查看更多>>摘要：By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News – Stanford researchers have developed an artificial intelligence-based tool - dubbed SandAI - that can reveal the histor y of quartz sand grains going back hundreds of millions of years. With SandAI, r esearchers can tell with high accuracy if wind, rivers, waves, or glacial moveme nts shaped and deposited motes of sand. The tool gives researchers a unique window into the past for geological and arch eological studies, especially for eras and environments where few other clues, s uch as fossils, are preserved through time. SandAI’s approach, called microtextu ral analysis, can also help with modern-day forensic investigations into illegal sand mining and related issues.
查看更多>>摘要：By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News – New research on Artificial Intelligenc e is the subject of a report. According to news reporting from Tarragona, Spain, by NewsRx journalists, research stated, “As society experiences accelerated age ing, understanding the complex biological processes of human ageing, which are a ffected by a large number of variables and factors, becomes increasingly crucial . Artificial intelligence (AI) presents a promising avenue for ageing research, offering the ability to detect patterns, make accurate predictions, and extract valuable insights from large volumes of complex, heterogeneous data.” Financial support for this research came from Ministerio de Ciencia, Innovacin y Universidades.
查看更多>>摘要：By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News – Researchers detail new data in Machine Learning. According to news originating from Lund, Sweden, by NewsRx correspond ents, research stated, “Childhood stunting is a serious public health concern in Rwanda. Although stunting causes have been documented, we still lack a more in- depth understanding of their local factors at a more detailed geographic level.” Financial supporters for this research include Norwegian Agency for Development Cooperation - NORAD, Lund University, University of Rwanda, SIDA-Rwanda Bilatera l Programme.
查看更多>>摘要：By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News – Fresh data on Artificial Intelligence are presented in a new report. According to news originating from Tianjin, Peopl e’s Republic of China, by NewsRx correspondents, research stated, “This paper ai ms to systematically review the application of artificial intelligence (AI) in t he tourism industry. By integrating human-computer interaction, machine learning , big data and other relevant technologies, the study establishes a comprehensiv e research framework that explores the systematic connections between AI and var ious facets of tourism.” Financial support for this research came from National Natural Science Foundatio n of China (NSFC).
查看更多>>摘要：By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News – New research on Machine Learning is th e subject of a report. According to news reporting out of Columbia, Missouri, by NewsRx editors, research stated, “RNA molecules play a crucial role in various biological processes, with their functionality closely tied to their structures. The remarkable advancements in machine learning techniques for protein structur e prediction have shown promise in the field of RNA structure prediction.” Financial support for this research came from National Institutes of Health (NIH ) - USA. Our news journalists obtained a quote from the research from the University of M issouri, “In this perspective, we discuss the advances and challenges encountere d in constructing machine learning-based models for RNA structure prediction. We explore topics including model building strategies, specific challenges involve d in predicting RNA secondary (2D) and tertiary (3D) structures, and approaches to these challenges. In addition, we highlight the advantages and challenges of constructing RNA language models.”
查看更多>>摘要：By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News – New research on Machine Learning is th e subject of a report. According to news reporting originating from Shanghai, Pe ople’s Republic of China, by NewsRx correspondents, research stated, “Biomolecul ar simulations often suffer from the ‘time scale problem’, hindering the study o f rare events occurring over extended time scales. Enhanced sampling techniques aim to alleviate this issue by accelerating conformational transitions, yet they typically necessitate well-defined collective variables (CVs), posing a signifi cant challenge.” Our news editors obtained a quote from the research from Shanghai Jiao Tong Univ ersity, “Machine learning offers promising solutions but typically requires rich training data encompassing the entire free energy surface (FES). In this work, we introduce an automated iterative pipeline designed to mitigate these limitati ons. Our protocol first utilizes a CV-free count-based adaptive sampling method to generate a data set rich in rare events. From this data set, slow modes are i dentified using Koopman-reweighted time-lagged independent component analysis (K TICA), which are subsequently leveraged by on-the-fly probability enhanced sampl ing (OPES) to efficiently explore the FES.”
