Every time you ask ChatGPT a question, your request triggers a data relay race. Information leaves memory, passes through a CPU for preprocessing, travels to a GPU for heavy computation, and then makes its way back — and that entire journey repeats for every single word the AI generates. The bottleneck is structural — it means routing through some of the most expensive and power-intensive chips in the industry on every single request. That inefficiency is exactly what XCENA , a startup with offices in South Korea and the U.S., is trying to solve. The four-year-old startup has designed a chip that places compute capabilities much closer to DRAM — the fast, short-term memory chips that store data a processor is actively using — allowing routine data operations to be handled near memory, without the costly round trips between CPUs, GPUs, and memory. If it works at scale, the implications for AI infrastructure costs could be significant, which largely explains investor enthusiasm around the company.…