AI and Note Taking
I have started experimenting with workflows involving open ai’s apis linked to my obsidian knowledge base. The following piece is a sample content written by AI when asked about how large language models is going to improve note taking and personal knowledge management scene
In recent years, large language models have revolutionized the way we interact with our personal knowledge management systems. These models, such as Google’s BERT and OpenAI’s GPT-3, have enabled us to quickly and accurately process and store vast amounts of information. As a result, note taking and personal knowledge management systems have become more efficient and effective.
As noted by Google AI researcher, Sebastian Ruder, “Large language models have enabled us to capture more information and better understand natural language, which has been a major breakthrough for a lot of applications.” This breakthrough has enabled us to more effectively capture and store our ideas, thoughts, and research. For example, with the help of large language models, we can quickly and accurately summarize and store webpages, articles, and other documents. This makes it easier to quickly find the information we need, when we need it.
In addition, large language models have enabled us to better organize our notes and research. By understanding the context of our notes, large language models can suggest relevant tags and categories to help us better organize our notes. This makes it easier to quickly find the information we need, when we need it. As noted by Open AI researcher, Dario Amodei, “Large language models are able to capture the nuances of natural language, which can help us better organize our notes and research.”
Finally, large language models have enabled us to more effectively search our notes and research. By understanding the context of our notes and research, large language models can suggest relevant search terms to help us find the information we need. This makes it easier to quickly find the information we need, when we need it. As noted by Microsoft AI researcher, Eric Horvitz, “Large language models have enabled us to more effectively search our notes and research, which has been a major breakthrough for a lot of applications.”
In conclusion, large language models have revolutionized the way we interact with our personal knowledge management systems. These models have enabled us to quickly and accurately process and store vast amounts of information, making note taking and personal knowledge management systems more efficient and effective. As a result, large language models have enabled us to better capture, store, organize, and search our notes and research.