Nvidia dominates AI hardware but their chips are expensive and often supply-constrained. Many startups can't afford current premium pricing.
Build either hardware (ASICs, FPGAs) or software (optimized CUDA alternatives) that offer better price/performance for specific AI workloads. Focus on inference rather than training initially.
The simplest version could be optimized software libraries for existing hardware. Then move to custom hardware designs.
Biggest risk is competing with Nvidia's ecosystem moat and continuous innovation.