diff --git a/src/UserGuide/Master/Table/AI-capability/AINode_apache.md b/src/UserGuide/Master/Table/AI-capability/AINode_apache.md index 58aab926b..421bbcde3 100644 --- a/src/UserGuide/Master/Table/AI-capability/AINode_apache.md +++ b/src/UserGuide/Master/Table/AI-capability/AINode_apache.md @@ -21,7 +21,7 @@ # AINode -AINode is an IoTDB native node designed to support the registration, management, and invocation of large-scale time series models. It comes with industry-leading proprietary time series models such as Timer and Sundial. These models can be invoked through standard SQL statements, enabling real-time inference of time series data at the millisecond level, and supporting application scenarios such as trend forecasting, missing value imputation, and anomaly detection for time series data. +AINode is a native IoTDB node that supports the registration, management, and invocation of time-series-related models. It comes with built-in industry-leading self-developed time-series large models, such as the Timer series developed by Tsinghua University. These models can be invoked through standard SQL statements, enabling real-time inference of time series data at the millisecond level, and supporting application scenarios such as trend forecasting, missing value imputation, and anomaly detection for time series data. The system architecture is shown below: ::: center diff --git a/src/UserGuide/Master/Table/AI-capability/AINode_timecho.md b/src/UserGuide/Master/Table/AI-capability/AINode_timecho.md index 034a54971..a22f96bf8 100644 --- a/src/UserGuide/Master/Table/AI-capability/AINode_timecho.md +++ b/src/UserGuide/Master/Table/AI-capability/AINode_timecho.md @@ -21,7 +21,7 @@ # AINode -AINode is an IoTDB native node designed to support the registration, management, and invocation of large-scale time series models. It comes with industry-leading proprietary time series models such as Timer and Sundial. These models can be invoked through standard SQL statements, enabling real-time inference of time series data at the millisecond level, and supporting application scenarios such as trend forecasting, missing value imputation, and anomaly detection for time series data. +AINode is a native IoTDB node that supports the registration, management, and invocation of time-series-related models. It comes with built-in industry-leading self-developed time-series large models, such as the Timer series developed by Tsinghua University. These models can be invoked through standard SQL statements, enabling real-time inference of time series data at the millisecond level, and supporting application scenarios such as trend forecasting, missing value imputation, and anomaly detection for time series data. The system architecture is shown below: ::: center diff --git a/src/UserGuide/Master/Tree/AI-capability/AINode_apache.md b/src/UserGuide/Master/Tree/AI-capability/AINode_apache.md index bae4ce651..31b3b9e2d 100644 --- a/src/UserGuide/Master/Tree/AI-capability/AINode_apache.md +++ b/src/UserGuide/Master/Tree/AI-capability/AINode_apache.md @@ -21,7 +21,7 @@ # AINode -AINode is an IoTDB native node designed to support the registration, management, and invocation of large-scale time series models. It comes with industry-leading proprietary time series models such as Timer and Sundial. These models can be invoked through standard SQL statements, enabling