The Grok system features chips with high speed but limited onboard RAM, requiring approximately 600 chips for inference, contrasted with Nvidia H100 chip capable of the same task alone. Grok is facing financial challenges and needs a significant increase in utilization to break even due to unit economics. Notably, Grok chips only perform inference, not training, indicating a trend where models increasingly focus on post-training computations. This points towards a direction of custom chips for specific language model use cases optimized for inference, hinting at potential advancements in chip design even with existing fabrication nodes. This emphasizes the importance of chip designs tailored for inference tasks, showcasing the evolving landscape of hardware breakthroughs in the realm of AI technology.