How can we accelerate the journey of finding better #battery materials? The answer is found in the Molecular Universe. Learn more from Qichao Hu (胡启朝) at the #IMLB conference tomorrow. #AI4Science #Materialscience #AI #LiMetal #Battery #Crowdsource
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10^11, the number of people that have ever lived on planet earth, their data led to the training and development of chatgpt, and eventually to AGI 10^11, is also the number of small molecules that could be used for batteries, if we map their molecular properties and train our AI for Science models, imagine what that would lead to. (hint, we only mapped 10^3 so far, and that already led to smart phones, laptops, and EVs) Molecular Universe SES AI Corp
How can we accelerate the journey of finding better #battery materials? The answer is found in the Molecular Universe. Learn more from Qichao Hu (胡启朝) at the #IMLB conference tomorrow. #AI4Science #Materialscience #AI #LiMetal #Battery #Crowdsource
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I help executives & SMBs leverage AI to streamline their business workflows & digital marketing strategies. Get in touch to learn how to boost sales, increase efficiency & spark creativity 🚀
Massive step towards the dream of stable fusion energy production, thanks to AI. I've always wondered how abundant free energy will alter the geopolitical landscape. "Princeton Engineering - Engineers use AI to wrangle fusion power for the grid" The article discusses how AI can predict and avoid instabilities in plasma, which is a major challenge in fusion research. The researchers used a technique called deep reinforcement learning to train the AI on data from past experiments. The AI was able to successfully predict and avoid instabilities in real-time experiments. This is a promising step forward in the development of fusion power. https://buff.ly/42P4puN
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#PARTICUOLOGY Special Issue Article✨ NeuroPNM: Model reduction of pore network models using neural networks (Open Access) Robert Jendersie, Ali Mjalled, Xiang Lu, Lucas Reineking, Reza Kharaghani*, Martin Mönnigmann*, Christian Lessig* https://lnkd.in/eKU6BUvu Reacting particle systems play an important role in many industrial applications, for example, biomass drying end the manufacturing of pharmaceuticals. The numerical modeling and simulation of such systems is of great importance for an efficient, reliable, and environmentally sustainable operation of the processes. The complex thermodynamical, chemical, and flow processes that take place in the particles are a particular challenge in the simulation. One approach for overcoming this challenge is to compute effective physical parameters from single-particle, high-resolution simulations. This can be combined with model reduction methods if the dynamical behavior of particles must be captured. Pore network models (#PNM) with their unrivaled resolution have thereby been used successfully as high-resolution models, for instance to obtain the macroscopic diffusion coefficient of drying. This article reports the results on the use of #neural #networks for parameter identification and model reduction based on three-dimensional pore network models. The results provide a powerful complement to existing methodologies for reactor-level simulations with many thermally-thick particles. This article is published in the special issue “1st International Workshop on Reactive Particle-Gas Systems--Special issue organized by the Collaborative Research Centre BULK-REACTION”, which was edited by Prof. Viktor Scherer and Prof. Francesca Di Mare from Ruhr University Bochum, and Prof. Dominiquen Thévenin and Prof. Evangelos Tsotsas from Otto-von-Guericke University Magdeburg. https://lnkd.in/gQhZ8wba More detailed in Chinese can be found on WeChat: https://lnkd.in/euni9GdZ #PoreNetworkModels #NeuralNetworks #ParameterEstimation #ReducedOrderModel
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Unlocking Limitless Clean Energy: When Human Ingenuity Meets Artificial Intelligence. 🔬💡 Researchers at Princeton Plasma Physics Laboratory have harnessed the power of AI to improve control over fusion reactions, which could potentially solve our energy problems. Advances include perfect vessel design for super-hot plasma, optimized heating methods, and stable control of fusion reactions. The triumph of technology is a testament to the power of the human mind coupled with artificial intelligence. Consider this - if we can successfully harness fusion energy, we naturally ask, what could be next? What other monumental challenges can we overcome by combining our ingenuity with the power of AI? #AI #CleanEnergy https://lnkd.in/eAzXJTUm
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QAI harnesses quantum physics, boosting AI's speed and unlocking game-changing solutions in fields like medicine, materials, and more. I t's a transformative leap for AI's future. . . . #QuantumAI #FutureofAI #QAIRevolution #GameChanger #QuantumSupremacy #PostQuantumWorld⏳ #QuantumEthics⚖️ #GetReadyForQAI #TheFutureIsQuantum
