Artificial Intelligence has come a long way by surpassing human level performances in many industries. DNN’s (Deep Neural Networks) massive computational capabilities have an important role in this development progression of AI. However, there is still lot to explore in how machine learning algorithms deal with new and never-experienced scenarios. Humans on the other hand can easily respond to new scenarios transferring knowledge acquired in other related contexts.
Higher cognitive functions such as attention, concept formation, memory and meta cognition are important aspects to facilitate learning. Their operation plays an important role in simplifying complex problems and driving generalizations. Linking neural networks with external memory resources can enhance the learning capabilities of machines.
Analyzing the intelligent system of IDS (Innovative Design System) in reference to its cognitive capabilities shows that it requires multi memory architecture, including interconnected knowledge types such as declarative, procedural, attentional, episodic, and intentional (goal related).
Pattern recognition and formation is included in the knowledge creation of this system’s major functions. These cognitive processes have the capability of recognizing the stage where they lack the information to perform effectively on its own and automatically draws information from other knowledge creation mechanisms.
This cross-mechanism interaction results in highly effective performance of the IDS system thinking capabilities and generates better design decisions on various stages of the project delivery process: also known as cognitive synergy.
System learning mechanism is familiar with the situation called ‘Stuck’ which means that there is inadequate information for making the bold judgement in the next step. This is the scenario included in cognitive synergy
where system in ‘Stuck’ mode takes help from ‘other’ cognitive mechanisms.
System design identifies the ‘other’ cognitive mechanisms that can support in the effective decision which could be the external memory resources in certain specific cases.
Cognitive computing is essential in IDS because the problems are complex, information and circumstances are constantly shifting, and the final outcome is usually dependent on context.
This phenomenon is the cognitive schematic in which the relationship between context, procedures, and goals are evaluated; all possible relationships are analyzed; and new procedures in reference to context are created as needed.
Major factors of delay in the current project delivery process:
Project delivery process goes through phases that are considered in the master plan of IDS as well:
New subsystems of IDS include:
They are the extension of cognitive computing technologies incorporated for effective system performance.
IDS - DORM (Subsystem of IDS)
IDS introduces its customized platform called IDS-DORM system. This is the embedded platform including all data organization & management tools. This includes the multi-level settings with specific tools and libraries.
IDS-DORM system functions as an information hub for all modules and components of IDS required in building design project delivery process. The nature of this platform is adaptive as it learns from any information change or as new goals and requirements evolve.
IDS-DORM system is interactive with other processors, devices, cloud services and people and at the same time solve any ambiguous problems arises. It has the potential to identify and extract the contextual elements needed for specific functions.
To be continued…..
Dexign 3D Research supplements the intelligent system of IDS: a breakthrough towards Artificial General Intelligence.