real-time inference of time series data at the millisecond level, and supporting application scenarios such as trend forecasting, missing value imputation, and anomaly detection for time series data. +AINode is a native IoTDB node that supports the registration, management, and invocation of time-series-related models. It comes with built-in industry-leading self-developed time-series large models, such as the Timer series developed by Tsinghua University. These models can be invoked through standard SQL statements, enabling real-time inference of time series data at the millisecond level, and supporting application scenarios such as trend forecasting, missing value imputation, and anomaly detection for time series data. The system architecture is shown below: ::: center diff --git a/src/UserGuide/Master/Tree/AI-capability/AINode_timecho.md b/src/UserGuide/Master/Tree/AI-capability/AINode_timecho.md index da8fc5728..d3662dcf6 100644 --- a/src/UserGuide/Master/Tree/AI-capability/AINode_timecho.md +++ b/src/UserGuide/Master/Tree/AI-capability/AINode_timecho.md @@ -21,7 +21,7 @@ # AINode -AINode is an IoTDB native node designed to support the registration, management, and invocation of large-scale time series models. It comes with industry-leading proprietary time series models such as Timer and Sundial. These models can be invoked through standard SQL statements, enabling real-time inference of time series data at the millisecond level, and supporting application scenarios such as trend forecasting, missing value imputation, and anomaly detection for time series data. +AINode is a native IoTDB node that supports the registration, management, and invocation of time-series-related models. It comes with built-in industry-leading self-developed time-series large models, such as the Timer series developed by Tsinghua University. These models can be invoked through standard SQL statements, enabling real-time inference of time series data at the millisecond level, and supporting application scenarios such as trend forecasting, missing value imputation, and anomaly detection for time series data. The system architecture is shown below: diff --git a/src/UserGuide/V1.3.x/AI-capability/AINode_apache.md b/src/UserGuide/V1.3.x/AI-capability/AINode_apache.md index 6b17ebb4c..0bce3831d 100644 --- a/src/UserGuide/V1.3.x/AI-capability/AINode_apache.md +++ b/src/UserGuide/V1.3.x/AI-capability/AINode_apache.md @@ -21,7 +21,7 @@ # AINode -AINode is an IoTDB native node designed to support the registration, management, and invocation of large-scale time series models. It comes with industry-leading proprietary time series models such as Timer and Sundial. These models can be invoked through standard SQL statements, enabling real-time inference of time series data at the millisecond level, and supporting application scenarios such as trend forecasting, missing value imputation, and anomaly detection for time series data. +AINode is a native IoTDB node that supports the registration, management, and invocation of time-series-related models. It comes with built-in industry-leading self-developed time-series large models, such as the Timer series developed by Tsinghua University. These models can be invoked through standard SQL statements, enabling real-time inference of time series data at the millisecond level, and supporting application