Recent well liked threads

Buat temen-temen yang mau kuliah tapi budget beli laptop terbatas, sebenernya bisa diakalin sih dengan "alternatif" lain.

Disclaimer: Saya bukannya mau promosiin Linux ya, inget, saya cuma memberikan solusi,.

Sebenernya dengan harga 2jutaan, temen-temen bisa dapet laptop second, tapi 2jutaan ini bukan pas bgt 2juta rupiah ya, yaaa mungkin 2,5-2,8 lah.

Namanya barang second, tentu temen-temen juga harus rombak "sedikit" dalemnya.

Selama motherboard dan LCD ngga bermasalah, temen-temen bisa "rombak" isinya biar membuat laptop itu agak powerful untuk sekedar kebutuhan ngetik, buat ppt, browsing, nonton film.

Tapi perlu kembali temen-temen sadari, kan laptopnya bekas nih, nah harus siapin dana darurat.

@alainpaulweber on en est aujourd'hui @cab2626 que c Via pierre Marion des services secret franc maçon qui ont récupérer les archives pedocriminels sortie de l'Elysée et mis ds un garage par le colonel Prouteau la gauche comme la droite ce sont arrangées "extraits" de ma conv JDCroix

@alainpaulweber @cab2626 111 Princesse J. de Croix 🥰fait bcps d'erreurs de dates de compréhension c un extrait de notre 1ere conv 1 com que j'ai poser sur ma colo "cheval Pr Tous" ou elle a de suite compris la famille de Roger Cailles "Dutroux" "Jet service" a étée revendu a la hollande "Zanvoort" 😄

@alainpaulweber @cab2626 ✊Justice 111 ✞ 333 💫🗡️ Contre FM 666 ⚜ 🥰"111" Vues 3 gouttes de sang sur la neige qui me guide, et sur mon "Carnet"qui ouvre une enquête @anatolium 1 hasard qui prend du sens l'uni'vers "1" Franc Sait me confirme que je suis bien sur mon chemin

https://x.com/ChomaratL/status/1975440684967674008?s=20

1\#Ucraina Fronte di Pokrovsk: Russi avanzano a Hryshyne, continua la stabilizzazione di Pokrovsk, ormai quasi totalmente abbandonata da ucraini.

2\#Ucraina Fronte di Lyman: Infiltrazione russa sotto droni, sul fianco orientale di Dobrysheve

3\#Ucraina Fronte di Sumy: Regimento Bolshoy pianta bandierina a Pokrovka, salvo poi prendersi probabilmente drone in testa poco più là. Ampliata grey in villaggio di confine sostanzialmente vuoto.

🚨 I've spent weeks inside the Epstein files — not looking for names, but for infrastructure.

What I found: Jeffrey Epstein wasn't just a sex trafficker. He was a switchboard — routing government secrets, Wall Street intelligence, and political power through one network.

The same network that built the censorship machine that targeted your speech during COVID.

Five parts. All sourced to DOJ documents. Here's the whole investigation 🧵👇

PART 1: The DOJ released thousands of pages of Epstein files. Buried inside them is a 20-year financial architecture designed to turn pandemics into a profit center.

Offshore vaccine funds. Donor-advised fund structures naming "pandemic" as a key area — three years before COVID.

JPMorgan treated a convicted sex offender as the operational architect of a Gates-linked charitable fund.
Every claim sourced. Every document numbered.

🔗 sayerji.substack.com/p/breaking-the…

PART 2: Inside Project Molecule — the 14-page JPMorgan proposal that turned biology into investable infrastructure.

$20M to "finance the surveillance network in Pakistan." Parametric triggers. Reinsurance markets. Vaccine capital positioned in structures designed for offshore flexibility and arm's-length profit.

This wasn't pandemic response. It was pandemic business planning — years before any pandemic.

🔗 sayerji.substack.com/p/inside-proje…

New paper!

What if you could guarantee (using a mix of formal verification and PDE theory) that a neural network would *always* give you the correct answer, even when making inferences arbitrarily far away from the training data?

