Psychedelegate

Spreading seeds

[Psychedelegate @psychedelegate]

@funeralreceiver Hello. I am American in Brazil (SP)

[Psychedelegate @psychedelegate]

@cremieuxrecueil Protoss vs Zerg

[Psychedelegate @psychedelegate]

@downbadcomment What you *thought* was rock bottom!

[Psychedelegate @psychedelegate]

@mouse_math Math isn’t restricted to human. Bees, AI, visual cortex do math.

Applied math is a structure-preserving map of whatever it’s modeling. Pure math is syntax with no referent.

[Psychedelegate @psychedelegate]

@avidseries Tell us more about Trump corruption

[Psychedelegate @psychedelegate]

@redaction Genesis 1:26:
"And God said, Let Us make man in Our image, after Our likeness”

[Psychedelegate @psychedelegate]

@the_errant_way Eugenics, organized by the state…what could possibly go wrong. Free market eugenics would be much better

[Psychedelegate @psychedelegate]

@lizisamused While this is true for “normal” men (not sadistic or psychopathic), there are outliers, about 3% of the population.

[Psychedelegate @psychedelegate]

@beffjezos https://t.co/2wHDL90TrA

[Dan Burmawi @DanBurmawy]

There is a species of ant that approaches the edge of another colony, kills a single worker, and then takes on the dead ant’s scent.

For ants, scent is everything. Wearing that scent, the intruder walks in with no resistance. The workers pass by without concern.

The intruder moves inward, toward the queen, then It sprays the queen with a different scent that makes the workers turn on her. Then they surround her and kill her.

The intruder does not need to fight anyone. The colony does the work itself.

Once the queen is gone, the intruder reproduces. The true invader is no longer an intruder. It is the future.

This is how ideological takeover works.

A destructive foreign ideology takes the scent of familiar ideas and walks in as if it belongs.

It speaks the native vocabulary, justice, equality, compassion, rights, progress. It uses these words and quietly changes what they point to.

Then it moves inward.

It alters how foundations are perceived. Responsibility is made to smell like cruelty, law like oppression, borders like hatred, tradition like danger, history like guilt.

At that point, the civilization turns on itself.

Its courts, universities, churches, media, and bureaucracies begin treating their own foundations as threats. They believe they are defending the system.

They are enforcing what now smells legitimate. They do not see the intruder because it sounds exactly like them.

And when the founding principles are finally removed, discredited, dismantled, erased, the foreign ideology does not need to conquer anything. It inherits what is left.

The queen is gone. The colony is no longer itself.

The most effective conquest is the one that convinces a society that its own foundations are the enemy, and that killing them is an act of virtue.

[Psychedelegate @psychedelegate]

@angeld23_ Brutally retarded

[Psychedelegate @psychedelegate]

@Topboix Incorrect take. What matters is expertise differential x alignment.

[Psychedelegate @psychedelegate]

@williameijer Delirious take. They’re competing with other women.

[Psychedelegate @psychedelegate]

@The4thWayYT Deifying a golem—What could possibly go wrong…

[Psychedelegate @psychedelegate]

@PilpsYT It didn’t mention genes

[Psychedelegate @psychedelegate]

@Giuliano_Mana How many such geniuses never even made it to history, and their knowledge lost for eons until independently discovered by other people? How many were alive in our lifetime and no one the interacted with could understand their insights?

[Psychedelegate @psychedelegate]

@Babygravy9 To be fair, he didn’t spend a trill on the thrill

[Psychedelegate @psychedelegate]

This is a flaw in marginal vs cumulative thinking. “It’s only a one-time 0.014% of my income on a 1st date” with some girl they’re not even interested in, but these microdecisions add up to a grander behavioral and spending pattern.

Setting the bar at that level that early on mostly just filters for gold-differs and suggests he’s more likely to let a girl he actually does like totally cuck him financially in the future.

If she knows he’s making $5M/yr and won’t meet him for a more “basic” 1st date, she ain’t the one. Dude doesn’t seem to realize that he’s the prize, not the girls. Maybe the girl is making a lot of money. But does he want the baggage/unavailability that will come with that? Probably not, unless she somehow has bandwidth for their relationship.

[Psychedelegate @psychedelegate]

@ArtemisConsort https://t.co/vy84Caq6MQ

[Psychedelegate @psychedelegate]

