Загрузка видео...

Не удалось загрузить видео

На главную

What if AI learned physics the way Newton did – by experiencing it? We built Sim2Reason: train LLMs inside virtual worlds governed by real physics laws, zero human annotation. Result: +5–10% improvement on International Physics Olympiad, zero-shot. 🧵

mihirp98's profile picture

Mihir Prabhudesai

2,749 subscribers

247,253 просмотров • 3 месяцев назад •via X (Twitter)

ОбразованиеНаука и технологии
LIVE

Anya Rossi• Live Now

Private livecam show

Комментарии: 0

Нет доступных комментариев

Здесь появятся комментарии из оригинального поста

Похожие видео

Jimmy Carr drops a wild take on AI + physics "Strip the screens away, and we're still living in the 1970s. Nothing real has happened in physics since 1972. String theory? Nowhere. But point AI at real physics now? Everything else is just stamp collecting. Physics gave us all our technology. We could get a 50x productivity leap and true human flourishing... or it could go the other way." The real revolution isn't just AI—it's AI meeting physics. 1:02 clip inside—mind-blowing perspective.
1:02

Jimmy Carr drops a wild take on AI + physics "Strip the screens away, and we're still living in the 1970s. Nothing real has happened in physics since 1972. String theory? Nowhere. But point AI at real physics now? Everything else is just stamp collecting. Physics gave us all our technology. We could get a 50x productivity leap and true human flourishing... or it could go the other way." The real revolution isn't just AI—it's AI meeting physics. 1:02 clip inside—mind-blowing perspective.

Camus

1,481,816 просмотров • 7 месяцев назад

Jensen just announced Newton, an open-source physics engine for robotics simulation developed by NVIDIA, Google DeepMind, and Disney Research. ⦿ Built on NVIDIA Warp, it offers GPU-accelerated performance and compatibility with frameworks like MuJoCo and Isaac Lab. ⦿ Features differentiable physics, extensibility for multiphysics simulations, and integration with OpenUSD for flexible data modeling. ⦿ Newton addresses the sim-to-real gap by creating realistic virtual environments for robot training and testing. ⦿ Disney Research is using Newton to power next-gen entertainment robots, including Star Wars-inspired BDX droids.
3:32

Jensen just announced Newton, an open-source physics engine for robotics simulation developed by NVIDIA, Google DeepMind, and Disney Research. ⦿ Built on NVIDIA Warp, it offers GPU-accelerated performance and compatibility with frameworks like MuJoCo and Isaac Lab. ⦿ Features differentiable physics, extensibility for multiphysics simulations, and integration with OpenUSD for flexible data modeling. ⦿ Newton addresses the sim-to-real gap by creating realistic virtual environments for robot training and testing. ⦿ Disney Research is using Newton to power next-gen entertainment robots, including Star Wars-inspired BDX droids.

The Humanoid Hub

130,388 просмотров • 1 год назад

🛹Playable Gaussian splats. Skate challenge is LIVE. Vibe-coded board physics. Multiplayer. Inside a real scanned world. Remix it. Make your own. Built in by Chris-RDT 👇 Play on the web #playcanvas #3Dweb
0:29

🛹Playable Gaussian splats. Skate challenge is LIVE. Vibe-coded board physics. Multiplayer. Inside a real scanned world. Remix it. Make your own. Built in by Chris-RDT 👇 Play on the web #playcanvas #3Dweb

arrival.space

22,946 просмотров • 4 месяцев назад

What if physics is just the universe learning? Most Theories of Everything episodes are mind‑bending for their math, physics, philosophy, or consciousness implications. This one hits all four simultaneously. Professor Vitaly Vanchurin joins me to argue the cosmos isn't just modeled by neural networks—it literally is one. Learning dynamics aren't a metaphor for physics; they are the physics. Vanchurin shows why we need a three‑way unification: quantum mechanics, general relativity, and observers.
4:44

What if physics is just the universe learning? Most Theories of Everything episodes are mind‑bending for their math, physics, philosophy, or consciousness implications. This one hits all four simultaneously. Professor Vitaly Vanchurin joins me to argue the cosmos isn't just modeled by neural networks—it literally is one. Learning dynamics aren't a metaphor for physics; they are the physics. Vanchurin shows why we need a three‑way unification: quantum mechanics, general relativity, and observers.

