According to Sawyer Merritt, Tesla has officially launched its in-house AI training supercomputer in 2026, aimed at advancing autonomous vehicle technology (source: https://t.co/vJVU5PY949). This development allows Tesla to internally process massive datasets for self-driving models, reducing reliance on external cloud providers and potentially lowering operational costs. The move positions Tesla to accelerate AI model improvements and deployment cycles, creating significant business opportunities in the automotive AI sector. The integration of proprietary AI infrastructure is expected to enhance vehicle safety, extend autonomy features, and open new revenue streams in AI-powered mobility solutions.

According to Sawyer Merritt, Tesla has announced a strategic partnership with Samsung to manufacture advanced semiconductors in the U.S. specifically designed for AI inference and training workloads. This move strengthens Tesla's position in the AI hardware supply chain and directly addresses ongoing demand for high-performance compute. Additionally, Tesla has expanded its AI training compute capacity, bringing its Cortex infrastructure to a total of 81,000 H100 equivalents. This significant increase enables faster model training and supports Tesla's ambitions in autonomous driving and AI-powered services, presenting substantial business opportunities in AI chip design and large-scale training infrastructure (source: Sawyer Merritt, Twitter, Oct 22, 2025).