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My second not quite book recommendation this week is Mustafa Suleyman's The Coming Wave, written by one of the co-founders of DeepMind, and chosen by the FT as one of its Business Books of the Year. It is an impressive tour d'horizon of the epic technological changes we are facing and their interactions with government and society. Suleyman takes in the latest developments in generative AI; advanced robotics; gene editing; quantum computing and more besides. He speaks passionately about the life-, indeed species-changing disruption this is going to bring, governments' inability to be honest about the scale of that disruption. In general, Suleyman is a techno-optimist, but he is also realistic about the winners and losers. His thesis is that big companies will dwarf governments; democratic governments will become yet more unstable; and authoritarian regimes will be strengthened. In general, fragility will increase, our current lifestyles cannot be maintained, and most of us will be out of a job. Suleyman offers a neat ten potential solutions to the threat of AI, including an aspiration toward containment of the technology through supra-national co-operation. Just as the UN was in some ways built to contain nuclear power, it must now pivot to contain AI. These suggestions came in his final chapter and were not wholly convincing. Indeed, he spends so much of the book arguing how hard it is to contain technology it is scarcely credible that he believes his own recommendations. As I said, this book works as a summary of the major issues facing us. I didn't learn anything particularly new and it didn't change my thinking on the topic at all. This is partly because the FT has been recommending so many great books over the past couple of years that deep dive into each of the individual topics that I found this one rather superficial. So, it works an executive summary. But the interested reader will probably want more, or have already read more. #bookrecommendation #bookreview #generativeai
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Did you hear about the "Graph Networks for Materials Exploration", or GNoME for short, deep learning tool published by Google DeepMind this week? The #GNoME tool has discovered no less than 2.2 million new inorganic crystals, and identified 380,000 of them as the most stable, giving researchers a pre-filtered list of new materials to go away and synthesize for experimental research. Some 736 of them have already been created independently in research labs around the world. Among these candidates are materials that have the potential to develop future transformative technologies ranging from #superconductors, powering #supercomputers, and next-generation batteries to boost the efficiency of electric vehicles. To put it into context.. This discovery of materials would be equivalent to about 800 years’ worth of knowledge and demonstrates an unprecedented scale and level of accuracy in predictions. As always, link to blog and research papers are in the comments below! #DeepMind #GoogleDeepMind
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https://lnkd.in/dFV6xFky GRATE TECHNOLOGICAL STRATEGY TURN Quantum AI is a cutting-edge system that combines quantum computing and artificial intelligence to analyze financial data and predict market trends. It breaks down complex data into smaller parts and then uses advanced algorithms to find patterns and trends. GENETICALLY QUANTUM COMPUTING ORIGINATES QUAMTUM +AI + AGI = ASI GRATE
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|Solution Architect-SAP S/4 OTC,BTP |Quantum Computing's |AI/ML |Quantum Advisory-Govt Org|| EB1A "Einstein Visa" Recipient |CENG(I)|TOGAF|FBCS|FIETE |AAAS|FICS|FRSS|SMIEEE|(Lets Adopt Smart Technologies to Human Lives).
Life is short, and we are not a legacy to rule over. Why do we have such foolish attachments to "earthen pots—the bodies composed of earthly elements"? Therefore, refrain from pursuing this path, as you must seek "Yogic Salvations" with Lord Shiva—"The infinite limitless in earth." After devoting a significant amount (since childhood) of time to studying the epics of Shiva Puranam, an innovative idea emerged, leading to the filing of a patent for the treatment of incurable diseases, under the heading "Vedic quantum computing and AI impactful for mankind." #cureble#everything is cureble#vedic quantum# quantum computings#time-travel is needed for mankind #Love all# serve all formankind#AI#ML#QAI#QML#omm namo shivayam#amen#
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In this work, we present how the convolutional neural networks (#CNN) machine learning method can predict the bandgap and the absorption quality of perovskite thin films. This can help to speed up time consuming material optimizations by reducing lab time spent on recurrent characterization. "Optoelectronic perovskite film characterization via machine vision" (Solar Energy Elsevier) by Milan Harth, Luigi Vesce, Ioannis Kouroudis, Maurizio Stefanelli, Aldo Di Carlo, Alessio Gagliardi from Technical University of Munich, CHOSE Centre for Hybrid and Organic Solar Energy, Università di Roma Tor Vergata, CNR - ISM Istituto di Struttura della Materia Thanks to Diamond-Horizon EU Project #perovskite #gosolar #solarenergy #DIAMONDeuproject #upscaling #machinelearning
Optoelectronic perovskite film characterization via machine vision
sciencedirect.com
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