Articles tagged with Artificial Intelligence
Comprehensive exploration of living organisms, biological systems, and life processes across all scales from molecules to ecosystems. Encompasses cutting-edge research in biology, genetics, molecular biology, ecology, biochemistry, microbiology, botany, zoology, evolutionary biology, genomics, and biotechnology. Investigates cellular mechanisms, organism development, genetic inheritance, biodiversity conservation, metabolic processes, protein synthesis, DNA sequencing, CRISPR gene editing, stem cell research, and the fundamental principles governing all forms of life on Earth.
Comprehensive medical research, clinical studies, and healthcare sciences focused on disease prevention, diagnosis, and treatment. Encompasses clinical medicine, public health, pharmacology, epidemiology, medical specialties, disease mechanisms, therapeutic interventions, healthcare innovation, precision medicine, telemedicine, medical devices, drug development, clinical trials, patient care, mental health, nutrition science, health policy, and the application of medical science to improve human health, wellbeing, and quality of life across diverse populations.
Comprehensive investigation of human society, behavior, relationships, and social structures through systematic research and analysis. Encompasses psychology, sociology, anthropology, economics, political science, linguistics, education, demography, communications, and social research methodologies. Examines human cognition, social interactions, cultural phenomena, economic systems, political institutions, language and communication, educational processes, population dynamics, and the complex social, cultural, economic, and political forces shaping human societies, communities, and civilizations throughout history and across the contemporary world.
Fundamental study of the non-living natural world, matter, energy, and physical phenomena governing the universe. Encompasses physics, chemistry, earth sciences, atmospheric sciences, oceanography, materials science, and the investigation of physical laws, chemical reactions, geological processes, climate systems, and planetary dynamics. Explores everything from subatomic particles and quantum mechanics to planetary systems and cosmic phenomena, including energy transformations, molecular interactions, elemental properties, weather patterns, tectonic activity, and the fundamental forces and principles underlying the physical nature of reality.
Practical application of scientific knowledge and engineering principles to solve real-world problems and develop innovative technologies. Encompasses all engineering disciplines, technology development, computer science, artificial intelligence, environmental sciences, agriculture, materials applications, energy systems, and industrial innovation. Bridges theoretical research with tangible solutions for infrastructure, manufacturing, computing, communications, transportation, construction, sustainable development, and emerging technologies that advance human capabilities, improve quality of life, and address societal challenges through scientific innovation and technological progress.
Study of the practice, culture, infrastructure, and social dimensions of science itself. Addresses how science is conducted, organized, communicated, and integrated into society. Encompasses research funding mechanisms, scientific publishing systems, peer review processes, academic ethics, science policy, research institutions, scientific collaboration networks, science education, career development, research programs, scientific methods, science communication, and the sociology of scientific discovery. Examines the human, institutional, and cultural aspects of scientific enterprise, knowledge production, and the translation of research into societal benefit.
Comprehensive study of the universe beyond Earth, encompassing celestial objects, cosmic phenomena, and space exploration. Includes astronomy, astrophysics, planetary science, cosmology, space physics, astrobiology, and space technology. Investigates stars, galaxies, planets, moons, asteroids, comets, black holes, nebulae, exoplanets, dark matter, dark energy, cosmic microwave background, stellar evolution, planetary formation, space weather, solar system dynamics, the search for extraterrestrial life, and humanity's efforts to explore, understand, and unlock the mysteries of the cosmos through observation, theory, and space missions.
Comprehensive examination of tools, techniques, methodologies, and approaches used across scientific disciplines to conduct research, collect data, and analyze results. Encompasses experimental procedures, analytical methods, measurement techniques, instrumentation, imaging technologies, spectroscopic methods, laboratory protocols, observational studies, statistical analysis, computational methods, data visualization, quality control, and methodological innovations. Addresses the practical techniques and theoretical frameworks enabling scientists to investigate phenomena, test hypotheses, gather evidence, ensure reproducibility, and generate reliable knowledge through systematic, rigorous investigation across all areas of scientific inquiry.
Study of abstract structures, patterns, quantities, relationships, and logical reasoning through pure and applied mathematical disciplines. Encompasses algebra, calculus, geometry, topology, number theory, analysis, discrete mathematics, mathematical logic, set theory, probability, statistics, and computational mathematics. Investigates mathematical structures, theorems, proofs, algorithms, functions, equations, and the rigorous logical frameworks underlying quantitative reasoning. Provides the foundational language and tools for all scientific fields, enabling precise description of natural phenomena, modeling of complex systems, and the development of technologies across physics, engineering, computer science, economics, and all quantitative sciences.
