The Inception of the brainful Paradigm

🧠 brainful📄 paper

Founder's Monologue

The disjoint and, more notably, destructured nature of knowledge acquisition has, for the longest time, troubled me deeply. The demands of higher-level learning exposed the inadequacy of simply storing and retrieving information.

Being a diligent organiser and hard worker does not overcome the fact that the traditional folder and file-based system introduced in the 20th century no longer fits the purpose of modern 21st-century productivity and cognitive demands. I realized that true productivity lies in the ability to effectively process, connect, and utilize knowledge – a realization that fueled my exploration of more intelligent knowledge management systems.

The realisation that it is the tools that shape your thinking is an important one. I realised in my penultimate year of high school in a theory of knowledge class that making connections between ideas, especially across areas of knowledge, is the most effective method of learning. This is also why there are vast amounts of evidence on the benefits of effective knowledge mapping (e.g mind maps, concept maps) in facilitating higher-order thinking (Okada 2007).

It is troubling to fathom basic capabilities in modern software do not support such models. The fact that you cannot draw a simple bidirectional let alone directional, link between two files on a system or within any modern note-taking software or productivity suite was troubling at the time. It is only now, at the time of writing this, in 2024, that the first versions of such links have begun to appear in some software, yet vastly primitive.

This is a defining moment.  The convergence of AI,  advanced web technologies, and decades of research has created an unprecedented opportunity to revolutionize how we think and learn.  Recognizing that the tools I envisioned were nowhere to be found, I questioned the status quo.

If no one else was going to do it, I knew the time was now

Founding Principles

brainful was born from a desire to create a knowledge management system that empowers users to think more effectively and creatively. This required modelling the way the mind learns effectively and accurately based on the following key principles:

- centralisation of knowledge : No knowledge is separated or stored in separate locations. Unlike traditional fragmented file-based systems, brainful consolidates all your knowledge in a unified space. This eliminates the need to switch between applications or struggle to locate information, fostering a seamless flow of thought.
- commonality of structure : Every piece of information within brainful is represented in a consistent and interconnected 'block' abstract data structure. This allows for effortless linking, analysis, and synthesis of diverse knowledge sources.

- rapid access and retrieval : modern knowledge management systems are slow to operate and often cannot handle the automated simultaneous loading of multiple documents. brainful is engineered for speed and efficiency using cutting-edge enterprise-grade solutions for demanding use cases.

- seamless workspace state handling : handle different 'projects of thought' separately. Imagine seamlessly switching between different projects or lines of inquiry without losing your train of thought. brainful's workspace state management allows you to capture and restore complete work environments, preserving context and boosting productivity.

- sentient and knowledgeable AI : the AI, or rather, system of agents, should know your knowledge and you better than you, to facilitate the process of deep and higher-order learning throughout Bloom's Taxonomy, from learning to analysing to evaluating to creation of knowledge. It is in its truest sense, an intelligent thinking partner.

- proactive system : modern software is built to be reactive. Traditional web programs were a one-way affair, with simple server requests to produce static web pages. Modern web design allows for reactive web applications through interactivity using JavaScript. However, true augmentation of human intelligence demands that the user be guided or instructed. The system must be proactive (in that it is able to initiate interaction with the user independently) rather than a strict client interacting with the system.

- human-agent collaboration : collaboration is critical to developing, critiquing, and validating ideas and output. Enabling multi-room document-based collaboration rooms with agent involvement can be highly beneficial to output.

The brainful Paradigm

The principles above collectively encapsulate the 'brainful paradigm' – a new approach to knowledge management that prioritizes fluidity, interconnectedness, and collaborative agentic and human cognitive augmentation. It pushes forth a networked note-taking approach to knowledge acquisition that is adopted through the diligent use of the following five key relationships:

- Vertical Block Relationships (Hierarchical) : This shows how blocks are related in a parent-child structure. Example: A block about "Pets" might have child blocks for "Dogs" and "Cats".

- Horizontal Block Relationships (Associative) : These are can be uni or bi-directional connections between related blocks. Example: Your "Coffee" block might be linked to both "Caffeine" and "Morning Routines".

- Block-BlockReference Relationships (Evidential) : These connect your blocks to their block references (sources). Example: Your block about "Climate Change Effects" might be linked to several scientific papers.

- [Block/BlockReference]-Entity Relationships (Organizational) : This shows how blocks are organized using entities (tags). Example: Blocks such as this one are tagged with 🧠 brainful , and are related as a collection, even if they're not directly linked.

- [Block/BlockReference]-BlockSpace Relationships (Meta-organizational ): This is the highest level of organisation, for managing big ideas (e.g. projects, assignments, plans, orchestration) that requires synchronising a state of particular blocks and/or BlockReferences over an extended period of time. BlockSpaces bring together all of these data structures in a saved state that allows switching between such states seamless

In essence, this mode of work forces you to modularise and deconstruct knowledge into its primitive parts and derive meaningful connections between them.

References

Okada, Alexandra (2007). Using knowledge maps applied to open learning to foster

thinking skills. In: The 12th Cambridge International Conference on Open and Distance

Learning, 25-28Sep 2007, New Hall, Cambridge, UK.