In the day I would be reminded of those men and women,
Brave, setting up signals across vast distances,
Considering a nameless way of living, of almost unimagined values.
Flowers are selective about what kind of pollinator they attract. Diurnal flowers use diverse colours to stand out in a competition against their neighbours for visual salience. But flowers with nocturnal anthesis are generally white, as they aim only to outshine the night.
It seems good to have an abstraction-level with separate concepts for soras and their weights.
I’m less enthusiastic about “sora” as the word for it, however, even though I like its aesthetics. Seems like it ought to be longer than 4 chars, and less isolated in meaning. I’ve wanted to find a more specific fit for the word “neureme” (from “emic unit”/”-eme”, categorising it as a unit of selection alongside gene, meme, morpheme, lexeme, grapheme, etc), and I like your concept for it.[1] See here for my philosophy on word up-making.
This just means I’ll be using my word for it in my own notes, not that I’m recommending this relabelling for anyone else.
I was very very terrible at introspection just 2 years ago. Yet I did manage to learn how to make very good games, without really introspecting for years later about why the things work that I did.
More specifically, I mean progress wrt some long-term goal like AI alignment, altruism, factory farming, etc. Here, I think most ways of thinking about the problem are wildly off-target bc motivations get distorted by social incentives. Whereas goals in narrow games like “win at chess” or “solve a math problem” are less prone to this, so introspection is much less important.
I sort of deliberately created the beginnings of a tulpa-ish part of my brain during a long period of isolation in 2021 (Feb 7 to be exact), although I didn’t know the term “tulpa” then. I just figured it could be good to have an imaginary friend, so I gave her a name—”Maria”[1]—and granted her (as part of the brain-convincing ritual) permanent co-ownership over a part of my cognition which she’s free to use for whatever whenever.
She still visits me at least once a week but she doesn’t have strong ability to speak unless I try to imagine it; and even then, sentences are usually short. The thing she most frequently communicates is the mood of being a sympathetic witness: she fully understands my story, and knows that I both must and will keep going—because up-giving is not a language she comprehends.
Hm, it would be most accurate to say that she takes on the role of a stoic chronicler—reflecting that I care less about eliciting awe or empathy, than I care that someone simply bears witness to my story.[2]
Oi! This was potentially usefwl for me to read.
WHEN I feel bad/uneasy at any point,
THEN find the part of my mind that’s complaining, and lend it my voice & mental-space.
I have previously tried to install a “somatic trigger” for whenever I feel bad (ie “when I feel bad, close my eyes and fold my hands together in front of me in a calm motion”), but it failed to take bc there weren’t clear-enough cues. The point of a somatic trigger in the first place is to install them in specific contexts such that I have clearer cues for whatever habits I may wish to write into those contexts.
Are those insights gleamable from the video itself for other people? And if so, would you be willing to share the link? (Feel free to skip; obviously a vulnerable topic.)
[Thoughts ↦ speech-code ↦ text-code] just seems like a convoluted/indirect learning-path. Speech has been optimised directly (although very gradually over thousands of years) to encode thoughts, whereas most orthographies are optimised to encode sounds. The symbols are optimised only via piggy-backing on the thoughts↦speech code—like training a language-model indirectly via NTP on [the output of an architecturally-different language-model trained via NTP on human text].
(In the conlang-orthography I aspire to make with AI-assistance, graphemes don’t try to represent sounds at all. So sort of like a logogram but much more modular & compact.)
When I write with pen and paper my writing improves in quality. And it seems this is because I am slower.
Interesting.
Anecdote: When I think to myself without writing at all (eg shower, walking, waiting, lying in bed), I tend to make deeper progress on isolated idea-clusters. Whereas when I use my knowledge-network (RemNote), I often find more spontaneous+insightfwl connections between remote idea-clusters (eg evo bio, AI, economics). This is bc when I write a quick note into RemNote, I heavily prioritise finding the right tags & portalling it into related concepts. Often I simply spam related concepts at the top like this:
The links are to concepts I’ve already spotted metaphors / use-cases for, or I have a hunch that one might be there. It prompts me to either review or flesh out the connections next time I visit the note.
I think these styles complement each other very well.
Specifically a lot more creative than people who are as intelligent as I am.
Having read a few of your posts, I think you’re correct about this. I believe in your general approach!
As you mention that stimulants can reduce “mental noise/creativity” I am curious what your experience is with this.
