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I was talking with somebody about their migration recently [0], and we got to speculating about AI and how it might have helped. There were basically 2 paths:

- Use the AI and ask for answers. It'll generate something! It'll also be pleasant, because it'll replace the thinking you were planning on doing.

- Use the AI to automate away the dumb stuff, like writing a bespoke test suite or new infra to run those tests. It'll almost certainly succeed, and be faster than you. And you'll move onto the next hard problem quickly.

It's funny, because these two things represent wildly different vibes. The first one, work is so much easier. AI is doing the job. In the second one, work is harder. You've compressed all your thinking work, back-to-back, and you're just doing hard thing after hard thing, because all the easy work happens in the background via LLM.

If you're in a position where there's any amount of competition (like at work, typically), it's hard to imagine where the people operating in the 2nd mode don't wildly outpace the people operating in the first, both in quality and volume of output.

But also, it's exhausting. Thinking always is, I guess.

[0] Rijnard, about https://sourcegraph.com/blog/how-not-to-break-a-search-engin...

> You have to remember EVERYTHING. Only then you can perform the cognitive tasks necessary to perform meaningful knowledge work.

You don't have to remember everything. You have to remember enough entry points and the shape of what follows, trained through experience and going through the process of thinking and writing, to reason your way through meaningful knowledge work.

> You have to remember EVERYTHING. Only then you can perform the cognitive tasks necessary to perform meaningful knowledge work.

If humans did not have any facilities for abstraction, sure. But then "knowledge work" would be impossible.

You need to remember some set of concrete facts for knowledge work, sure, but it's just one—necessary but small—component. More important than specific factual knowledge, you need two things: strong conceptual models for whatever you're doing and tacit knowledge.

You need to know some facts to build up strong conceptual models but you don't need to remember them all at once and, once you've built up that strong conceptual understanding, you'll need specifics even less.

Tacit knowledge—which, in knowledge work, manifests as intuition and taste—can only be built up through experience and feedback. Again, you need some specific knowledge to get started but, once you have some real experience, factual knowledge stops being a bottleneck.

Once you've built up a strong foundation, the way you learn and retain facts changes too. Memorization might be a powerful tool to get you started but, once you've made some real progress, it becomes unnecessary if not counterproductive. You can pick bits of info up as you go along and slot them into your existing mental frameworks.

My theory is that the folks who hate memorization are the ones who were able to force their way through the beginner stages of whatever they were doing without dull rote memorization, and then, once there, really do not need it any more. Which would at least partly explain why there are such vehement disagreements about whether memorization is crucial or not.

It’s the same with math. A lot of people say they don’t need to be able to do basic arithmetic because they can use a calculator. But I think that you can process the world much better and faster if at a minimum you have some intuition about numbers and arithmetic.

It’s the same with a lot of other things. AI and search engines help a lot but you are at an advantage if at least you have some ability to gauge what should be possible and how to do it.

> If you can’t produce a comprehensive answer with confidence and on the whim the second you read the question, you don’t have the sufficient background knowledge.

While the article makes some reasonable points, this is too far gone. You don't need to know how to "weigh each minute spend on flexibility against the minutes spent on aerobic capacity and strength" to put together a reasonable workout plan. Sure, your workouts might not be as minmaxed as they possibly could be, but that really doesn't matter. So long as the plan is not downright bad, the main thing is that you keep at it regularly. The same idea extends to nearly every other domain, you don't need to be a deep expert to get reasonably good results.

I am sympathetic to memory-focused tools like Anki and Zettelkasten (haven't used the latter myself, though) but I think this post is a bit oversimplified.

I think there are at least two models of work that require knowledge:

1. Work when you need to be able to refer to everything instantly. I don't know if this is actually necessary for most scenarios other than live debates, or some form of hyper-productivity in which you need to have extremely high-quality results near-instantaneously.

(HN comments are, amusingly, also an example – comments that are in-depth but come days later aren't relevant. So if you want to make a comment that references a wide variety of knowledge, you'll probably need to already know it, in toto.)

