Artificial Intelligence (AI) refers to the simulation of human intelligence processes by machines, especially computer systems. These processes include learning (the acquisition of information and rules for using the information), reasoning (using rules to reach approximate or definite conclusions), and self-correction.
https://www.sciencedirect.com/science/article/pii/S0140366423002724?via%3Dihub
This review explores how Artificial Intelligence (AI), particularly Generative Adversarial Networks (GANs) and Supervised Learning, revolutionizes ocular imaging in space, offering new insights into Spaceflight Associated Neuro-Ocular Syndrome (SANS), a condition affecting astronauts' eyes during long-duration space missions.
Researchers demonstrate an AI-driven automated workflow for discovering efficient polymer membranes for carbon capture, overcoming previous limitations. This approach combines generative design and physical validation, offering a computational screening alternative before lab validation. The study showcases the effectiveness of the proposed method, promising accelerated material discovery.
Aeras Intel, a visionary MedTech company, is proud to announce its official launch as an independent company. Aeras Intel's origins come from IoT innovations within the dental manufacturer DENTALEZ and its unyielding mission to simplify all aspects of managing critical equipment and redirecting the time and energy savings to improving the user and patient experiences. Aeras Intel is now operating as a privately held, independent Delaware-based corporation, Aeras, Inc.
The research paper focuses on Ren Wang's groundbreaking work in fortifying artificial intelligence systems using insights from the human immune system, aiming to enhance AI robustness and resilience. Wang's research borrows adaptive mechanisms from B cells to create a novel immune-inspired learning approach, with potential applications in AI-driven power system control and stability analysis, making AI models more powerful and reliable.
The research paper delves into the future of leadership, discussing the potential for AI to assist and even substitute human leaders. It explores the effectiveness of AI in addressing employees' psychological needs and highlights the importance of understanding the ethical implications and the evolving roles of human leaders in this digital landscape.
Robot preachers and AI programs are being utilized to share religious beliefs, but research shows that they may undermine credibility and lead to reduced donations for religious groups, as participants viewed them as less credible and were less likely to support them compared to human religious leaders. The study highlights the challenges of fully automating religious leadership and the potential impact on congregational commitment when relying more on technology than on human faith leaders.
Researchers explore the core elements shared between human intelligence and artificial general intelligence (AGI), emphasizing scale, multimodality, alignment, and reasoning. The study delves into brain-inspired artificial intelligence, advancements in large language models, and the potential for AGI to enhance human intelligence and cognition.
Researchers from the CAS Institute of Atmospheric Physics developed an AI-powered model using deep learning algorithms that surpasses traditional methods in predicting central Pacific El Nino events, offering potential advancements in seasonal climate forecasting. The study highlights the significance of artificial intelligence in enhancing predictions of significant climate events, providing valuable insights for disaster preparedness and risk reduction worldwide.
This comprehensive review explores the integration of machine learning (ML) techniques in forest fire science. The study highlights the significance of early fire prediction and detection for effective fire management. It discusses various ML methods applied in forest fire detection, prediction, fire mapping, and data evaluation. The review identifies challenges and research priorities while emphasizing the potential benefits of ML in improving forest fire resilience and enabling more efficient data analysis and modeling.
The research investigates the conceptual difficulties faced by ChatGPT, an AI-powered tool, in comprehending and responding to chemistry problems related to Introduction to Material Science. The study highlights the limitations of ChatGPT's text-based capabilities and proposes the use of converters that can transform text into graphical representations to overcome these limitations.
"PhotoShelter launches AI Visual Search, a groundbreaking capability that allows users to search their entire asset library based on visual descriptions recognized by AI, eliminating manual tagging and expediting content discovery. The metadata-less image search streamlines workflows, improves efficiency, and maximizes content ROI, ensuring content creators can find the right images faster and easier."
Researchers at Georgia Tech and Hanoi University of Science and Technology have developed an innovative AI/ML approach using Expanse supercomputer to identify potential superconductors, such as chromium hydride, capable of functioning at room temperature. This breakthrough holds promise for transforming technology with ultra-efficient electricity grids, energy-efficient computer chips, and powerful magnets for levitating trains and controlling fusion reactors.
Machine learning models identify miRNA biomarkers with potential clinical significance, shedding light on the complex landscape of cancer. The study reveals the relevance of specific miRNAs in cancer classification and highlights their potential as diagnostic and classification biomarkers.
Scientists are using automated wildlife sensors and artificial intelligence (AI) over the next four years to demonstrate the effectiveness of agri-environment and peatland restoration schemes in improving biodiversity.
"Lero's new public survey aims to uncover citizens' hopes and fears about AI and software, focusing on issues of responsibility and ethics. This project seeks to address the underrepresentation of public sentiment in ongoing debates, amidst rising concerns over biases in AI and potential human rights abuses."
The study in the ACS journal Medicinal Chemistry Letters offers an in-depth analysis of AI and ML methods used in generative chemistry to create synthetically feasible molecular structures. The authors recommend rigorous evaluation, experimental validation, and adherence to strict guidelines to enhance the role of AI in drug discovery and ensure the novelty and validity of AI-generated molecules.
Technology experts convened at Oak Ridge National Laboratory's Department of Energy for the Trillion-Pixel GeoAI Challenge workshop to discuss the future of geospatial systems. The event emphasized advancements in artificial intelligence, cloud infrastructure, high-performance computing, and remote sensing, highlighting their potential in addressing national and human security concerns like disaster response and land-use planning.
The Coalition for Epidemic Preparedness Innovations (CEPI) and the Houston Methodist Research Institute (HMRI) are partnering to use artificial intelligence (AI) in developing faster vaccines against future viral threats. They aim to achieve this through a $4.98 million project using AI to identify viral structures for potential vaccine candidates, contributing to a global 'Vaccine Library' for a rapid response to emerging diseases, with the overarching goal of compressing vaccine development to within 100 days of a pathogen's identification.
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