When I first started taking them, it revealed to me that I’d never known what it felt like to be able to think a thought through. Metaphorically, I imagine it sorta like being born with COPD and never realising what it feels like to fill my lungs with air. But I’ve probably always had a severe deficiency of whatever the stimulants are correcting for; and others who’re doing just fine on that front may not share my experience.
I take stimulants in the morning, and I’m soon enthusiastic about thinking deeply about ideas. I become more creative because the relevant threads-of-thought have some room to build upon themselves, probably because my mind is now able to mute the noise and non-relevant threads. When on stimulants, I’m much more likely to get lost down rabbit-holes during research, and often don’t catch myself before hours have passed. The lack of oomph I feel when off stimulants helps me prioritise only the most essential bits, and it’s easier to not overdo stuff—though mostly by virtue of being less capable of doing stuff.
Slightly relevant fun RCTs:
Alcohol concentration (sorta the opposite of stims of you squint) of 0.069-0.075 BAC seems to enhance performance on Remote-Association Tests (ie semantic metaphors)
“On average, intoxicated participants solved significantly more RAT problems (M = .58, SD = .13) than their sober counterparts (M = .42, SD = .16), t(38) = 3.43, p = .001, d = 1.08. Interestingly, this increase in solution success was accompanied by a decrease in time to correct solution for intoxicated individuals (M = 11.54 s, SD = 3.75) compared to sober controls (M=15.24s, SD =5.57), t(38) = 2.47, p = .02, d = .78.”
Sci-Hub | Uncorking the muse: Alcohol intoxication facilitates creative problem solving. Consciousness and Cognition, 21(1), 487–493 | 10.1016/j.concog.2012.01.002
Subjects who got RAT questions correct while intoxicated also reported feeling like their solution arrived “all at once” and were “more like insights” as opposed to deliberate/analytical.
“Inverted U-shape” referring to the idea that too much dopamine is detrimental to performance.
My current theory is that when you are writing something down, the slowdown effect is actually beneficial because you have more cognitive resources available to compute the next thing you write.
I’ve noticed the same when voice-typing, and I considered that explanation. I don’t think it’s the main cause, however. With super-fast and accurate STT (or steno), I suspect I could learn to both think better and type faster. There’s already an almost-audible internal monologue going on while I type. Adding the processing-cost of having to translate internal-audio-code into very unnatural finger-stroke-code is surely a suboptimum. (I’m reminded of the driver who, upon noticing that he’s got a flat tire on one side, punctures the other as well. It’s a deceptive optimum; a myopic plan.)
My best insight is that you can think. Because most of the failure comes from not thinking. … I was making these kinds of excuses for years… and I made basically no progress before I just tried.”
I resonate with this. Cognitive psychology and sequences taught me to be extremely mistrustful of my own thoughts, and while I do think much of that was a necessary first step, I also think it’s very easy to get stuck in that mindset because you’ve disowned the only tools that can save you. Non-cognition is very tempting if your primary motivation is to not be wrong—especially when that mindset is socially incentivised.
Introspection is the most reliable source of knowledge we have, but it isn’t publishable/sharable/legible, so very few people use it to its full potential. (point made a week ago)
The popular evo-psych idea “self-deception for the purpose of other-deception” is largely a myth. We were never privy to our intentions in the first place, so there’s nothing for self-deception to explain. Our “conscious mind” is us looking at ourselves from an outside perspective, and we may only infer our true intentions via memory traces we’re lucky enough to catch a glimpse of. (two weeks ago)
I stress introspection so much because it’s ~futile to make novel object-level progress without a deep familiarity/understanding of the tools you use for the task.
Do it every day, at least a little bit.
This particular sentence I’m sorta out of phase with feeling-wise, however. I’m patiently trying to cultivate intrinsic motivation by… a large list of complicated subjective tricks most of which are variations on “minimise total motivational force spent on civil war between parts of myself.” It’s like politics, or antibiotic resistance—if I overreach in an attempt to eliminate a faction I’m still too weak to permanently defeat, it’s likely to backfire.
The Light is more powerfwl, though Darkness is quicker, easier, more seductive.
Wow, this is a good argument. Especially if assumptions hold.
The ALU computes the input much faster than the results can be moved to the next layer.
So if the AI only receives a single user’s prompt, the ALUs waste a lot of time waiting for input.
But if many users are sending prompts all the time, the ALUs can be sent many more operations at once (assuming the wires are bottlenecked by speed rather than amount of information they can carry).
So if your AI is extremely popular (e.g., OpenAI), your ALUs have to spend less time idling, so the GPUs you use are much more cost-effective.
