Semantic description: think of image / video generation from prompts of 10 to 100 words
Putting it all together:
Low end:
High end:
This is the consciously accessed data stream only, which is why it is much smaller than the full human brain.
“But the full latent input-output capabilities of human brain can be obtained by training the brain on its experience!” Yes, and that training makes use of data not consciously accessed, which I believe is much bigger than the consciously-accessed data stream.
Kolmogorov complexity of a human baby’s brain
A baby hasn’t begun learning, so I’ll assume that the human genome is a sufficient description of a baby’s brain.
Kolmogorov complexity
Kolmogorov complexity of any generic human-level observer
I really have no idea. The space of mind designs is huge; there are likely some very compact designs. to bits, maybe?
I think that this should be in a framework that takes into account granularity in some sense. Like I assume you are thinking about the kolmogorov complexity of simulating a system observationally similar to
Case 1: This is either A: A generic, realistic looking adult brain (hard to estimate the complexity), vs B: the brain of an individual person (~amount of synapses).
When you say claude opus is more intelligent than haiku, in case B it would definitely have more complexity, but in case A:
---If opus and Haiku were trained on the same dataset they would have almost the same complexity except for the num_parameters in the code. (Opus would have 1-2 bits more)
---More interestingly, it could be that Opus seems to have more geenral intelligence, rather than just knowledge because the architecture is more expressive and can learn an underlying algorithm that is a little bigger, but if you simulated Opus and Haiku with a more advanced architecture, maybe both would have the same “raw intelligence”. This is related to the texture vs shape bias in image classifiers. Models above 1B start recognizing stuff by shape rather than texture, which seems more like a simple algorithmic improvement rather than something that fundamentlaly required a higher parameter count.
Case 2: your subjective experience (could be compiled into a list of brain activations and sensory data)
Case 3: a generic human baby brain.
Case 4: Step 1: take laws of physics + a PRNG, simulate a universe, presumably it will have some intelligences. Step 2: build an “intelligence detector”, something that can detect human-like civilizations, e.g by finding complex radio emissions, then seek the brains somehow. This likely fits in less than 1MB.
Browser extensions, userscripts, and userstyles to make Youtube / Twitter less distracting
Userstyles
Requires a browser extension such as Stylus (GitHub, Chrome, Firefox) (The Microsoft Edge Add-on named “Stylus” is by a different developer; use caution)
Youtube hide algorithmic suggestions
Note: if YouTube changes its DOM element names, then the renamed elements will no longer be hidden unless you update this userstyle correspondingly.
Userstyle: Youtube hide algorithmic suggestions
@-moz-document domain("youtube.com″) {
/* Comment out any elements you want to keep; the line to blank out subscriptions page is commented out by default */
/* PLAYER OVERLAYS */
.ytp-ce-element,
.ytp-paid-content-overlay,
.iv-promo,
.ytp-pause-overlay,
.ytp-suggestion-set,
ytd-horizontal-card-list-renderer,
.ytp-fullscreen-grid-stills-container,
.ytp-endscreen-next,
.ytp-endscreen-previous,
.ytp-endscreen-content,
.ytd-compact-autoplay-renderer,
/* WATCH PAGE SIDEBAR */
.ytd-watch-next-secondary-results-renderer,
/* HOME PAGE—blank out*/
[page-subtype=”home”],
/* SUBSCRIPTIONS PAGE—blank out (inactive)*/
/*[page-subtype=”subscriptions”],*/
/* SEARCH PAGE — hide “recommended” / “for you” shelves but keep organic results */
ytd-search ytd-shelf-renderer,
/* Shorts shelf (appears on home, search, sidebar) */
grid-shelf-view-model,
/* Chip cloud (Topic filter bar) */
yt-chip-cloud-renderer
{
display: none !important;
}
}
Why? Youtube shorts pages encourage scrolling and watching many shorts videos. Normal Youtube watch pages don’t, especially if algorithmic suggestions are hidden.
