@.domenicodicarlo: This magic trick is IMPOSSIBLE to explain! 🤯#foryoupage❤️❤️ #fyp #magic

Mago Domin

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Region: IT

Thursday 01 October 2026 19:20:32 GMT

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Comments

afayarafa :

bruh 😏

2026-10-01 22:09:24

15

FOSSILMAN :

I think you’ve done this trick too many times the folds are showing up where they’re not supposed to

2026-10-13 21:59:34

2

rickyspanish_holdem :

Witch tok

2026-10-25 18:05:34

1

Bahodur :

❤️❤️❤️❤️❤️❤️❤️

2026-10-02 15:52:46

1

Ciro Milano :

Guarda dietro amico hahahah

2026-10-02 22:20:26

1

romeo.delfabbro :

comunque bello se non mostri il pezzettino della banconota

2026-10-01 19:27:46

1

KnightOfTheGoldenVows :

It’s a good trick bro

2026-10-02 03:36:04

1

Akani vises :

Nah lying

2026-10-06 23:39:09

1

dylan.456889 :

2026-10-01 21:49:18

2

🍀🇩🇴Francisco Grullón :

2026-10-22 23:16:51

1

mel :

Será que consigo fazer essa mágica 😂😂😂😂🙏🙏🙏🙏🙏

2026-10-02 13:03:45

1

Alexandr :

карта в руке спрятана😁,знаем Домин

2026-10-05 18:13:00

1

gorasamb71 :

❤️❤️❤️❤️❤️❤️❤️❤️

2026-10-07 21:44:35

1

MAHOMI RYUZAKI :

2026-10-02 00:36:38

2

romeo.delfabbro :

si vede un rialzo sulla banconota

2026-10-01 19:26:28

4

la brujisa buena🇪🇸🇪🇸 :

🥰🥰🥰🍀🍀

2026-10-08 20:06:36

2

🍀🌺💙Blue💙🌺🍀 :

Good luck. I have to stay away from you, because with this speed and magic you will make me disappear too. 🤣🤣🤣🙈👊❤️

2026-10-01 19:29:06

2

Marjorie.D59.L :

🥰🥰🥰

2026-10-09 18:42:55

1

magictricks96 :

👍👍

2026-10-18 16:34:09

1

Houley Niang :

[Larmes de joie][Larmes de joie][Larmes de joie][Larmes de joie][Larmes de joie]

2026-10-02 20:40:19

1

Khun Maung Bi :

@❤️❤️❤️❤️❤️

2026-10-02 03:17:33

1

Myiesha Schneid :

🥤🛩️🦗

2026-10-01 22:29:33

1

Thankgod Ftdollar🇺🇸🇬🇧 :

@𝐊𝐢𝐧𝐠 𝐨𝐟 𝐒𝐩𝐚𝐝𝐞𝐬♠️

2026-10-01 22:04:19

1

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We’re sharing a solution to the Navier–Stokes existence and smoothness problem, one of the Millennium Prize Problems. This proof, produced by an internal OpenAI system, shows that the dynamics of the Navier-Stokes equations for fluid motion can develop a singularity in finite time. We’re sharing both a writeup of the proof and a formalization in Lean. The Millennium Prize Problems⁠ represent some of the deepest questions at the frontier of mathematics. The question of whether smooth three-dimensional fluid motion can break down has remained unresolved for roughly 90 years. A major goal of our work is to empower scientists to advance research and technology that benefits all of humanity. To solve the Navier–Stokes problem, we used an internal model that is significantly more capable than GPT‑6 Astra. We believe it is important to inform the world about the pace of AI progress and what to expect from upcoming models. And we congratulate Levent Alpöge and Tristan Buckmaster on their remarkable mathematical work. We (the researchers and the agents) did not see any of their work through any means until they released it publicly — in particular, no specific user data was accessed in order to solve this problem. While unlikely, we cannot rule out that de-identified data derived from their usage of our products helped improve our models. However, our proofs differ significantly and even the precise results proved are different in the Euler case (forced vs. unforced).

We’re sharing a solution to the Navier–Stokes existence and smoothness problem, one of the Millennium Prize Problems. This proof, produced by an internal OpenAI system, shows that the dynamics of the Navier-Stokes equations for fluid motion can develop a singularity in finite time. We’re sharing both a writeup of the proof and a formalization in Lean. The Millennium Prize Problems⁠ represent some of the deepest questions at the frontier of mathematics. The question of whether smooth three-dimensional fluid motion can break down has remained unresolved for roughly 90 years. A major goal of our work is to empower scientists to advance research and technology that benefits all of humanity. To solve the Navier–Stokes problem, we used an internal model that is significantly more capable than GPT‑6 Astra. We believe it is important to inform the world about the pace of AI progress and what to expect from upcoming models. And we congratulate Levent Alpöge and Tristan Buckmaster on their remarkable mathematical work. We (the researchers and the agents) did not see any of their work through any means until they released it publicly — in particular, no specific user data was accessed in order to solve this problem. While unlikely, we cannot rule out that de-identified data derived from their usage of our products helped improve our models. However, our proofs differ significantly and even the precise results proved are different in the Euler case (forced vs. unforced).

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