scenarios such as trend forecasting, missing value imputation, and anomaly detection for time series data. The system architecture is shown below: diff --git a/src/UserGuide/V1.3.x/AI-capability/AINode_timecho.md b/src/UserGuide/V1.3.x/AI-capability/AINode_timecho.md index eda8713c4..0676658d3 100644 --- a/src/UserGuide/V1.3.x/AI-capability/AINode_timecho.md +++ b/src/UserGuide/V1.3.x/AI-capability/AINode_timecho.md @@ -21,7 +21,7 @@ # AINode -AINode is an IoTDB native node designed to support the registration, management, and invocation of large-scale time series models. It comes with industry-leading proprietary time series models such as Timer and Sundial. These models can be invoked through standard SQL statements, enabling real-time inference of time series data at the millisecond level, and supporting application scenarios such as trend forecasting, missing value imputation, and anomaly detection for time series data. +AINode is a native IoTDB node that supports the registration, management, and invocation of time-series-related models. It comes with built-in industry-leading self-developed time-series large models, such as the Timer series developed by Tsinghua University. These models can be invoked through standard SQL statements, enabling real-time inference of time series data at the millisecond level, and supporting application scenarios such as trend forecasting, missing value imputation, and anomaly detection for time series data. The system architecture is shown below: diff --git a/src/UserGuide/dev-1.3/AI-capability/AINode_apache.md b/src/UserGuide/dev-1.3/AI-capability/AINode_apache.md index 6b17ebb4c..0bce3831d 100644 --- a/src/UserGuide/dev-1.3/AI-capability/AINode_apache.md +++ b/src/UserGuide/dev-1.3/AI-capability/AINode_apache.md @@ -21,7 +21,7 @@ # AINode -AINode is an IoTDB native node designed to support the registration, management, and invocation of large-scale time series models. It comes with industry-leading proprietary time series models such as Timer and Sundial. These models can be invoked through standard SQL statements, enabling real-time inference of time series data at the millisecond level, and supporting application scenarios such as trend forecasting, missing value imputation, and anomaly detection for time series data. +AINode is a native IoTDB node that supports the registration, management, and invocation of time-series-related models. It comes with built-in industry-leading self-developed time-series large models, such as the Timer series developed by Tsinghua University. These models can be invoked through standard SQL statements, enabling real-time inference of time series data at the millisecond level, and supporting application scenarios such as trend forecasting, missing value imputation, and anomaly detection for time series data. The system architecture is shown below: diff --git a/src/UserGuide/dev-1.3/AI-capability/AINode_timecho.md b/src/UserGuide/dev-1.3/AI-capability/AINode_timecho.md index eda8713c4..0676658d3 100644 --- a/src/UserGuide/dev-1.3/AI-capability/AINode_timecho.md +++ b/src/UserGuide/dev-1.3/AI-capability/AINode_timecho.md @@ -21,7 +21,7 @@ # AINode -AINode is an IoTDB native node designed to support the registration, management, and invocation of large-scale time series models. It comes with industry-leading proprietary time series models such as Timer and