New York gold futures fell 1.00% intraday to $4,459.00/oz.

SK Hynix’s Global News Center says GPUs and AI accelerators remain central to large-model training and complex inference, but AI performance in production is now constrained more by data supply and movement than raw compute. Over the past 20 years server peak compute has roughly tripled every two years while DRAM bandwidth rose only ~1.6x and interconnect bandwidth ~1.4x, creating a growing “memory wall” that forces accelerators to idle waiting for data. SK Hynix argues the solution is system design around data paths: keep hot data close to processors, fetch massive datasets efficiently via storage and networks, and coordinate software scheduling, prefetching and task allocation to avoid new bottlenecks. The piece warns that isolated improvements in GPUs, memory, storage or networking will not restore end-to-end performance; semiconductor, server, network, cloud and storage vendors must co-design across the full data-flow stack. Faster GPUs remain central, but the next binding constraint for AI performance will be how quickly and efficiently data reaches and is processed by those GPUs.

India and Uzbekistan agreed to a $5 billion bilateral trade deal to be achieved over the next four years.