2. Work when you need to "know a small piece of what you don't remember as a whole", or in other terms, know the map, but not necessarily the entire territory. This is essentially most knowledge work: research, writing, and other tasks that require you to create output, but that output doesn't need to be right now, like in a debate.

For example, you can know that X person say something important about Y topic, but not need to know precisely what it was – just look it up later. However, you do still need to know what you're looking for, which is a kind of reference knowledge.

--

What is actually new lately, in my experience, is that AI tools are a huge help for situations where you don't have either Type 1 or Type 2 knowledge of something, and only have a kind of vague sense of the thing you're looking for.

Google and traditional search engines are functionally useless for this, but asking ChatGPT a question like, "I am looking for people that said something like XYZ." This previously required someone to have asked the exact same question on Reddit/a forum, but now you can get a pretty good answer from AI.

The author makes a lot of bold claims and I don’t take his main one serious re: remembering everything. I think he’s being intentionally hyperbolic. But the gist is sound to me, if you can put one together. He needs an editor.

> To find what you need online, you require a solid general education and, above all, prior knowledge in the area related to your search. > > [...] > > If you can’t produce a comprehensive answer with confidence and on the whim [...] you don’t have the sufficient background knowledge. > > [...] > > This drives us to one of the most important conclusions of the entire field of note-taking, knowledge work, critical thinking and alike: You, not AI, not your PKM or whatever need to build the knowledge because only then it is in your brain and you can go the next step. > > [...] > > The advertised benefits of all these tools come with a specific hidden cost: Your ability to think. [This passage actually appears ahead of the previous one–ed.]

This is best read alongside: https://news.ycombinator.com/item?id=45154088

Before the internet we asked people around us in our sphere. If we wanted to know the answer to a question, we asked, they made up an answer, and we believed it and moved on.

Then the internet came, and we asked the internet. The internet wasn't correct, but it was a far higher % correct than asking a random person who was near you.

Now AI comes. It isn't correct, but it's far higher % correct than asking a random person near you, and often asking the internet which is a random blog page which is another random person who may or may not have done any research to come up with an answer.

The idea that any of this needs to be 100% correct is weird to me. I lived a long period in my life where everyone accepted what a random person near them said, and we all believed it.

I agree with the point being made, even if it is taken to an extreme. I would say you don't need to remember everything, but you do need to have been exposed to it. Not knowing what you don't know is a huge handicap in knowledge work.

“Try to learn something about everything and everything about something.”

The actual central point is that the brain requires conditioning via experience. That shouldn't be controversial, and I can't decide if the general replies here are an extended and ironic elaboration of his point or not.

If you never memorize anything, but are highly adept at searching for that information, your brain has only learned how to search for things. Any work it needs to do in the absence of searching will be compromised due to the lack of conditioning/experience. Maybe that works for you, or maybe that works in the world that's being built currently, but it doesn't change the basic premise at all.

I've been having conversations about this topic with friends recently and I keep coming back to this idea that most engineering work, which I will define as work that begins with a question and without a clear solution, requires a lot of foundational understanding of the previous layer of abstraction. If you imagine knowledge as a pyramid, you can work at the top of the pyramid as long as you understand the foundation that makes up your level, however to jump a level above or below that would require building that foundation yet again. Computer science fits well into this model where you have people at many layers of abstractions who all work very well within their layer but might not understand as much about the other layers. But regardless of where you are in the pyramid, understanding ALL the layers underneath will lead to better intuition about the problems of your layer. To farm out the understanding for these things will obviously end up having negative impact not just on overall critical thinking, but on the way we intuit how the world works.

This piece reminds me of another article musing on the necessity of manual memory: https://numinous.productions/ttft/#how-important-is-memory.

That article articulated the reason slightly differently, arguing you need to hold multiple concepts in your head at the same time in order to develop original ideas.

Still, I'm not sure you have to remember everything, but I agree you have to remember the foundational things at the right abstraction layer, upon which you are trying to synthesize something new.

One thing that I like is that things are much easier in person. When someone shows me an AI overview they just googled on their phone, I can say "I don't think that's true." Then we can discuss. The more we talk about the subject, the more we develop our knowledge. It's not black and white.