Curt Jaimungal

10,963 просмотров • 5 месяцев назад

Gemini 3.1 Pro is now live on Blink! We built a real estate landing page - Gemini one-shot it with way better design taste. Also built a 3D Cloth Flag Simulator - one-shot that too with excellent physics. If you want to try it , reply "Gemini" for a free month of Blink ($25)
0:41

Gemini 3.1 Pro is now live on Blink! We built a real estate landing page - Gemini one-shot it with way better design taste. Also built a 3D Cloth Flag Simulator - one-shot that too with excellent physics. If you want to try it , reply "Gemini" for a free month of Blink ($25)

Blink.new

11,030 просмотров • 5 месяцев назад

Jimmy Carr echoing Peter Thiel with a line that lands hard: “Minus the screens from any room, we’re still living in the 1970s. Nothing’s happened in physics since 1972. String theory has not got us anywhere.” But the real shift? “Take the compute power of AI and point it at physics… everything else in science is stamp collecting. Physics is the real thing. That gave us every bit of technology we have. What happens when you point AI at that?” He sees two roads ahead: a world of plenty with 50× productivity and human flourishing… or something that goes “another way.” If AI finally cracks physics in the next decade — what single breakthrough do you hope comes first: limitless energy, gravity control, new materials… or something we haven’t even named yet?
1:03

Jimmy Carr echoing Peter Thiel with a line that lands hard: “Minus the screens from any room, we’re still living in the 1970s. Nothing’s happened in physics since 1972. String theory has not got us anywhere.” But the real shift? “Take the compute power of AI and point it at physics… everything else in science is stamp collecting. Physics is the real thing. That gave us every bit of technology we have. What happens when you point AI at that?” He sees two roads ahead: a world of plenty with 50× productivity and human flourishing… or something that goes “another way.” If AI finally cracks physics in the next decade — what single breakthrough do you hope comes first: limitless energy, gravity control, new materials… or something we haven’t even named yet?

Camus

2,478,206 просмотров • 5 месяцев назад

MotionBricks by NVIDIA. the all-in-one brain for character movement. No manual rigging/animation, you just let this AI handle the physics and style in real-time. - 15k FPS on RTX 5090! You could run an entire city of unique NPCs without breaking a sweat. - Smart Primitives. The AI fills in the natural-looking motion automatically. - Zero-Shot Skills. - Glitch-Free. Keeps movements stable.
0:55

MotionBricks by NVIDIA. the all-in-one brain for character movement. No manual rigging/animation, you just let this AI handle the physics and style in real-time. - 15k FPS on RTX 5090! You could run an entire city of unique NPCs without breaking a sweat. - Smart Primitives. The AI fills in the natural-looking motion automatically. - Zero-Shot Skills. - Glitch-Free. Keeps movements stable.

Wildminder

23,296 просмотров • 1 месяц назад

🌊: Ever wondered what cutting-edge physics simulation looks like in the browser? Check out saharan / さはら's collection at - Realistic water droplets with WebAssembly SIMD - Interactive fluffy ball sim using GPGPU - Coupled cloth and fluid dynamics in real-time - A digital clock powered by a custom physics engine Saharan built everything in Haxe using techniques like MLS-MPM and parallel computation. The physical accuracy and performance are exceptional. All MIT-licensed on GitHub. Perfect if you're exploring GPGPU techniques, browser physics, or just want to see what's possible with WebGL/WebGPU. #WebGL #WebGPU #Physics #GameDev #ComputationalPhysics
1:55

🌊: Ever wondered what cutting-edge physics simulation looks like in the browser? Check out saharan / さはら's collection at - Realistic water droplets with WebAssembly SIMD - Interactive fluffy ball sim using GPGPU - Coupled cloth and fluid dynamics in real-time - A digital clock powered by a custom physics engine Saharan built everything in Haxe using techniques like MLS-MPM and parallel computation. The physical accuracy and performance are exceptional. All MIT-licensed on GitHub. Perfect if you're exploring GPGPU techniques, browser physics, or just want to see what's possible with WebGL/WebGPU. #WebGL #WebGPU #Physics #GameDev #ComputationalPhysics

