I personally struggle with resource overwhelm sometimes…
How often do you research to get insights, deeper knowledge or validate a hypothesis?
How do you research and learn?
What are your favourite tools and what are you biggest pain points?
I read a lot. I used to have time to read basically whatever, and would generally just follow the bibliographic of referential trails in other books. Now, my time is much more limited, so whenever I want/need to learn about something new, I'm more disciplined and devise an "essential reading list" as a first step. To do this, I'll perform a basic google search for the topic, check a wikipedia article, or search for the topic on a publisher's website. I'll read the abstract for each book and try to determine which ones are oriented toward beginners. I'll usually select at least three "beginner books" and read them, along with a couple of select "advanced" books that I know I'll have to wait to get to until later.
I try to read for at least 45 minutes each day and I take notes on the books I read. From there I move on to the more advanced stuff I gathered and use my old habit of following bibliographic references for more.
Umberto Eco has a book on how to write a PHD thesis, How to Write a Thesis
. I think a lot of the techniques described in that book are valuable for any kind of research, whether your aim is to write a thesis or just to learn something new.
Funny enough but I started reading more once have child. Before it was irregular activity. But now I allocated time because it’s the only way I can have a chance to read.
I'm working my way through Building a Second Brain by Tiago Forte. I can't say I've digested it well enough to recommend it, but a key point that stuck with me is to get into the habit of making a note of things you encounter day-to-day (including while reading and researching), and using the "PARA" method to file them into projects, resources, areas, or the Gmail-like "archive." Projects are things you're actively working on -- 2023 taxes, planning a night out for your anniversary, reaching a level of proficiency with LLMs, etc. Resources are a little longer-lived than projects; they're subjects you find interesting that don't have a clear start or finish the way a project does, like a bash cheatsheet, or a gardening hobby. Finally, an area is something that never goes away, like personal finances or family paperwork.
These groups have helped me organize my "lifestream" a lot better. Rather than torturing myself about deciding the perfect place for everything I learn, PARA helps me understand that organization is more of a lifecycle with stages over time. Something might go into a project folder today, but when that project is complete (or abandoned), its parts can go into reusable resources, mini-brain areas, or the archive. That fluidity has made filing of information a lot easier.
This isn't a full answer to your whole question. But knowing how to deal with the influx of daily information, and developing more of an opinion what a research session's work product should look like, is a piece of the puzzle.
What do we do? There are infinite methods, tools, apps, and only so many hours in a day. Do you just keep trying tools/methodologies till one clicks with you?
Fell into that trap before. You recognize that no note taking system is perfect, so you just pick one that doesn’t get in your way. After shuttling between a bunch, I was most productive just using Apple notes for a long time. I use Obsidian now. Feels good and doesn’t lock me in.
What do we do? There are infinite methods, tools, apps, and only so many hours in a day. Do you just keep trying tools/methodologies till one clicks with you?
It's the same in the productivity world as it is in the programming one. Problems never have a perfect solution and you have limited resources and different bottlenecks. People come up with different things, that work for them, that might not work for others.
You can find interesting things if you overlap Software and Personal Behavior resources
Personal resources: time, energy, friction, memory, agency
Software resources: time, computation complexity, memory, business logic
I spent a long time searching, and then trying to invent my own "perfect" system. Where to archive done items, how to organize item priorities, what date format to use, etc.
I saw the system as this external thing that if I could get it just right maybe my life would be solved (exaggerating obviously).
Eventually my focus shifted from the system itself, to my interaction with it. I realized that it wasn't about having a system, it was about removing as much friction as possible.
Yes. Find one that works. Don't strive for perfection in it. And then move on. Don't keep obsessing over organization if what you are doing is working.
As someone who never enjoyed reading non-fiction books (and still doesn't), I've talked about this topic with someone who successfully devours books on the topic of "How to be a great boss". Their suggestion was that while there are many Greats, each with a devout following of their own, you as a non-convert aren't really expected to deeply study GTD and the like and then either Join The Club or better have a good reason not to like this magnum opus. That space of books can be enjoyed simply by lightly reading them, seeing what sticks with you - personally - and then moving on. Since the subject and the methods on offer are so broad, it is really ok to just think "meh" and not waste anymore time on PARA etc., if in that specific case the method just doesn't resonate with you. This is how I arrived at my very slimmed down version of Bullet Journaling - it was supposed to solve my problem and I realized that it's ok not to be a stationery influencer with forty shades of pastels arranged in slightly chaotic groups so they look nice on the Insta.
