LLM latency bottlenecks keep AI memory bandwidth in focus

The article separates AI inference into phases and highlights token generation as the harder real-time workload. For RamTrend, the takeaway is that accelerator performance is increasingly judged by how quickly systems can move and reuse model data, not only by raw compute throughput. That keeps bandwidth, cache design, and memory-adjacent architecture choices central to AI infrastructure planning, although the item does not announce a new memory order or supply change.