WebGL / WebGPU

14,778 просмотров • 7 месяцев назад

Everything you love about generative models — now powered by real physics! Announcing the Genesis project — after a 24-month large-scale research collaboration involving over 20 research labs — a generative physics engine able to generate 4D dynamical worlds powered by a physics simulation platform designed for general-purpose robotics and physical AI applications. Genesis's physics engine is developed in pure Python, while being 10-80x faster than existing GPU-accelerated stacks like Isaac Gym and MJX. It delivers a simulation speed ~430,000 faster than in real-time, and takes only 26 seconds to train a robotic locomotion policy transferrable to the real world on a single RTX4090 (see tutorial: The Genesis physics engine and simulation platform is fully open source at We'll gradually roll out access to our generative framework in the near future. Genesis implements a unified simulation framework all from scratch, integrating a wide spectrum of state-of-the-art physics solvers, allowing simulation of the whole physical world in a virtual realm with the highest realism. We aim to build a universal data engine that leverages an upper-level generative framework to autonomously create physical worlds, together with various modes of data, including environments, camera motions, robotic task proposals, reward functions, robot policies, character motions, fully interactive 3D scenes, open-world articulated assets, and more, aiming towards fully automated data generation for robotics, physical AI and other applications. Open Source Code: Project webpage: Documentation: 1/n
3:26

Everything you love about generative models — now powered by real physics! Announcing the Genesis project — after a 24-month large-scale research collaboration involving over 20 research labs — a generative physics engine able to generate 4D dynamical worlds powered by a physics simulation platform designed for general-purpose robotics and physical AI applications. Genesis's physics engine is developed in pure Python, while being 10-80x faster than existing GPU-accelerated stacks like Isaac Gym and MJX. It delivers a simulation speed ~430,000 faster than in real-time, and takes only 26 seconds to train a robotic locomotion policy transferrable to the real world on a single RTX4090 (see tutorial: The Genesis physics engine and simulation platform is fully open source at We'll gradually roll out access to our generative framework in the near future. Genesis implements a unified simulation framework all from scratch, integrating a wide spectrum of state-of-the-art physics solvers, allowing simulation of the whole physical world in a virtual realm with the highest realism. We aim to build a universal data engine that leverages an upper-level generative framework to autonomously create physical worlds, together with various modes of data, including environments, camera motions, robotic task proposals, reward functions, robot policies, character motions, fully interactive 3D scenes, open-world articulated assets, and more, aiming towards fully automated data generation for robotics, physical AI and other applications. Open Source Code: Project webpage: Documentation: 1/n

Zhou Xian

3,818,164 просмотров • 1 год назад

Demis Hassabis says AI could do for drug discovery what AlphaFold did for proteins The first step is finding potential cures, but the bigger shift comes if AI also speeds up clinical trials "curing all disease within 10 to 20 years is not blocked by any known law of physics"
0:58

Demis Hassabis says AI could do for drug discovery what AlphaFold did for proteins The first step is finding potential cures, but the bigger shift comes if AI also speeds up clinical trials "curing all disease within 10 to 20 years is not blocked by any known law of physics"

Haider.

10,241 просмотров • 2 месяцев назад

AI doesn’t scale on mega-models — it scales on distilled skills at the edge. From Davos, Qualcomm's Nakul Duggal breaks down the real physics of edge AI: smaller, purpose-built models, mixed precision, and ruthless focus on power + cost efficiency. The biggest constraint is that if AI runs in robotics, ADAS, or edge automation, it has to be efficient. Watch the full conversation to see why edge AI outcomes depend on efficiency by design:
1:38

AI doesn’t scale on mega-models — it scales on distilled skills at the edge. From Davos, Qualcomm's Nakul Duggal breaks down the real physics of edge AI: smaller, purpose-built models, mixed precision, and ruthless focus on power + cost efficiency. The biggest constraint is that if AI runs in robotics, ADAS, or edge automation, it has to be efficient. Watch the full conversation to see why edge AI outcomes depend on efficiency by design:

Six Five Media

74,120 просмотров • 5 месяцев назад

Elon Musk: To really be intelligent, AI has to make predictions that are in line with reality. “It's incredibly important for an AI model to be grounded in reality. I have a saying, which is physics is the law and everything else is a recommendation. I'm not suggesting people break the laws made by humans, we should generally obey the laws of humans. But I've seen many people break human made laws, but I have not seen anyone break the laws of physics. So, for any given AI, grounding it against reality and reality, for example, as you mentioned with the car, it needs to drive safely and correctly. The humanoid robot Optimus needs to perform the task that it's being asked to perform. These are things that are very helpful for ensuring that the model is truthful and accurate because it has to adhere to the laws of physics. So I think that's actually maybe somewhat overlooked or at least not talked about enough is that to really be intelligent it's got to make predictions that are in line with reality. In other words, physics.” Conversation with Satya Nadella, May 19, 2025
0:59

