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- #007 | Context Management > Time Management
#007 | Context Management > Time Management
Hi, I’m Ryan! You are receiving this because you have signed up to my weekly newsletter for Natural Language Processing (#NLP365), Entrepreneurship, and Life Design content!
Hey friends,
Last week, we talked about predictable vs unpredictable projects and how context management is the solution to counter unpredictable projects / tasks. Although I am still early in the experiment phase, I have found the following methods to be very useful in helping me manage context between different projects. But first up, what does context management means? Recall that unpredictable tasks have two characteristics:
Time and effort does not guarantee progress
It takes a long time for you to get “in the zone” or “in the context”
There’s not much we can do with the first characteristic but if we can alleviate the second one, it can help us better compound our effort from each time block, moving us slowly towards a solution. Context management, therefore, means techniques that can help us quickly get back up to speed again (back in context) whenever we resume a project / task. Here are the two methods that I have experimented with and found some success:
Narrative LoggingNarrative logging is very similar to daily journalling, but rather than writing about your day in general, you do narrative logging for EACH of your project. The goal here is to write down your thought process and flow for each project so that everytime you pick up the project again, you can review your most recent thought process and get back up to speed quicker. The question to ask yourself for narrative logging is:
Permanent NotesThere are three types of notes: Capture, Literature, and Permanent Notes.Capture notes are used to quickly capture all your random thoughts and ideas so that you can review them ready. If you don’t write your thoughts down, you will most likely forget them. Literature notes are notes you make on different information sources. This is the note type that everyone is familiar with. For example, you make notes on your lecture slides, books, podcasts, videos, etc.Permanent notes are organisation of literature notes to make sense of what you have learned. A popular example of permanent notes is your degree thesis. When you are writing your thesis, as part of your literature review, not only do you need to consume different papers and make notes (literature notes) but you also need to organise them into a cohesive story / group. Another example of permanent notes is cheatsheet where everytime you consume something new, you will add new knowledge to the same note and make the cheatsheet more robust and useful overtime. Thus, permanent notes gets more informative over time.Permanent notes help with context management because it allows you to capture the knowledge that you have gained from each time block and as a result, less context is loss between session as knowledge has already been captured.
This week I finished reading:
Storyworthy (16th Feb - 19th Feb 2021)
Total: 14 / 26 books | 1 / 26 level 4 notes | 0 / 12 actions
❓Question of the Week
How do you usually deal with context management?
Share with me your thoughts by replying to this email 👻 👻 👻
🐦 Tweet of the Week
Your life is purchased by where you spend your attention.
— James Clear (@JamesClear)
4:43 PM • Feb 17, 2021
💡 Quote of the Week
Peacetime and wartime management techniques can both be highly effective when employed in the right situations, but they are very different. The peacetime CEO does not resemble the wartime CEO — The Hard Thing About Hard Things
🔥 Recommendation(s) of the Week
GeForce RTX 3090 — My department asked me to look into what GPU I need for my PhD this week and so I spend an hour browsing the internet to see which GPU I should get. From my quick research, GeForce RTX 3090 seems to be a great GPU. Its performance is very close to Tesla V100 with relatively low cost! Check it out :)
If you guys know any better GPUs I can look into, please reply and let me know! It would helpful :)
🔦 AI Research Paper(s) Spotlight of the Week
I spent the whole week trying to make BERTweet work 😥 What was supposingly a two day work turned into five days of debugging! BUT I am happy to share that on Friday, I finally got it to work and I now hold the SOTA model for NER! So much power muahahaha 😈
But this also means that I didn’t get to read any new research papers this week. And so instead, I will display my notes on Knowledge Graph vs Property Graph here. I am still building my understanding regarding the difference between the two but here’s what I got so far:
Knowledge Graph don't have properties on edges whereas Linked Property Graph does. To directly model property on edges, we can use SPARQL* and RDF*
Terminology Difference —> Labels
SHACL is the language for creating ontologies (aka rules and constraints for RDF graphs). Ontologies is what you used to turn RDF graphs into knowledge graphs.
Terminology Difference —> Properties
🎥 This Week on YouTube
That’s it for this week! I hope you find something useful from this newsletter. More to come next Sunday! Have a good week ahead! 🎮