But online? @grok is this true?

A bit too extreme, but there definitely is something to it; trivially, you need to challenge your mind all the time and at regularly work at the edge of your current abilities to progress further. I like this part a lot:

"In knowledge work the bottleneck is not the external availability of information. It is the internal bandwidth of processing power which is determined by your innate abilities and the training status of your mind."

Before the internet I siloed knowledge that I could lookup to books. Don't worry, the kids will be ok.

Descartes' brief rules for the direction of the mind [1] is pertinent here, as it articulates beautifully what it means to do "thinking" and how that relates to "memory".

Concepts have to be "internalized" into intuition for much of our thinking, and if they are externalized, we become a meme-copy machine as opposed to a thinking machine.

[1] https://en.wikipedia.org/wiki/Rules_for_the_Direction_of_the...

The irony here is using fitness as an example of knowable things.

Fitness guidelines is very much not a settled science, and is highly variable per individual beyond the very basics (to lose weight eat fewer calories than you burn, to build muscle you should lift heavy things).

For every study saying that 8-12 reps x3 is the optimal muscle growth strategy there is another saying that 20x2 is better, and a third saying that 5x5 is better. If you want to know how much protein you should eat to gain muscle mass, good luck; most studies have settled on 1.6g/kg per day as the maximum amount that will have an effect, but you can find many reputable fitness sources suggesting double that.

You can memorize "facts", but they will change as the state of the art changes... or is Pluto still a planet?

The ability to parse information and sources, as well as knowing the limits of your knowledge is far more important than memorizing things.

A lot of good ideas in this comment section.

I’ll say this: between store, search, synthesize and share, store and synthesize are consistently the most difficult to nail down.

A society that wishes to succeed in creating an activated and knowledgeable populous should be interested in how to train people to notice better, and to create insightful follows.

In the words of David Deutsch (paraphrasing): knowledge consists of conjecture and error correction

> Looks good alright? Or does it? How do you know? You can’t if you don’t have sufficient background knowledge … If you can’t produce a comprehensive answer with confidence and on the whim the second you read the question, you don’t have the sufficient background knowledge.

> “I just ask ChatGPT for that, too!”, the AI generation might ask. Ok, and then what? How can you assess the answers … you are taking on an impossible task, because you can’t use enough of your brain for your cognitive operations.

So it’s Zeno’s paradox of knowing stuff?

It can’t be impossible to know things, you’ve just got to decide when you know enough to get going on. Otherwise you’re mired in analysis paralysis and you never get anything done.

I do agree that deep knowledge of the foundations a subject - particularly a skilled practice or craft - is a path to proficiency and certainly a requirement for mastery. But there are plenty of times when you can get away with ‘just reading the documentation’ and doing as instructed.

You do not first need to invent the universe in order to begin exercising, you can just start talking a 20 minute walk after lunch.

While I agree with the gist of the article, I think the AI example is poor, because we know AI can make stuff up and it's a problem. So this failure of AI to be reasonably correct weakens the argument. In the old days, you would rely on an expert (through say a book, like encyclopedia) to tell you this. The issue then becomes who you trust.

I would say your own knowledge is like a memory cache. If you know stuff, then the relevant work becomes order of magnitudes faster. But you can always do some research and get other stuff in the cache.

(Human mind is actually more than a cache because you also create mental models, which typically stay with you. So it's easier to pickup details after they get evicted, because the mental model is kept. I think the goal of memorising stuff in school should be exactly that - forget all the details, but in the learning process build a good mental model that you have for life.)

You definitely do not need to remember everything, it’s not worth the effort to try, famously in programming even the best look up things they have looked up before.

Memory is helpful but brains aren’t hard drives, they aren’t designed to store information perfectly.

AI is not a replacement for a greybeard.

That said AI, Search and the like can be quite useful and helpful.

I remember things just fine, just not at the sufficient detail to remember all aspects at the drop of a pin. What I hold on to are the core concepts that allow me to hit the ground running when I have to interact with the subject-matter again.