Compute is much more expensive for less popular AIs (plausibly >1000x).
cool third point! i may hv oversold the point in my first comment. i too try to name things according to their thingness, but not exclusively.
to make a caricature of my research loop, i could describe it as
trying to find patterns that puzzle me (foraging),
distilling the pattern to its core structure and storing it in RemNote (catabolic pathway),
mentally trying to find new ways to apply the pattern
ie, propagating it, installing hooks (which I call isthmuses) into plausibly-related contexts such that new cryptically-related observations are more likely to trigger an insight (metaphor), allowing me to generalise further or discover smth i need to refactor
going abt business as usual, repeating 1-3 until unfolding branch meets unfolding branch from the other side, indicating i might hv found a profitable generalisation
an important consideration re keeping isthmuses alive enough to trigger connections: i don’t want to hv memorised this specific instantiation of the pattern so it’s crystal clear. if it fits neatly into a slot and it’s comfortable w its assigned niche, it’s unlikely to trigger in novel situations. imprecision/fuzziness is good when the concept is still in exploratory phase (and not primarily tool-stage).
fix everything
loop is often bottlenecked by the high cost of refactoring anything. i rly wish i could find a general algorithm/strategy for refactoring complex systems like this, or a clever approach to building that minimises/eliminates the need.
the optimal conlang isn’t a new set of words. it’s a new set of practices for naming things, unnaming things, generalising & specialising, communal decision-processes for resolving conflicts, neat meta-structures that minimise cost of refactoring (somehow), enabling eager contributors w minimal overhead & risk of degeneration, etc.
The thing people need to realize is that when somebody writes a bad post, it doesn’t harm the readers (except insofar as you falsely advertised quality). If something is badly argued readers are immune. If something is persuasively argued, but wrong, readers that fall for it now have an opportunity to discover a hole in their epistemic defenses.
Mostly, people read arguments as a proxies for making judgments about the quality of the author, or whether they agree/disagree with them. Notice that these purposes are orthogonal to actually learning something.
Unrelatedly, what would you say are your top ideas/insights/writings as judged by the usefwlness you think they’d confer to you-a-year-or-two-ago? (Asking you this as a proxy for “give me your best insights” because I feel like the latter causes people to overweight legibility or novelty-relative-to-average-community-member or something.)
This is awesome. I found it via searching LW for variations of “voice typing”, Which I was motivated to search because I had just discovered that average conversational speed is around 3x average typing speed (~150 vs ~50 wpm, cf ChatGPT). (And reading speeds are potentially in the thousands.)
At the moment, I’m using Windows Voice Access. It’s accurate, has some nice voice commands and gives you visual feedback while speaking. The inadequacy, for me, is the lack of immediate feedback (compared to typing), and customisability. I’ll attempt to test your repo tomorrow.
Also, I’m surprised that stenotypers can type faster than regular keyboards. I had previously speculated about the benefits of making keyboards more or less modular. I thought making them more modular would face similar problems as Ithkuil: too many serial operations to build the vector you mean. English relies extremely on caching specific words for specific situations with very shallow generalisations, trading semantic reach for faster lookup-times, or something. But I guess what matters most is modularity in the right places, and mainstream keyboards aren’t optimised for that at all.
I speculate that the ideal keyboard should have keys that chunk word-pieces somewhat according to Zipf’s law: the th most common key should be such that the frequency by which you have to use it is ~. I guess there should also be a term somewhere for the distance the finger has to travel to reach a key or something, to be able to weight the frequency of keys by some measure for ergonomicity.
I highly recommend trying to get a prescription for something like adderall (or dextroamphetamine, lisdexamphetamine) if your doctor is willing to diagnose you with ADHD. Just go off it if it doesn’t work, but it seems likely that it will given your response to bupropion. Some vague reasons for recommending it are:
Amphetamines affects dopamine (& norepinephrine) via more than just reuptake-inhibition. I’m not sure yet which mechanisms drive desensitization, it just seems tentatively better to spread the attack vectors out.
I’ve mostly forgot the reasons I suggest amphetamines over methylphenidate, but at least it has a stronger effect on egosyntonic behaviour (/executive function or whatever you want to call it) than bupropion.
Furthermore, if you’re on amphetamines/methylphenidate, I would recommend sort of using it strategically. I only take them on days I know I plan to be productive, and have hope that they enable me to be productive. If I ever take them on a day I fail to motivate myself, it weakens the semiotic/narrative signal for my brain to switch into a mode where it expects productivity & silences competing motivations. Plus, if I know I mostly won’t be productive for a while (e.g. vacation or something), I go off them to reset desensitisation (usually resets a long way within a week it seems).