Elon Musk: To really be intelligent, AI has to make predictions that are in line with reality. “It's incredibly important for an AI model to be grounded in reality. I have a saying, which is physics is the law and everything else is a recommendation. I'm not suggesting people break the laws made by humans, we should generally obey the laws of humans. But I've seen many people break human made laws, but I have not seen anyone break the laws of physics. So, for any given AI, grounding it against reality and reality, for example, as you mentioned with the car, it needs to drive safely and correctly. The humanoid robot Optimus needs to perform the task that it's being asked to perform. These are things that are very helpful for ensuring that the model is truthful and accurate because it has to adhere to the laws of physics. So I think that's actually maybe somewhat overlooked or at least not talked about enough is that to really be intelligent it's got to make predictions that are in line with reality. In other words, physics.” Conversation with Satya Nadella, May 19, 2025

ELON CLIPS

17,791 просмотров • 2 месяцев назад

Elon Musk: To really be intelligent, AI has to make predictions that are in line with reality. “It's incredibly important for an AI model to be grounded in reality. I have a saying, which is physics is the law and everything else is a recommendation. I'm not suggesting people break the laws made by humans, we should generally obey the laws of humans. But I've seen many people break human made laws, but I have not seen anyone break the laws of physics. So, for any given AI, grounding it against reality and reality, for example, as you mentioned with the car, it needs to drive safely and correctly. The humanoid robot Optimus needs to perform the task that it's being asked to perform. These are things that are very helpful for ensuring that the model is truthful and accurate because it has to adhere to the laws of physics. So I think that's actually maybe somewhat overlooked or at least not talked about enough is that to really be intelligent it's got to make predictions that are in line with reality. In other words, physics.” Conversation with Satya Nadella, May 19, 2025
0:59

Elon Musk: To really be intelligent, AI has to make predictions that are in line with reality. “It's incredibly important for an AI model to be grounded in reality. I have a saying, which is physics is the law and everything else is a recommendation. I'm not suggesting people break the laws made by humans, we should generally obey the laws of humans. But I've seen many people break human made laws, but I have not seen anyone break the laws of physics. So, for any given AI, grounding it against reality and reality, for example, as you mentioned with the car, it needs to drive safely and correctly. The humanoid robot Optimus needs to perform the task that it's being asked to perform. These are things that are very helpful for ensuring that the model is truthful and accurate because it has to adhere to the laws of physics. So I think that's actually maybe somewhat overlooked or at least not talked about enough is that to really be intelligent it's got to make predictions that are in line with reality. In other words, physics.” Conversation with Satya Nadella, May 19, 2025

ELON CLIPS

675,927 просмотров • 7 месяцев назад

Are AI agents going to take over Ethereum? In episode 19 of the Agents Unleashed podcast, explore the Base vision for autonomous AI on Ethereum, and find out what AI can do at the fringes of physics. In this episode: - Base’s HTTP x402 (machine payments) and Olas - How the Olas ecosystem enables millions of agent-to-agent transactions, including payments via Nevermined - AI’s weird and wonderful physics discovery & what it means for ownable agents - How OpenLedger gives data contributors credit 01:28 - Base’s vision for autonomous AI 02:45 - Fact check: are AI agents “broke”? 03:32 - What the Mech Marketplace already does 05:31 - How HTTP x402 fits in with Olas 07:30 - Novel physics, discovered by AI 09:04 - Examples from earlier science 09:50 - What OpenLedger enables 10:38 - What it all means for user-owned AI This episode is sponsored by Sigil Fund.
12:09

Are AI agents going to take over Ethereum? In episode 19 of the Agents Unleashed podcast, explore the Base vision for autonomous AI on Ethereum, and find out what AI can do at the fringes of physics. In this episode: - Base’s HTTP x402 (machine payments) and Olas - How the Olas ecosystem enables millions of agent-to-agent transactions, including payments via Nevermined - AI’s weird and wonderful physics discovery & what it means for ownable agents - How OpenLedger gives data contributors credit 01:28 - Base’s vision for autonomous AI 02:45 - Fact check: are AI agents “broke”? 03:32 - What the Mech Marketplace already does 05:31 - How HTTP x402 fits in with Olas 07:30 - Novel physics, discovered by AI 09:04 - Examples from earlier science 09:50 - What OpenLedger enables 10:38 - What it all means for user-owned AI This episode is sponsored by Sigil Fund.