I think everybody is struggling with this. I found very good example and that is Duolingo, it forces you to take lessons every day. And after month or so it's just in your mind, that feeling you need to finish something, no matter if it's 2 minutes, it's just that you are doing it each day.
I.e. I started learning Data Science lately (frontend developer here), and I just picked one course and learn each day few lessons. More and more, I'm convinced that these small steps are once that moves you forward whether you are learning something new or going to gym, what ever. Just show up, and do that small step each day.
Everything else will come together. You will need to do some research anyway if you want to 'finish' some task, so I don't bother with that. Just go, and learn.
The big icon with the streak and it turning red toward the end of the day really helps. Recognizing that some days you won't want to learn but just getting through it is ok. It's a really slow process if you're not deliberate but slow is better than none IMO.
A great experiment to do would be to sit people down and have a quiz application like Duolingo randomly choose answers, them seeing if the answers are right/wrong.
I suspect, much like experiments showing how people prefer/like (Familiarity effect) art they have seen in a previous session (even if months later and they don't remember and can't explain why they like it more than other art!), that students would pick up some correct/incorrect answers, because they can't help but read and notice any interesting differences from their mental model.
I have built an app which prepares exercises for you based on your subject and uses LLM-chosen emojis to represent each exericse. It notifies you with the emoji for each lesson each day with the idea of a visual cue but now you mention it using a dynamic icon for the app might be more important of a visual cue (to get the daily cadence/habit), rather than something recognisable
The question reminds me of the dilemma between exploration and exploitation [1]. The art (or skill) is learning when to stop and redirect. Talking to friends about certain learning curves and making sure I don't waste my time just researching or building things that are overloaded with features has helped me a lot. I think it's generally good to know that there's a tradeoff no matter what you're trying to learn or explore.
This is my second time seeing a reference to this concept today, but apparently the Wikipedia article was created in 2023. It's an interesting idea though... did it come from machine learning research?
I remember learning something akin to this in social psychology in the context of a single risk-taker fish breaking from the school of fish to explore and take risks which ultimately benefitted the whole group.
I remember discussing this idea with my friends 10 years ago, when I started my first engineering job and felt my time shifting from mostly exploration to exploitation. I had spent years learning for the sake of learning, with no strings attached. Then, all of a sudden, I was applying what I had learned in exchange for money, and the people I worked for expected something valuable to come from how I spent my time.
I didn’t research machine learning, but my friends did, so it could have been an idea I picked up from someone else.
Anyway, I think it’s a valuable framework because we need to make time for exploration—it’s a great way to let go, have fun, and dissolve the fear of failure.
The terminology is widely used, and has been for decades, in reinforcement learning; so you're close.
The general idea is that your agent, however it is training, has to balance trying new things to possibly find the global maxima instead of getting hooked on a rewarding local maxima.
it's about a century old but the recent popularity of AI made more people aware of it, I personally became aware of it more than a decade while learning about reinforcement learning (the old kind with GOFAI) but it's also used in social fields, biology stuff like foraging theory or really anything that involve an agent with a brain.
Not really. You're making the choice to explore or exploit at each branch. It's closer to an A-star search, where the weights and heuristics are uncovered over time.
Also, the typical framing of the problem is the same "kind" of choice being repeatedly executed (e.g., betting on a coin-flip of unknown bias, or balancing the gain of consumer purchasing information vs exploiting known information when setting items into aisle end-caps in a grocery store). That has a lot more structure than arbitrary graphs, enough so to make it worthy of its own dedicated study (especially given the real-world applicability).
I really love Anki as a tool, especially to learn mechanical things (like vim key bindings), to remember arguments of key articles, and to situate myself back in the thoughts that I previously had.
For mechanical things:
I was able to learn lazygit keybindings by heart in a week that take care of 95% of my usage.
To remember key arguments of an article:
I make a card like
In the article _The Bitter Lesson_, what types of methods work better in the long run?
General methods that use computation (search/learning)
For situating myself:
I take a project I worked on and I make a card on what I found challenging, or the tools I used. Or what I learned after. A lot of our problem solving is pattern matching to things we've seen before so leveraging this is really powerful.
I don't normally post here- normally I lurk. But this spoke to me.
Learning and research is something you(someone) has to impose on themselves as a self-discipline(like working out, eating right or some other habit). I learned this early in my adolescent years- but it was not honed or realized until university. Once I got into college, I found out that I need to push myself to do the research for things I wanted to pursue- even if it wasn't directly related- in order to achieve my end goal. In comparison, as a naive kid- I would research hitboxes, best shooter tactics and related gaming notes. Now, I open myself to anything and everything- because I realize now 20 years later, that I can easily make what I learn into something I benefit/enjoy from with enough effort and perspective insight.
