- 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...
“Almost certainly succeed” requires that you mostly plan out the implementation for it, and then monitor the LLM to ensure that it doesn’t get off track and do something awful. It’s hard to get much other work done in the meantime.
I feel like I’m unlocking, like, 10% or 20% productivity gains. Maybe.
There is a certain amount of regular work that I don't want to automate away, even though maybe I can. That regular work keeps me in the domain. It leads to epiphany's in regards to the hard problems. It adds time and something to do in between the hard problems.
Exactly, some kinds of refactors are like this for me. Pretty mindless, kind of relaxing, almost algebraic. It's a pleasant way to wander around the code base just cleaning and improving things while you walk down a data or control flow. If you're following a thread then you don't even make decisions really, but you also get better acquainted with parts you don't know, and subconsciously get the practice holding some kind of gestalt in your head.
This kind of almost dream-like "grooming" seems important and useful, because it preps you for working with design problems later. Definitely formatting and style type trivia should absolutely be automated, and real architecture/design work requires active engagement. But there's a sweet spot in the middle.
Even before LLMs maybe you could automate some of these refactors with tools for manipulating ASTs or CSTs, if your language of choice had those tools. But automating everything that can be automated won't necessarily pay off if you're losing fluency that you might need later.
You cannot exclusively do hard things back to back to back every 8 hour day without fail. It will either burn you out, or you will make mistakes, or you will just be miserable.
Human brains do not want to think hard, because millions of years of evolution built brains to be cheap, and they STILL use like 10% of our daily energy.
Because as soon as you realize that the output doesn't do exactly what you need, or has a bug, or needs to be extended (and has gotten beyond the complexity that AI can successfully update), you now need to read and deeply understand a bunch of code that you didn't write before you can move forward.
I think it can actually be fine to do this, just to see what gets generated as part of the brainstorming process, but you need to be willing to immediately delete all the code. If you find yourself reading through thousands of lines of AI-generated code, trying to understand what it's doing, it's likely that you're wasting a lot of time.
The final prompt/spec should be so clear and detailed that 100% of the generated code is as immediately comprehensible as if you'd written it yourself. If that's not the case, delete everything and return to planning mode.
Yes, but you are thinking about the wrong things, so the effort get spent poorly.
It is usually much more efficient to build your own mental model than to try to search for a solution that solves exactly what you need from externally. Without that mental model it is hard to evaluate whether the external solution even does what you want, so its something you need to do either way.
For example, I believe writing unit tests is way too important to be fully relegated to the most junior devs, or even LLM generation! In other fields, "test engineer" is an incredibly prestigious position to have, for example "lead test engineer, Space X/ Nasa/etc" -- that ain't a slouch job, you are literally responsible for some of the most important validation and engineering work done at the company.
So I do question the notion that we can offload the "simple" stuff and just move on with life. It hasn't really fully worked well in all fields, for example have we really outsourced the boring stuff like manufacturing and made things way better? The best companies making the best things do typically vertically integrate.
But this is the idea behind compilers, type checkers, automated testing, version control, and etc. It's perfectly valid.
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.
When you're writing, you can often take your time. Too little knowledge, though, and it will require a lot of homework.
1- You may remember only the initial state and the brain does the rest, like with mnemonics
2- You may remember only the initial steps towards a solution, like knowing the assumptions and one or two insights to a mathematical proof?
I'd say a Zettlekasten user would agree with you if you mean 1
Brains are for thinking. Documents / PKM systems / tools are for remembering.
IOW: take notes, write things down.
FWIW I have a degree in cognitive psychology (psychobiology, neuroanatomy, human perception) and am an amateur neuroscientist. Somewhat familiar w/ the brain. :)
The point, I believe, was that the more you remember, the better you can think. As in you should strive to remember stuff, and not just be lazy and rely on LLMs. I agree with that.
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.
> So, coming back to the initial starting point that “you don’t have to remember anything”. The opposite is true. You have to remember EVERYTHING.
