Learning and Controlling Silicon Dopant Transitions in Graphene Using Scanning Transmission Electron Microscopy by Max Schwarzer, Jesse Farebrother, Joshua Greaves, Ekin Dogus Cubuk, Rishabh Agarwal, Aaron Courville, Marc G. Bellemare, Sergei Kalinin, Igor Mordatch, Pablo Samuel Castro, Kevin M. Roccapriore

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Catalyzing next-generation Artificial Intelligence through NeuroAI by Anthony Zador, Sean Escola, Blake Richards, Bence Ölveczky, Yoshua Bengio, Kwabena Boahen, Matthew Botvinick, Dmitri Chklovskii, Anne Churchland, Claudia Clopath, James DiCarlo, Surya Ganguli, Jeff Hawkins, Konrad Körding, Alexei Koulakov, Yann LeCun, Timothy Lillicrap, Adam Marblestone, Bruno Olshausen, Alexandre Pouget, Cristina Savin, Terrence Sejnowski, Eero Simoncelli, Sara Solla, David Sussillo, Andreas S. Tolias, Doris Tsao

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Visual Navigation with Asynchronous Proximal Policy Optimization in Artificial Agents by Fanyu Zeng, Chen Wang

“…Our experiments are tested in DeepMind Lab, and the experimental results show that the artificial agents with appoNav perform better than the compared algorithm.…”
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Transformer-Based Approach for Solving Mathematical Problems Using Automatic Speech Recognition by Ante Grgurevic, Marina Bagic Babac

“…We utilize Transformer and TP-Transformer models, trained on DeepMind’s Mathematics dataset, to generate an appropriate mathematical answer from the provided input sequence. …”
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La ola que Viene. Tecnología, poder y el gran dilema del Siglo XXI de Mustafa Suleyman, con la colaboración de Michael Bhaskar by Javier Surasky

“…Su autor principal, cofundador de DeepMind, introduce el concepto de “contención” como un marco crucial para gestionar el avance tecnológico, argumentando que si bien el progreso tecnológico no puede ni debe detenerse, debe contenerse de manera efectiva a través de mecanismos técnicos, culturales, legales y políticos interconectados. …”
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Entropy-Guided Distributional Reinforcement Learning with Controlling Uncertainty in Robotic Tasks by Hyunjin Cho, Hyunseok Kim

“…Our experiments demonstrated an 11% increase in average evaluation return compared to traditional fixed-discount-factor approaches in the DeepMind Control Suite and Gymnasium robotics environments. …”
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Eficácia e impacto na experiência do cliente by Thaís Yassue Domingos Tagawa, Isabella Correia Aguiar, Leonardo Villani

“…Este estudo analisa a aplicação dos modelos generativos ChatGPT (OpenAI) e Gemini (Google DeepMind) na fidelização e engajamento de clientes. …”
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Dynamic Path Planning of Unknown Environment Based on Deep Reinforcement Learning by Xiaoyun Lei, Zhian Zhang, Peifang Dong

“…In this paper, we apply double Q-network (DDQN) deep reinforcement learning proposed by DeepMind in 2016 to dynamic path planning of unknown environment. …”
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The Impact of Research Data Infrastructures: The Case of the AlphaFold Database by Angelo Kenneth Romasanta, Jonathan Wareham, Laia Pujol Priego

“…To better understand the benefits of these public resources, this study explores the AlphaFold (AFDB) database, a collaboration between DeepMind and the European Molecular Biology Laboratory (EMBL) that democratizes access to protein structure data. …”
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A Systematic Review of Gen-AI Applications in Education: Rewards, Challenges and Future Prospects by Everleen Nekesa Wanyonyi, Millicent Kathambi Murithi

“…Innovation of models such as ChatGPT, Bard, DALL-E, Midjourney, and DeepMind has transformed academia. The widespread use of AI systems has sparked debates on how to effectively train future-relevant competencies while maintaining learning integrity. …”
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Inteligencia Artificial y Juegos de Tablero: Desde el Turco hasta AlphaZero by Ivan Francisco Valencia, Rosa María Valdovinos Rosas, J. Raymundo Marcial Romero, Roberto Alejo Eleuterio

“…Se muestra una breve revisión histórica de los agentes que se han desarrollado para diversos juegos y se describe el agente AlphaZero, creado por DeepMind, el cual hoy en día es el agente más avanzado en esta área es capaz de vencer a campeones humanos en el juego de Go, el cual se considera el juego de tablero más complejo que existe, incluso más que el ajedrez. …”
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Evaluating Large Language Models for Preoperative Patient Education in Superior Capsular Reconstruction: Comparative Study of Claude, GPT, and Gemini by Yukang Liu, Hua Li, Jianfeng Ouyang, Zhaowen Xue, Min Wang, Hebei He, Bin Song, Xiaofei Zheng, Wenyi Gan