Sundial. These models can be invoked through standard SQL statements, enabling real-time inference of time series data at the millisecond level, and supporting application scenarios such as trend forecasting, missing value imputation, and anomaly detection for time series data. +AINode is a native IoTDB node that supports the registration, management, and invocation of time-series-related models. It comes with built-in industry-leading self-developed time-series large models, such as the Timer series developed by Tsinghua University. These models can be invoked through standard SQL statements, enabling real-time inference of time series data at the millisecond level, and supporting application scenarios such as trend forecasting, missing value imputation, and anomaly detection for time series data. The system architecture is shown below: diff --git a/src/UserGuide/latest-Table/AI-capability/AINode_apache.md b/src/UserGuide/latest-Table/AI-capability/AINode_apache.md index 58aab926b..421bbcde3 100644 --- a/src/UserGuide/latest-Table/AI-capability/AINode_apache.md +++ b/src/UserGuide/latest-Table/AI-capability/AINode_apache.md @@ -21,7 +21,7 @@ # AINode -AINode is an IoTDB native node designed to support the registration, management, and invocation of large-scale time series models. It comes with industry-leading proprietary time series models such as Timer and Sundial. These models can be invoked through standard SQL statements, enabling real-time inference of time series data at the millisecond level, and supporting application scenarios such as trend forecasting, missing value imputation, and anomaly detection for time series data. +AINode is a native IoTDB node that supports the registration, management, and invocation of time-series-related models. It comes with built-in industry-leading self-developed time-series large models, such as the Timer series developed by Tsinghua University. These models can be invoked through standard SQL statements, enabling real-time inference of time series data at the millisecond level, and supporting application scenarios such as trend forecasting, missing value imputation, and anomaly detection for time series data. The system architecture is shown below: ::: center diff --git a/src/UserGuide/latest-Table/AI-capability/AINode_timecho.md b/src/UserGuide/latest-Table/AI-capability/AINode_timecho.md index 034a54971..a22f96bf8 100644 --- a/src/UserGuide/latest-Table/AI-capability/AINode_timecho.md +++ b/src/UserGuide/latest-Table/AI-capability/AINode_timecho.md @@ -21,7 +21,7 @@ # AINode -AINode is an IoTDB native node designed to support the registration, management, and invocation of large-scale time series models. It comes with industry-leading proprietary time series models such as Timer and Sundial. These models can be invoked through standard SQL statements, enabling real-time inference of time series data at the millisecond level, and supporting application scenarios such as trend forecasting, missing value imputation, and anomaly detection for time series data. +AINode is a native IoTDB node that supports the registration, management, and invocation of time-series-related models. It comes with built-in industry-leading self-developed time-series large models, such as the Timer series developed by Tsinghua University. These models can be invoked through standard SQL statements, enabling