I see it like this: it is absolutely wrong to think that you don't have to remember anything. In fact, ideally you would remember everything. The more you remember, the better you can think. Now in practice, it's impossible to remember absolutely everything, so we should strive to remember as much as we can. And of course we need to be clever in how we select what we remember (but that seems obvious).
The point is really that it is common to say "it's useless to remember it because you can ask your calculator or an LLM", and the article strongly disagrees with that.
And the more experience with computers I get, the more I realize that there's actually not that many pure unique and mutually orthogonal _concepts_ in computer science and software engineering. Yes, a competent engineer must know, feel, live these concepts, and it takes a lot of work and exposure to crystallize them in the brain from all the libraries, books, programs, architectures one has seen. But there's not a lot of them! And once you are intimate with all of them, you can grok anything computer-related quickly and efficiently: because your brain will just wuickly find the "coordinates" of that thing in the concept space, ans that's all you'll have to understand and recall later.
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.
It's simply different people we're talking about. Certain personalities are always going to gravitate to the "search for reason" model in life rather than "reason about facts".
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.
IMO, this is the whole point of the article: AI tools "help" a lot when we are completely uninformed. But in doing that, they prevent us from getting informed in the first place. Which is counter-productive in the long term.
I like to say that learning goes in iterations:
* First you accept new material (the teacher shows some mathematical concept and proves that it works). It convinces you that it makes sense, but you don't know enough to actually be sure that the proof was 100% correct.
* Then you try to apply it, with whatever you could memorise from the previous step. It looked easy when the teacher did it, but when you do it yourself it raises new questions. But while doing this, you memorise it. Being able to say "I can do this exercise, but in this other one there is this difference and I'm stuck" means that you have memorised something.
* Now that you have memorised more, you can go back to the material, and try to convince yourself that you now see how to solve that exercise you were stuck with.
* etc.
It's a loop of something like "accept, understand, memorise, use". If, instead, you prompt until the AI gives you the right answer, you're not learning much.
Great way of framing it - simple and cuts straight to the heart of the issue.
That might be a good criteria for how much to memorize: do you want to be able to do it live?
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.
People do the same with AI, ask it about something they know little about then assume it is correct, rather than checking their ideas with known values or concepts they might be able to error check.
This, and knowing by heart all the simple formulas/rules for area/volume/density and energy measurements.
The classic example being pizza diameter.
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.
“Try to learn something about everything and everything about something.”
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.
There, I've shaved a ton of the spread off of your argument. Possibly enough to moot the value of the AI, depending on the domain.
How about we pick an LLM evaluation and get specific? They have strengths and weaknesses. Some do outperform humans in certain areas.
Often I see people latching on to some reason that “proves” to them “LLMs cannot do X”. Stop and think about how powerful such a claim has to be. Such claims are masquerading as impossibility proofs.
Cognitive dissonance is a powerful force. Hold your claims lightly.
There are often misunderstandings here on HN about the kinds of things transformer based models can learn. Many people use the phrase “stochastic parrots” derisively; most of the time I think these folks are getting it badly wrong. A careful reading of the original paper is essential, not to mention follow up work.
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...
> 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
But online? @grok is this true?
And he likely had a point. What I recently noticed is that my father, who had very little formal education but happened to have very old-school teachers who hammered him with memorizing a lot of poetry, which he continued in adult life, is more verbally fluent somehow than a lot of young kids who don't have command of grammar any more. ("would of")
Granted they likely don't write or read much either but directionally if you keep outsourcing mental work, you degrade. When I studied Japanese I liked the term a teacher had for his defense of memorizing Kanji by handwriting, which he called "neuro-muscular". Like playing scales on the guitar or piano there is something that keeps you snappy in memorization and rote practice that goes away if you only passively search.
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.
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.
Few people have the time to figure things out and so it isn't knowable even though all the steps are easy to lay out.
"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."
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
> “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.
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.)