查看更多>>摘要：By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News – New research on Artificial Intelligenc e is the subject of a report. According to news reporting originating from Antib es, France, by NewsRx correspondents, research stated, “Liver vessel segmentatio n from routinely performed medical imaging is a useful tool for diagnosis, treat ment planning and delivery, and prognosis evaluation for many diseases, particul arly liver cancer. A precise representation of liver anatomy is crucial to defin e the extent of the disease and, when suitable, the consequent resective or abla tive procedure, in order to guarantee a radical treatment without sacrificing an excessive volume of healthy liver.” Our news editors obtained a quote from the research from the Department of Vascu lar Surgery, “Once mainly performed manually, with notable cost in terms of time and human energies, vessel segmentation is currently realized through the appli cation of artificial intelligence (AI), which has gained increased interest and development of the field. Many different AI-driven models adopted for this aim h ave been described and can be grouped into different categories: thresholding me thods, edge- and region-based methods, model-based methods, and machine learning models. The latter includes neural network and deep learning models that now re present the principal algorithms exploited for vessel segmentation.”
查看更多>>摘要：By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News – Data detailed on Robotics - Androids h ave been presented. According to news reporting originating from Taipa, People’s Republic of China, by NewsRx correspondents, research stated, “PurposeAlong wit h the development of the robotics industry, service robots have been gradually u sed in the hospitality industry.” Funders for this research include Grants-in-Aid for Scientific Research (KAKENHI ), University of Macau.
查看更多>>摘要：By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News – Current study results on Support Vecto r Machines have been published. According to news reporting out of Bejaia, Alger ia, by NewsRx editors, the research stated, “In the last two decades, active set methods for training support vector machines (SVMs) have received a lot of atte ntion due to their robustness and have shown excellent results for training larg e-scale problems. In this paper, we propose the primal simplex method to solve t he quadratic programming problem encountered during the training phase of an SVM classification problem.” Our news journalists obtained a quote from the research from the University of B ejaia, “Our novel approach, named PSM-SVM, generates iteratively a decreasing se quence of feasible points that converges to the optimal solution. Contrary to ex isting active set algorithms, PSM-SVM has the particularity to avoid using the n ull -space matrix and also the reduced Hessian matrix when the descent direction is calculated at each iteration. In addition, it starts with a workingset havin g only one support vector and also guarantees the nonsingularity of the basic ma trix during all the iterations process. We have theoretically proven its global convergence and calculated its computational complexity.”
查看更多>>摘要：By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News – Investigators publish new report on ar tificial intelligence. According to news reporting from the University of Chines e Academy of Social Sciences by NewsRx journalists, research stated, “ [Purpose/Significance] This study aims to explore the challeng es that artificially intelligent (AI) scientists may bring to scientific epistem ology. [Method/Process] Scientific discove ry has long been of interest to AI researchers. The next big step in AI is the d evelopment of AI scientists.” The news reporters obtained a quote from the research from University of Chinese Academy of Social Sciences: “AI scientists should be able to independently moti vate, make, understand, and communicate discoveries. Although the current robot scientists are still just a form of AI-driven automated experimental apparatus, and the best AI systems today cannot define their own hypothesis space and exper imental design. At best, they can be considered to be a primitive form of AI sci entists. Clearly, the specific path of AI-driven scientific research or the tran sition to AI scientists will inevitably be influenced by the frontier developmen t of AI. Current AI systems must overcome the following major technical challeng es: 1) making strategic choices in their research goals; 2) developing the abili ty to generate exciting and novel hypotheses in areas that push boundaries; 3) d esigning innovative approaches and experiments to test hypotheses that go beyond the use of prototype experiments; 4) focusing on and describing important disco veries in a way that can be understood by human scientists. The highly autonomou s AI scientists can either make discoveries on their own or collaborate with oth er human and machine scientists to make Nobel-level discoveries. After reviewing the relevant AI applications in scientific research, this study illustrates the main characteristics of AI scientists and the two disruptive changes they bring about at the epistemological level: a leap in AI capabilities and AI for Scienc e as the 5th paradigm of scientific research. [Results/Conclu sions] The implications of AI for Science are revolutionary, but recent AI-driven explorations in scientific research increasingly support th e possibility of its realization. In this situation, discussions on the epistemo logical issues of relevant sciences need to go beyond general philosophical deba tes and instead explore epistemological strategies for the coming scientific rev olution in AI. In view of the coming scientific revolution in AI, this study pro poses four strategies. First, we should pay more attention to the problems and s olutions in the process of developing AI scientists. Second, the key to advancin g the scientific revolution in AI is to find ways to eliminate factors that may lead to failure.”
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