Opening — Why this matters now Buildings quietly consume around a third of the world’s energy. Most of that consumption is governed not by grand strategy, but by human habit: when people cook, charge vehicles, cool rooms, or forget to turn things off. For decades, Building Energy Management Systems (BEMS) promised optimization. In practice, they delivered dashboards—dense, technical, and mostly ignored. ...
Opening — Why this matters now We keep telling ourselves a comforting story: if an AI explanation isn’t good enough, just refine it. Add another round. Add another chart. Add another paragraph. Surely clarity is a monotonic function of effort. This paper politely demolishes that belief. As agentic AI systems—LLMs that reason, generate code, analyze results, and then revise themselves—move from demos into decision‑support tools, explanation quality becomes a first‑order risk. Not model accuracy. Not latency. Explanation quality. Especially when the audience is human, busy, and allergic to verbose nonsense. ...
Introduction Recently, 01.AI launched its enterprise AI platform, aiming to provide businesses with access to open-source LLMs, retrieval-augmented generation (RAG), model fine-tuning, and AI-powered assistants. This move is part of 01.AI’s broader effort to demonstrate relevance in the ongoing AI arms race, especially as the company has previously secured significant funding under the reputation of Li Kaifu. Given the rapid evolution of AI, 01.AI faces mounting pressure to show tangible business value to its investors—yet, its latest offering falls into the common trap of many AI enterprise solutions: prioritizing model deployment over true business integration. ...