Summary: In 2025, six key paradigm shifts are redefining the AI landscape. RLVR (Reinforcement Learning with Verifiable Rewards) has become a core training method, enabling models to develop reasoning-like strategies through optimization on objective tasks like math and coding. This has shifted computational focus from pre-training to extended RL training. The concept of "ghost" vs. "animal" intelligence highlights the unique, jagged capability profile of LLMs, which excel in verifiable domains but remain brittle elsewhere, leading to widespread skepticism of benchmark performance. Cursor emerged as a new application-layer paradigm, demonstrating how vertical-specific tools can orchestrate multiple LLM calls into complex workflows. Claude Code redefined local AI by running powerful coding agents directly on user devices, integrating deeply with private data and environments. "Vibe Coding" lowered the barrier to programming, allowing both amateurs and professionals to build software through natural language description. Finally, Google's Nano banana signaled the next major computing paradigm by moving beyond text to a multi-modal, graphical user interface for LLMs, better aligning with human visual and spatial cognition.
marsbit2025.12.22




