Recently, while organizing my Notion, I realized I had inherited the bookmarking habits from my Evernote days. I meticulously categorized information collected from the internet by purpose and type. Essentially, these were individual pieces of information waiting to be organized, lacking connections between them. Yet, the connection and integration of information are precisely the efficiency skills for acquiring knowledge in the AI era.
Mindset Pitfalls#
Becoming aware of this issue took a week of reflection, and I found I was still trapped in habitual thinking patterns. I habitually applied standard parent-child structures and library-style categorization to meticulously tag and classify the information I gathered from the internet. This process was essentially me manually labeling data, consuming my own time and energy.
This process was neither efficient nor particularly tedious; it prompted me to consider whether I could streamline and optimize this complex system. Drawing on some past reflections, I took three actions:
- Simplify page hierarchies to a maximum of three levels. Consolidate all information under a broad thematic category, using language I understand to connect various related pieces of information.
- Use AI tools to summarize collected articles, extracting and retaining core viewpoints and examples.
Simplifying Pages#
Assign a primary theme to a page, for example: Content Creation. Under this page, I would list all tutorial articles, tools, personal exploration experiences, industry development directions, etc., that I could find. I would also handle the titles, main text, and extended links of this content to facilitate quick retrieval via search later.
Since the content is displayed on the parent-level page, there’s little need for extensive sub-pages for expansion; having two levels of sub-pages is more than sufficient.
On new thematic pages, I focus on recording exploration experiences in plain language and connect to other pages through hyperlinks and references, linking information within Notion. I also use color highlighting, background colors, and other methods to mark important information, allowing me to quickly extract key points during later reading.
AI Summarization#
After collecting articles, in the past, I needed to spend time reading them, summarizing their content, and then deciding which thematic page they belonged on. Now, I delegate this process directly to AI, using tools like ChatGPT to summarize page content.
I then read this summary and, based on the extracted points, refer back to the original article’s description of those points. This process is particularly convenient for logical reasoning and assessing the completeness of information. It effectively reduces the difficulty of information processing for me. Now, my processing time for a piece of information might drop from several minutes to tens of seconds, greatly increasing my personal efficiency.
Applying the above approach to reorganize previously collected concepts and articles, I noticed that personal experience descriptions often contained too many personal verbal habits or subjective descriptions. In the past, while reading such articles and information, our brains would perform a simplification process on the information.
Now, after delegating this process to AI, I feel I focus more on how to understand the core information: Is anything missing? Is the logic complete? Is the entire process verifiable?
My mental focus has shifted to exploring the essence of problems, and this thinking process happens to align closely with the approach of mathematical research. After processing, information becomes a precise, quantifiable discussion tool, which is precisely the role mathematics plays.
This information processing process perfectly aligns with Shannon’s Information Theory, which I once read about. Information Theory has profoundly influenced the development of modern computing and artificial intelligence.
Summary#
During the process of streamlining information, I sorted through past thoughts and tool usage experiences, using AI to perform a kind of “discard and detach” on this information. Interestingly, this validated the correctness of Information Theory and mathematical thinking processes. It successfully sparked a strong interest in these two concepts, and I plan to explore them more deeply in the future.
Curiosity will always be the driving force of human progress!
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