Measurement and optimisation of the performance of probabilistic networks generated by Net AI

Net AI是由KADlytics有限公司开发的一项新颖的专利技术。Net AI可以自动创建一个连接数字资产、知识和人员的项目内部依赖关系网络。Net AI的主要市场是高价值的协同工程项目，如建筑、机械和软件工程。工程项目以大量的依赖关系为特征，包括显性的和隐性的，理解依赖关系网络对于需要考虑以下因素的项目经理是非常有价值的：谁对什么负责？谁知道什么？变化的影响？让步的代价是什么？学术和工业文献发现，缺乏对高价值项目的这些方面的理解是造成代价高昂的失败和超支的常见原因。到目前为止，项目依赖关系的管理和后续分析都是通过对项目成员的调查和访谈来手工进行的。捕获这些信息所花费的时间导致网络立即过时。Net AI通过实时生成和更新这些网络，并且比目前可能的细节水平更高，从而打破了这种做法。Net AI还会随着项目的发展做出预测和建议（例如，决定某人离开时的工作分配，在公司内分配工作和知识，以及评估变更的传播）。Net AI是一种新兴的最先进的技术，在证明其性能方面提出了一个特别的挑战：i)覆盖“真实”依赖关系，ii)随着项目发展识别依赖关系的置信度。我们最初的客户需要这种理解和证据，以形成他们的内部业务案例。类似地，我们需要这些证据来管理期望和量化Net AI的能力，并因此受益，例如，在项目的第一季度内自动建立50%的关键依赖关系。这种证据的缺乏目前阻碍了我们客户的投资决策。由于Net AI是一种独特的AI技术，因此没有现有的现成技术或方法可以应用，因此本项目努力开发它们，专门用于测量和优化上述i和ii方面的Net AI性能。当这些技术建立起来，并且Net AI的有效性在跨行业得到证明时，它将有助于实现英国和世界范围内高价值设计项目的潜在巨大成本节约。

Net AI is a novel proprietary technology developed by KADlytics Limited. Net AI can automatically create a network of intra-project dependencies linking digital assets, knowledge and personnel. Net AI's primary market is high-value collaborative engineering projects, such as those in construction, mechanical and software engineering. Engineering projects feature a wealth of dependencies, both explicit and implicit, and understanding the network of dependencies is extremely valuable to Project Managers who need to consider factors such as: Who is responsible for what? Who has knowledge of what? The impact of change? The cost of concessions? It is a lack of understanding of these aspects of high value projects that academic and industrial literature have found to be the common causes for costly failures and overruns.To this day, the management and subsequent analysis of project dependencies has been manual using surveys and interviews with project members. The time it takes to capture this information results in networks that are immediately out-of-date. Net AI disrupts this practice by generating and updating these networks in real-time and to a higher-level of detail than currently possible. Net AI also makes predictions and recommendations as a project evolves (e.g. determining work allocation when someone leaves, distributing work and knowledge across the company, and evaluating the propagation of change).Net AI is an emerging state-of-the-art technology and poses a particular challenge in terms of evidencing its performance in terms of: i) coverage of 'real' dependencies and ii) confidence levels in the identification of dependencies as a project evolves. Our initial customers require this understanding and evidence in order to form their internal business case. Similarly, we require this evidence to manage expectations and to quantify the capability of Net AI and hence benefits e.g. 50% of critical dependencies automatically established within the first quarter of a project. This lack of evidence is currently withholding investment decisions by our customers. Since Net AI is a unique AI technology there are no existing off-the-shelf techniques or approaches that can be applied and hence this project endeavours to develop them specifically to measure and optimise the performance of Net AI with respect to i & ii above.When these techniques are established and effectiveness of Net AI demonstrated cross-industry, it will assist with realisation of potentially huge cost savings for high-value design projects in the UK and world wide.