Introducing BEACONS. arXiv link below. (1/15)

Link: 
In physics, we often want to use neural networks to infer new solutions to systems of PDEs. But outside of the spatiotemporal ranges on which they're trained, even physics-informed neural networks (PINNs) struggle to extrapolate correctly. (2/15)arxiv.org/abs/2602.14853

Back in the 90s, excellent work was done by Mhaskar, Pinkus and others on *quantitative* versions of the fêted Universal Approximation Theorems for neural networks: how accurately can a shallow neural network with N hidden neurons approximate a d-dimensional function? (3/15)

THE REID HOFFMAN FILES

I OCR'd all 1.4 million documents from the DOJ's Epstein FOIA release.

Then I tested every public claim Reid Hoffman ever made about Jeffrey Epstein.

13 claims. 0 true.

This is the very first email. August 2013.

[EFTA01960550]

Link: justice.gov/epstein/files/…

Since 2019, Reid Hoffman has made 13 testable public claims about Jeffrey Epstein:

1. He only had "few interactions" with Epstein
2. Those interactions were all "at the request of Joi Ito," then-director of the MIT Media Lab
3. They were all "for the purposes of fundraising for MIT". Nothing personal
4. His "last interaction with Epstein was in 2015"
5. He was "never a client" of Epstein's financial advisory services
6. He had "no engagement with him other than fundraising"
7. He didn't know who Epstein was before visiting his island.
8. He spent only "one night" on Epstein's private island
9. It was Joi Ito who "asked if Epstein could attend" the 2015 Palo Alto dinner, not Hoffman who invited him
10. When Epstein emailed him after 2015, his replies were "code for never"
11. "I did not go to the ranch". (Epstein's Zorro Ranch in New Mexico)
12. All post-2015 meetings were "coordinated by Joi Ito"

All are complete lies.

What is Reid Hoffman hiding?

This thread is a compendium of various messages that Hoffman and Epstein exchanged. Consider it a trailer of what's next.

What governs the geometry of time and space embeddings in LLMs?

We show it follows from translation symmetry in language statistics.

With Dhruva Karkada, @DanKorchinski, Andres Nava, @yasamanbb
arxiv.org/abs/2602.15029

Even removing all month–month co-occurrences does not break the circle.

The structure is collective: seasonal words mediate the coupling.

Words have continuous latent attributes — season, geography, historical time —
and co-occur preferentially with others sharing them.

This induces smooth low-dimensional manifolds in embedding space.

Ich hatte jetzt mal Zeit, in die Inszenierung von Milo Rau am Thalia Theater in Hamburg reinzuschauen. Beim zufälligen Reinzappen fiel mir folgende 👇 Szene aus der „Vernehmung“ des „Zeugen“ Feroz Khan auf, einem jungen deutsch-pakistanischen Influencer, der für die AfD wirbt. /2

Wenn es jemandem in dieser Szene an Respekt mangelt, dann nicht Khan, sondern der „Anklägerin“ Gabriele Heinecke – selbst wenn diese ihre Respektlosigkeit („Totaler Bullshit!“) im süßlichen Bastelstundentonfall dahersäuselt. /3

Doch die „Richterin“, die Ex-Justizministerin Herta Däubler-Gmelin (SPD), maßregelt nicht sie, sondern Khan – obgleich er nichts getan oder gesagt hat, was eine solch schroffe Maßregelung rechtfertigen würde.

(Die ganze „Vernehmung“👇 ab 2:04:09) /4youtube.com/live/KjwfRttxs…

If you study the roots of a large part of conditioned inhibition what you find is that the way the UK is set up is to make areas that are "achieving" and "doing well for yourself" as institutionally clashing with erotic/sexual expression

It implicates parenting and children

In the UK what happens is that if you look the way society is governed, you have Lily Phillips and the law of the land = No problem

BUT then if you take the 'Professions' what are the 'Professions' = Teacher, Doctor, Nurse, Police..

Like what do you want to be when you grow up?

And it covers loads of areas, armed forces, lots of areas.

The parents want the daughters and children to strive to become a 'Professional' or whatever it is that parents want for their kids

So due to the prohibitions that are built into society the parents groom their kids

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