Looking at the example he gives of an exercise plan, I'm not sure the advice is very good. He says don't do the simplistic plan the LLM gave, and be aware of technical stuff like "discussions of Olaf Alexander Bu on the difference between capacity and power numbers".

My experience as a bit of geek is it's easy to get caught up in theory and do stuff that doesn't work in practice. Better than either the LLM or theorising is an experienced coach who can look at what you are doing and say don't to that - it's all wrong - do this etc.

"To find what you need online, you require a solid general education and, above all, prior knowledge in the area related to your search." And get off my lawn. That's more a criticism of search engines than AI, anyway.

Insisting that people know exercise physiology to work out is a bit much. That's what trainers and coaches are for. Now drop and give me twenty.

The real problem with LLMs remains that they can't really do the job of thinking yet, because they're wrong too often. They can both hallucinate and get lost. What the AI situation will be in five years, we don't know.

Possibly worth considering the source: the author coaches on a mechanism for collecting and collating information. They have a vested interest in the notion you have to do the work (instead of letting the machine do it for you); indeed, they hope you do the work using this method they coach on...

(That having been said: I've used zettelkasten myself a bit and I'd say it's worth a try. Probably not for everyone but the underlying idea of "building out an artifact to supplement your memory and understanding of what you've seen" is an intriguing approach).

But in how many cases is the "why" more important than the "how"?

People can drive a car, without understanding any of the mechanical and electrical systems of a car. In fact understanding these does essentially nothing for what most people use a car for.

>If you can’t produce a comprehensive answer with confidence and on the whim the second you read the question, you don’t have the sufficient background knowledge.

And then what? Why would this matter at all? You can successfully use a workout schedule without understanding what its strengths and weaknesses are and how they align with your goals.

I once saw a comment that said "AIs are great for things that are hard to find, but easy to verify". Which I agree with.

In order to verify, we need knowledge.

If the AI is the last stop ("I asked my LLM and it said that"), it's the wrong way to do it. If the AI is part of the process ("The LLM mentioned this, which made sense, and I confirmed it by [...]"), then it may (or may not) be useful.

In any case, "knowing it" is always more efficient than "having to search for it". So the more you know, the better.

> The reduced engagement with the material reduces the emotional weight of the whole line of action. You mind is an engine that is fuelled by emotion. Without any emotion, you don’t think. Rather, you try to imitate thinking efficiently.

This doesn't sound true and they don't seem to offer any support for the claim.

There's a whole host of emotion-driven cognitive biases, where an effective counter is to reduce the emotional weight of the whole line of action.

Of course, to their credit, it's only by remembering those biases that I could see their error

At my first software dev internship my manager asked me to code in languages I was not trained in. I told him I would need some time to study up on these. He scoffed and said just look up what you need on Google. Initially I resisted, I felt like it was too shallow. That it was akin to copying answers I didn't really comprehend. However it didn't take long to pick up the habit. Learning is like going to the gym now, it's self enforced discipline

I use AI at work, and certainly I’m doing less deep thinking over time. But at home, on side projects I still do it the traditional way. This is because I enjoy the process of thinking (rather than shipping. I actually never shipped any side project).

I guess I’m lucky, deep thinking (on interesting things at home) is a hobby so I feel less encouraged to automate that away. I never cared about my jobs, so as long as I bring home money, it’s fine.

It's like with math. You could theoretically only memorize the axioms and rederive everything else on the fly.

But in practice, you don't have enough working memory or processing power to do that, so you'd be stuck with the math a few derivation steps above the axioms only.

To actually use math for problem solving, you need to memorize everything up to the bleeding edge, and to train yourself to operate on intermediate-level abstractions intuitively.

I used to think it wasn't necessary to remember much, as long as I could look things up. But over time, I realized that without a personal mental framework, it's hard to judge whether what you find is actually valuable.

Some insights only emerge when knowledge has stayed in your mind long enough to collide and connect with other ideas. Tools can help, but it's the knowledge that has been internalized and shaped over time that holds the real power.

