The Memory Maze: Copper, Optics, and the Future of AI Data Movement

As AI models grow larger and more autonomous, every query requires extraordinary volumes of data to move quickly between memory and compute, making data movement one of the defining challenges for next-generation AI infrastructure.
In this episode of Tech Threads, Nandan Nayampally speaks with Srujan Linga, CEO and co-founder of Kandou AI, about why the industry’s so-called “memory wall” is actually a multidimensional “memory maze,” shaped by different requirements for bandwidth, latency and capacity.
They explore the limitations of relying exclusively on high-bandwidth memory, the untapped potential of copper interconnects, and how technologies such as Chord Signaling and Copper MIMO can increase bandwidth while reducing power and extending reach. The conversation also examines where copper and optics can complement one another, how advanced interconnects could turn an entire PCB into a larger multi-chip system, and why the economics and scalability of AI infrastructure must be considered alongside raw performance.
The result is a system-level perspective on what it will take to build more efficient, scalable and accessible AI infrastructure.