Охота на электроовец. Большая книга искусственного интеллекта - Сергей Сергеевич Марков

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Peng Z., Wang W., Dong L., Hao Y., Huang S., Ma S., Wei F. (2023). Kosmos-2: Grounding Multimodal Large Language Models to the World // https://arxiv.org/abs/2306.14824

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Jaegle A., Gimeno F., Brock A., Zisserman A., Vinyals O., Carreira J. (2021). Perceiver: General Perception with Iterative Attention // https://arxiv.org/abs/2103.03206

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Carreira J., Koppula S., Zoran D., Recasens A., Ionescu C., Henaff O., Shelhamer E., Arandjelovic R., Botvinick M., Vinyals O., Simonyan K., Zisserman A., Jaegle A. (2022). Hierarchical Perceiver // https://arxiv.org/abs/2202.10890

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Mak K.-R., Pichika M. R. (2019). Artificial intelligence in drug development: present status and future prospects / Drug Discovery Today, Vol. 24, Iss. 3, March 2019, pp. 773—780 // https://doi.org/10.1016/j.drudis.2018.11.014

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Fleming N. (2018). How artificial intelligence is changing drug discovery / Nature, Vol. 557, S55-S57 (2018) // https://doi.org/10.1038/d41586-018-05267-x

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Artificial Intelligence (AI) in Drug Discovery Market (2019). Report Code: HIT 7445 / MarketsAndMarkets, Nov 2019 // https://www.marketsandmarkets.com/Market-Reports/ai-in-drug-discovery-market-151193446.html

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USPEX Computational Materials Discovery // https://uspex-team.org/

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Li Q., Ma Y., Oganov A. R., Wang H., Wang H., Xu Y., Cui T., Mao H.-K., Zou G. (2009). Superhard monoclinic polymorph of carbon / Physical Review Letters, Vol. 102, p. 175506 // https://doi.org/10.1103/physrevlett.102.175506

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Dong X., Oganov A. R., Goncharov A. F., Stavrou E., Lobanov S., Saleh G., Qian G. R., Zhu Q., Gatti C., Deringer V. L., Dronskowski R., Zhou X. F., Prakapenka V. B., Konôpková Z., Popov I. A., Boldyrev A. I., Wang H. T. (2017). A stable compound of helium and sodium at high pressure / Nature Chemistry, Vol. 9, pp. 440—445 // https://doi.org/10.1038/nchem.2716

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Callaway E. (2020). ‘It will change everything’: DeepMind’s AI makes gigantic leap in solving protein structures / Nature, Vol. 588, pp. 203—204 // https://doi.org/10.1038/d41586-020-03348-4

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Baek M., DiMaio F., Anishchenko I., Dauparas J., Ovchinnikov S., Lee G. R., Wang J., Cong Q., Kinch L. N., Schaeffer R. D., Millán C., Park H., Adams C., Glassman C. R., DeGiovanni A., Pereira J. H., Rodrigues A. V., van Dijk A. A., Ebrecht A. C., Opperman D. J., Sagmeister T., Buhlheller C., Pavkov-Keller T., Rathinaswamy M. K., Dalwadi U., Yip C. K., Burke J. E., Garcia K. C., Grishin N. V., Adams P. D., Read R. J., Baker D. (2021). Accurate prediction of protein structures and interactions using a 3-track network // https://www.biorxiv.org/content/10.1101/2021.06.14.448402v1

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Jumper J., Evans R., Pritzel A., Green T., Figurnov M., Ronneberger O., Tunyasuvunakool K., Bates R., Žídek A., Potapenko A., Bridgland A., Meyer C., Kohl S. A. A., Ballard A. J., Cowie A., Romera-Paredes B., Nikolov S., Jain R., Hassabis D. (2021). Highly accurate protein structure prediction with AlphaFold / Nature, 15 July 2021 // https://doi.org/10.1038/s41586-021-03819-2

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Ford C. T. (2021). Protein Structure Prediction of the new B.1.1.529 SARS-CoV-2 Spike Variant with AlphaFold2 / Colby T. Ford, PhD, Nov 27, 2021 // https://colbyford.medium.com/protein-structure-prediction-of-b-1-1-529-sars-cov-2-spike-variant-with-alphafold2-39c5bf9cf9ed

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Ford C. T., Machado D. J., Janies D. A. (2021). Predictions of the SARS-CoV-2 Omicron Variant (B.1.1.529) Spike Protein Receptor-Binding Domain Structure and Neutralizing Antibody Interactions // https://doi.org/10.1101/2021.12.03.471024

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Hassabis D. (2022). AlphaFold reveals the structure of the protein universe / DeepMind blog, July 28, 2022 // https://www.deepmind.com/blog/alphafold-reveals-the-structure-of-the-protein-universe

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Jiang J. W., Songhori E., Wang S., Lee Y.-J., Johnson E., Pathak O., Nazi A., Pak J., Tong A., Srinivasa K., Hang W., Tuncer E., Le Q. V., Laudon J., Ho R., Carpenter R., Dean J. (2021). A graph placement methodology for fast chip design / Nature, Vol. 594, pp. 207—212 // https://doi.org/10.1038/s41586-021-03544-w

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Gershgorn D. (2017). DeepMind has a bigger plan for its newest Go-playing AI / Quartz, October 18, 2017 // https://qz.com/1105509/deepminds-new-alphago-zero-artificial-intelligence-is-ready-for-more-than-board-games/

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Ren F., Ward L., Williams T., Laws K. J., Wolverton C.,