moon girl

[CTFTHEORY @mathmaticulous]

Every prime number — 2, 3, 5, 7, 11, 13 — leaves a fingerprint in the gap between itself and the next prime.

Those gaps aren't random. They follow a strict set of rules that can be mapped onto just six positions on a circle, forming a machine that governs where every prime can go next.

This is the Prime Gap State Machine
A 6 state automaton running on modular arithmetic. The six positions are the only residues modulo 9 that prime numbers can occupy {1, 2, 4, 5, 7, 8}.

The Spine positions — 0, 3, and 6 — are permanently excluded. No prime above 3 ever lands there.

What you're watching is every prime number moving through those six positions as it flows along the number line.

The glowing yellow dots are primes in motion. Each dot travels from one node to the next according to the gap rule: add the gap, take the result mod 9, land on the next state. Zero violations across tens of millions of primes tested.

Those six states don't arrange themselves randomly on the circle. They split into exactly two groups, the Hard Wall states {1, 4, 7} and the Temporal states {2, 5, 8}. Each group sits at perfectly equal 120° spacing around the circle. One forms a red triangle.

The other forms a blue triangle. Two equilateral triangles, rotated relative to each other, superimposed on the same circle.

That is a hexogram Emerging from pure prime number arithmetic. Not designed. Not chosen. Forced by the structure of mod-9 arithmetic and the constraints that govern where primes can live.

This is from the Prime Lattice Coherence Framework original independent mathematical research showing that prime numbers organize themselves on a {2,3}-based lattice with a Hard Wall boundary at the prime 7. The hexagram you see is the geometric shadow of that boundary, cast onto a circle.

The universe keeps writing the same shapes.
https://t.co/qvpnQKziyl
https://t.co/8YNWsuqRmg

[Andrej Karpathy @karpathy]

In awe of SpaceX and its story - past, present and the future. You can think about it in 10+ different ways and continue re-blowing your mind in circles. Huge congrats to the team! 🚀

[Marc Andreessen 🇺🇸 @pmarca]

We're gonna abundance so much, you may even get tired of abundance. And you'll say, please, please, it's too much abundance. We can't take it anymore. Mr. Musk, it's too much, and I will say no it isn't, we have to keep abundance, we have to abundance more, we're gonna abundance more!

[Teddy - PolyBackTest.com @Bitcoin_Teddy]

MARC ANDREESSEN: "We had meetings with the Biden admin where they told us to not even start AI companies because there's no way they'll let them succeed."

JOE ROGAN: "What do you do after a meeting like that?"

MARC ANDREESSEN: "You go endorse Donald Trump."

LMAO

[Matt Walsh @MattWalshBlog]

Every country on planet Earth is built on conquest. Every “indigenous” tribe claimed its land by conquest. Every line on the map, across every continent and every ethnic group, was drawn by conquest. Apologizing for this is like apologizing for gravity.

[Dr Singularity @Dr_Singularity]

Abundance is coming. Actual, ridiculous, post scarcity abundance. The bottleneck was always (not enough) intelligence. That bottleneck just broke.

[Ac Hampton @HamptonAc_]

traits of people with high agency:

> book flights impulsively
> say "call me" instead of texting essays
> can become obsessed overnight
> walk around during phone calls
> buy before they feel ready
> don’t ask group chats for opinions
> can survive on very little comfort
> good at talking to strangers
> slightly delusional
> treat embarrassment like a temporary side effect
> can disappear socially without feeling guilty
> low tolerance for slow people
> thinks most problems are figureoutable
> dangerously optimistic
> oddly calm when things go wrong

[MTS @MTSlive]

SITUATION DETECTED: Google DeepMind’s AI agent autonomously solved 9 of 353 open Erdos problems in mathematics, at a cost of a few hundred dollars per problem.

[Satyam @sattyyouneed]

Imagine being this early

[Tesla Owners Silicon Valley @teslaownersSV]

Rockets need a hug too!

Starship becoming fully reusable is our ticket to Kardashev civilization.

[Naval @naval]

The latest IQ test involves data centers and water.

[Goodfire @GoodfireAI]

Neural networks do math by rotating shapes.

We found a shape-rotating calculator hidden inside an LLM – and it’s used for more than just math! (1/6)

[Andrew Côté @Andercot]

NASA scientist discovers a 'new force' he has tested over 2000 times and explains the method of operation and his test results, of achieving 2 milli-newtons of thrust with 6000 volts.

In a vacuum, with no propellant mass.

Welcome to the sci-fi future.

[etn. @etnshow]

BREAKING: London based Isomorphic Labs is in talks to raise more than $2 billion in a new round of funding led by Thrive Capital.

[Krinza @krinza]

in the next 3 years, every major AI lab will spin up its own bio arm and in-house wet labs.

biology is the next big bet in AI after code

pay attention.

[kache @yacineMTB]

I wonder when the panic will start to set in

[Andrej Karpathy @karpathy]

This is the the quote I've been citing a lot recently.

[How To Prompt @HowToPrompt__]

MIT proved every major AI model is secretly converging on the same "brain."

It’s called the “platonic representation hypothesis,” and it’s one of the most mind-blowing papers you’ll ever read.

You train a vision model purely on images. You train a language model purely on text.

They use completely different architectures. They process completely different data. They should have completely different "brains."

But as these models scale up, something impossible is happening.

When researchers measure how they organize information, the mathematical geometry is identical.

A model that only "sees" images and a model that only "reads" text are measuring the distance between concepts in the exact same way.

The models are converging.

The researchers named this after Plato’s Allegory of the Cave.

Plato believed that everything we experience is just a shadow of a deeper, hidden, perfect reality.

The paper argues that AI models are doing the exact same thing.

They are looking at the different "shadows" of human data, text, images, audio. And they are independently discovering the exact same underlying structure of the universe to make sense of it.

It doesn't matter what company built the AI.

It doesn't matter what data it was trained on.

As models get larger, they stop memorizing their specific tasks. They are forced to build a statistical model of reality itself.

And there is only one reality to map.

2024, Arxiv

[Brian Roemmele @BrianRoemmele]

Human memory is encoded as FFTs.

Not words and not images.

Sensor data holographically tied to the FFTs if present, memorizing the information.

[Donald J. Trump @realDonaldTrump]

Saint Michael the Archangel, defend us in battle. Be our defense against the wickedness and snares of the Devil. May God rebuke him, we humbly pray, and do thou, O Prince of the heavenly hosts, by the power of God, cast into hell Satan, and all the evil spirits, who prowl about the world seeking the ruin of souls. Amen.