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Testing Electromag Nodes on Apple M4 mac mini, very impressed with its performance in handling a complex scene like this. The magnetic field calculations are updated in realtime with no lag in EEVEE with a compositor node setup. The video shows the magnetic field of an embedded rogowski current... show more

Sam M

8,986 subscribers

48,749 просмотров • 1 год назад •via X (Twitter)

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Комментарии: 10

Фото профиля Asger Bjørn Jørgensen

Asger Bjørn Jørgensen1 год назад

This is truly remarkable, Sam 😍. And we wish to expand our design verification tools of power modules and PCBs in this direction. We understand that the CPU/GPU markets are way beyond us, but believe that efficient SiC/GaN design will require similar efforts. Thank you.

Фото профиля Michael Toutonghi (Mike.vrsc@)

Michael Toutonghi (Mike.vrsc@)1 год назад

Can you recommend how I might get started if I have some high voltage inductive actuators that I’d like to either optimize or redesign?

Фото профиля LiamHz

LiamHz1 год назад

@MasterTimBlais blender science vis!

Фото профиля Dagan Schoen

Dagan Schoen1 год назад

wait you use blender for sims?

Фото профиля Peter Mathia ✈

Peter Mathia ✈1 год назад

How do you run Blender?

Фото профиля Christian Simon

Christian Simon1 год назад

Can you tell us more about the pipe-line / integration ? From KiCAD to FEM (?) to Blender ?

Фото профиля Guttural Prayer

Guttural Prayer1 год назад

Love your massive work

Фото профиля Mark Ankcorn

Mark Ankcorn1 год назад

@DanielleFong Which one? Plain M4 or the Pro and how much RAM? Don’t leave the nerds hanging!!

Фото профиля Sam M

Sam M1 год назад

@DanielleFong plain M4 mac mini, base cheapest model. 16GB unified RAM

Фото профиля darthur

darthur1 год назад

Okay, I guess I need a new laptop now....

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140,624 просмотров • 3 лет назад

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Mario Nawfal

1,047,809 просмотров • 10 месяцев назад

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Alex Cheema

103,566 просмотров • 1 год назад

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@levelsio

423,642 просмотров • 18 дней назад

Make Pixels Dance: High-Dynamic Video Generation paper page: Creating high-dynamic videos such as motion-rich actions and sophisticated visual effects poses a significant challenge in the field of artificial intelligence. Unfortunately, current state-of-the-art video generation methods, primarily focusing on text-to-video generation, tend to produce video clips with minimal motions despite maintaining high fidelity. We argue that relying solely on text instructions is insufficient and suboptimal for video generation. In this paper, we introduce PixelDance, a novel approach based on diffusion models that incorporates image instructions for both the first and last frames in conjunction with text instructions for video generation. Comprehensive experimental results demonstrate that PixelDance trained with public data exhibits significantly better proficiency in synthesizing videos with complex scenes and intricate motions, setting a new standard for video generation.

Make Pixels Dance: High-Dynamic Video Generation paper page: Creating high-dynamic videos such as motion-rich actions and sophisticated visual effects poses a significant challenge in the field of artificial intelligence. Unfortunately, current state-of-the-art video generation methods, primarily focusing on text-to-video generation, tend to produce video clips with minimal motions despite maintaining high fidelity. We argue that relying solely on text instructions is insufficient and suboptimal for video generation. In this paper, we introduce PixelDance, a novel approach based on diffusion models that incorporates image instructions for both the first and last frames in conjunction with text instructions for video generation. Comprehensive experimental results demonstrate that PixelDance trained with public data exhibits significantly better proficiency in synthesizing videos with complex scenes and intricate motions, setting a new standard for video generation.

AK

102,444 просмотров • 2 лет назад