yt:channel:HcATder42GhyQRpbu1dr4Q HcATder42GhyQRpbu1dr4Q AI Journey 2025 https://www.youtube.com/channel/UCHcATder42GhyQRpbu1dr4Q 2008-03-18T19:00:23+00:00 yt:video:H116_h4HltM H116_h4HltM UCHcATder42GhyQRpbu1dr4Q AI Journey 2025 https://www.youtube.com/channel/UCHcATder42GhyQRpbu1dr4Q 2025-11-22T14:47:54+00:00 2026-09-01T01:27:26+00:00 What is Robotics Doing in the AI Era? | AIJ 2025 (12+) | Arabic Speaker — Gonzalo Ferrer, Skoltech The main point of discussion revolved around the current state and future directions of robotics, specifically focusing on embodied artificial intelligence. The speaker emphasized the shift from traditional methods to data-driven approaches to enhance robot efficiency and adaptability in real-world environments. Key challenges such as data scarcity, difficulty in acquiring high-quality training data, and the need for advanced algorithms and network architectures were discussed. Additionally, the importance of creating realistic simulations and utilizing diverse data sources, including online videos and knowledge graphs, was highlighted as crucial for advancing robotic capabilities. #aijourney #aijourney2025 #artificialintelligence #aiconference #artificialintelligenceconference #ai yt:video:A8ITp2EjNKM A8ITp2EjNKM UCHcATder42GhyQRpbu1dr4Q AI Journey 2025 https://www.youtube.com/channel/UCHcATder42GhyQRpbu1dr4Q 2025-11-22T14:47:06+00:00 2026-08-31T23:25:55+00:00 Data Flywheel via World Modeling for Self-correcting Autonomous Driving | AIJ 2025 (12+) | Arabic Generative Data Flywheel via World Modeling for Self-correcting Autonomous Driving Speaker — Kaicheng Yu, Westlake University During the session, issues related to the development and implementation of autonomous driving technologies were discussed. The importance of training algorithms based on real-world data and the necessity of creating new approaches to enhance the safety and efficiency of autonomous vehicles were emphasized. Key discussion topics included: - Challenges of data collection and annotation. - Search for optimal algorithm training methods. - Traditional approaches facing limitations due to data scarcity and annotation complexity. Initiatives proposed to address these challenges include: 1. Use of simulations and data generation to create realistic driving scenarios. 2. Development of algorithms capable of efficiently processing data from multiple sensors like cameras and LiDAR. 3. Automated learning techniques to minimize human resource requirements in the development process. Additionally, the potential of generative models to create new data and scenarios was highlighted, aiming to improve algorithm training and resilience against rare and extreme situations. The risks associated with autonomous vehicle safety and the need for rigorous algorithm testing and validation were also discussed. In conclusion, the session underscored that the successful implementation of autonomous driving technologies requires integrated efforts in data collection, algorithm development, and extensive testing. Generative models and simulations were identified as crucial tools to overcome existing challenges. #aijourney #aijourney2025 #artificialintelligence #aiconference #artificialintelligenceconference #ai yt:video:qpxyAaJmIHA qpxyAaJmIHA UCHcATder42GhyQRpbu1dr4Q AI Journey 2025 https://www.youtube.com/channel/UCHcATder42GhyQRpbu1dr4Q 2025-11-22T14:46:19+00:00 2026-08-31T21:01:57+00:00 Reliability of Modern LLMs through the Attention Patterns Analysis | AIJ 2025 (12+) | Arabic Reliability of Modern LLMs through the Lenses of Attention Patterns Analysis Speaker — Evgeny Burnaev, Skoltech, AIRI Institute The session addressed issues related to the development and application of large language models, their reliability and safety. Key aspects such as hallucinations, model accuracy and security, along with methods for their evaluation and improvement, were examined. It was emphasized that these concepts are defined based on data used for model training and validation. #aijourney #aijourney2025 #artificialintelligence #aiconference #artificialintelligenceconference #ai yt:video:FXq5pKsler4 FXq5pKsler4 UCHcATder42GhyQRpbu1dr4Q AI Journey 2025 https://www.youtube.com/channel/UCHcATder42GhyQRpbu1dr4Q 2025-11-22T14:45:35+00:00 2026-09-15T03:30:45+00:00 AI Journey 2025: Design the future of AI today! (12+) Scientists, visionaries, and global AI practitioners come together on one stage. Here you can hear the voices of those who don't just believe in the future—they are creating it! Among the speakers are the visionaries Kai-Fu Lee and Chen Qiufan, whose predictions about AI have become reality, along with dozens of other world-class AI gurus! We'll show how engineers and scientists make scientific and technological breakthroughs that shape our future today! The program includes presentations by researchers from different countries around the globe. Ride the wave with the AI of the future! Join AI Journey 2025! #aij2025 #aijourney #artificialintelligence #ai #conference #aijourney2025 yt:video:kvUJhbhsuuQ kvUJhbhsuuQ UCHcATder42GhyQRpbu1dr4Q