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MatterSim is expanding what AI can do for materials science—from faster large-scale simulations to MatterSim-MT, a new multi-task model for simulating properties beyond potential energy surfaces alone.

Microsoft Research

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14,723 次观看 • 4 个月前 •via X (Twitter)

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AI is a massive unlock for medicine because once you can simulate cells/human biology you can fast track cures for almost all diseases. Precision medicine becomes real. But if we can simulate cells then we are not far off from simulating the world Are we going to be running simulations within simulation? How many simulations deep are we?

AI is a massive unlock for medicine because once you can simulate cells/human biology you can fast track cures for almost all diseases. Precision medicine becomes real. But if we can simulate cells then we are not far off from simulating the world Are we going to be running simulations within simulation? How many simulations deep are we?

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NEWS: Waymo has introduced the Waymo World Model, "a frontier generative model built on Google DeepMind’s Genie 3 that sets a new bar for large-scale, hyper-realistic autonomous driving simulation." "By simulating the “impossible”, we proactively prepare the Waymo Driver for some of the most rare and complex scenarios—from tornadoes to planes landing on freeways—long before it encounters them in the real world. The model’s architecture offers high controllability, allowing our engineers to modify simulations with simple language prompts, driving inputs, and scene layouts. Notably, the Waymo World Model generates high-fidelity, multi-sensor outputs that include both camera and lidar data. This combination of broad world knowledge, fine-grained controllability, and multi-modal realism enhances Waymo’s ability to safely scale our service across more places and new driving environments. In the following sections we showcase the Waymo World Model in action, featuring simulations of the Waymo Driver navigating diverse rare edge-case scenarios." More info below.

NEWS: Waymo has introduced the Waymo World Model, "a frontier generative model built on Google DeepMind’s Genie 3 that sets a new bar for large-scale, hyper-realistic autonomous driving simulation." "By simulating the “impossible”, we proactively prepare the Waymo Driver for some of the most rare and complex scenarios—from tornadoes to planes landing on freeways—long before it encounters them in the real world. The model’s architecture offers high controllability, allowing our engineers to modify simulations with simple language prompts, driving inputs, and scene layouts. Notably, the Waymo World Model generates high-fidelity, multi-sensor outputs that include both camera and lidar data. This combination of broad world knowledge, fine-grained controllability, and multi-modal realism enhances Waymo’s ability to safely scale our service across more places and new driving environments. In the following sections we showcase the Waymo World Model in action, featuring simulations of the Waymo Driver navigating diverse rare edge-case scenarios." More info below.

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I’m pleased to join the new Mayors AI Forum, bringing together 10 cities from across the globe here in Madrid. AI offers enormous potential. Our task is to ensure it works for everyone.

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We trained a graph-native AI, then let it reason for days, forming a dynamic relational world model on its own - no pre-programming. Emergent hubs, small-world properties, modularity, & scale-free structures arose naturally. The model then exploited compositional reasoning & uncovered uncoded properties from deep synthesis: Materials with memory, microbial repair, self-evolving systems. Video shows it unfolding, made with Grok xAI.

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Elon on why the Moon is the key bridge to becoming multi-planetary: “We can build a self-growing city on the Moon faster than Mars. No atmosphere + 1/6th gravity = perfect for railguns/mass drivers to launch AI data centers into deep space using Moon materials. Could scale to 1,000+ terawatts of space-based AI compute. Plus… Moon vacations would be epic.” Visionary stuff from Elon🔥 Source: J.P. Morgan

Elon on why the Moon is the key bridge to becoming multi-planetary: “We can build a self-growing city on the Moon faster than Mars. No atmosphere + 1/6th gravity = perfect for railguns/mass drivers to launch AI data centers into deep space using Moon materials. Could scale to 1,000+ terawatts of space-based AI compute. Plus… Moon vacations would be epic.” Visionary stuff from Elon🔥 Source: J.P. Morgan

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Announcing the newest releases from Meta FAIR. We’re releasing new groundbreaking models, benchmarks, and datasets that will transform the way researchers approach molecular property prediction, language processing, and neuroscience. 1️⃣ Open Molecules 2025 (OMol25): A dataset for molecular discovery with simulations of large atomic systems. 2️⃣ Universal Model for Atoms: A machine learning interatomic potential for modeling atom interactions across a wide range of materials and molecules. 3️⃣ Adjoint Sampling: A scalable algorithm for training generative models based on scalar rewards. 4️⃣ FAIR and the Rothschild Foundation Hospital partnered on a large-scale study that reveals striking parallels between language development in humans and LLMs. Read more ➡️

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How sophisticated is the maths in AI? Go on, have a guess. Because guessing is what AI itself would do. Terry Tao introduces his Oxford Mathematics London Lecture, a journey through the potential for AI in science & maths. Watch from 5pm BST, Wed 7 August:

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ELON MUSK: Kardashev-Scale civilization will need Moon Bases and Mass Drivers. To reach a Kardashev-scale future for AI, humanity need space-based infrastructure including Moon bases, mass drivers, and large-scale solar power systems. Future AI may require energy at a scale far beyond what Earth can easily support. Solar-powered AI satellites launched from Earth could potentially generate terawatt-level power, but would require around 10 million tons of payload to orbit every year. That level of infrastructure could produce around twice the annual electricity use of the United States for AI power. The idea is not limited by physics; the real challenge is building at a massive enough scale. Lunar infrastructure could unlock petawatt-scale solar-powered AI, making Earth’s current economy look small by comparison.

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Elon Musk on building a self-growing city on the Moon: "You don't necessarily have to go through the moon to get to Mars. We can build a self-growing city on the moon faster than we could do so on Mars, and there's also the potential, if you say you want to scale far beyond what you can do from Earth, is that because the moon has no atmosphere and about 1/6 Earth's gravity, you can use an electromagnetic accelerator, a rail gun or mass driver, basically you don't need to use rockets to do AI data centers into deep space from the moon, you can literally just shoot them like a, like a rail gun type of thing, and and you can manufacture the solar, the solar and the radiators, solar power and radiators on the moon from moon materials that would allow scaling potentially to beyond 1000 terawatts a year, which is a truly staggering number. I think we can do probably do somewhere around one terawatt per year of AI space compute from Earth, but we can do 1000 terawatts or more from the moon."

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