Breaking Through the Information Volume Bottleneck of Traditional Organizations

By observing the operational characteristics of deep-learning networks in computers, it can be seen that larger training sample sizes and more neurons typically imply greater potential for intelligence. An increase in organizational individuals in the Intelligent Consortium may yield similar efficiency. Conversely, in traditional organizations, increasing the number of individuals raises management costs, weakening organizational vitality, which is similar to the efficiency characteristics of information processing systems under cybernetics.

Breaking through the information volume bottleneck enables greater intelligence potential, a higher total mobilization degree, and increased node individual mobilization degree. As stated in The Organizational Settings of Intelligenism regarding mobilization, a higher node individual mobilization degree leads to greater information uncertainty, increasing the difficulty of process management for individuals by the organization. Additionally, a higher node individual mobilization degree leads to greater information invocation, increasing management difficulty for the organization. However, when the Intelligenism organization breaks the information volume bottleneck of traditional organizations, it means the new paradigm organization can accommodate larger information volumes while maintaining healthy operations, enabling the Intelligent Consortium to mobilize high-node individual mobilization degree individuals.

The inverted triangle feedback structure of the Intelligent Consortium means that it exhibits an information diffusion state during operation, while traditional organizations continuously simplify and filter information, leading to a continuous contraction of information. This makes the Intelligent Consortium inherently expand and complicate information volume, and the increase in information complexity and volume can fully leverage the intelligence potential of the deep-learning network (in deep-learning network training, larger sample sizes and broader sample coverage are more conducive to intelligent learning).

Based on the views in Polanyi’s Personal Knowledge, objective knowledge ultimately evolves into the personal knowledge (tacit knowledge) of practitioners in practice, making personal knowledge more individualized and less replicable. In the mobilization process of traditional organizations, only the objective knowledge output of organizational individuals can be managed to a certain extent. Still, considering that the vast details of tacit knowledge cannot be fully described or summarized, actions based on tacit knowledge for decision-making and execution cannot be process-managed. They may even be restricted or weakened in traditional process management. After accepting the reality of tacit knowledge, directly applying it in the Intelligent Consortium for driving and action, while ignoring its generation process, is more preferable.