What is compared
传统: most operational tasks are sent to a large language model. NeuralOps: detached 系统 and rules handle scans, backups and validation; a model is used only when language or judgement is required.
演示 · website-ops carbon compare
估算 monthly CO₂e of conventional LLM-first website management versus NeuralOps detached-first routing. Same formula as the AINNA 碳模拟器.
ESG · compute efficiency
碳足迹：NeuralOps 与常规网站运营对比
本节估算了以下各项的算力能耗与 CO₂e： managing a hospital website and journal — audits, drafts, SEO, link checks, logs — not the carbon of every public page view. 图表 use the same layer model as the AINNA 碳模拟器.
Grounded factors
电网 factor default 0.74 kg CO₂e/kWh, PUE 1.4, and kWh per 1,000 requests by layer — all defaults from the AINNA 碳模拟器. Token reduction of up to 87% is an 内部基准 on a tested language workload, not a hospital-site measurement.
What this is not
Not a certified carbon audit. Not a claim of KPMC’s actual emissions. Not a guarantee of 87% reduction on every task. Adjust the sliders; the model recalculates 实时.
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— kWh
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— kWh
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— kg CO₂e / month
— kg / year
≤87%
内部 benchmark on tested token workload — 已施加 only as context, not multiplied into the kg figure.
| Layer | 对网站运营的意义 | kWh / 1,000 tasks | 传统 share | NeuralOps share |
|---|---|---|---|---|
| GPU 密集型 AI | 完整 LLM for every rewrite, scan summary or log read | 0.15 | 70% | 5% |
| 轻量 AI / CPU | Short classification or title suggestion | 0.05 | 20% | 15% |
| 规则-based | 验证, metadata, schema, spelling lists | 0.01 | 8% | 20% |
| 分离式 系统 | 链接爬取、站点地图、备份检查、可用性探测 | 0.005 | 2% | 60% |
估算 / simulation only. Formula: tasks × layer share × (kWh per 1,000 tasks) × PUE × grid factor. 来源: AINNA 碳模拟器 defaults. 更改 any input to see sensitivity. Do not treat the result as audited hospital ESG data.