Long-story-short(tldr)?
Just because you don't know something now, doesn't mean it won't be important to you later. When that day comes, the last thing on your mind will be passive interest- and moreso long-term passion. Which, in retrospect- the former is the dopamine calling you home to stay placated with who you are- rather than you want to be.
Nowadays when I'm ready to learn a new field, I start by talking to chatGPT to get a general picture of the field and a few introduction books, specifically ones that are admittedly objective, not propagandistic. After reading these books, I will have an understanding of the field in order to reasonably plan what and how to learn next.
The key is de-fragmentation, which is the most important discipline in this age. Read serious publications by professional authors. Stay away from any traffic-driven information. I can't say they are 100% rubbish, but spending time on them causes far far more damage than gain.
Embrace a project-oriented approach. The project can be an app, a paper, or an article.
Define what you want to do. Then start working on that. Embrace a top-down approach. Learn only on a need-to-know basis. When you need to know something for the app or the paper, learn that. Don't touch anything else. Make a list of stuff that you find interesting.
Always keep the completion of the project in your mind, and nothing else.
Project-based learning/research works the best.
Also allocate some hours per week for goal-free learning. Read/do whatever you want. But, keep it limited.
This is my strategy too. It always pays off in unexpected ways. Things I never thought I'd end up learning, then turn into things I never thought I'd end up using even once I'd learned them.
For the last ~3 years I worked for companies. No proper publication. But some articles here and there [0]. My Master’s thesis [T]. A (trivial) game to learn Ruby [1]. There are a lot that are not published anywhere.
I have left my full time job this month, and now pursuing full time research independently hoping some papers + job exp. + GRE lands me a PhD in a good research uni.
When you are working, try to make sure that the job aligns with your long term goals. Then learn a lot from work. Learning at work is effortless.
Thank you. That’s very helpful. My day job is pretty basic stuff so I’m trying to learn things on the side, but have the same worry that the day job is where the main learning opportunities would be, so I probably need to find a better gig. Thanks, and good luck on your PhD search.
I typically use Google to search for links and usually end up finding the top 2-3 most helpful ones. After reading through them, I have recently begun saving these links to my GitHub account for future reference. I use a web extension along with a keyboard shortcut to do this. Here is an example of a saved link: https://github.com/dvcoolarun/til
Keep a notebook with you at all times, make time to study and reflect on your notebook pages. Also use a computer if you want grad-level dialogue with the ai, very helpful as well. But strongly recommend sticking to physical notebook because can flip pages and can commit pages to memory as landscapes more readily.
Regarding learning, I usually start with YouTube videos to get a foundation of the topic to see if it interests me. If it does, I’ll look more for advanced courses or books and go from there.
For research, I usually just use a search engine and read what seem to be credible sources. News articles, court documents, studies, etc.
I do two things. First, I read voraciously (both fiction and nonfiction) -- and make it a point to include topics that aren't in my usual set of interests. Second, if I want to learn something in-depth, I invent a project that requires that knowledge to accomplish, then tackle it. Learn by doing, and all of that.
Insights come when I'm listening to music. I listen to music like most people watch movies -- I sit down and actually listen without doing something else at the same time. It's very meditative and it's quite common that I get "aha" moments regarding things that I've been learning or doing.
For learning new stuff or deeper understanding old stuff I use "browser tab based backtracking".
I research some books and articles on the topic. As soon as I realize that I do not understand something (it doesn't click), I open new tabs researching the points I don't understand and so on. After understanding I backtrack by closing the new tabs.
The important part is the meta analysis: does this rabbit hole serve my initial goal? Given what I understood, is my initial goal still valid or should I revisit it?
Learned a lot, works great for my brain.
Follow your innate curiosity, and respect the edifice of knowledge constructed by those who came before us (i.e., don't get sucked into quackery without a deep understanding of the SOTA).
I'm going through this right now. What I'm beginning to notice is that I need to have a direction. If I don't have a direction, I'll consume all content that seems interesting. It's frankly too much. So I should be more specialized/directed at a particular goal/purpose. This is purely for the sake to not experience content overload.
At least, that's my working hypothesis for now, still testing this out.