AI Journey 2025 https://www.youtube.com/channel/UCHcATder42GhyQRpbu1dr4Q 2025-11-22T14:45:23+00:00 2026-08-31T14:54:34+00:00 Automated Design of Algorithms | AIJ 2025 (12+) | Arabic Speaker — Ye Tian, Anhui University The session discussed the prospects and challenges associated with the automated design of artificial intelligence algorithms. Professor Ye Tian from Anhui University presented a report dedicated to the automated design of AI algorithms, emphasizing the importance of this technology for reducing costs and improving development efficiency. He noted that while AI algorithms can solve tasks automatically, their design requires significant effort and expense, making the automation of this process a pertinent task. #aijourney #aijourney2025 #artificialintelligence #aiconference #artificialintelligenceconference #ai yt:video:OR8VfuO_7ao OR8VfuO_7ao UCHcATder42GhyQRpbu1dr4Q AI Journey 2025 https://www.youtube.com/channel/UCHcATder42GhyQRpbu1dr4Q 2025-11-22T14:44:29+00:00 2026-09-01T02:11:16+00:00 Issues, Challenges and Development in Machine Learning | AIJ 2025 (12+) | Arabic Speaker — Dianhui Wang, Qingdao University of Science and Technology During the session, issues, challenges, and developments in the field of machine learning, particularly within the context of industrial applications, were discussed. The speaker, Professor Dianhui Wang from Qingdao University of Science and Technology, presented his research and experience in this area. He noted that despite the popularity of deep learning, simpler methods often suffice for real-world industrial applications. Key discussion topics included challenges related to the reliability and efficiency of machine learning models. Professor Wang emphasized that many contemporary approaches, such as multilayer perceptrons with backpropagation, do not always deliver stable and accurate results. He also highlighted the importance of weight initialization in models and proposed using stochastic configuration networks as a more effective solution. During the discussion, various solutions for improving machine learning in industry were proposed. Professor Wang presented his development—the stochastic configuration network—which he stated outperforms multilayer perceptrons in both speed and accuracy. He also stressed the importance of using lightweight models for next-generation automation, which can rapidly adapt to real-time changes. Opportunities and prospects for applying machine learning in industry were discussed. The professor noted that lightweight models could be particularly useful in scenarios with limited data and resources. He also expressed confidence that stochastic configurations and other innovative approaches could form the foundation for next-generation automation systems. In conclusion, it was stated that machine learning holds significant potential for enhancing manufacturing processes. However, realizing this potential requires continued research and development in reliable and efficient models. Professor Dianhui Wang expressed hope for further collaboration and knowledge exchange in this field. #aijourney #aijourney2025 #artificialintelligence #aiconference #artificialintelligenceconference #ai yt:video:J1FoaYQh80Y J1FoaYQh80Y UCHcATder42GhyQRpbu1dr4Q AI Journey 2025 https://www.youtube.com/channel/UCHcATder42GhyQRpbu1dr4Q 2025-11-22T14:43:42+00:00 2026-08-31T22:55:22+00:00 AI in the New Era: Foundations, Trends, Opportunities and Collaboration | AIJ 2025 (12+) | Arabic Artificial Intelligence in the New Era: Foundations, Trends, Opportunities and Global Collaboration Speaker — Anderson Rocha, University of Campinas Institute of Computing The session discussed the future prospects of artificial intelligence (AI) and its impact on various spheres of life. The speaker noted that AI has already become an integral part of our world and its further development is inevitable. It was emphasized that we must learn to coexist with AI by developing critical thinking and an understanding of its capabilities and limitations. Key topics of discussion included the challenges associated with trust in AI, the measurement of uncertainty, the fairness of data usage, and the security of AI systems. The discussion covered the necessity of developing small language models for specific tasks, which would be more efficient and specialized. Issues of global inequality in access to data and expertise were also raised, as was the importance of considering cultural context in AI development. During the discussion, proposals were made for creating specialized AI models for specific sectors such as healthcare and biotechnology. The importance of personalized medical services, which could be made more effective through the use of AI, was highlighted. Initiatives for developing methods to detect falsified information and protect against phishing were also proposed. The conversation explored the opportunities and prospects for using AI in various fields, including the design of new materials, content creation, and simulations. The speaker noted that AI could help address global