Memory is helpful but brains aren’t hard drives, they aren’t designed to store information perfectly.
Exactly. And those also come with doing the thing, or watching the thing being done, or reading about the thing, or thinking about the thing. You often don't have to actively try to kastle / cram / grok / etc the information to remember it. Just being exposed to it will make you remember some of it. Knowing where to get more accurate info is often a greater skill / benefit than knowing the details yourself. Especially in fields where knowing all the details yourself is almost impossible.
Weak article.
That said AI, Search and the like can be quite useful and helpful.
I predict the same thing will happen with the current AI tools: the bubble will burst, a bunch of folks will lose their shirts, and the world in general will come to a more realistic and sober understanding of what they are good for. We will figure out how to provide the useful parts without massive data centers and it will become natural. (I remember when things a graphics card can do trivially required a supercomputer with supporting staff.)
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.
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.
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.
(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).
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.
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
There is ALWAYS an "emotional/intuitive" response that precedes the rational, conscious thought. There's a ton of research on this (see system 1 vs system 2 thinking etc).
There is no way to stop the emotional "thought" from happening before the "rational thought". What you can do is build a loop that self reflects to understand why that emotion was triggered (sometimes, instead of "this feels bad because it's wrong", it's "this feels bad because it points to an inconvenient truth" or "I am hungry and everything I am reading feels bad")
Just functionally, it seems reasonable that something happened before that bad feeling to trigger it, e.g. "trying to fit this with already known things, and finding it doesn't".
If emotions did not weigh on recall, surely there would be no "emotion-driven cognitive biases"
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.
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.
Short run? Sure shipping seems to accelerate. But as you mentioned - you are actually downtooling and optimising for what you do outside of work. Which is what labour always does. But now you have a tool to enhance it!
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.
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.
I'm an older millennial, probably one of the last generations who was formally taught that organizations like the New York Times and CNN were authoritative, bibliography-worthy sources of information due to their reputation and standards. I haven't cared much about what either outlet has produced in years. For every good investigative piece there's a mountain of obvious propaganda or refusal to cover topics they find uncomfortable with any objectivity.
The signal to noise ratio is so low, why pay attention? There's a lot of bad takes on twitter and non-mainstream media (to put it mildly) but it at least makes me aware of more things.
Right. The skeptical newer generation knows better. It's the generation that is immune to influence. They're so resistant to it that they've finally driven advertisers to realize that spamming YouTube, IG, TikTok, with ads peddling some new hype every week is pointless.
Sarcasm aside, the newer generation, in any generation, is always as naive as they're said to be. You're not born with wisdom and your parents can't save you from the candle fire, no matter how much they try. Sooner or later, you'll have to burn that finger to learn. Life is an experience game. No way around it.
Yes. And then they turn around and trust that the Boston Marathon Bomber was some random kid because Reddit said so.
The new generation of netizens distrusts classic media and then suddenly trusts Reddit and Google searches and random blogs.
Bad Twitter arguments citing YouTube videos talking about a Redditors problem about Microsoft Updates and SSDs just broke through a week or two ago and nearly everyone involved in the discussion is utterly wrong.
Laughs in Polish GenZ voting for Konfederacja (alt-right)
Kanał Zero is the best example.
Of boomer propaganda. But don't worry, as voters evolve, so does propaganda.
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
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.
Wasn’t a good example for me.
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!
You are too hard on yourself though.
It is like a running race, when we are required to carry 50 Lb bags on our backs, while others are running freely.
At some point we need to accept and not worry too much!
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.
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.
If you want to remember everything good luck, but I am not convinced.
To the credit of the author and this individual post, you would have to go out of your way to come to that conclusion. That is, there isn’t anything present in the actual article to suggest that what you’re alleging is valid.
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.
How do you tell when someone who disagrees with you is coming from a place of feeling threatened or devalued vs. a place you'd consider legitimate?
Hoping your methods are reliable and transferable, you're applying them to "a great deal" of posts so maybe they'd be helpful to me too.
