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Jousef Murad

@Jousefm2 • 19,826 subscribers

CEO & Lead Engineer at @_apexagency | 📈 AI Automations & Agents for Businesses | Eindhoven 🇳🇱 | ⚙️ Engineer ➡️ Siemens Technology Partner

Shorts

⚡Physics-Informed Neural Networks (PINN)⚡ PINNs are neural networks that are trained to solve supervised learning tasks while respecting any given laws of physics described by general nonlinear partial differential equations. 👉 Full Tutorial:

⚡Physics-Informed Neural Networks (PINN)⚡ PINNs are neural networks that are trained to solve supervised learning tasks while respecting any given laws of physics described by general nonlinear partial differential equations. 👉 Full Tutorial:

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600-Million-Cell Jet External Aerodynamics Simulation Solved in Just 14 Hours🚀 The jet was meshed in 30 minutes using rapid octree meshing on 480 CPU cores and solved in just 14 hours on 20 NVIDIA L40 GPU cards using wall function LES. 🔗

600-Million-Cell Jet External Aerodynamics Simulation Solved in Just 14 Hours🚀 The jet was meshed in 30 minutes using rapid octree meshing on 480 CPU cores and solved in just 14 hours on 20 NVIDIA L40 GPU cards using wall function LES. 🔗

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Introducing Eye Contact by NVIDIA 👀 NVIDIA just released a new Eye Contact feature that uses AI to make you look into the camera.

Introducing Eye Contact by NVIDIA 👀 NVIDIA just released a new Eye Contact feature that uses AI to make you look into the camera.

11,875,663 просмотров • 3 лет назад

I’m amazed by the performance of #Gemini3 🚀 I just built a pure JavaScript Computational Fluid Dynamics (CFD) solver that runs entirely in a single HTML file - no plugins, no backend, and no installation required. #CFD #VibeCoding #LatticeBoltzmann #Engineering #Simulation

I’m amazed by the performance of #Gemini3 🚀 I just built a pure JavaScript Computational Fluid Dynamics (CFD) solver that runs entirely in a single HTML file - no plugins, no backend, and no installation required. #CFD #VibeCoding #LatticeBoltzmann #Engineering #Simulation

139,304 просмотров • 6 месяцев назад

Φ-SO : Physical Symbolic Optimization - Learning Physics from Data 🧠 The Physical Symbolic Optimization package uses deep reinforcement learning to discover physical laws from data. Here is Φ-SO discovering the analytical expression of a damped harmonic oscillator.

Φ-SO : Physical Symbolic Optimization - Learning Physics from Data 🧠 The Physical Symbolic Optimization package uses deep reinforcement learning to discover physical laws from data. Here is Φ-SO discovering the analytical expression of a damped harmonic oscillator.

433,091 просмотров • 2 лет назад

⚡F1 Car rear wing DRS activation - CFD simulation⚡ The drag reduction system (DRS) is a form of driver-adjustable bodywork aimed at reducing aerodynamic drag in order to increase top speed and promote overtaking. Simulation Owner: Luke Morgan

⚡F1 Car rear wing DRS activation - CFD simulation⚡ The drag reduction system (DRS) is a form of driver-adjustable bodywork aimed at reducing aerodynamic drag in order to increase top speed and promote overtaking. Simulation Owner: Luke Morgan

Jousef Murad | AI Automations & Agents

96,056 просмотров • 2 лет назад

💧 A Raindrop... but with 8 billion (!) Voxel resolution in 512GB memory across 8 GPUs 🤯 Great project by the smart @ProjectPhysX! Mini 🧵👇

💧 A Raindrop... but with 8 billion (!) Voxel resolution in 512GB memory across 8 GPUs 🤯 Great project by the smart @ProjectPhysX! Mini 🧵👇

29,792 просмотров • 3 лет назад

⚡Quadruple Pendulum⚡ A quadruple pendulum simulated with no friction. Since it is impossible to achieve that level of certainty, we cannot predict the motion of a pendulum.👇

⚡Quadruple Pendulum⚡ A quadruple pendulum simulated with no friction. Since it is impossible to achieve that level of certainty, we cannot predict the motion of a pendulum.👇

12,234 просмотров • 3 лет назад

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