Reports · GCRI · Established
Artificial intelligence · Data and compute
Reports 中的人工智能与自主系统
Trustworthy artificial intelligence, robotics-enabled autonomy, computational methods and social effects. This page shows the series it feeds, the evidence behind it and how to contribute.
- 系列
- 2
- 系统
- 4
- 方法
- 7
What this area brings to the editions.
Trustworthy artificial intelligence, robotics-enabled autonomy, computational methods and social effects.
9 findings of the drafted editions that bear on Artificial Intelligence and Autonomous Systems.
Drawn from the Baseline Edition 2026 drafts through the 系统 this area reads. Each opens at its anchor in its edition, with its numbered sources.
- ARE阿拉伯联合酋长国Gas gave 68% of electricity generation in 2025, down from 97% in 2019, while nuclear reached 21% and solar 10%; total generation rose from 138 to 184 TWh.REPORTED · COUNTRY-ARE-ENE-003
- ARG阿根廷Low-carbon sources supplied 42% of electricity in 2025, and renewables including large hydro covered 40.2% of demand.REPORTED · COUNTRY-ARG-ENE-003
- AU非洲联盟In 2024, 55.1% of people in Sub-Saharan Africa had electricity, up from 46.4% in 2018; about 579 million had none (derived).REPORTED · COUNTRY-AU-ENE-002
- AUS澳大利亚Wind and solar supplied 33% of electricity in 2025; fossil fuels supplied 61% and coal 43%.REPORTED · COUNTRY-AUS-ENE-003
- BRA巴西Renewables supplied 86.8% of electricity in 2025. Hydropower fell 4.8% to 401.4 TWh while gas generation rose 22.7%, and wind and solar together supplied 26.4%.REPORTED · COUNTRY-BRA-ENE-005
- CHE瑞士In 2025 hydropower supplied 55.5% of domestic electricity generation, nuclear power 27.2% and photovoltaics 11.8%, and final electricity consumption was 57,970 GWh.REPORTED · COUNTRY-CHE-ENE-003
- CHN中国Coal supplied 54.8% of electricity in 2025 and 51.4% of total energy consumption, while wind and solar supplied 21.9% of electricity.REPORTED · COUNTRY-CHN-ENE-006
- EU欧洲联盟Renewables supplied 25.2% of gross final energy consumption in 2024, 17.3 points below the 42.5% target for 2030.REPORTED · COUNTRY-EU-ENE-003
- GS-02全球能源Global energy demand grew 1.3% (8 EJ) in 2025, down from 2% in 2024, and electricity demand grew nearly 3%, more than twice as fast.REPORTED · SECTOR-ENERGY-GLOBAL-ENE-001
From Foundry evidence to the series.
The evidence, step by step, from the 系统 this area reads to the series it feeds.
How Artificial Intelligence and Autonomous Systems reaches 报告: what it reads, how it reads it, the sealed cut and the series it feeds.
| 步骤 | 发生的事项 | 来源 |
|---|---|---|
| 01 What it reads | Artificial Intelligence and Autonomous Systems reads NXS-NXQ(软件、模型与能力生命周期) 与 NXS-LAB(研究、实验与模拟): governed sources with their releases, never a value without its source. | |
| 02 How it reads them | Artificial intelligence and machine learning and AI evaluation and assurance engineering turn the evidence into findings, with assumptions and limits stated beside each value. | |
| 03 The cut is sealed | Each quarter the evidence is sealed in one cut, so OBSERVED, REPORTED and ESTIMATED values stay apart and every edition can be rebuilt. | |
| 04 The series it feeds | The cut feeds Exponential Technology and 实验室 Evidence, from the Baseline Edition 2026 into the quarterly series. | |
| 05 Who decides | Decisions stay with the authorities that hold them, under their own rules; an edition informs a decision and never makes it. |
A teaching model of the evidence path, not a forecast and not a record of any run; the systems, methods and series named come from the registries. Sources: Reports 中的人工智能与自主系统 (2026); Artificial Intelligence and Autonomous Systems home (2026).
The series it feeds, and what backs each.
| 系列 | Foundry systems it draws on | Academy disciplines | Series home |
|---|---|---|---|
| 指数级技术 | NXS-NXQ the capability catalogue and fitness assessments of machine capabilities NXS-LAB benchmark comparisons and experiment records for fast-changing technologies | 人工智能与机器学习 创新与前沿技术治理 量子技术 | Exponential Technology series home |
| 实验室 证据 | NXS-LAB what was tried, under which conditions, and what happened, including negative results | 研究、证据与科学政策衔接 复杂 系统 and systems modelling | Labs Evidence series home |
The systems, methods and teaching behind it.
- NXS-NXQNXS-NXQNXS-NXQRooms: Capabilities, Competence.
- NXS-LABNXS-LABNXS-LABRooms: Experiments, Benchmarks.
- NXS-STU(组合、仪表板与工作流)NXS-STUNXS-STURooms: Composer, Populations.
- NXS-NSF(信任、授权与保证)NXS-NSFNXS-NSFRooms: Authority, Assurance.
- STEM 方法STEM 公共资源人工智能与机器学习The canonical method page, with its limits.
- STEM 方法STEM 公共资源AI 评估与保证工程The canonical method page, with its limits.
- STEM 方法STEM 公共资源高性能计算、云计算与边缘计算The canonical method page, with its limits.
- STEM 方法STEM 公共资源概率与统计The canonical method page, with its limits.
- STEM 方法STEM 公共资源网络安全与密码学The canonical method page, with its limits.
- STEM 方法STEM 公共资源社会与行为科学The canonical method page, with its limits.
- Academy disciplineRisk Academy人工智能与机器学习技术与数字系统学院
- Academy disciplineRisk Academy人工智能安全与评估技术与数字系统学院
- Academy disciplineRisk Academy机器人与自主系统技术与数字系统学院
- 领域GCRI人工智能The field across science, governance and finance.
- 领域GCRI数据与算力The field across science, governance and finance.
Where the same subject is reported elsewhere.
- Counterpart · GRF报告Innovation NexusShared: Artificial intelligence.
- Counterpart · GRF报告人工智能与数字治理Shared: Artificial intelligence.
- Counterpart · GRA报告人工智能与金融模型风险Shared: Artificial intelligence.
- Standards areaNexus Standards数据与数据集Data and evidence. Parts NS-3, NS-3b, NS-11, NS-1.
- Standards areaNexus Standards软件与供应链Trust, verification and assurance. Parts NS-12, NS-11, NS-1.
- Standards areaNexus Standards人工智能、模型与代理Digital, cyber and AI. Parts NS-12, NS-10, NS-11.
- Standards areaNexus Standards情景、模型与前瞻Systemic risks. Parts NS-12, NS-3b, NS-11.
- Standards areaNexus Standards隐私与数据保护Data and evidence. Parts NS-10, NS-11, NS-3.
- Standards areaNexus Standards金融与支付数据Finance, insurance and the economy. Parts NS-9, NS-10, NS-11, NS-14.
Contribute on Artificial Intelligence and Autonomous Systems.
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