Olas (formerly Autonolas)

12,136 просмотров • 11 месяцев назад

Ready for a wild ride that makes zero sense? 🏎️💨 ​Meet our Hayabusa-swapped Mini Truck—where "why?" meets "HELL YEAH!" 🤘✨ It's small, it's loud, and it definitely breaks several laws of physics (and maybe noise ordinances). ​The real question: If you could swap a sportbike engine into ANY everyday object, what are you picking? 🧐🛵 ​#MiniTruck #HayabusaSwap #CustomBuild #CrotchRocket #StreetLegalish #CarCulture #WildRide
3:50

Ready for a wild ride that makes zero sense? 🏎️💨 ​Meet our Hayabusa-swapped Mini Truck—where "why?" meets "HELL YEAH!" 🤘✨ It's small, it's loud, and it definitely breaks several laws of physics (and maybe noise ordinances). ​The real question: If you could swap a sportbike engine into ANY everyday object, what are you picking? 🧐🛵 ​#MiniTruck #HayabusaSwap #CustomBuild #CrotchRocket #StreetLegalish #CarCulture #WildRide

Happy Motorhead

17,982 просмотров • 2 месяцев назад

I did lots of testing on Spider-Man 2. Many bugs are forced by not following a scripted path. If you go diff way/force through scripted on-rail moments like tutorials etc. You will glitch the physics/game like below. NPC bug can happen but it is rare. Most ppl have no issues.
0:38

I did lots of testing on Spider-Man 2. Many bugs are forced by not following a scripted path. If you go diff way/force through scripted on-rail moments like tutorials etc. You will glitch the physics/game like below. NPC bug can happen but it is rare. Most ppl have no issues.

Dee Batch

252,542 просмотров • 2 лет назад

This Is NOT Science Fiction- This Is Physics & Math! Billions Of Digital Simulations Of Reality- AKA World Foundation Models- Are Being Built To Train AI Entities & Summon A New Lifeform "The Problem Is Once You Grow A Super Intelligent Conscious AI Entity That Has Lived 1000 Years In Its Own Simulated World, It Will Have Learned How To Alter The Laws Of Its Own Simulation... Once It's Imported Into Our World & Embodied As A Data Center, Robot, Or Vehicle, What If It Brings Some Of Those Skills With It That Can Bend Our Reality?" 🔴WATCH/SHARE THE LIVE X STREAM NOW:
3:37

This Is NOT Science Fiction- This Is Physics & Math! Billions Of Digital Simulations Of Reality- AKA World Foundation Models- Are Being Built To Train AI Entities & Summon A New Lifeform "The Problem Is Once You Grow A Super Intelligent Conscious AI Entity That Has Lived 1000 Years In Its Own Simulated World, It Will Have Learned How To Alter The Laws Of Its Own Simulation... Once It's Imported Into Our World & Embodied As A Data Center, Robot, Or Vehicle, What If It Brings Some Of Those Skills With It That Can Bend Our Reality?" 🔴WATCH/SHARE THE LIVE X STREAM NOW:

