A new machine learning algorithm analyzed high-resolution digital images of herbarium specimens, revealing that factors other than climate have a strong effect on leaf size within a plant species. The study also demonstrates how AI can be used to transform static specimen collections and quickly document climate change effects.
SourceUniversity of New South Wales·JournalAmerican Journal of Botany·TypeComputational simulation/modeling·DateJun 19, 2023
Apple MacBook Pro 14-inch (M4 Pro)
Apple MacBook Pro 14-inch (M4 Pro) powers local ML workloads, large datasets, and multi-display analysis for field and lab teams.
Researchers developed a new method for controlling lower limb exoskeletons using deep reinforcement learning, enabling more robust and natural walking control. The system has the potential to benefit users with spinal cord injuries, multiple sclerosis, stroke, and other neurological conditions.
SourceKessler Foundation·JournalJournal of NeuroEngineering and Rehabilitation·TypeComputational simulation/modeling·DateJun 15, 2023
Generative AI raises fundamental questions about the creative process and human's role in it. Researchers highlight gaps in understanding perceptions of AI-generated content, ownership, credit, labor economics, and media ecosystem impact.
SourceMassachusetts Institute of Technology·JournalScience·DateJun 15, 2023
A new approach to enhance artificial intelligence-powered computer vision technologies has been developed by UCLA researchers, adding physics-based awareness to data-driven techniques. This hybrid methodology aims to improve how AI-based machinery sense, interact, and respond to their environment in real time.
SourceUniversity of California - Los Angeles·JournalNature Machine Intelligence·TypeCommentary/editorial·DateJun 14, 2023
A new research project at University of Leicester will develop a digital 'twin' of the UK using artificial intelligence and big data to inform environmentally-friendly land use. The project aims to reduce emissions from cattle and sheep farming, which contribute around 10% of the UK's emissions.
Apple iPhone 17 Pro
Apple iPhone 17 Pro delivers top performance and advanced cameras for field documentation, data collection, and secure research communications.
Research by Francis de Véricourt and Huseyin Gurkan found that trust in machines' decision-making ability is key to effective learning. They discovered that biased learning occurs when humans override algorithmic decisions without observing the machine's correctness, leading to incorrect usage of machines in decision making.
SourceESMT Berlin·JournalManagement Science·TypeComputational simulation/modeling·DateJun 14, 2023
A new research paper challenges the idea that unlimited trials are needed to learn safe actions in unfamiliar environments. The team presents a fresh approach that ensures learning safe actions with complete confidence while managing tradeoffs between optimality and exposure to unsafe events.
SourceUniversity of Pittsburgh·JournalIEEE Transactions on Automatic Control·DateJun 14, 2023
A machine-learning study has found that individual characteristics, including age and weight, determine which drug combinations most effectively reduce COVID-19 recurrence rates. The study used real-world data from a hospital in China and identified unique treatment combinations for different demographic groups.
SourceUniversity of California - Riverside·JournalFrontiers in Artificial Intelligence·TypeData/statistical analysis·DateJun 13, 2023
Researchers have developed a new AI model that can quickly screen large libraries of potential drug compounds against target proteins. The ConPLex model uses language analysis to match potential drugs with proteins without needing to calculate molecular structures, enabling fast screening of over 100 million compounds per day.
SourceMassachusetts Institute of Technology·JournalProceedings of the National Academy of Sciences·DateJun 9, 2023
MethaneMapper is an artificial intelligence-powered hyperspectral imaging tool that can detect real-time methane emissions and trace them to their sources. With a performance accuracy of 91%, it has the potential to revolutionize the way we monitor oil and gas operations and curb climate change.
SourceUniversity of California - Santa Barbara·JournalEcology Letters·DateJun 8, 2023
SAMSUNG T9 Portable SSD 2TB
SAMSUNG T9 Portable SSD 2TB transfers large imagery and model outputs quickly between field laptops, lab workstations, and secure archives.
A group of educators is urging caution when using artificial intelligence (AI) in special education, highlighting its potential to benefit students with disabilities. The authors emphasize the need for careful consideration of AI's uses and limitations, including information literacy, consent, and critical thinking.
SourceUniversity of Kansas·JournalJournal of Special Education Technology·TypeCommentary/editorial·DateJun 8, 2023
A chemist at the University of Kansas has developed a digital tool that can spot scientific text generated by ChatGPT with 99% accuracy. The tool, which was published in Cell Reports Physical Science, uses human insight and intuition to identify key differences between human-written and AI-generated texts.
SourceUniversity of Kansas·JournalCell Reports Physical Science·DateJun 8, 2023
Researchers at NYU Grossman School of Medicine have developed an AI tool called NYUTron that can accurately estimate patients' risk of death, length of hospital stay, and other factors important to care. The tool achieved impressive results in predicting readmission rates, improving upon standard methods by up to 7%.
