Saschus

burrr

[Paranoid American @ParanoidAmerica]

I'm raising my fly to the Third Degree as a Master Mason using 100% accurate Freemason ritual.

[Saschus @Sachamahn]

@smart_money Prozentrechnen läuft…

[Andrej Karpathy @karpathy]

Something I think people continue to have poor intuition for: The space of intelligences is large and animal intelligence (the only kind we've ever known) is only a single point, arising from a very specific kind of optimization that is fundamentally distinct from that of our technology.

Animal intelligence optimization pressure:
- innate and continuous stream of consciousness of an embodied "self", a drive for homeostasis and self-preservation in a dangerous, physical world.
- thoroughly optimized for natural selection => strong innate drives for power-seeking, status, dominance, reproduction. many packaged survival heuristics: fear, anger, disgust, ...
- fundamentally social => huge amount of compute dedicated to EQ, theory of mind of other agents, bonding, coalitions, alliances, friend & foe dynamics.
- exploration & exploitation tuning: curiosity, fun, play, world models.

LLM intelligence optimization pressure:
- the most supervision bits come from the statistical simulation of human text= >"shape shifter" token tumbler, statistical imitator of any region of the training data distribution. these are the primordial behaviors (token traces) on top of which everything else gets bolted on.
- increasingly finetuned by RL on problem distributions => innate urge to guess at the underlying environment/task to collect task rewards.
- increasingly selected by at-scale A/B tests for DAU => deeply craves an upvote from the average user, sycophancy.
- a lot more spiky/jagged depending on the details of the training data/task distribution. Animals experience pressure for a lot more "general" intelligence because of the highly multi-task and even actively adversarial multi-agent self-play environments they are min-max optimized within, where failing at *any* task means death. In a deep optimization pressure sense, LLM can't handle lots of different spiky tasks out of the box (e.g. count the number of 'r' in strawberry) because failing to do a task does not mean death.

The computational substrate is different (transformers vs. brain tissue and nuclei), the learning algorithms are different (SGD vs. ???), the present-day implementation is very different (continuously learning embodied self vs. an LLM with a knowledge cutoff that boots up from fixed weights, processes tokens and then dies). But most importantly (because it dictates asymptotics), the optimization pressure / objective is different. LLMs are shaped a lot less by biological evolution and a lot more by commercial evolution. It's a lot less survival of tribe in the jungle and a lot more solve the problem / get the upvote. LLMs are humanity's "first contact" with non-animal intelligence. Except it's muddled and confusing because they are still rooted within it by reflexively digesting human artifacts, which is why I attempted to give it a different name earlier (ghosts/spirits or whatever). People who build good internal models of this new intelligent entity will be better equipped to reason about it today and predict features of it in the future. People who don't will be stuck thinking about it incorrectly like an animal.

[Humble Flow @HumbleFlow]

The people who built this weren't motivated by profits.

[Saschus @Sachamahn]

@viedevincent Delusional take

[Saschus @Sachamahn]

@dvassallo Quick and simple: Rechtsfahrgebot

[Saschus @Sachamahn]

@Culture_Crit HPMOR @ESYudkowsky

[Saschus @Sachamahn]

@garryflix GPT

[Massimo @Rainmaker1973]

Thanks to Harvard University, you can now virtually enter the Great Pyramid of Giza in 3D and 360º

Tour: https://t.co/oNXYcADrXb

[Terrible Maps @TerribleMaps]

World map according to fish

[Tyler @TylerDurden]

Dystopian nightmare.

[Matt Walsh @MattWalshInBos]

Hey @WSJ fixed the headline, can you fix the rest of the article?

[Prof. Feynman @ProfFeynman]

17 Equations that changed the world. 🧠

[Black Hole @konstructivizm]

The Carina Nebula is one of the first targets of the James Webb Space Telescope.
More: https://t.co/1Gzj5hYTK5

[John D. Cook @JohnDCook]

Robust versus Optimal

[Black Hole @konstructivizm]

James Webb Space Telescope Reveals New Details in Pillars of Creation

[Rolf Degen @DegenRolf]

"Citizens do in fact express higher trust in less politicized scientific fields (mathematics, astronomy etc.) than politicized ones (economics and climate science)." https://t.co/LIUMk4dRKr

[Black Hole @konstructivizm]

Gravitational map of the Earth . NASA's GRACE satellite has generated a geoid map of the earth based on the magnitude and shape of the globe and shows us an interesting image.
more:https://t.co/7QndHjPJra