challenges, such as providing food for the planet's growing population. However, risks associated with energy consumption and the need to develop energy-efficient solutions were also voiced. In conclusion, the speaker emphasized that artificial intelligence should be not merely a tool, but an extension of human intellect. A proposal was made to develop a human-centric approach to AI, where the human remains at the center of the process. Confidence was expressed that AI will play a crucial part of our future, and that it is important to define how we wish to harness its potential. #aijourney #aijourney2025 #artificialintelligence #aiconference #artificialintelligenceconference #ai yt:video:B47sWE0QZeQ B47sWE0QZeQ UCHcATder42GhyQRpbu1dr4Q AI Journey 2025 https://www.youtube.com/channel/UCHcATder42GhyQRpbu1dr4Q 2025-11-22T14:42:54+00:00 2026-09-01T01:59:29+00:00 AI Horizons: Next Decade Research | AIJ 2025 (12+) | Arabic Speakers: - Dmitry Chernyshenko, Deputy Prime Minister of the Russian Federation - Alexander Boukhanovsky, ITMO University - Andrey Kuznetsov, AIRI Institute - Ivan Oseledets, AIRI Institute - Arutyun Avetisyan, Ivannikov Institute for System Programming of the Russian Academy of Sciences - Andrey Neznamov, Sber, AI Alliance Network - Ajith Abraham, Sai University - Ye Tian, Anhui University - Bo Song, Tsinghua University - Neelakandan Subramani, SNKDIR Lab, R.M.K Engineering College - Alexander Gasnikov, Innopolis University - Yuri Visilter, State Scientific Research Institute of Aviation Systems - Dmitry Yudin, AIRI Institute, MIPT - Evgeny Burnaev, Skoltech, AIRI Institute - Alexey Osadchii, AIRI Institute, HSE University - Nebojša Bačanin-Džakula, Singidunum University - Anderson Rocha, University of Campinas Institute of Computing - Anh-Huy Phan, Skoltech - Dianhui Wang, Qingdao University of Science and Technology #aijourney #aijourney2025 #artificialintelligence #aiconference #artificialintelligenceconference #ai yt:video:pdzL2GLxNCY pdzL2GLxNCY UCHcATder42GhyQRpbu1dr4Q AI Journey 2025 https://www.youtube.com/channel/UCHcATder42GhyQRpbu1dr4Q 2025-11-22T14:42:05+00:00 2026-08-31T15:55:27+00:00 Generative AI in Healthcare | AIJ 2025 (12+) | Arabic Speaker — Ajith Abraham, Sai University The session examined the prospects and challenges associated with implementing generative artificial intelligence in healthcare. Results from multi-year research in this field were presented. It was emphasized that artificial intelligence could significantly enhance healthcare quality, accelerate diagnostics, and reduce the workload of medical staff. Key discussion topics included using AI for analyzing medical images, personalized treatment, vaccine development, and healthcare risk management. Challenges related to ensuring data security and confidentiality, ethical concerns, and integrating new technologies into existing medical systems were noted. Capabilities of generative AI in recognizing medical scans, predicting diseases such as Alzheimer's, and assisting in treating rare conditions including leukemia and scoliosis were presented. Prospects for using AI for personalized medical services and chat-bots that could expand healthcare access in remote areas were also mentioned. Risks associated with potential AI errors, data biases, and the necessity for thorough model validation were discussed. The importance of ethical technology use and ensuring transparency in decision-making was emphasized. In conclusion, it was determined that generative artificial intelligence has enormous potential for transforming healthcare but requires a comprehensive implementation approach, including developing regulatory frameworks, training medical personnel, and creating reliable data management systems. #aijourney #aijourney2025 #artificialintelligence #aiconference #artificialintelligenceconference #ai yt:video:oQzsabwKtNQ oQzsabwKtNQ UCHcATder42GhyQRpbu1dr4Q AI Journey 2025 https://www.youtube.com/channel/UCHcATder42GhyQRpbu1dr4Q 2025-11-22T14:41:15+00:00 2026-08-31T22:08:55+00:00 Artifiсial Intelligence and Mathematical Laws | AIJ 2025 (12+) | Arabic Speaker — Vladimir Spokoiny, Weierstrass Institute, IITP RAS, HSE University During the session, fundamental aspects of artificial intelligence and its mathematical foundations were discussed. Professor Vladimir Spokoyny from Berlin University presented a report dedicated to explaining the workings of AI through mathematical laws. He noted that AI can be viewed as a system that solves optimization problems based on data. Vladimir emphasized the importance of understanding how mathematical laws govern AI's behavior and allow for the prediction of its performance within specific tasks. A key topic of discussion was the investigation of AI's fundamental principles, such as the method of maximum likelihood introduced by Fisher, and its application to contemporary problems. The speaker explained that classical statistical procedures can be reinterpreted within this framework, leading to a better understanding of AI's behavior. He also addressed the problem of data dimensionality