“…MethodsIn total, 10 sports medicine clinical experts formulated 11 SCR issues and developed preoperative patient education strategies during a webinar, inputting 12 text commands into Claude-3-Opus (Anthropic), GPT-4-Turbo (OpenAI), and Gemini-1.5-Pro (Google DeepMind). A total of 3 experts assessed the language models’ responses for correctness, completeness, logic, potential harm, and overall satisfaction, while preoperative education documents were evaluated using DISCERN questionnaire and Patient Education Materials Assessment Tool instruments, and reviewed by 5 postoperative patients for readability and educational value; readability of all responses was also analyzed using the cntext package and py-readability-metrics. …”
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Advancing Early Wildfire Detection: Integration of Vision Language Models with Unmanned Aerial Vehicle Remote Sensing for Enhanced Situational Awareness by Leon Seidel, Simon Gehringer, Tobias Raczok, Sven-Nicolas Ivens, Bernd Eckardt, Martin Maerz

“…We evaluated both cloud-based (OpenAI, Google DeepMind) and open-weight, locally deployed VLMs on a novel evaluation dataset specifically curated for understanding forest fire scenes. …”
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Agentes de Inteligencia Artificial en Medicina: Optimización y potenciación de la redacción académica para la divulgación científica by Elisabeth Virginia Benitez Rosales, Raymond Marquina

“…Se describen aplicaciones específicas en la medicina, como el uso de algoritmos de aprendizaje profundo—incluyendo redes neuronales convolucionales y modelos generativos—para el diagnóstico por imágenes médicas, detección de patologías y la medicina personalizada, fundamentada en análisis genéticos y predictivos, ejemplificado por herramientas como AlphaFold de Google DeepMind. También se destaca la utilización de la IA para optimizar la producción de escritos académicos, reduciendo significativamente el tiempo de procesamiento de grandes volúmenes de información y potenciando la colaboración y actualización en la investigación científica. …”
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Novel Artificial Intelligence Applications in Energy: A Systematic Review by Tai Zhang, Goran Strbac

“…Notable outcomes include DeepMind-based reinforcement learning cutting data centre cooling energy by 40%, multi-agent control boosting virtual power plant revenue by 28%, AI-enhanced planning slashing the computation time by 87% without sacrificing solution quality, battery management AI raising efficiency by 30%, and machine learning accelerating hydrogen catalyst discovery 200,000-fold. …”
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Counting the chorus: A bioacoustic indicator of population density by Amanda K. Navine, Richard J. Camp, Matthew J. Weldy, Tom Denton, Patrick J. Hart

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Real-Time High-Resolution Global PWV Retrieval Based on Weather Forecast Foundation Models and Cross-Validation With Radiosonde, GNSS, and ERA5 by Junsheng Ding, Wu Chen, Junping Chen, Jungang Wang, Yize Zhang, Lei Bai

“…This research introduces a novel scheme for retrieving high-resolution surface-domain PWV with real-time and forecasting capabilities with global coverage, utilizing weather forecast foundation models represented by Huawei Cloud Pangu-Weather, Google DeepMind GraphCast, and Shanghai AI Lab FengWu. The accuracy of the new scheme is cross-validated against PWVs from radiosondes, Global Navigation Satellite Systems (GNSSs), and the fifth generation ECMWF reanalysis (ERA5). …”
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Comprehensive review of artificial intelligence applications in renewable energy systems: current implementations and emerging trends by Chukwuebuka Joseph Ejiyi, Dongsheng Cai, Dara Thomas, Sandra Obiora, Emmanuel Osei-Mensah, Caroline Acen, Francis O. Eze, Francis Sam, Qingxian Zhang, Olusola O. Bamisile

“…Real-world case studies, like Google’s collaboration with DeepMind for optimizing wind energy output and Australia’s National Electricity Market integrating Artificial Intelligence for grid stability, underscore the practical impact of Artificial Intelligence in renewable energy. …”
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SENTRIN- Mesin Catur Berbasis Neural Network Menggunakan Long Short Term memory (LSTM) by Rafi Indra Fattah, Putra Pandu Adikara, Budi Darma Setiawan

“…Saat ini, penggunaan Neural Network pada pengembangan mesin catur sedang mengalami peningkatan dan telah membawa hasil yang menjanjikan sejak pertama kali diperkenalkan oleh AlphaZero milik Google DeepMind pada tahun 2017. Penelitian ini bertujuan untuk membawa potensi pendekatan baru pada ranah pengembangan mesin catur berbasis Neural Network dengan memperkenalkan mesin catur Deeplefish yang melakukan gerakan berdasarkan keluaran model Long Short Term Memory (LSTM). …”
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Evaluating the Effectiveness of Large Language Models in Providing Patient Education for Chinese Patients With Ocular Myasthenia Gravis: Mixed Methods Study by Bin Wei, Lili Yao, Xin Hu, Yuxiang Hu, Jie Rao, Yu Ji, Zhuoer Dong, Yichong Duan, Xiaorong Wu

“…For 23 common patients with OMG-related questions, ChatGPT o1-preview scored highest in correctness (4.44), completeness (4.44), helpfulness (4.47), and safety (4.6). GEMINI (Google DeepMind) provided the easiest-to-understand responses in readability assessments, while GPT-4o had the most complex responses, suitable for readers with higher education levels. …”
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