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@viviansousal:

Vivian Sousa
Vivian Sousa
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Region: BR
Tuesday 03 March 2026 23:06:06 GMT
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brunobarrosf_
Bruno Barros 🇧🇷💢 :
Perigosaaaa 🤣
2026-04-11 17:34:56
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#CapCut #foryoupage #variltiktok #M #💫
#CapCut #foryoupage #variltiktok #M #💫
Jaka jest Twoja ukryta supermoc według znaku zodiaku? 🔮 Zgadza się to u Was? Napiszcie w komentarzu Sprawdźcie resztę znaków: 👇 ♈ Baran: zabieram innym strach♉ Byk: zdejmuję z ludzi stres♊ Bliźnięta: rozkręcam każdą imprezę i nudę♌ Lew: oddaję innym swoją odwagę♍ Panna: naprawiam cudze błędy♎ Waga: godzę skłóconych ludzi♏ Skorpion: biorę na siebie cudzy ból♐ Strzelec: przynoszę innym farta♑ Koziorożec: jestem oparciem w kryzysie♒ Wodnik: otwieram ludziom oczy♓ Ryby: leczę złamane serca#zodiak #astrologia #supermoc #znakizodiaku
Jaka jest Twoja ukryta supermoc według znaku zodiaku? 🔮 Zgadza się to u Was? Napiszcie w komentarzu Sprawdźcie resztę znaków: 👇 ♈ Baran: zabieram innym strach♉ Byk: zdejmuję z ludzi stres♊ Bliźnięta: rozkręcam każdą imprezę i nudę♌ Lew: oddaję innym swoją odwagę♍ Panna: naprawiam cudze błędy♎ Waga: godzę skłóconych ludzi♏ Skorpion: biorę na siebie cudzy ból♐ Strzelec: przynoszę innym farta♑ Koziorożec: jestem oparciem w kryzysie♒ Wodnik: otwieram ludziom oczy♓ Ryby: leczę złamane serca#zodiak #astrologia #supermoc #znakizodiaku
الشيخ ياسر الدوسري حفظه الله
الشيخ ياسر الدوسري حفظه الله
#ابو_علي خليلك كرامه شويه
#ابو_علي خليلك كرامه شويه
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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