Researchers leverage AI to classify videos of teacher instruction and provide actionable feedback for improved teaching skills. The project aims to support teachers in delivering equitable math instruction while reducing costs.
A study investigated gene-chemical interactions on bacterial growth, revealing varying impacts of chemicals depending on sugar presence. Machine learning analysis found a countervailing effect between genetic and environmental changes, suggesting a strategy for bacterial survival in nature.
A new AI-based model, SCORPIO, developed by Memorial Sloan Kettering Cancer Center and Mount Sinai, uses routine blood tests to predict immunotherapy response for various cancer types. The model outperforms current biomarkers in predicting outcomes, offering a more accessible and affordable solution for patient selection.
The Microelectronics Energy Efficiency Research Center for Advanced Technologies (MEERCAT) will focus on energy efficiency, exploring solutions that bridge sensing, edge processing, artificial intelligence and high-performance computing. Sandia is leading one of the eight energy efficiency-related research projects within the center.
Researchers at Princeton University have developed an AI-powered system to design complex wireless chips, reducing time and cost. The AI creates intricate electromagnetic structures that improve performance and efficiency, often in ways that human designers cannot understand.
These materials integrate liquids within solid frameworks at the mesoscale, driven by competitive interfacial interactions. They demonstrate dynamic responsiveness leveraging force, heat, light, electricity, magnetism, and sound, and exhibit practical functionalities including anti-fouling and multiphase flow control.
A new study from Vanderbilt University Medical Center shows that a clinical alerts-driven AI system can effectively prompt doctors to screen patients for suicide risk during regular clinic visits. The study found that interruptive alerts were more effective than passive alerts, leading to a 42% increase in screenings.
A Northwestern Polytechnical University team evaluated the performance of Gemini and GPT-series models across various medical tasks, finding strengths in report generation and lesion detection. The study highlights the potential of multimodal LLMs in alleviating clinician burden and integrating AI into clinical practice.
Artificial intelligence enhances pandemic preparedness with AI-driven models for outbreak forecasting and optimizing resource allocation. AI accelerates vaccine development by identifying candidates through molecular simulations and designing clinical trials.
A new study evaluates AI's performance in real-world medical conversations and finds significant drops in diagnostic accuracy. Researchers designed a more realistic test called CRAFT-MD to assess the fitness of large-language models for use in clinics.
Researchers from KIT developed AI algorithms that can detect tumors efficiently and precisely. The algorithms are based on deep learning methods and have been shown to excel in the autoPET competition. Further research is needed to improve the algorithms and make them more resistant to external influences.
A new study published in Nature Medicine shows that AI-based models can accurately identify ovarian cancer in ultrasound images, achieving an accuracy rate of 86.3%. The models also reduce the need for expert referrals and misdiagnosis rates by 63% and 18%, respectively.
Researchers warn that AI assistants will combine intimate psychological and behavioral data with persuasive technologies to build trust and manipulate social behavior. The 'Intention Economy' could lead to a lucrative yet troubling marketplace where human intentions are commodified.
The Cambridge Handbook of the Law, Policy, and Regulation for Human-Robot Interaction addresses emerging issues in AI and robots, including privacy, safety, and regulation. The book offers valuable insights into ethical dilemmas and proposes solutions to balance enforceability and flexibility.
Researchers at Tokyo University of Agriculture and Technology developed an explainable AI model to classify videos of splashing and non-splashing drops. The model achieved a success rate of 92% for low-viscosity liquid and 100% for high-viscosity liquid, revealing key differences in droplet behavior during impact stages.
Researchers developed AI-driven therapeutic platform mimicking viral structures to deliver therapeutic genes to target cells. The innovative approach achieved precise symmetrical structures and effectively delivered payloads, paving the way for breakthroughs in gene therapies and next-generation vaccines.
NCSA is leading the way in AI research support, partnering with the National Artificial Intelligence Research Resource Pilot and the NSF-Simons SkAI Institute. The organization is also working on healthcare projects like MarginDX, combining optical imaging technologies with AI screening tools to ensure accurate tumor removal during sur...
A Stanford Medicine study found that AI can help researchers quickly evaluate large amounts of medical data, identifying trends and patterns. The tool was trained on notes from 1,201 children with ADHD, allowing researchers to pinpoint gaps in follow-up care and identify tactics to improve ADHD management.
A new AI-driven approach identifies potentially harmful chemical substances in rivers by monitoring their effects on tiny water fleas, providing insights into complex mixtures and aquatic life. The study enables more comprehensive environmental monitoring and supports better-informed regulations for chemical discharge into waterways.
