DeepSeek

DeepSeek's Positioning

DeepSeek positions itself as an "industry accelerator," similar to how lithium batteries and Tesla drive the electric vehicle industry. Rather than being a disruptive innovator, it focuses on bridging the gap between lab research and real-world applications.

By adopting an open-source model, DeepSeek challenges the dominance of major AI computing power providers like OpenAI, disrupting existing platform ecosystems. This shift benefits small and mid-sized AI application developers by providing greater access to powerful AI tools.

AI Technology Trends

• Scaling Law remains valid – Increasing model parameters and computational capacity continues to be the primary strategy for technological advancement, particularly in emerging multimodal AI fields.

• Shifting computational demand – In the future, 90% of AI computing power will be dedicated to inference rather than training. Tech giants like Meta and AWS are ramping up their investments in AI infrastructure to accommodate this shift.

Industry Development & Market Opportunities

• First wave of AI monetization – Leading AI companies have already achieved profitability.

• Second wave of AI adoption – The next phase will benefit software enterprises and businesses with strong customer bases and proprietary data.

• B2B AI market is maturing – Clear business models and revenue strategies are already in place.

• B2C AI market remains uncertain – Companies must explore new AI-driven consumer applications to unlock growth.

• AI Agents are the next big thing – AI-powered autonomous agents are a confirmed industry trend. Notably, 35% of YC-backed startups are now focused on Agent-based AI applications.

Industry Methodology & Competitive Landscape

• Systematic industry forecasting – Predicting the future of AI requires continuous industry tracking, identifying key variables, and analyzing market signals.

• Divergence in AI development between the U.S. and China – Geopolitical factors are shaping distinct AI ecosystems, forcing businesses to adopt differentiated strategies.

• Challenges of national AI competition – Global AI ecosystems are increasingly driven by multinational corporations, making it difficult for protectionist policies (e.g., U.S. tariffs) to halt cross-border technological collaboration.