This NEW AI System SIMULATES REALITY (Genesis A.I Just Changed EVERYTHING!)

So today we got probably one of the craziest announcements this year that could truly change the future of robotics. This is the Genesis project. This is a revolutionary new tool that combines the creative power of generative AI with the accuracy of real world physics. Imagine being able to create virtual environments and train in a way that's not just realistic, but a way that is incredibly fast and, and efficient. That's exactly what Genesys does. Now, this project has been in development for two years, with over 20 research labs collaborating to make it a reality. The result is a powerful physics engine that can create dynamic four dimensional worlds. And these worlds are fully interactive and incredibly detailed, making them perfect for developing advanced robotics and applications in physical AI, which is a field of teaching machines to understand and interact with the physical world. Now, Genesis stands out because it's written in Python, a programming language that many people already know. And even so, it's shockingly fast. 10 to 80 times faster than the other high end tools that rely on powerful GPUs like Isaac Sim, Jim and MJX. For example, it can train a robot to walk in just 26 seconds using a single Nvidia RTX 4, which is an incredible achievement. Now, the speed isn't just for show. It's about making cutting edge technology available to more researchers and developers. Now, what's crazy about this is that this is actually open source. This means anyone can access this code and learn from it and use it to create their own projects. I think this is probably going to be one of the largest developments for robotics, because one of the main problems that we do have in terms of trying to advance robotics is the data collection issue. And collecting data for robotics is tedious because as you all know, many people currently use teleoperation. And this makes sense because you're interacting with the robot in a real physical world. And of course you can collect that data because you know exactly where the robot is, how it interacts with the world, and how the tasks are achieved successfully or unsuccessfully. But if we have something like this, which is a true physics simulation, something that is very accurate in terms of the one to one mapping of the physical world, then things are going to speed up at a ridiculous pace. And we've seen before with prior projects when we've used previous simulations like Nvidia's Isaac Sim or Nvidia's Isaac Gym, what that has done for the pace of robotics. So if this is something that is widely used and is remarkably more efficient than those other tools from Nvidia, then then this is going to be something that completely changes the game. And we all know companies and countries are really, really trying to work hard when it comes to robotics. So with something like this being embedded into the ecosystem of AI and robotics, we're probably going to see things explode overall. I mean, one of the things that we have to understand is that the real problem is not the humanoid robots platform. Humanoid robots are really successful at doing a variety of different tasks. The main problem is, of course, the autonomy and ensuring that we can get enough data to scale our efforts across the world. So this is going to be something that I think is going to be really fascinating, especially when we start seeing first use cases. Of course, right now this is something that they have just released. So it will be a little bit of time before we start to see the real world implications of this. I can imagine there are some developers probably already hacking away at their labs, figuring out the best ways and the best settings to get to grips with this kind of software. So for me, this is largely one of the craziest AI updates, robotics updates, because this has a wide range of applications that most of us simply cannot fathom. Before we get into all of the futuristic sci fi outcomes of this, let's take a look at how good this simulator is and some of the key features that differentiates it from any software that's existed before. Now. The Genesis project introduces a groundbreaking feature, a generative agent that can handle every step of teaching robots how to operate in realistic environments entirely on its own. First, it autonomously designs virtual environments that mimics real world spaces like kitchens, living rooms, and other everyday settings. Then it proposes the tasks for the robots to perform, such as opening a microwave, picking up objects, or navigating through furniture. But it doesn't stop there. It also creates the reward systems, which are like the incentives for robots, teaching them what success looks like. For instance, if a robot successfully opens a microwave, the system gives it a reward, helping it learn faster and better. And finally, it automates the entire process of writing robotic policies, which are the detailed instructions or strategies that guide how robots move, think, and interact with their environment. That means that robots don't just get trained, they become smarter and more capable of of handling complex tasks, all while developers and researchers save time and effort. And by combining these capabilities, Genesis sets a new standard for how robots learn and adapt to the physical world. Now, what's crazy about this physics engine that can simulate an incredibly diverse range of physical phenomena? This engine actually combines state of the art physics solvers like npm, Material Point Method, sph, Smooth particle hydrodynamics, FEM phase, finite element method, Rigid body dynamics, and pbd, among many others. And this makes it capable of realistically simulating virtually anything you can imagine, from rigid objects, to objects like metal, to soft deformables like cloth and rubber, to complex materials like liquid and smoke, and even elastic or plastic bodies. And it doesn't stop there. Genesis even supports advanced simulations for articulated systems like robot muscles and thin shell materials, which are crucial for robotics and physical AI. And what this means is that Genesis can simulate real world physics at an unprecedented level of detail and accuracy. Imagine being able to replicate how a piece of fabric moves in the wind, how liquids splash and flow, or how robot muscles stretch and contract, all in a virtual environment. These simulations are not just for show. They play a critical role in training AI models and robots to interact with the physical world in realistic ways ways. By bringing all of these physical capabilities into one unified engine, Genesis makes it easier for developers to research and create highly realistic simulations. Beyond its incredible ability to simulate rigid objects, liquids and deformable materials, Genesis also takes robotics to the next level by supporting soft robotics. This is a game changer, because soft robots, like those made to mimic muscles or organic movements, are notoriously difficult to simulate. Genesis bridges that gap. It's the first ever platform to provide full support for soft muscle simulations and soft robot interactions with rigid structures. What's even better is that Genesis includes a configuration system similar to urdf, which is commonly used in robotics. This makes it easier than ever to design, test and refine soft robotic systems in virtual environments. For example, you can simulate how a soft robot might crawl or interact with its surroundings, which has huge potential for industries like healthcare, search and rescue, and more. And if soft robotics wasn't impressive enough, Genesis continues to push the boundaries with its unparalleled computational capabilities. One standout feature is its GPU parallelized IK solver. Ik, or inverse kinematics, is a critical process in robotics that calculates the joint movements needed for a robotic arm to reach a specific target. Normally, this is computationally expensive and time consuming, especially when dealing with multiple robotic systems. But Genesis takes this to a whole new level. It can solve IK for an incredible 10,000 robotic arms, like the highly advanced Franke arms, simultaneously in under 2 milliseconds using a single RTX 4090. This level of speed and efficiency is unprecedented and opens up new possibilities for large scale robotics simulations, industrial automation, and complex research projects. With Genesis, the limits of what we thought was possible in robotics are being redefined. Another groundbreaking capability of Genesis is its support for native, non convex collision handling. This might sound technical, but it's a huge deal in the world of simulations. Instead of simpler terms, most physics engines struggle to handle collisions between objects with complex, irregular shapes like gears, chains, or any object that isn't smooth or simple. These shapes are called non convex, and accurately simulating their collisions requires advanced algorithms. Genesis tackles this challenge head on with built in support for these types of interactions. This means it can accurately simulate how irregularly shaped objects bump, slide, or even interlock with one another, all while maintaining physical realism. For example, if you're working on a robotic system that interacts with intricate machinery or components, Genesis ensures that every collision and movement behaves as it would in the real world. This capability makes Genesis a powerful tool for industries like manufacturing, robotics, and game development, where precise collision handling is crucial.