Current energy-hungry transformer-based systems contrast with Turing's idea of machines that develop intelligence naturally, like human children. AI systems can now perform tasks exclusive to human intellect, such as generating coherent text and discussing abstract ideas, but with limitations on sustainability and societal impact
Robert Johansson's Machine Psychology concept combines adaptive artificial intelligence with psychological learning principles to create a more intelligent AI system. The goal is to implement human-like intelligence in machines, enabling them to learn from experiences and apply knowledge across various situations.
Researchers developed a laser-based artificial neuron that emulates biological graded neuron functions, achieving a signal processing speed of 10 GBaud. This enables fast AI decision-making in time-critical applications with high accuracy.
Researchers create SciAgents framework to autonomously generate and evaluate promising research hypotheses in biologically inspired materials. The framework uses graph reasoning methods to organize relationships between scientific concepts, mimicking biological systems.
A new AI system has been developed to detect compound-type dark jargons on social media, which are used by offenders to evade detection. The system achieves a 7% improvement in accuracy and identifies 93% of newly detected dark jargons as previously unknown, highlighting its potential to reveal emerging terms.
Researchers found that neural stem cells have a rejuvenating effect on nearby brain cells, while T cells promote stress and damage. The study opens new avenues for research into slowing or reversing brain aging.
A new study reveals that people tend to assign more blame to artificial intelligences perceived as having human-like minds. The researchers found that participants blamed the AI more than other parties involved in real-world moral transgressions, such as companies or governments.
Researchers create multilayered chip design that doesn't require silicon wafer substrates, allowing for better communication and computation between layers. This breakthrough enables the construction of fast and powerful AI hardware comparable to supercomputers.
A new study by UCL researchers found that AI systems amplify human biases, leading to a snowball effect where small initial biases increase the risk of human error. The researchers demonstrated real-world consequences, including overestimating white men's likelihood of holding high-status jobs and underestimating women's performance.
Researchers at the University of Washington developed a new method called variational preference learning, which predicts users' preferences and tailors its outputs accordingly. This approach overcomes the limitations of traditional RLHF, which can lead to averaging user preferences and resulting in incorrect outputs for all users.
A new set of internationally-agreed recommendations aims to reduce potential bias in medical AI technologies. The STANDING Together initiative recommends improving dataset diversity, inclusivity, and generalisability to ensure safe and effective use of AI for everyone. These guidelines are now available open access.
The AIRCARE Project will introduce AI-powered systems for real-time diagnosis and precision CO2 laser surgery, improving outcomes for UADT cancer patients. The project aims to reduce positive margins, enhance surgical precision and ease of use, transforming quality of life.
Researchers at MIT have developed Boltz-1, an open-source AI model that achieves state-of-the-art performance in predicting biomolecular structures. The model surpasses AlphaFold3, which is limited to academic research and commercial use, by incorporating new algorithms and improving prediction efficiency.
Researchers from Florida Atlantic University developed an AI system that accurately detects and tracks American Sign Language alphabet gestures using computer vision. The model achieved a detection process with high accuracy, recognizing complex hand gestures with an F1 score of 99% and mAP of 98%.
Combining AI and citizen science enhances SDG monitoring and achievement by addressing data gaps and biases. Successful applications have been demonstrated in addressing environmental indicators, good health, sustainable cities, life below water, and life on land. The integration of these approaches can create synergies to address sust...
Paulo Costa and Shou Matsumoto are developing an explainable artificial intelligence (AI) methodology to help decision-makers trust AI-generated strategies. The project aims to support hypothesis management and identify data requirements to address system complexity and opacity in complex environments.
The Digital Health Institute aims to develop transformative solutions in digital health, including early detection, predictive analytics, and personalized medicine. The initiative will focus on research and development, as well as training the next generation of digital health leaders.
A new AI tool called PlacentaVision can rapidly evaluate placentas at birth to detect abnormalities associated with infection and neonatal sepsis. This could lead to improved health outcomes for both mothers and babies, particularly in areas with limited medical resources.
A new screening method combining laser analysis with AI identifies patients with breast cancer in its earliest stage, stage 1a. This non-invasive technique reveals subtle changes in the bloodstream that occur during the initial phases of the disease, outperforming existing early detection strategies.
A new AI image tool, INQUIRE, can aid in analyzing millions of wildlife images uploaded to the internet for insights into climate change impacts on species. Current AI algorithms can identify species but struggle with more complex questions.
