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#GigaBerlinArt #TechPainters #RoboticMuralist.
At Tesla’s Gigafactory Berlin-Brandenburg, creativity meets technology in a remarkable initiative to transform concrete surfaces into stunning artworks. Inspired by Elon Musk’s vision to turn the factory into a canvas, the project began with local graffiti crews. However, the sheer scale of the endeavor required innovative solutions, leading to the collaboration with a robotic muralist startup. This groundbreaking graffiti printer combines cutting-edge technology with artistry, using a triangulation method to maneuver its print head along factory walls. With 12 paint cans onboard, the robot sprays precise dots of color—10 million per wall and 300 million for the west side alone—creating intricate designs composed of five distinct colors. The curated artworks draw inspiration from Berlin’s vibrant culture, Tesla’s groundbreaking products, and the factory itself—described as “the machine that builds the machine.” A blend of global and in-house artistic talent has contributed to the ongoing project, making Giga Berlin not just a hub for innovation but also a celebration of art and ingenuity.

Courtesy: X:@Tesla.

#FactoryArt #BerlinCulture #GigaBerlinTransformation #MachineThatBuildsTheMachine.

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Spin Hall nano-oscillators (SHNOs) are nanoscale spintronic devices that convert direct current into high-frequency microwave signals through spin wave auto-oscillations. This is a type of nonlinear magnetization oscillations that are self-sustained without the need for a periodic external force.

Theoretical and simulation studies found that propagating spin-wave modes, in which spin waves move across materials instead of being confined to the auto-oscillation region, can promote the coupling between SHNOs.

This coupling may in turn be harnessed to adjust the timing of oscillations in these devices, which could be advantageous for the development of neuromorphic computing systems and other spintronic devices.

Are you ready to be amazed by the incredible advancements in artificial intelligence? In 2024, AI has reached unprecedented heights, showcasing breakthroughs that are revolutionizing industries and reshaping our everyday lives. This video explores the top 9 AI breakthroughs you won’t believe are real, highlighting innovations that are both astonishing and game-changing.

From groundbreaking developments in natural language processing to cutting-edge applications in healthcare, transportation, and creative arts, we cover the most significant strides in AI technology. Discover how these breakthroughs are enhancing efficiency, improving decision-making, and creating new possibilities that were once thought to be science fiction.

But it’s not just about the technology; we’ll also discuss the implications of these advancements. As AI becomes more integrated into our lives, understanding the benefits and challenges it presents is essential. This video provides insights into how these breakthroughs could change the way we interact with machines and each other.

What are the top AI breakthroughs of 2024? How is AI changing the world? What innovations in AI should I know about? What are the latest advancements in artificial intelligence? How will AI impact our future?This video will answer all these questions. Make sure you watch till the end!

A research team from DGIST’s (President Kunwoo Lee) Division of Energy & Environmental Technology, led by Principal Researcher Kim Jae-hyun, has developed a lithium metal battery using a “triple-layer solid polymer electrolyte” that offers greatly enhanced fire safety and an extended lifespan. This research holds promise for diverse applications, including in electric vehicles and large-scale energy storage systems.

Conventional solid polymer electrolyte batteries perform poorly due to structural limitations which hinder an optimal electrode contact.

This could not eliminate the issue of “dendrites” either, where lithium grows in tree-like structures during repeated charging and discharging cycles.

We report the use of a multiagent generative artificial intelligence framework, the X-LoRA-Gemma large language model (LLM), to analyze, design and test molecular design. The X-LoRA-Gemma model, inspired by biological principles and featuring ~7 billion parameters, dynamically reconfigures its structure through a dual-pass inference strategy to enhance its problem-solving abilities across diverse scientific domains. The model is used to first identify molecular engineering targets through a systematic human-AI and AI-AI self-driving multi-agent approach to elucidate key targets for molecular optimization to improve interactions between molecules. Next, a multi-agent generative design process is used that includes rational steps, reasoning and autonomous knowledge extraction. Target properties of the molecule are identified either using a Principal Component Analysis (PCA) of key molecular properties or sampling from the distribution of known molecular properties. The model is then used to generate a large set of candidate molecules, which are analyzed via their molecular structure, charge distribution, and other features. We validate that as predicted, increased dipole moment and polarizability is indeed achieved in the designed molecules. We anticipate an increasing integration of these techniques into the molecular engineering workflow, ultimately enabling the development of innovative solutions to address a wide range of societal challenges. We conclude with a critical discussion of challenges and opportunities of the use of multi-agent generative AI for molecular engineering, analysis and design.