roman @Nozelcode

Every creator has references. The difference is what you do with them. Turn inspiration into your next project with Dreamina Canvas 👇 dreamina.capcut.com/ai-tool/home/?…

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roman @Nozelcode

6 hours ago

Found a cinematic shot you want to study? Upload it. Extract Prompt reveals the thinking behind the visual, helping you move from inspiration to creation. #VideoEditing

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You can reverse-engineer the prompt behind any clip now. Prompt tools hand you a clip you can't control. A canvas hands you a project you can. Dreamina 2.0 is canvas-first — the new way AI video is made. #Dreamina #DreaminaPartner Here's exactly how 👇

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roman @Nozelcode

7 hours ago

@liambraus the deepseek guys are built different

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roman @Nozelcode

7 hours ago

@leilamakes if Mark to Fix actually keeps the rest of the clip intact that’s the whole product

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roman @Nozelcode

7 hours ago

everyone is fighting for the agi crown deepseek is just sitting in the backseat writing code honestly, that might be the most realistic part of this whole video

MAX @maxxmalist

8 hours ago

The race for AGI Script: Sherpa by Pocket FM Video: Seedance 2.5

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roman @Nozelcode

8 hours ago

@zentalksai factory automation is about to move way faster than people expect

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roman @Nozelcode

8 hours ago

@liambraus egocentric data is so underrated. third person footage teaches robots nothing useful

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roman @Nozelcode

8 hours ago

@silvanrec i will start to use this

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roman @Nozelcode

8 hours ago

@liambraus llevo 3 de estos hechos y ya me siento otro programando

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roman @Nozelcode

8 hours ago

@heyfredds desde el lado de creador que sí graba, esto da un poco de miedo pero también es el futuro del contenido low cost

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roman @Nozelcode

8 hours ago

@marcusyul esto deja claro que la infra de simulacion va a ser tan importante como el propio modelo

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roman @Nozelcode

8 hours ago

the internet gave llms an almost unlimited source of training data. robotics never had an equivalent. until now, scaling physical ai has meant collecting expensive real-world data and testing policies on physical hardware. midcentury is attacking both bottlenecks: 2m+ hours of real-world data 20k+ tasks 50+ environments massively parallel simulation physical ai needs its own scaling infrastructure.

Midcentury @MidcenturyAI

9 hours ago

Introducing Midcentury. We’re building the data and simulation infra for physical AI. Today, we’re coming out of stealth with a $15M Series Seed to scale robotics beyond polished demos. We’re already supporting frontier labs with: → The world’s largest egocentric dataset: