On Monday, December 1, veteran tech analyst Ben Thompson published an in-depth article on his widely followed blog Stratechery, framing the AI industry's competitive landscape as a classic "hero's journey."

Thompson, renowned for his sharp business strategy insights, identified NVIDIA and OpenAI as the two protagonists in the AI narrative of recent years. One emerged from a startup to become a consumer tech phenomenon, while the other transformed from a gaming chipmaker into the "arsenal" of the AI revolution. However, like Luke Skywalker facing the Death Star, both companies now confront their "Empire Strikes Back" moment—Google's full-scale counterattack.

**Google's Two-Pronged Offensive** Thompson highlights Google's dual strategy. First, the launch of its powerful Gemini 3 model outperformed OpenAI's most advanced models in benchmarks, challenging OpenAI's dominance as the "premier model provider." Second, and more critically, Google began marketing its custom TPU chips—previously reserved for internal use—as alternatives to NVIDIA’s GPUs, securing partnerships with Anthropic and Meta. This move directly threatens NVIDIA’s lucrative stronghold.

**NVIDIA’s Cracks in the Moat** Thompson dissects NVIDIA’s three key advantages: superior performance, GPU flexibility, and the CUDA developer ecosystem. Yet, as Google’s TPUs catch up in performance, the first pillar weakens. The deeper risk lies in CUDA’s ecosystem. Drawing parallels to AMD’s disruption of Intel in data centers, Thompson notes that hyperscalers like Google and Microsoft have both the incentive and resources to break NVIDIA’s CUDA monopoly. "The pressure and possibility of escaping CUDA are higher than ever," he warns, signaling long-term margin erosion risks.

**OpenAI’s Ace: 800 Million Users** Despite OpenAI’s financial fragility, Thompson argues its moat is fundamentally different. Unlike NVIDIA’s reliance on a handful of corporate clients, ChatGPT’s strength lies in its 800 million weekly active users. "A moat’s resilience scales with independent users," Thompson asserts, emphasizing that shifting consumer habits is far harder than convincing a CEO to switch tech stacks. This network effect, he contends, is OpenAI’s toughest barrier for Google to breach.

**OpenAI’s Blind Spot: Monetization Missteps** Here, Thompson delivers his harshest critique: OpenAI’s refusal to adopt advertising is a "strategic failure." For a user-aggregator platform, ads aren’t just revenue—they fuel product improvement via data and personalization. He contrasts OpenAI’s subscription-only model with Google’s ad-driven innovation post-search launch, calling it a "dereliction of commercial duty" that cedes the free-user market to Google.

**The Ultimate Test of Aggregation Theory** Thompson frames this clash as a litmus test for his Aggregation Theory: Can an entrenched aggregator (Google) crush a nascent rival (OpenAI) that underutilizes its aggregator advantage? The outcome, he suggests, will redefine tech competition—pitting sheer resources against user-demand mastery as the decisive factor.

In summary: NVIDIA’s vulnerability stems from its reliance on a few high-risk clients, while OpenAI’s strength—its massive user base—is being undermined by monetization myopia. This battle’s resolution could reshape the rules of tech supremacy.