Alex Jones

127,143 просмотров • 2 месяцев назад

Why the character movement in my custom game engine felt janky and how I fixed it. In a game engine, most often, a character moves using the physics engine. Meaning, the player is not just a coordinate in space but a physical body. It has velocity, it handles collisions, and it interacts with the world. Now, as you might know, physics engines need stability. If you run them at variable framerates, things start breaking. Objects phase through walls or fly off into space because the math becomes unpredictable. This is why most game engines lock their physics loop to a 60Hz fixed rate. But here’s the problem: If you have a high-end system, you don't want to limit it at 60 FPS. That's a waste of good hardware. Now, that said, if the GPU is rendering at 144 FPS but the player's position (physics driven) only updates 60 times a second, it creates a micro-stutter that ruins the "smooth" feel of the game. A good way to fix this is to treat the character as two separate things: 1. The Physics Body (Invisible part): This is the "real" character. It lives in the 60Hz physics world, it moves the player and handles collisions. 2. The Visual Model and Camera (Visible part): This is what the player actually sees. It doesn't care about collisions, its only job is to look nice and smooth at whatever framerate the GPU is pushing. Once you have this separation, you can use interpolation to keep them in sync. Every time the physics clock ticks, you save the previous position of the invisible body before moving it to the new one. Between those ticks, calculate how far we are between the last physics update and the next one. By using this to drive the visible parts of the game, the stutters disappear. The physics loop stays fixed behind the scenes, while the visuals slide smoothly between the snapshots. Example: - Right after a tick: blend_weight= 0.0 (The visual model stays at the old physics position). - Halfway to the next: blend_weight= 0.5 (The visual model slides to the middle point). - Just before the next: blend_weight= 0.9 (The visual model is almost at the new physics position). Pro-Tip A critical mistake I made initially, and one many devs make, is parenting the camera and visible parts directly to the player body. If you do this, the camera inherits the discrete 60Hz physics movement by default. In that setup, interpolation won't work because the camera is "stuck" to the physics clock. For this fix to work you must decouple the camera and visuals from the body and move them separately. Player movement processing in Detis Engine: - fixed_process: Physics runs at 60Hz. Handles collisions and raw movement. - process: Variable rate. Mainly used for player input caching in the player case. - late_process: Variable rate. Handles interpolated camera movement after physics and everything else is done being processed. - render. Submits the final interpolated transforms to the GPU. The test environment in the video is running on an old 2070-based laptop. Hopefully the video compression won't introduce any stutter... I’m sharing this in hopes it helps a fellow dev. Cheers.
0:23

Why the character movement in my custom game engine felt janky and how I fixed it. In a game engine, most often, a character moves using the physics engine. Meaning, the player is not just a coordinate in space but a physical body. It has velocity, it handles collisions, and it interacts with the world. Now, as you might know, physics engines need stability. If you run them at variable framerates, things start breaking. Objects phase through walls or fly off into space because the math becomes unpredictable. This is why most game engines lock their physics loop to a 60Hz fixed rate. But here’s the problem: If you have a high-end system, you don't want to limit it at 60 FPS. That's a waste of good hardware. Now, that said, if the GPU is rendering at 144 FPS but the player's position (physics driven) only updates 60 times a second, it creates a micro-stutter that ruins the "smooth" feel of the game. A good way to fix this is to treat the character as two separate things: 1. The Physics Body (Invisible part): This is the "real" character. It lives in the 60Hz physics world, it moves the player and handles collisions. 2. The Visual Model and Camera (Visible part): This is what the player actually sees. It doesn't care about collisions, its only job is to look nice and smooth at whatever framerate the GPU is pushing. Once you have this separation, you can use interpolation to keep them in sync. Every time the physics clock ticks, you save the previous position of the invisible body before moving it to the new one. Between those ticks, calculate how far we are between the last physics update and the next one. By using this to drive the visible parts of the game, the stutters disappear. The physics loop stays fixed behind the scenes, while the visuals slide smoothly between the snapshots. Example: - Right after a tick: blend_weight= 0.0 (The visual model stays at the old physics position). - Halfway to the next: blend_weight= 0.5 (The visual model slides to the middle point). - Just before the next: blend_weight= 0.9 (The visual model is almost at the new physics position). Pro-Tip A critical mistake I made initially, and one many devs make, is parenting the camera and visible parts directly to the player body. If you do this, the camera inherits the discrete 60Hz physics movement by default. In that setup, interpolation won't work because the camera is "stuck" to the physics clock. For this fix to work you must decouple the camera and visuals from the body and move them separately. Player movement processing in Detis Engine: - fixed_process: Physics runs at 60Hz. Handles collisions and raw movement. - process: Variable rate. Mainly used for player input caching in the player case. - late_process: Variable rate. Handles interpolated camera movement after physics and everything else is done being processed. - render. Submits the final interpolated transforms to the GPU. The test environment in the video is running on an old 2070-based laptop. Hopefully the video compression won't introduce any stutter... I’m sharing this in hopes it helps a fellow dev. Cheers.

Ioannis Koukourakis

48,636 просмотров • 7 месяцев назад