Userscript: Youtube redirect shorts to normal video page
// ==UserScript==
// @name Youtube redirect shorts to normal video page
// @description Redirect youtube.com/shorts to youtube.com/watch?v=
// @version 0.1
// @match https://www.youtube.com/shorts/*
// @run-at document-start
// ==/UserScript==
let normalYoutube = window.location.href.replace(”/shorts/”, ”/watch?v=”);
window.location.replace(normalYoutube);
Youtube disable playlist auto-advance
If you want to advance to the next video, you need to click on it. Not automatic ⟶ slightly more friction ⟶ slightly harder to get sucked in
Userscript: Youtube disable playlist auto-advance
// ==UserScript==
// @name Youtube disable playlist auto-advance
// @description Pause 1.5 s before video end to prevent playlist auto-advance
// @version 0.1
// @match https://www.youtube.com/watch?*&list=*
// @run-at document-idle
// ==/UserScript==
(function() {
‘use strict’;
const PAUSE_BEFORE_END = 1.5; // seconds — needs to be at least 0.25 + YouTube’s auto-advance window
// --- Pause near the end using timeupdate (fires ~4/sec) ---
document.addEventListener(‘timeupdate’, function(e) {
if (e.target.tagName !== ‘VIDEO’) return;
const video = e.target;
const timeRemaining = video.duration—video.currentTime;
if (timeRemaining > 0 && timeRemaining ⇐ PAUSE_BEFORE_END && !video.paused) {
video.pause();
}
}, true);
})();
Browser extensions
Stylus, for userstyles (GitHub, Chrome, Firefox) (The Microsoft Edge Add-on named “Stylus” is by a different developer; use caution)
Focused YouTube (duplicates “Youtube hide algorithmic suggestions” userstyle above, but the extension developer could update Youtube DOM element names if / when Youtube changes them)
Sure! Focused YouTube is equivalent to my “Youtube hide algorithmic suggestions” userstyle. If that’s all you need, then you don’t need to write your own custom CSS / script.
Gorton, G. (2018), Financial Crises is a survey article. I thought its explanation of banking and financial crises as information shocks was enlightening.
Banking and financial crises as information shocks
Money, or bank notes, (or similar on-demand debt liabilities of a bank,) need to be information-insensitive (thus, interchangeable: $1 at Bank A == $1 at Bank B) to facilitate exchange. Otherwise, uninformed agents (any non banking-professionals) face adverse selection, haircuts on bank debts they hold, and thus withdraw from banking-facilitated commerce.
Banking crises are triggered by common-knowledge information releases (eg. news broadcast) that are unexpectedly bad (actual news worse than forecast by more than a threshold) (cites Gorton, 1988), which make “money at those particular banks” information-sensitive ($1 at those particular banks might not be worth $1).
Financial crises are slightly more general: debt liabilities of companies in general go from being information-insensitive (interchangeable: usable as general collateral, with holders indifferent between different companies’ debt) to information-sensitive (particular companies’ debt might not be worth face value)
Banking crises
Frequency:
147 banking crises in 1970–2011 (cites Laeven & Valencia, 2012)
Business cycle peaks and credit booms are only loosely linked to banking crises:
Only about 30% of banking crises were preceded by a credit boom (cites Laeven & Valencia, 2012)
Most credit booms are not followed by a banking crisis (cites Gorton & Ordonez, 2018)
Good booms (not followed by a banking crisis): Positive and lasting shock to Total Factor Productivity (TFP) and Labour Productivity (LP)
Bad booms (followed by a banking crisis): Positive but transient shock to TFP and LP
Kolmogorov complexity of the human brain at one instant:
10 to 1000 bits per synapse for weights
Total:
Probably not significantly compressible, considering that e.g. Claude Opus is significantly smarter than Claude Haiku
Kolmogorov complexity of “100 years of subjective experience that thinks he is [puffymist], a particular human who lived on Earth at
Temporal resolution of perception (“frame rate”): 10 to 30 frames per second
excludes audio, which has high sample rate but low bitrate
Uncompressed information per subjective-moment “frame”:
Empirically: conscious processing
Let’s say there are
Compression: call it a factor of
Low-level redundancy: video compression-like between-frame redundancy
High-level redundancy: routines, mental “well-worn grooves”, repetitive daily / yearly patterns
Semantic description: think of image / video generation from prompts of 10 to 100 words
Putting it all together:
Low end:
High end:
This is the consciously accessed data stream only, which is why it is much smaller than the full human brain.
“But the full latent input-output capabilities of human brain can be obtained by training the brain on its experience!” Yes, and that training makes use of data not consciously accessed, which I believe is much bigger than the consciously-accessed data stream.
Kolmogorov complexity of a human baby’s brain
A baby hasn’t begun learning, so I’ll assume that the human genome is a sufficient description of a baby’s brain.
Kolmogorov complexity
Kolmogorov complexity of any generic human-level observer
I really have no idea. The space of mind designs is huge; there are likely some very compact designs.
I think that this should be in a framework that takes into account granularity in some sense. Like I assume you are thinking about the kolmogorov complexity of simulating a system observationally similar to
Case 1: This is either A: A generic, realistic looking adult brain (hard to estimate the complexity), vs B: the brain of an individual person (~amount of synapses).
