Beyond the Transformer: Why localized context windows are the next bottleneck for AGI.
Everyone is chasing larger context windows (1M+), but the retrieval accuracy (Needle In A Haystack) is still sub-optimal for professional use. I’m theorizing that we’re hitting a physical limit of the Transformer architecture. The future isn't a "bigger window," but a better "active memory" management at the infrastructure level. I’d love to hear some thoughts on RAG-Hybrid architectures vs. native long-context models. Which one actually scales for enterprise knowledge bases? submitted by /u/Foreign-Job-8717 [link] [comments]
