Why OpenAI and Anthropic will own the Chip Business

Instruction Sets as Historical Monopolies

• Intel (x86) and ARM built decades-long monopolies by controlling instruction sets.
• Licensing or compatibility dictated who could build chips, and locked the ecosystem to their terms.

AI’s Shift

• In AI, the model (Claude, GPT, Gemini) becomes the functional equivalent of the instruction set.
• The architecture of inference chips is defined by the model (layer sizes, precision, memory bandwidth).
• This makes the model owner the new monopoly power. You cannot build an independent inference chip for GPT without OpenAI’s cooperation.

Blocking Copycats

• Closed weights: The core IP is the model itself, not the chip. Without access to weights, no competitor can “copy” GPT’s instruction set.
• Ecosystem lock-in: Software runtimes, quantization methods, and compilers become proprietary extensions—like CUDA for NVIDIA.
• Vertical integration: Model makers who build custom inference chips tie the hardware directly to their model, blocking substitution.

Strategic Result

• Chip vendors: Reduced to subcontractors unless they align with a model owner.
• Model owners: Achieve monopoly status equivalent to Intel/ARM in the last era, but with stronger lock-in because the instruction set (model weights) is closed IP.
• Barrier to copying: High — not from semiconductor know-how, but from legal/IP control over model architectures and trained weights.