[umbrella] Paimon 2.0 Planning

Apache Paimon, as a high-performance data lake format, has achieved significant results in the field of structured data processing.
With the deepening of AI application scenarios, the demand for fusion analysis of multimodal data (such as text, images, audio, video, etc.)
is increasing day by day. We have invested a lot of development work in cross modal retrieval, unified storage, and efficient analysis.

Paimon 2.0 development, focusing on breaking through multimodal data support and creating a more powerful data lake solution.

Core objective:
- Unified Storage for structure & multimodal & vector.
- Efficient Search for data and vectors and full text.
- PyPaimon integrate to AI system like Ray, Pytorch.

This is an umbrella planning issue rather than a scoped implementation task, and it names no files, tests, or entry points. Start by reviewing the Paimon 2.0 objectives for unified multimodal, vector, and structured storage, search, and PyPaimon integration, then identify a concrete subtask with explicit completion criteria before beginning work.

Written by the indexing model from the issue text.