and proposed the concept of effective dimensionality, which plays a crucial role in AI optimization. During the discussion, new approaches to AI optimization were proposed, including the use of perturbed optimization methods and random matrix theory. Vladimir presented findings from his research demonstrating that increasing a problem's dimensionality can improve the geometric properties of the objective function without increasing its effective dimensionality. This allows for the use of classical optimization methods with greater accuracy. Challenges and prospects for AI development were also discussed. It was noted that modern problems require new mathematical tools and theories, such as perturbation theory and second-order methods. He emphasized that increasing the number of parameters in AI models can lead to improved performance, but requires careful consideration of effective dimensionality and the geometric properties of the functions. In conclusion, it was stated that to understand and optimize AI performance, it is necessary to account for the effective dimensionality of problems and Fisher's laws. It was underscored that studying AI is impossible without data, and new approaches to expanding problem dimensionality to improve their geometric properties were proposed. These results could form the basis for the further development of AI theory and practice. #aijourney #aijourney2025 #artificialintelligence #aiconference #artificialintelligenceconference #ai yt:video:TiSUVnBE3IQ TiSUVnBE3IQ UCHcATder42GhyQRpbu1dr4Q AI Journey 2025 https://www.youtube.com/channel/UCHcATder42GhyQRpbu1dr4Q 2025-11-22T14:40:26+00:00 2026-09-01T00:59:39+00:00 Characterizing the Logic of Transcriptional Control at the DNA Level | AIJ 2025 (12+) | Arabic Characterizing the Regulatory Logic of Transcriptional Control at the DNA Sequence Level by Ensembles of Thermodynamic Models Speaker — Alexandre Ferreira Ramos, University of São Paulo The session explored the regulation of genetic information and its impact on living organism development. The speaker explained how biological systems can be represented as computational machines, where DNA and RNA serve as information carriers while enzymes function as reading and writing devices. Particular focus was given to the regulatory logic of transcriptional control that determines which genes become activated based on environmental conditions. Discussion centered on how regulatory mechanisms can help understand cellular adaptation to environmental changes. Questions were also raised regarding how evolution and adaptation affect genetic system efficiency, and how these processes could be modeled using statistical methods. Various approaches to modeling regulatory processes were proposed during the discussion, including using neural networks and model ensembles for genetic information analysis. The speaker explained how such models could help comprehend cellular learning and adaptation processes, as well as their potential for predicting gene expression under different conditions. The conversation covered potential applications of these models in biology and medicine, along with risks associated with genetic information interpretation. It was noted that understanding regulatory mechanisms could lead to developing new treatment and diagnostic methods. However, challenges were also identified, including the need for further model refinement and study, plus ethical considerations in using genetic information. Ultimately, it was observed that integrating biological and computational approaches could significantly enhance our understanding of genetic processes and promote new technology development in biology and medicine. Emphasis was placed on the necessity of continuing research and fostering interdisciplinary collaboration among biologists, mathematicians, and artificial intelligence specialists to achieve these goals. #aijourney #aijourney2025 #artificialintelligence #aiconference #artificialintelligenceconference #ai yt:video:fFBt-JCFFGI fFBt-JCFFGI UCHcATder42GhyQRpbu1dr4Q AI Journey 2025 https://www.youtube.com/channel/UCHcATder42GhyQRpbu1dr4Q 2025-11-22T14:39:29+00:00 2026-09-01T01:45:08+00:00 Successes and challenges of large model languages | AIJ 2025 (12+) | Arabic Speaker — Ivan Oseledets, AIRI Institute During the session, the main points of discussion revolved around the following key aspects: 1. Successes and Problems of Large Language Models (LLMs): Discussed both the achievements and challenges faced by LLMs, highlighting their ability to compress vast amounts of data effectively while noting issues like limited memory and lack of deep reasoning capabilities. 2. Impact on Industries: Explored how LLMs are being applied across different sectors, particularly in medicine where they have shown promise in passing medical exams but fall short when it comes to real-world clinical decision-making. 3. Scaling and Data Compression: Emphasized the systematic approach to scaling LLMs, involving larger datasets, improved hardware, and advanced optimization techniques. 