When you say claude opus is more intelligent than haiku, in case B it would definitely have more complexity, but in case A:
---If opus and Haiku were trained on the same dataset they would have almost the same complexity except for the num_parameters in the code. (Opus would have 1-2 bits more)
---More interestingly, it could be that Opus seems to have more geenral intelligence, rather than just knowledge because the architecture is more expressive and can learn an underlying algorithm that is a little bigger, but if you simulated Opus and Haiku with a more advanced architecture, maybe both would have the same “raw intelligence”. This is related to the texture vs shape bias in image classifiers. Models above 1B start recognizing stuff by shape rather than texture, which seems more like a simple algorithmic improvement rather than something that fundamentlaly required a higher parameter count.
Case 2: your subjective experience (could be compiled into a list of brain activations and sensory data)
Case 3: a generic human baby brain.
Case 4: Step 1: take laws of physics + a PRNG, simulate a universe, presumably it will have some intelligences. Step 2: build an “intelligence detector”, something that can detect human-like civilizations, e.g by finding complex radio emissions, then seek the brains somehow. This likely fits in less than 1MB.
Browser extensions, userscripts, and userstyles to make Youtube / Twitter less distracting
Userstyles
Requires a browser extension such as Stylus (GitHub, Chrome, Firefox)
(The Microsoft Edge Add-on named “Stylus” is by a different developer; use caution)
Youtube hide algorithmic suggestions
Note: if YouTube changes its DOM element names, then the renamed elements will no longer be hidden unless you update this userstyle correspondingly.
Userstyle: Youtube hide algorithmic suggestions
Twitter hide sidebar
https://userstyles.world/style/752/minimal-twitter-uncropped
Userscripts
Requires a browser extension such as Tampermonkey
Youtube redirect shorts to normal video page
Why? Youtube shorts pages encourage scrolling and watching many shorts videos. Normal Youtube watch pages don’t, especially if algorithmic suggestions are hidden.
Userscript: Youtube redirect shorts to normal video page
Youtube disable playlist auto-advance
If you want to advance to the next video, you need to click on it. Not automatic ⟶ slightly more friction ⟶ slightly harder to get sucked in
Userscript: Youtube disable playlist auto-advance
Browser extensions
Stylus, for userstyles (GitHub, Chrome, Firefox)
(The Microsoft Edge Add-on named “Stylus” is by a different developer; use caution)
Tampermonkey, for userscripts (Website)
Bonus
Focused YouTube (duplicates “Youtube hide algorithmic suggestions” userstyle above, but the extension developer could update Youtube DOM element names if / when Youtube changes them)
uBlock Origin (GitHub, Chrome, Firefox) - block Youtube injected ad segments
SponsorBlock—on Youtube, crowdsource sponsored video segments and labels and optionally skips them
DeArrow—on Youtube, crowdsource less clickbaity video titles and thumbnails
Video speed controller (GitHub, Chrome, Firefox)
I much prefer a maintained, trustworthy extension (which there are a couple out there) than unversioned userscripts
Sure! Focused YouTube is equivalent to my “Youtube hide algorithmic suggestions” userstyle. If that’s all you need, then you don’t need to write your own custom CSS / script.
Gorton, G. (2018), Financial Crises is a survey article. I thought its explanation of banking and financial crises as information shocks was enlightening.
via: New York Fed (2024). Tracing Bank Runs in Real Time
via: Twitter: Patrick McKenzie
Banking and financial crises as information shocks
Money, or bank notes, (or similar on-demand debt liabilities of a bank,) need to be information-insensitive (thus, interchangeable: $1 at Bank A == $1 at Bank B) to facilitate exchange. Otherwise, uninformed agents (any non banking-professionals) face adverse selection, haircuts on bank debts they hold, and thus withdraw from banking-facilitated commerce.
Banking crises are triggered by common-knowledge information releases (eg. news broadcast) that are unexpectedly bad (actual news worse than forecast by more than a threshold) (cites Gorton, 1988), which make “money at those particular banks” information-sensitive ($1 at those particular banks might not be worth $1).
Financial crises are slightly more general: debt liabilities of companies in general go from being information-insensitive (interchangeable: usable as general collateral, with holders indifferent between different companies’ debt) to information-sensitive (particular companies’ debt might not be worth face value)
Banking crises
Frequency:
147 banking crises in 1970–2011 (cites Laeven & Valencia, 2012)
Business cycle peaks and credit booms are only loosely linked to banking crises:
Only about 30% of banking crises were preceded by a credit boom (cites Laeven & Valencia, 2012)
Most credit booms are not followed by a banking crisis (cites Gorton & Ordonez, 2018)
Good booms (not followed by a banking crisis): Positive and lasting shock to Total Factor Productivity (TFP) and Labour Productivity (LP)
Bad booms (followed by a banking crisis): Positive but transient shock to TFP and LP