paper(intro): edit-pass through §1 Introduction done

- §1 Introduction rewritten with AHBM-first opening, in-paper KernBench
  platform overview, GQA motivation and three architectural requirements,
  three matching HW-SW co-design mechanisms (GQA-aware placement,
  PE_IPCQ, composite-command GEMM under PE_SCHEDULER), broader-
  applicability outlook (PE_IPCQ as collective substrate, composite
  command for fused operator pipelines), and outline. Consistent with
  the Executive Summary structure.
- Executive Summary: extended broader-applicability closing with a
  forward-looking line previewing FFN/MoE integration.
- §5 section heading renamed from
  "All-Reduce Acceleration via PE_IPCQ" to
  "PE_IPCQ and Collective Communication".
- Title page date line refined to "2026 H1 Report".

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>

docs/report/1H-codesign-paper/sections/00-exec-summary.tex

@@ -30,4 +30,7 @@ composite-command execution enables efficient fusion of memory
 movement, GEMM kernels, normalization, and other element-wise
 operations. Together with the hierarchical data-placement framework,
 these capabilities form a reusable foundation for future AI kernels
-and communication libraries on AHBM.
+and communication libraries on AHBM. Looking ahead, these same mechanisms provide
+the basis for optimizing FFN-intensive workloads such as Mixture-of-Experts (MoE)
+layers and for developing integrated optimization strategies spanning both attention
+and MoE components within next-generation AI models.