Joking aside, I worry when I start working again too. I think recognizing that struggling is learning and aiming to get into the rhythm/habit of struggling even when you're tired - even a little bit - compounds. I'm also toying with the idea of cohort-based learning
I built https://histre.com/ to help with this. We all go through the explore -> filter -> decide loop when researching online. There weren't any good tools to help with that, until now :)
I work on a programming language with a friend. We try to remove as much of the pain points of day to day programming as possible, and it's very motivating to find solutions to various problems we've had for a long time.
I dont, then i realize i'm getting behind and madly try to catch up then realize its so hard to do when you dont sleep properly and start sleeping better then realize I'm getting behind and the cycle starts again.
I wouldn't say I "research," but I do learn. I do that by reading books
I don't read *that* much (for reference: I read 24 books last year; this year 5, so far). Every month I have a goal of how many pages I want to read. This month it's set at 8 pages per day, but usually I go well above that, only going to 8 pages if I'm not feeling like reading that day, which is rarer and rarer.
I also stopped taking notes, it's distracting and makes reading feel like a chore and pretty unenjoyable for me, but YMMV with regards to note-taking.
If I feel like I don't understand something, I will go back and re-read that, or re-read the whole book, multiple times if I have to. By re-reading books, you pick up pieces you missed on your first or second time (or third, and so on) reading them. It's also better to read a single book 1000 times than to read 1000 books one time, something I've learned thanks to Nassim Nicholas Taleb.
Speaking of Taleb, he recommends not continuing to read a book if it gets boring to you - to be bored of a single book but not of the act-of-reading-itself-type of a deal. I think that's very smart too. I intuitively did that before I read this recommendation of his.
Did I mention you should his books? Because you should, everyone should.
I used to approach topics by picking the top five-ten books on the subject and reading them. This works, but not as well as I think most people assume. The reality is that you end up not really remembering most of the information you learn. Reading can shape your mind in a way similar to how a river shapes a canyon, but it doesn’t necessarily convert directly to actionable insights.
Instead, I have begun to rely on encyclopedias and spaced repetition, with the idea being that I will actually remember all of the data I’m inputting.
To use an example: I read a popular biography about Rockefeller last year. I can remember the vague outlines of it, but realistically if you asked me to summarize the book, I couldn’t write more than a page. I think most people have a similar experience with reading. Can you name the last ten books you read and write a brief essay about each? Almost certainly not, even if you read a ton.
To combat this, I’ve been adding specific details about Rockefeller to an Anki deck. Things like, “Where was Rockefeller born?” Or “How many companies was Standard Oil split into?” My thesis is that knowing a few hundred facts like this is an order of magnitude more productive than reading a book about the subject. Encyclopedias are thus useful for this purpose, as they present a huge amount of information about a subject in a format amendable for memorizing.
Honestly, what exactly is the purpose of knowing when was Rockefeller born or how many companies was his company split into? I think what you get out of a book like this is gist of his character and what made him successful so that you can pick up some of his traits. All this information is stored somewhere in your brain in some way.. it can possibly be used at some point without you even realizing.
It was just an example. More realistically the facts are about his specific decisions he made, business events, etc. – the kind of thing you'd want to know if you're interested in business history and/or reading the book to glean some kind of entrepreneurial knowledge.
A better example might be related to the Roman emperor Augustus. Memorizing the various events of his life, his personal quirks, and so forth is absolutely going to give you a sense of the man moreso than just reading a random biography about him.
I do agree that a book provides the "gist" of the subject's character, but I think you can get that from watching a 30-minute documentary, not reading a 500-page book.
> All this information is stored somewhere in your brain in some way.. it can possibly be used at some point without you even realizing.
It's a pretty big assumption, if you're implying that we somehow remember everything we read.
In any case, I think the best approach is probably to combine reading a book with specific facts that easily fit into a SRS system. This is something I've been thinking about quite a bit, in fact: how would one design a narrative-based book such that it is more easily remembered? My initial thought is something like this: at the end of every chapter, a list of 100+ specific points made is presented. You could also include a premade Anki deck with the ebook edition.
“In my ChatGPT custom instructions, I have instructed ChatGPT to “Give me 2-4 follow-up questions that I can ask on the topic” (⬅ copy-paste that into your prompt ). And the results are marvelous.”
I try to read for at least 45 minutes each day and I take notes on the books I read. From there I move on to the more advanced stuff I gathered and use my old habit of following bibliographic references for more.
Umberto Eco has a book on how to write a PHD thesis, How to Write a Thesis . I think a lot of the techniques described in that book are valuable for any kind of research, whether your aim is to write a thesis or just to learn something new.