Google's Strength Doesn't Equal NVDA Disruption: Insights on AI Chip Competition and Infrastructure Investment

据Jdon：Google Gemini 3 has overtaken competitors, expected to generate over $50B in incremental AI revenue by 2026. Google’s TPU 7 (Ironwood) matches NVDA’s B200 performance with 30x better energy efficiency, and TPU shipments are projected to reach 1.5-2M units in 2025, narrowing the gap with NVDA’s 5-6M GPU units.
据OFweek：NVDA faces customer concentration risks, with top four clients contributing over 40% of revenue, but retains over 80% of AI accelerator market share.

雪球用户（via 雪球帖子）：Google’s TPU+OCS architecture offers cost and scalability advantages, but NVDA’s CUDA ecosystem and global supply chain make it irreplaceable for most companies. Anthropic’s 1M TPU order validates demand, but TPU is limited to Google’s closed stack.
Reddit users：AI infrastructure is a core barrier, with investment opportunities in optical modules (LITE), NAND flash, and energy storage due to power supply bottlenecks.

Both research and social media agree on AI infrastructure as a critical competitive barrier. Google’s TPU advancements threaten NVDA in specific use cases, but NVDA’s ecosystem and supply chain ensure short-term dominance. Investment implications include supply chain beneficiaries (LITE, optical modules) and energy sectors to address power constraints.