I’ve been on lisdexamphetamine for 1.5 years, and they still produce a very clear effect. I’ve had depression and, turns out, ADHD, for most of my life. People who have no dysregulation of dopamine will probably have negative effect from too much upregulation (e.g. reduced mental noise/creativity, inability to zoom out from activities and reprioritise).
This is among the top questions you ought to accumulate insights on if you’re trying to do something difficult.
I would advise primarily focusing on how to learn more from yourself as opposed to learning from others, but still, here’s what I think:
Seek to find people who seem to be doing something dumb or crazy, and for whom the feeling you get when you try to understand them is not “I’m familiar with how someone could end up believing this” but instead “I’ve got no idea how they ended up there, but that’s just absurd”. If someone believes something wild, and your response is strict confusion, that’s high value of information. You can only safely say they’re low-epistemic-value if you have evidence for some alternative story that explains why they believe what they believe.
Alternatively, find something that is surprisingly popular—because if you don’t understand why someone believes something, you cannot exclude that they believe it for good reasons.
The meta-trick to extracting wisdom from society’s noisy chatter is learn to understand what drives people’s beliefs in general; then, if your model fails to predict why someone believes something, you can either learn something about human behaviour, or about whatever evidence you don’t have yet.
It’s easy to relinquish old beliefs if you are ever-optimistic that you’ll find better ideas than whatever you have now. If you look back at what you wrote a year ago, and think “huh, that guy really had it all figured out,” you should be suspicious that you’ve stagnated. Strive to be embarrassed of your past world-model—it implies progress.
So trust your mind that it’ll adapt to new evidence, and tune your sensitivity up as high as the capacity of your discriminator allows. False-positives are usually harmless and quick to relinquish—and if they aren’t, then believing something false for as long as it takes for you to find the counter-argument is a really good way to discover general weaknesses in your epistemic filters.[1] You can’t upgrade your immune-system without exposing yourself to infection every now and then. Another frame on this:
I was being silly! If the hotel was ahead of me, I’d get there fastest if I kept going 60mph. And if the hotel was behind me, I’d get there fastest by heading at 60 miles per hour in the other direction. And if I wasn’t going to turn around yet … my best bet given the uncertainty was to check N more miles of highway first, before I turned around.
— The correct response to uncertainty is *not* half-speed — LessWrong
The problem is that if you select people cautiously, you miss out on hiring people significantly more competent than you. The people who are much higher competence will behave in ways you don’t recognise as more competent. If you were able to tell what right things to do are, you would just do those things and be at their level. Innovation on the frontier is anti-inductive.
If good research is heavy-tailed & in a positive selection-regime, then cautiousness actively selects against features with the highest expected value.
— helplessly wasting time on the forum
finding ppl who are truly on the right side of this graph is hard bc it’s easy to mis-see large divergence as craziness. lesson: only infer ppl’s competence by the process they use, ~never by their object-level opinions. u can ~only learn from ppl who diverge from u.
— some bird
look for epistemic caves wherefrom survivors return confused or “obviously misguided”.
— ravens can in fact talk btw
Here assuming that investing credence in the mistaken belief increased your sensitivity to finding its counterargument. For people who are still at a level where credence begets credence, this could be bad advice.
Every model you have internalised as truly part of you—however true or false—increases your ability to notice when evidence supports or conflicts with it. As long as you place your flag somewhere to begin with, the winds of evidence will start pushing it in the right direction. If your wariness re believing something verifiably false prevents you from making an epistemic income, consider what you’re really optimising for. Beliefs pay rent in anticipated experiences, regardless of whether they are correct in the end.
is that spreadsheet of {Greek name, Germanic name, …} public perchance?