real-time inference of time series data at the millisecond level, and supporting application scenarios such as trend forecasting, missing value imputation, and anomaly detection for time series data. The system architecture is shown below: ::: center diff --git a/src/UserGuide/latest/AI-capability/AINode_apache.md b/src/UserGuide/latest/AI-capability/AINode_apache.md index bae4ce651..31b3b9e2d 100644 --- a/src/UserGuide/latest/AI-capability/AINode_apache.md +++ b/src/UserGuide/latest/AI-capability/AINode_apache.md @@ -21,7 +21,7 @@ # AINode -AINode is an IoTDB native node designed to support the registration, management, and invocation of large-scale time series models. It comes with industry-leading proprietary time series models such as Timer and Sundial. These models can be invoked through standard SQL statements, enabling real-time inference of time series data at the millisecond level, and supporting application scenarios such as trend forecasting, missing value imputation, and anomaly detection for time series data. +AINode is a native IoTDB node that supports the registration, management, and invocation of time-series-related models. It comes with built-in industry-leading self-developed time-series large models, such as the Timer series developed by Tsinghua University. These models can be invoked through standard SQL statements, enabling real-time inference of time series data at the millisecond level, and supporting application scenarios such as trend forecasting, missing value imputation, and anomaly detection for time series data. The system architecture is shown below: ::: center diff --git a/src/UserGuide/latest/AI-capability/AINode_timecho.md b/src/UserGuide/latest/AI-capability/AINode_timecho.md index da8fc5728..d3662dcf6 100644 --- a/src/UserGuide/latest/AI-capability/AINode_timecho.md +++ b/src/UserGuide/latest/AI-capability/AINode_timecho.md @@ -21,7 +21,7 @@ # AINode -AINode is an IoTDB native node designed to support the registration, management, and invocation of large-scale time series models. It comes with industry-leading proprietary time series models such as Timer and Sundial. These models can be invoked through standard SQL statements, enabling real-time inference of time series data at the millisecond level, and supporting application scenarios such as trend forecasting, missing value imputation, and anomaly detection for time series data. +AINode is a native IoTDB node that supports the registration, management, and invocation of time-series-related models. It comes with built-in industry-leading self-developed time-series large models, such as the Timer series developed by Tsinghua University. These models can be invoked through standard SQL statements, enabling real-time inference of time series data at the millisecond level, and supporting application scenarios such as trend forecasting, missing value imputation, and anomaly detection for time series data. The system architecture is shown below: diff --git a/src/zh/UserGuide/Master/Table/AI-capability/AINode_apache.md b/src/zh/UserGuide/Master/Table/AI-capability/AINode_apache.md index 7e528963f..9be944359 100644 --- a/src/zh/UserGuide/Master/Table/AI-capability/AINode_apache.md +++ b/src/zh/UserGuide/Master/Table/AI-capability/AINode_apache.md @@ -21,7 +21,7 @@ # AINode -AINode 是支持时序大模型注册、管理、调用的 IoTDB 原生节点，内置业界领先的自研时序大模型，如 Timer、Sundial 等，可通过标准 SQL 语句进行调用，实现时序数据的毫秒级实时推理，可支持时序趋势预测、缺失值填补、异常值检测等应用场景。 +AINode 是支持时序相关模型注册、管理、调用的 IoTDB 原生节点，内置业界领先的自研时序大模型，如清华自研时序模型 Timer 系列，可通过标准 SQL 语句进行调用，实现时序数据的毫秒级实时推理，可支持时序趋势预测、缺失值填补、异常值检测等应用场景。 系统架构如下图所示： diff --git a/src/zh/UserGuide/Master/Table/AI-capability/AINode_timecho.md b/src/zh/UserGuide/Master/Table/AI-capability/AINode_timecho.md index 53370fd52..562cd2f20 100644 --- a/src/zh/UserGuide/Master/Table/AI-capability/AINode_timecho.md +++ b/src/zh/UserGuide/Master/Table/AI-capability/AINode_timecho.md @@ -21,7 +21,7 @@ # AINode -AINode 是支持时序大模型注册、管理、调用的 IoTDB 原生节点，内置业界领先的自研时序大模型，如 Timer、Sundial 等，可通过标准 SQL 语句进行调用，实现时序数据的毫秒级实时推理，可支持时序趋势预测、缺失值填补、异常值检测等应用场景。 +AINode 是支持时序相关模型注册、管理、调用的 IoTDB 原生节点，内置业界领先的自研时序大模型，如清华自研时序模型 Timer 系列，可通过标准 SQL 语句进行调用，实现时序数据的毫秒级实时推理，可支持时序趋势预测、缺失值填补、异常值检测等应用场景。 系统架构如下图所示： diff --git a/src/zh/UserGuide/Master/Tree/AI-capability/AINode_apache.md b/src/zh/UserGuide/Master/Tree/AI-capability/AINode_apache.md index d3b350672..9d92fb365 100644 --- a/src/zh/UserGuide/Master/Tree/AI-capability/AINode_apache.md +++ b/src/zh/UserGuide/Master/Tree/AI-capability/AINode_apache.md @@ -21,7 +21,7 @@ # AINode -AINode 是支持时序大模型注册、管理、调用的 IoTDB 原生节点，内置业界领先的自研时序大模型，如 Timer、Sundial 等，可通过标准 SQL 语句进行调用，实现时序数据的毫秒级实时推理，可支持时序趋势预测、缺失值填补、异常值检测等应用场景。 +AINode 是支持时序相关模型注册、管理、调用的 IoTDB 原生节点，内置业界领先的自研时序大模型，如清华自研时序模型 Timer 系列，可通过标准 SQL 语句进行调用，实现时序数据的毫秒级实时推理，可支持时序趋势预测、缺失值填补、异常值检测等应用场景。 系统架构如下图所示： diff --git a/src/zh/UserGuide/Master/Tree/AI-capability/AINode_timecho.md b/src/zh/UserGuide/Master/Tree/AI-capability/AINode_timecho.md index ae5ddf117..91f167168 100644 --- a/src/zh/UserGuide/Master/Tree/AI-capability/AINode_timecho.md +++ b/src/zh/UserGuide/Master/Tree/AI-capability/AINode_timecho.md @@ -21,7 +21,7 @@ # AINode -AINode 是支持时序大模型注册、管理、调用的 IoTDB 原生节点，内置业界领先的自研时序大模型，如 Timer、Sundial 等，可通过标准 SQL 语句进行调用，实现时序数据的毫秒级实时推理，可支持时序趋势预测、缺失值填补、异常值检测等应用场景。 +AINode 是支持时序相关模型注册、管理、调用的 IoTDB 原生节点，内置业界领先的自研时序大模型，如清华自研时序模型 Timer 系列，可通过标准 SQL 语句进行调用，实现时序数据的毫秒级实时推理，可支持时序趋势预测、缺失值填补、异常值检测等应用场景。 系统架构如下图所示： diff --git a/src/zh/UserGuide/V1.3.x/AI-capability/AINode_apache.md b/src/zh/UserGuide/V1.3.x/AI-capability/AINode_apache.md index e88a3e77d..354ce29da 100644 --- a/src/zh/UserGuide/V1.3.x/AI-capability/AINode_apache.md +++ b/src/zh/UserGuide/V1.3.x/AI-capability/AINode_apache.md @@ -21,7 +21,7 @@ # AINode -AINode 是支持时序大模型注册、管理、调用的 IoTDB 原生节点，内置业界领先的自研时序大模型，如 Timer、Sundial 等，可通过标准 SQL 语句进行调用，实现时序数据的毫秒级实时推理，可支持时序趋势预测、缺失值填补、异常值检测等应用场景。 +AINode 是支持时序相关模型注册、管理、调用的 IoTDB 原生节点，内置业界领先的自研时序大模型，如清华自研时序模型 Timer 系列，可通过标准 SQL 语句进行调用，实现时序数据的毫秒级实时推理，可支持时序趋势预测、缺失值填补、异常值检测等应用场景。 系统架构如下图所示： ::: center diff --git a/src/zh/UserGuide/V1.3.x/AI-capability/AINode_timecho.md b/src/zh/UserGuide/V1.3.x/AI-capability/AINode_timecho.md index 14d8bbf6b..0e3b6ee97 100644 --- a/src/zh/UserGuide/V1.3.x/AI-capability/AINode_timecho.md +++ b/src/zh/UserGuide/V1.3.x/AI-capability/AINode_timecho.md @@ -21,7 +21,7 @@ # AINode -AINode 是支持时序大模型注册、管理、调用的 IoTDB 原生节点，内置业界领先的自研时序大模型，如 Timer、Sundial 等，可通过标准 SQL 语句进行调用，实现时序数据的毫秒级实时推理，可支持时序趋势预测、缺失值填补、异常值检测等应用场景。 +AINode 是支持时序相关模型注册、管理、调用的 IoTDB 原生节点，内置业界领先的自研时序大模型，如清华自研时序模型 Timer 系列，可通过标准 SQL 语句进行调用，实现时序数据的毫秒级实时推理，可支持时序趋势预测、缺失值填补、异常值检测等应用场景。 