> Rowlands et al. wrote about the so called “digital natives” that they lack the critical and analytical thinking skills to evaluate the information they find on the internet.

This doesn't match the cultural shift in the last 20 years. A generation of people grew up with chat rooms and immediately discovered the ability to misrepresent oneself on the internet. "On the internet, no one knows you're a dog", as they say. That whole demographic assumes that media is lying by default. Compare that to previous generations that trusted certain media institutions like cable news, newspapers, radio shows, etc. because the production value and scarcity of media instilled trust.

Trust in media institutions is at an all time low, and will likely never recover. That has to be attributed to the newer generations. They are more skeptical of propaganda than ever before. To them, the high production value media outlets are just a quaint legacy variety of content slop.

It's like a cache level issue.

In the old world, you had your wet brain memory. You needed to fill it with the order of the alphabet, so that you could make use of paper reference works. You also needed some arithmetic and some English style notes, in case you wanted to express yourself. You had to remember things like there/their/they're and that kind of thing. You needed a small encyclopedia so that you could have a clue about where general knowledge could be found.

On top of this, you were expected to layer on your professional knowledge. If you were a doctor, a huge number of Latin terms. A more detailed understanding of how the body works that you got from the base installation. Something about how the profession works. You would get a sense for what was likely through experience. A BS detector, in some ways.

All because your brain ain't gonna get bigger, and paper information technology was what it was: found in a library, limited in size, hard to search, slow to update.

Nowadays, the brain cache is no different in capability. But the external memory system you are accessing is completely different. It's massive, it can update in real time, and it's very searchable.

So you need to keep different things in your brain cache to take advantage of this.

But what do you need?

The only component that really matters is the BS detector.

Not only do I not need to be able to do long division, I don't even need to know that a calculator exists for calculating my tax, a calculator containing the Haversine formula is out there somewhere, and a so on. I just assume something like epochconverter exists, and that I can plug a timestamp into it and get something readable out.

I just assume that I will be able to find things that I want, the tradeoff being that I don't have sit there and refresh my math knowledge to calculate distances on a sphere, type out a program, and run it for a single output. The other side of this coin is of course, I don't know whether the guy whose work I am borrowing did it correctly, whether he has some sort of interest he's not disclosed, and whether it's safe. I also have to compromise on any variation between what he built and what I wanted.

I do this with almost everything now. I can't help it, having grown up and been educated before the internet exploded, and having started work just as the explosion was happening.

So I'd say you actually don't have to remember everything, but you do have to use your judgement in everything.

See also: https://www.pearlleff.com/in-praise-of-memorization

It was a typical attitude among my physicist and mathematician friends that memorizing was for suckers, even though it was often required to reproduce long proofs or derivations. These were people to whom mathematics came naturally; their understanding, memory, curiosity, and experience just compressed that knowledge until it was trivial to memorize. Unfortunately, many walked away with a sense of not needing to know things until they need them, but good luck with that in a systems design interview.

I am either too stupid or too lazy to remember everything. Or my version of ADHD specifically restricts my ability to remember things, or to have sufficient energy to engage daily with the process needed to memorize information (e.g. build and review anki decks).

I gave up on Anki. I abandoned org-roam and switched to trillium with very simple summaries of hand written notes. I don't summarize articles I read, I simply save them to my bookmarks with good tags.

I might be stupider now, I don't know. My mandarin improves at the same pace it did before, when I was doing daily flashcards, according to my mandarin teacher. Except now I don't have the torturous Todo item of "do mandarin flashcards" weighing on me every day, or the huge catch-up if I miss even two days (again, I am stupid - I usually miss 20% of my cards, daily. Often the same cards. I have forgotten the same word over 100 times.)