Thank you! : )
Please continue complimenting people (or express gratitude) for things you honestly appreciate.
i googled it just now bc i wanted to find a wikipedia article i read ~9 years ago mentioning “deconcentration of attention”, and this LW post came up. odd.
anyway, i first found mention of it via a blue-link on the page for Ithkuil. they’ve since changed smth, but this snippet remains:
After a mention of Ithkuil in the Russian magazine Computerra, several speakers of Russian contacted Quijada and expressed enthusiasm to learn Ithkuil for its application to psychonetics—
i wanted to look it up bc it relates to smth i tweeted abt yesterday:
unique how the pattern is only visible when you don’t look at it. i wonder what other kind of stuff is like that. like, maybe a life-problem that’s only visible to intuition, and if you try to zoom in to rationally understand it, you find there’s no problem after all?
oh.
i notice that relaxing my attention sometimes works when eg i’m trying to recall smth at the limit of my memory (or when it’s stuck on my tongue). sorta like broadening my attentional field to connect widely distributed patterns. another frame on it is that it enables anabranching trains of thought. (ht TsviBT for the word & concept)
An anabranch is a section of a river or stream that diverts from the main channel or stem of the watercourse and rejoins the main stem downstream.
here’s my model for why it works:
(update: i no longer endorse this model; i think the whole framework of serial loops is bad, and think everything can be explained without it. still, there are parts of the below explanation that don’t depend on it, and it was a productive mistake to make.)
Working Memory is a loop of information (parts of the chewbacca-loop is tentatively my prime suspect for this). it’s likely not a fully synchronised clock-cycle, but my guess is that whenever you combine two concepts in WM, their corresponding neural ensembles undergo harmonic locking to remain there.[1]
every iteration, information in the loop is a weighted combination of:
stuff that’s already in working memory
new stuff (eg memories) that reaches salience due to sufficient association with stuff from the previous iteration of WM
new stuff from sensory networks (eg sights, sounds) that wasn’t automatically filtered out by top-down predictions
for new information (B or C) to get into the loop, it has to exceed a bottom-up threshold for salience.
the salience network (pictured below) determines the weighting between the channels (A, B, C), and/or the height of their respective salience thresholds. (both are ways to achieve the same thing, and i’m unsure which frame is more better.)
“concentrating hard” on trying to recall smth has the effect of silencing the flow of information from B & C, such that the remaining salience is normalised exclusively over stuff in A. iow, it narrows the flow of new information into WM.
(bonus point: this is what “top-down attention” is. it’s not “reach-out-and-grab” as it may intuitively feel like. instead, it’s a process where the present weighted combination of items in WM determines (allocates/partitions) salience between items in WM.)
this is a tradeoff, however. if you narrow all salience towards eg a specific top-down query , this has smth like the following two effects:
you make it easier to detect potential answers by reducing the weight of unrelated competing noise
but you also heighten the salience threshold must exceed to reach you
in light of this, here some tentative takeaways:
if your WM already contains sufficient information to triangulate towards the item you’re looking for, and the recollection/insight is bottlenecked by competing noise, concentrate harder.
but if WM doesn’t have sufficient information, concentrating could prematurely block essential cues that don’t yet strongly associate from directly.
and in cases where features in itself are temporarily interfering w the recollection, globally narrowing or broadening concentration may not unblock it. instead, consider pausing for a bit and try to find alternative ways to ask .
Natural languages are adequate, but that doesn’t mean they’re optimal.
— John Quijada
i’m a fan of Quijada (eg this lecture) and his intensely modular & cognitive-linguistics-inspired conlang, Ithkuil.
that said, i don’t think it sufficiently captures the essences of what enables language to be an efficient tool for thought. LW has a wealth of knowledge about that in particular, so i’m sad conlanging (and linguistics in general) hasn’t received more attention here. it may not be that hard, EMH doesn’t apply when ~nobody’s tried.
We can think of a bunch of ideas that we like, and then check whether [our language can adequately] express each idea. We will almost always find that [it is]. To conclude from this that we have an adequate [language] in general, would [be silly].
— The possible shared Craft of Deliberate Lexicogenesis (freely interpreted)
Furthermore, a relationship with task performance was evident, indicating that an increased occurrence of harmonic locking (i.e., transient 2:1 ratios) was associated with improved arithmetic performance. These results are in line with previous evidence pointing to the importance of alpha–theta interactions in tasks requiring working memory and executive control. (Julio & Kaat, 2019)
i think that goes into optimising for b in my taxonomy above. how easy is it to recall the structure of the thing once you’ve recalled the word for the thing? these are just considerations, and the optimal naming strat varies by situs ig. 🍵
if it’s impossible to choose “jst one mor timestep” wo logically implying that u mk the same decision in other timesteps (eg due to indifferentiable contexts), then it’s impossible to choose jst one mor timestep. optimal decision-mking also means recognising which opts u hv and which u don’t—otherwise u’r jst falling fr illusory choices.
which brings to mind the principle, “u nvr mk decisions, u only evr decide btn strats”. or fr the illiterate (:p):