1/2
In the era of SI-scale systems, we will not understand the most powerful technologies. We will get used to them—and the people who get used to them fastest will dominate.
John von Neumann put the underlying reality bluntly: “In mathematics you don’t ‘understand’ things. You just get used to them.” That was already true of advanced mathematics and quantum mechanics. It is about to become true of the central engines of technological and economic progress. The generative processes that produce new mathematics, designs, strategies, and scientific results will increasingly run through systems whose internal trajectories cannot be fully reconstructed by human minds in human time. We will confirm the outputs. We will not possess compact, first-principles accounts of how they were produced.
Truth fluency—the ability to use these systems and their outputs with the facility of a native speaker rather than the labor of deriving every rule from first principles—has always mattered. A fluent speaker generates and evaluates novel, correct sentences without necessarily being able to state all the underlying rules or reconstruct every developmental step. They have compressed the regularities and internalized the irregularities through massive exposure and use. The same pattern will apply to domains shaped by opaque high-capability systems. Practitioners will recognize when a construction “sounds right,” when it is anomalous in a useful way, and how to extend or stress-test it—even when no human-scale derivation of the generative path exists. What changes is the scale and stakes: fluency is no longer merely helpful. It becomes the primary mode of competence once full derivation is routinely unavailable.
This fluency is built and maintained through cognitive compression. People who can rapidly form compact, coherent narratives or structural scaffolds that organize large volumes of partially opaque information will hold the advantage. These are not full explanations; they are high-utility interfaces. Competitive memorizers already demonstrate the principle: they do not store raw data but encode it in structured spatial or narrative forms that support accurate retrieval and manipulation. In technical domains the same capacity lets someone absorb an AI-generated result, embed it in existing knowledge, note its likely failure modes, and keep a working model that remains predictive. Those who insist on deriving everything from scratch before using it will lag.
Because the generative process itself is not fully recoverable, these working models cannot be validated by internal derivation alone. Radical empiricism becomes mandatory. The models must be tested continuously against external reality: formal verification, physical measurement, adversarial probes, and downstream outcomes. Theory still generates candidates and designs the tests, but progress is adjudicated by confrontation with the world rather than by completeness of the internal story. The systems are more like complex physical phenomena than pure mathematical constructions whose every step is transparent.

[Psychedelegate @psychedelegate]

2/2

Alongside fluency sits a deeper developmental edge that can be called gnosis without mystification: the capacity to be already, or rapidly become, tuned to the underlying regularities of a domain so that the right templates form with less corrective friction. Organisms whose early priors cohere with the major structures of their environment require less data and make fewer costly errors before usable models emerge. In humans this appears as variation in how readily certain people extract high-level causal sketches, notice when a narrative fails to predict, and feel the grain of a domain before they can fully articulate it. Under conditions where complete reconstruction is rare, this tuning is not ornamental. It is the difference between slowly assembling a usable interface and remaining outside the system, waiting for an explanation that may never arrive in human-scale form. It is concrete and empirical—measurable in the speed of productive engagement and the quality of subsequent tests—yet it retains the older sense of direct acquaintance with reality that precedes full propositional grasp.
The resulting practice combines both. It resembles skilled use of a language whose full grammar remains incompletely known: generate and evaluate candidate expressions, maintain compact mental models that support prediction, subject those models to external checks, and iteratively improve both. People who join strong compression ability and rapid empirical updating with a developmental tuning that already approximates the relevant structures will navigate the regime more effectively than those who treat fluency as optional or who wait for complete derivations. Getting used to the systems is no longer a temporary stage on the way to understanding. For the most powerful technologies, it is the permanent condition of competence.
”

The dialogue that resulted in this essay:

https://t.co/OdUuA4rqxW

[Psychedelegate @psychedelegate]

1/2
In the era of SI-scale systems, we will not understand the most powerful technologies. We will get used to them—and the people who get used to them fastest will dominate.
John von Neumann put the underlying reality bluntly: “In mathematics you don’t ‘understand’ things. You just get used to them.” That was already true of advanced mathematics and quantum mechanics. It is about to become true of the central engines of technological and economic progress. The generative processes that produce new mathematics, designs, strategies, and scientific results will increasingly run through systems whose internal trajectories cannot be fully reconstructed by human minds in human time. We will confirm the outputs. We will not possess compact, first-principles accounts of how they were produced.
Truth fluency—the ability to use these systems and their outputs with the facility of a native speaker rather than the labor of deriving every rule from first principles—has always mattered. A fluent speaker generates and evaluates novel, correct sentences without necessarily being able to state all the underlying rules or reconstruct every developmental step. They have compressed the regularities and internalized the irregularities through massive exposure and use. The same pattern will apply to domains shaped by opaque high-capability systems. Practitioners will recognize when a construction “sounds right,” when it is anomalous in a useful way, and how to extend or stress-test it—even when no human-scale derivation of the generative path exists. What changes is the scale and stakes: fluency is no longer merely helpful. It becomes the primary mode of competence once full derivation is routinely unavailable.
This fluency is built and maintained through cognitive compression. People who can rapidly form compact, coherent narratives or structural scaffolds that organize large volumes of partially opaque information will hold the advantage. These are not full explanations; they are high-utility interfaces. Competitive memorizers already demonstrate the principle: they do not store raw data but encode it in structured spatial or narrative forms that support accurate retrieval and manipulation. In technical domains the same capacity lets someone absorb an AI-generated result, embed it in existing knowledge, note its likely failure modes, and keep a working model that remains predictive. Those who insist on deriving everything from scratch before using it will lag.
Because the generative process itself is not fully recoverable, these working models cannot be validated by internal derivation alone. Radical empiricism becomes mandatory. The models must be tested continuously against external reality: formal verification, physical measurement, adversarial probes, and downstream outcomes. Theory still generates candidates and designs the tests, but progress is adjudicated by confrontation with the world rather than by completeness of the internal story. The systems are more like complex physical phenomena than pure mathematical constructions whose every step is transparent.