To The Moon

Building the AI Future

Yesterday's market reaction was a textbook case of misinterpretation. Many investors immediately framed Google's progress with TPU as a direct negative for Nvidia — as if any advancement by one major tech player must automatically threaten another. This mirrors the old narrative from two years ago, when some believed Meta's rise would somehow "kill Google." The idea that AI is a zero-sum arena has always been flawed.

Google TPU

In reality, Google's $Alphabet(GOOGL)$  strength only reinforces the long-term certainty of the AI megatrend. And that is inherently positive for Nvidia$NVIDIA Corp(NVDA)$  . The two companies are not fighting over a fixed pie — they are validating and expanding a rapidly growing market.

Nvidia's GPUs deliver universal compute: flexible, programmable, and capable of handling the complex and unpredictable workloads required for AGI-level development. Google's TPUs, on the other hand, are purpose-built accelerators optimized for extreme efficiency and large-scale inference on stable, well-defined pathways. These are two fundamentally different approaches to compute. They do not replace one another — they complement each other.

Even inside Google, where TPU development has been ongoing for years, roughly 70% of its internal compute still comes from Nvidia hardware. The reason TPU conversations are becoming louder now isn't because GPUs are losing relevance — it's because inference demand is exploding. As inference becomes larger and more stable, it finally makes economic sense for hyperscalers to invest more in ASICs to lower costs. This doesn't shrink the compute market; it expands it into new layers.

The future of compute

The future AI landscape will be powered by hybrid architectures: GPU + ASIC. Nvidia's moat remains unmatched — CUDA, ecosystem depth, developer tooling, supply chain mastery, and universal programmability. TPUs are Google's specialized weapon within its own ecosystem, not a head-to-head replacement. A growing market needs more types of compute, which means more collaboration and more investment across the industry. In short, the size of the AI pie isn't determined by who wins or loses, but by how much capital, power, and infrastructure the giants are willing to pour in. As long as CapEx keeps rising, the AI pie will only get bigger.

The growing pie

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