4. New Architectures and Algorithms: Introduced innovative approaches such as ARM-T (Associative Recursive Memory Transformer) and GigaEvo, an evolutionary algorithm designed to enhance model performance through iterative refinement. 5. Future Prospects and Challenges: Highlighted the potential for LLMs to evolve into tools for building multi-agent systems capable of solving complex tasks reliably. Also mentioned the need for overcoming current limitations, such as enabling learning during inference and accessing external knowledge sources. 6. Synthetic Data Generation: Discussed the role of LLMs in generating synthetic data to address data scarcity in specialized domains like medicine and finance. Overall, the discussion centered on balancing the significant progress made in LLMs with the ongoing efforts needed to overcome existing barriers toward achieving more robust and versatile AI systems. #aijourney #aijourney2025 #artificialintelligence #aiconference #artificialintelligenceconference #ai yt:video:mh5PK9CjJXI mh5PK9CjJXI UCHcATder42GhyQRpbu1dr4Q AI Journey 2025 https://www.youtube.com/channel/UCHcATder42GhyQRpbu1dr4Q 2025-11-22T14:38:37+00:00 2026-09-01T03:32:21+00:00 Recent Advances in Bio-Inspired Metaheuristics | AIJ 2025 (12+) | Arabic Recent Advances in Bio-Inspired Metaheuristics: Theoretical Insights and Practical Application Speaker — Nebojša Bačanin-Džakula, Singidunum University #aijourney #aijourney2025 #artificialintelligence #aiconference #artificialintelligenceconference #ai yt:video:KJIewjPEzHk KJIewjPEzHk UCHcATder42GhyQRpbu1dr4Q AI Journey 2025 https://www.youtube.com/channel/UCHcATder42GhyQRpbu1dr4Q 2025-11-22T14:37:32+00:00 2026-08-31T23:41:07+00:00 Next Generation of Artificial Intelligence | AIJ 2025 (12+) | Arabic Speakers: - Maxim Eremenko, Sber - Danis Dinmukhametov, Gold Medal Winner, IOAI 2025 - Zongyan Duan, Silver Medal Winner, IOAI 2025 - Shaleen Bhartiya, Winner of Al Challenge 2021, CEO and Founder, BrainWaveML - Qiwen Xu, Silver Medal Winner, IOAI 2024 The session examined the transformational impact of artificial intelligence on scientific research and education. The discussion aimed to define strategic directions for training the new generation of specialists and to assess the potential of AI as a tool for scientific progress. The significance of the discussion was underscored by comparing AI's influence to fundamental innovations such as electricity and the internet. Primary attention was given to the problem of declining youth engagement with AI tools during academic breaks, indicating a lack of a systemic approach to education. Challenges related to the need to develop independent thinking among students in the era of readily available AI solutions, and the insufficient adaptation of educational programs to rapidly changing technologies, were also debated. As solutions, the active involvement of young people in academic competitions and practical activities was proposed. To bridge the technological gap, an initiative was launched to develop a specialized AI community among youth, following the example of Chinese automation experience. Particular emphasis was placed on the importance of combining the expertise of different generations of researchers. The significant potential of AI for processing data volumes unmanageable for human analysis was noted, pointing to new horizons for scientific discoveries. Prospects are linked to the creation of educational ecosystems that integrate academic knowledge with practical skills. However, risks of technological lag exist if there is insufficient attention to the development of new tools and over-reliance on ready-made AI solutions. A conclusion was formulated on the critical importance of a ten-year program for developing AI education for schoolchildren as a foundation for technological sovereignty. The necessity of balancing the use of AI with the development of independent thinking was emphasized, where technology should serve as a tool for enhancing intellectual capabilities, not replacing them. The key role of intergenerational interaction for effective technological advancement was defined. #aijourney #aijourney2025 #artificialintelligence #aiconference #artificialintelligenceconference #ai yt:video:N2ytwii2Cnc N2ytwii2Cnc UCHcATder42GhyQRpbu1dr4Q AI Journey 2025 https://www.youtube.com/channel/UCHcATder42GhyQRpbu1dr4Q 2025-11-22T13:33:10+00:00 2026-08-31T22:31:24+00:00 AI Journey 2025: The future we create together (12+) RUS Welcome to the annual international conference where scientists, engineers, and industry leaders create the future with AI. Experts and industry leaders from all over the world will share some of the best AI use cases in business and talk about technological announcements and key barriers to AI adoption. One of the most anticipated events is a presentation by Chen Qiufan, co-author of the bestseller AI 2041, on the topic of “The Future of AI: From Fiction to Reality.” Want to be a co-author of the future? Ride the wave with AI! Join AI Journey 2025! #aij2025 #aijourney #artificialintelligence #ai #conference #aijourney2025