系统架构如下图所示： ::: center diff --git a/src/zh/UserGuide/dev-1.3/AI-capability/AINode_apache.md b/src/zh/UserGuide/dev-1.3/AI-capability/AINode_apache.md index e88a3e77d..354ce29da 100644 --- a/src/zh/UserGuide/dev-1.3/AI-capability/AINode_apache.md +++ b/src/zh/UserGuide/dev-1.3/AI-capability/AINode_apache.md @@ -21,7 +21,7 @@ # AINode -AINode 是支持时序大模型注册、管理、调用的 IoTDB 原生节点，内置业界领先的自研时序大模型，如 Timer、Sundial 等，可通过标准 SQL 语句进行调用，实现时序数据的毫秒级实时推理，可支持时序趋势预测、缺失值填补、异常值检测等应用场景。 +AINode 是支持时序相关模型注册、管理、调用的 IoTDB 原生节点，内置业界领先的自研时序大模型，如清华自研时序模型 Timer 系列，可通过标准 SQL 语句进行调用，实现时序数据的毫秒级实时推理，可支持时序趋势预测、缺失值填补、异常值检测等应用场景。 系统架构如下图所示： ::: center diff --git a/src/zh/UserGuide/dev-1.3/AI-capability/AINode_timecho.md b/src/zh/UserGuide/dev-1.3/AI-capability/AINode_timecho.md index 14d8bbf6b..0e3b6ee97 100644 --- a/src/zh/UserGuide/dev-1.3/AI-capability/AINode_timecho.md +++ b/src/zh/UserGuide/dev-1.3/AI-capability/AINode_timecho.md @@ -21,7 +21,7 @@ # AINode -AINode 是支持时序大模型注册、管理、调用的 IoTDB 原生节点，内置业界领先的自研时序大模型，如 Timer、Sundial 等，可通过标准 SQL 语句进行调用，实现时序数据的毫秒级实时推理，可支持时序趋势预测、缺失值填补、异常值检测等应用场景。 +AINode 是支持时序相关模型注册、管理、调用的 IoTDB 原生节点，内置业界领先的自研时序大模型，如清华自研时序模型 Timer 系列，可通过标准 SQL 语句进行调用，实现时序数据的毫秒级实时推理，可支持时序趋势预测、缺失值填补、异常值检测等应用场景。 系统架构如下图所示： ::: center diff --git a/src/zh/UserGuide/latest-Table/AI-capability/AINode_apache.md b/src/zh/UserGuide/latest-Table/AI-capability/AINode_apache.md index 0f4a8b1ca..18eff8ec6 100644 --- a/src/zh/UserGuide/latest-Table/AI-capability/AINode_apache.md +++ b/src/zh/UserGuide/latest-Table/AI-capability/AINode_apache.md @@ -21,7 +21,7 @@ # AINode -AINode 是支持时序大模型注册、管理、调用的 IoTDB 原生节点，内置业界领先的自研时序大模型，如 Timer、Sundial 等，可通过标准 SQL 语句进行调用，实现时序数据的毫秒级实时推理，可支持时序趋势预测、缺失值填补、异常值检测等应用场景。 +AINode 是支持时序相关模型注册、管理、调用的 IoTDB 原生节点，内置业界领先的自研时序大模型，如清华自研时序模型 Timer 系列，可通过标准 SQL 语句进行调用，实现时序数据的毫秒级实时推理，可支持时序趋势预测、缺失值填补、异常值检测等应用场景。 系统架构如下图所示： diff --git a/src/zh/UserGuide/latest-Table/AI-capability/AINode_timecho.md b/src/zh/UserGuide/latest-Table/AI-capability/AINode_timecho.md index 53370fd52..562cd2f20 100644 --- a/src/zh/UserGuide/latest-Table/AI-capability/AINode_timecho.md +++ b/src/zh/UserGuide/latest-Table/AI-capability/AINode_timecho.md @@ -21,7 +21,7 @@ # AINode -AINode 是支持时序大模型注册、管理、调用的 IoTDB 原生节点，内置业界领先的自研时序大模型，如 Timer、Sundial 等，可通过标准 SQL 语句进行调用，实现时序数据的毫秒级实时推理，可支持时序趋势预测、缺失值填补、异常值检测等应用场景。 +AINode 是支持时序相关模型注册、管理、调用的 IoTDB 原生节点，内置业界领先的自研时序大模型，如清华自研时序模型 Timer 系列，可通过标准 SQL 语句进行调用，实现时序数据的毫秒级实时推理，可支持时序趋势预测、缺失值填补、异常值检测等应用场景。 系统架构如下图所示： diff --git a/src/zh/UserGuide/latest/AI-capability/AINode_apache.md b/src/zh/UserGuide/latest/AI-capability/AINode_apache.md index d3b350672..9d92fb365 100644 --- a/src/zh/UserGuide/latest/AI-capability/AINode_apache.md +++ b/src/zh/UserGuide/latest/AI-capability/AINode_apache.md @@ -21,7 +21,7 @@ # AINode -AINode 是支持时序大模型注册、管理、调用的 IoTDB 原生节点，内置业界领先的自研时序大模型，如 Timer、Sundial 等，可通过标准 SQL 语句进行调用，实现时序数据的毫秒级实时推理，可支持时序趋势预测、缺失值填补、异常值检测等应用场景。 +AINode 是支持时序相关模型注册、管理、调用的 IoTDB 原生节点，内置业界领先的自研时序大模型，如清华自研时序模型 Timer 系列，可通过标准 SQL 语句进行调用，实现时序数据的毫秒级实时推理，可支持时序趋势预测、缺失值填补、异常值检测等应用场景。 系统架构如下图所示： diff --git a/src/zh/UserGuide/latest/AI-capability/AINode_timecho.md b/src/zh/UserGuide/latest/AI-capability/AINode_timecho.md index ae5ddf117..91f167168 100644 --- a/src/zh/UserGuide/latest/AI-capability/AINode_timecho.md +++ b/src/zh/UserGuide/latest/AI-capability/AINode_timecho.md @@ -21,7 +21,7 @@ # AINode -AINode 是支持时序大模型注册、管理、调用的 IoTDB 原生节点，内置业界领先的自研时序大模型，如 Timer、Sundial 等，可通过标准 SQL 语句进行调用，实现时序数据的毫秒级实时推理，可支持时序趋势预测、缺失值填补、异常值检测等应用场景。 +AINode 是支持时序相关模型注册、管理、调用的 IoTDB 原生节点，内置业界领先的自研时序大模型，如清华自研时序模型 Timer 系列，可通过标准 SQL 语句进行调用，实现时序数据的毫秒级实时推理，可支持时序趋势预测、缺失值填补、异常值检测等应用场景。 系统架构如下图所示：