jevons paradox, which suggests that more efficient technology leads to greater consumption of resources. As foundational models become commoditized, the focus will shift to applications, pushing more resources toward the deployment of AI in specific tasks, or “inference,” rather than training models. This shift could spark increased demand for custom-designed chips like XPUs, optimized for specific AI applications, as opposed to traditional GPUs. Nvidia has already observed that demand for inference chips is growing faster than for training chips, signaling a broader industry shift.

  3. U.S. Chip Export Controls Will Deserve Careful Reassessment
    DeepSeek’s success came from utilizing less advanced and fewer chips than its U.S. counterparts, illustrating how innovation can thrive even under constraints. Despite ongoing U.S. export controls that may limit DeepSeek and other Chinese companies in the short term, these restrictions are unlikely to halt their progress. The U.S. risks isolating its chip technologies from China’s market, potentially on a permanent basis. Additionally, the export controls may undermine U.S. efforts to address trade imbalances with China, as the country may opt to focus on developing its own capabilities rather than relying on U.S. imports.

  4. U.S. and Chinese Tech Leaders’ Interests May Align
    While initially concerning to U.S. investors, DeepSeek’s breakthrough and its open-source model have been embraced by many major U.S. tech companies. Cloud platforms like Microsoft, AWS, and Hugging Face are already incorporating models based on DeepSeek’s R-1, noting that cheaper large language models should increase demand for their cloud services, boosting their revenue streams. In the long run, businesses across both countries could benefit from the productivity gains and cost savings that AI applications offer. This could foster potential collaboration between U.S. and Chinese tech leaders, despite existing tensions. The evolution of AI presents a tremendous opportunity for both superpowers to collaborate, especially as they pursue artificial general intelligence, though ongoing geopolitical conflicts could limit this cooperation.

Emerging AI Investment Opportunities Beyond Big Tech

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The ongoing artificial intelligence (AI) revolution, described as the “biggest platform shift since electricity,” is predicted to create lucrative opportunities for smaller tech firms, according to Clare Pleydell-Bouverie, co-lead fund manager at Liontrust Asset Management.

In an interview with CNBC, Pleydell-Bouverie emphasized that the dominant players of the last tech cycle—referred to as the “Magnificent Seven,” which includes Alphabet, Amazon, Apple, Meta, Microsoft, Nvidia, and Tesla—may not necessarily lead in this new phase of technological transformation. Instead, emerging firms focused on AI applications and infrastructure are poised to become significant players.

“This year, we’ve concentrated on the AI infrastructure layer, which is essential for scaling this technology,” Pleydell-Bouverie stated. She highlighted sectors like silicon chip production, semiconductor equipment manufacturing, and network infrastructure as critical to enabling AI growth. Companies like Broadcom, Amphenol, and Arista Networks are vital in building the foundational layers of AI’s technological stack.

The “stack,” as described by Pleydell-Bouverie, includes several layers:

  1. AI Infrastructure: Firms providing hardware and connectivity, such as chips, cables, and networks.
  2. Foundation Model Providers: Companies creating large-scale machine-learning models, which she characterized as highly competitive and commoditized.
  3. AI Engineering Firms: Those enabling businesses to integrate AI into their operations and services.

While the infrastructure layer currently holds the most value, Pleydell-Bouverie foresees this shifting toward application and integration in the near future.

Nvidia’s Strategic Position in AI
Nvidia remains a standout in the AI space, which Pleydell-Bouverie compares to Apple’s dominance during the smartphone revolution. However, she argues that Nvidia is often misunderstood as merely a chip provider.

“Nvidia is positioning itself as the operating system for the next generation of AI-infused software,” she noted, pointing to the company’s strategic shift toward integrating software and hardware to power AI applications. Nvidia’s shares have surged by over 180% in 2024, fueled by demand for its advanced AI chips like Blackwell.

Pleydell-Bouverie sees Nvidia as the primary beneficiary of the AI boom in 2025, likening its current trajectory to Apple’s rise under Steve Jobs, who combined hardware innovation with software integration to dominate the tech landscape.

As AI continues to redefine industries, investors are encouraged to look beyond traditional Big Tech giants and explore opportunities in emerging firms that are reshaping the AI ecosystem.