But, the other day I went to trivia in Cambridge UK, where I was probably the dumbest person in the town and almost certainly in the pub! And everyone was answering very interesting questions with correct answers, about geography, history, science, even the geography of the Americas which as an American should at least have been something I knew better than my British colleagues! Nope. It made me regretful that I grew up in suburban America and didn't get a nice bit of background education like Europeans do, or maybe for me being dumb or having ADHD. It I always admired smart people and I always wanted to count myself amongst them - it's why I brute forced my way into engineering by picking the lowest barrier to entry bit (frontend) and gritting my teeth and smashing pencils through hour after hour of tutorial and project until I finally had a portfolio I could get hired off of. And still almost always, dumbest person in the company (there have been less productive than me, though), and no idea how to change it. I'm wondering again if there's something I can do to be smarter.

I am fascinated by the promise of zettelkasten, spaced repetition, fish oil, whatever, but none of it seems to deliver!

Another one of those things that will separate humans on different levels of consciousness even more.

Enough people simply don't want to train their minds. For a lot of people, IT is just a job. Programmers, consultants, ... CEOs and CTOs, people want money and that's fine. Some just don't want a boss.

Some of these people will replace the training of their minds with other stuff, pure experience and laughter. Somewhere else all the time. Other will only train specific parts of their minds, actively or passively.

The big question is, IMO: what will the young face when they enter school, when they enter university, the job market. Will humanity be able to keep the variety it is currently maintaining or is the reduction one of the first steps towards singularity?

All above is rather obvious but the side effects of outsourcing much of everything systematic and structural to AI will build up. Will people care less or more about law and justice? Or just the same? Privacy? Safety? Morals and ethics?

MITM already create a rift between customers and companies. AI will make this rift bigger.

So it's not just the training of the mind that we can't circumvent, it's the (heartwarming I know) the heart as well. How to care for your creation, product and customer if your are completely alienated from almost everything except the balance sheet? Ah, wait, there are a couple of million people like that already. So we'll just have more of those. But don't they read a lot and cooperate and mentor and fiddle with politics, investments and are life long learners and stuff ... I wonder.

Off topic: This site has an input somewhere that takes focus on page load, but I can't see it. When I used the arrow down key some previously used suggestions jumped into view in a dropdown menu.

I use chatgpt to learn a ridiculous amount of knowledge that was not possible in 2020.

If you are using it to only decrease cognitive load (instead of keeping cognitive load constant while doing MORE), then you’re using it wrong

We can remember it for you wholesale specifically

Reminds me of when I debug why my aquascape (I’m a beginner) keeps having algae outbreak such as GSA and Cyanobacteria.

I have a lot of things correct, CO2, light, photoperiod. LLM told me that I have too much kH and gH and too much phosphate.

Followed the LLM advice, didn’t work. Apparently its an outdated advice. My kH and gH is high (not using RoDi water, just NJ tap water) but not that high such that plants struggle to get CO2, and my level of phosphate doesn’t necessarily what made the algae bloom.

Turns out my nutrition was the culprit. I bottomed out on Nitrogen all the time. But when I told that my Nitrate is 0 the LLM didn’t say a thing and instead “you got everything correct”.

Digital bullshit.

TLDR: firing and forgetting the first result off of a single google search isn't the best long term approach. But this guy had a bri..coaching to sell you that apparently makes you a better human being

i will now no longer press F3 or / instead i will read.

Surprised this is on top. Human beings have been using tools to augment memory since writing. Lots of these tools are faulty but then so too is memory.

If you want to remember everything good luck, but I am not convinced.

A great deal of anti-AI posts as of late seem like milquetoast pearl clutching to me. They don’t want to outright say they feel threatened/devalued but the arguments they put forward are not only unconvincing, but in this case among many others actively work against them.

nb. I tried really hard to not point out the smugness of Zettelkasten which I suspect emboldens this feeling of superiority, because I’d rather sit this one out and see how it goes. Something tells me the AI will win by a landslide.

As someone who can answer all of those questions about the workout plan in depth, it’s not a bad plan. It’s actually quite good. Missing a little detail but that’s OK.

Wasn’t a good example for me.

you can hoard anything, including knowledge.

Isn’t the irony of Pheadrus (the dialogue where Socrates speaks against writing) that its a written work, in a dramatic setting? Like, yes, writing, technology can make us stupid, but this article was written and transmitted to us via social media.