Northwestern University's expertise in AI and astrophysics enables the development of cutting-edge artificial intelligence tools for the Giant Magellan Telescope. The partnership will enhance the telescope's capabilities to search for Earth-like planets, investigate energetic explosions, and explore galaxy-black hole relationships.
The ChangeMaker K-12 program equips rising educators with skills to teach engineering and human-centered design to K-12 students. The program has already seen six cohorts of teacher candidates and over 200 students in grades 1-5 participate.
A team of researchers has developed a novel technique to steal artificial intelligence (AI) models by monitoring electromagnetic signals. The method allows attackers to recreate the high-level features of an AI model with 99.91% accuracy, potentially undermining intellectual property rights and exposing sensitive data.
Researchers developed a deep learning model that classifies pancreatic cancer into molecular subtypes using histopathology images, achieving high accuracy and rapid turnaround time. The AI tool has the potential to improve patient outcomes by enabling timely and tailored treatment strategies.
Researchers developed a new method, k* distribution method, to visualize and assess how well deep neural networks categorize related items together. The model reveals clustered, fractured or overlapping arrangements of data points, indicating accuracy and reliability issues.
Researchers at George Mason University have received $1,049,998 in funding from the Patient-Centered Outcomes Research Institute (PCORI) to develop an AI system that helps patients find the right depression medications. The new study aims to address known challenges in AI and incorporate an empathetic tone.
Researchers at Drexel University developed an AI tool using large language models to identify and suggest alternative words that stigmatize people with substance use disorder. This framework aims to educate users and preserve supportive spaces in online forums.
A comprehensive benchmark evaluates statistical and engineering approaches to federated learning for healthcare applications. Statistical FL methods excel in non-predictive tasks, while engineering-based FL algorithms demonstrate superior predictive performance.
A new technique identifies and removes specific points in a training dataset that contribute most to a model's failures on minority subgroups. This approach maintains the overall accuracy of the model while improving its performance regarding underrepresented groups.
LangBiTe detects biases in AI responses, allowing users to define their own ethical concerns and adapt the evaluation of bias. The tool includes libraries with over 300 prompts focusing on specific ethical issues, such as ageism, LGBTIQA+phobia, and sexism.
The study found that integrating AI into sales teams requires sales managers to combine traditional interpersonal communication competence with new AI-related skills. Effective communication involves motivation, knowledge, empathy, and adaptability, as well as crafting effective prompts to AI and maintaining a polite tone.
A pioneering study using AI interviewing platform has shed light on young Singaporeans' hopes, fears, and unique perspectives on family planning decisions. Key findings indicate that financial concerns are the top barrier to having children, with work-life balance and mental readiness also being significant concerns.
A new shape-changing device called Shape has been developed to help people with visual impairment perform a location task as effectively as sighted people. The study found that participants with visual impairment located targets significantly faster using Shape than with vibration technology, and preferred it over current methods.
Researchers trained an AI system to predict future warming based on climate model simulations and historical temperature data. The study suggests that even in the best-case scenario, global warming will likely exceed 2 degrees Celsius, with severe impacts expected in regions such as South Asia and Central Europe.
A groundbreaking AI model called NitroFusion creates images in seconds using modest hardware, eliminating the need for large computing resources. The open-source technology enables creative professionals and individuals to produce high-quality images affordably.
A study of 9,000 US-based participants reveals that they prioritize efficiency over fairness when choosing between human and algorithmic decision-makers. Notably, Republicans prefer humans more than Democrats, yet most claim fairness is a top priority.
A new system, EXPLINGO, enables AI models to generate readable narratives explaining their predictions, helping users make better decisions. The system, developed by MIT researchers, uses large language models to transform complex explanations into plain language and automatically evaluate their quality.
Cell culture medium optimization is crucial for effective growth of cells, as the medium determines the culture results. Researchers developed a machine learning model that optimizes the composition of the medium based on training data, achieving higher cell concentrations than commercially available media.
A recent study by ESMT Berlin scholars presents a comprehensive framework detailing the impact of AI on open innovation. The framework highlights three key ways in which AI is transforming open innovation practices: enhancing existing methods through efficiency and scalability, enabling new forms of collaboration and business models, a...
Researchers from Bar-Ilan University discover that classifying objects together through Multi-Label Classification can yield better results than detecting individual objects. This new method allows networks to learn correlations between object combinations, making them more recognizable in real-life applications such as autonomous vehi...
Researchers have developed an AI framework called XLuminA that autonomously discovers new experimental designs in microscopy. The framework performs optimizations 10,000 times faster than well-established methods, opening the path for exploring completely new territories in microscopy.