SourceNYU Langone Health / NYU Grossman School of Medicine·JournalNature·DateJun 7, 2023
A team of researchers developed a tool to identify AI-generated academic science writing with high accuracy, using characteristics such as predictability, paragraph structure and vocabulary. The model outperformed existing AI text detectors and has potential applications in assessing student essays.
SourceCell Press·JournalCell Reports Physical Science·TypeComputational simulation/modeling·DateJun 7, 2023
GQ GMC-500Plus Geiger Counter
GQ GMC-500Plus Geiger Counter logs beta, gamma, and X-ray levels for environmental monitoring, training labs, and safety demonstrations.
Researchers developed a new AI framework that significantly improves the ability to analyze team communication, enabling adaptive training technologies to facilitate effective team collaboration. The framework performed substantially better than previous AI technologies in classifying dialogue and following information flow.
SourceNorth Carolina State University·TypeComputational simulation/modeling·DateJun 6, 2023
Researchers at Mount Sinai have developed an AI model called HeartBEiT that can analyze electrocardiograms as language, enabling more accurate diagnoses. The model outperformed established methods in comparison tests and demonstrated improved performance with lower sample sizes.
SourceThe Mount Sinai Hospital / Mount Sinai School of Medicine·Journalnpj Digital Medicine·TypeComputational simulation/modeling·DateJun 6, 2023
Optical memristors have the potential to transform high-bandwidth neuromorphic computing, machine learning hardware, and artificial intelligence. However, scalability is a significant challenge that needs to be addressed to unlock their full potential.
SourceUniversity of Pittsburgh·JournalNature Photonics·DateJun 5, 2023
Sky-Watcher EQ6-R Pro Equatorial Mount
Sky-Watcher EQ6-R Pro Equatorial Mount provides precise tracking capacity for deep-sky imaging rigs during long astrophotography sessions.
A new study by Carnegie Mellon University researchers finds that crime risk assessment tools, such as machine learning models, are prone to cohort bias when ignoring social change dynamics. This bias can generate inequality in the criminal justice system, distinct from racial bias.
SourceCarnegie Mellon University·JournalProceedings of the National Academy of Sciences·DateJun 5, 2023
A recent study has found that microbes play a crucial role in storing carbon in the soil, with a four-fold greater importance than other processes. This breakthrough could lead to improved soil health and increased food security through targeted farm management practices.
Researchers developed a method using artificial intelligence to track changes in brain synapses, enabling better understanding of how connections change with learning, aging, injury and disease. Machine learning was leveraged to enhance image quality, allowing for detection and tracking of individual synapses.
SourceJohns Hopkins Medicine·JournalNature Methods·DateJun 5, 2023
Celestron NexStar 8SE Computerized Telescope
Celestron NexStar 8SE Computerized Telescope combines portable Schmidt-Cassegrain optics with GoTo pointing for outreach nights and field campaigns.
A new framework developed by Carnegie Mellon University researchers significantly reduces consumers' privacy risk while preserving advertisers' utility in mobile location data analysis. The framework uses machine learning to quantify personalized privacy risks and performs personalized data obfuscation.
SourceCarnegie Mellon University·JournalInformation Systems Research·DateJun 5, 2023
Researchers trained a robotic chef to watch and learn from cooking videos, enabling it to identify ingredients and actions. The robot recognized 93% of the correct recipe from 16 videos, including variations and new recipes, showcasing its potential for automated food production and cost-effective deployment.
SourceUniversity of Cambridge·JournalIEEE Access·DateJun 4, 2023
Researchers updated their protein localization prediction model, MULocDeep, to provide more targeted predictions for biological discoveries. The tool helps researchers design more effective experiments and advance scientific discoveries related to drug development and treating diseases like epilepsy.
SourceUniversity of Missouri-Columbia·JournalNucleic Acids Research·DateJun 2, 2023
Researchers develop AI-based method to quantify cracking patterns in reinforced concrete structures, enabling more accurate and efficient assessments of structural damage. The approach uses graph theory and machine learning algorithms to create a unique 'fingerprint' for each set of cracks, allowing for quick and consistent evaluations.
SourceDrexel University·JournalComputer-Aided Civil and Infrastructure Engineering·TypeComputational simulation/modeling·DateJun 1, 2023
Anker Laptop Power Bank 25,000mAh (Triple 100W USB-C)
Anker Laptop Power Bank 25,000mAh (Triple 100W USB-C) keeps Macs, tablets, and meters powered during extended observing runs and remote surveys.
Researchers at North Carolina State University have developed a new methodology called Patch-to-Cluster attention (PaCa) that addresses the challenges of vision transformers. PaCa improves ViT's ability to identify, classify, and segment objects in images while reducing computational demands and enhancing model interpretability.
SourceNorth Carolina State University·TypeComputational simulation/modeling·DateJun 1, 2023
Researchers developed an AI system, Geneformer, to predict how disruptions in human gene connections cause disease. The model, trained on data from thousands of genes, can identify potential drug targets for diseases like heart disease and cancer.
A new study published in The Neuroradiology Journal introduces an artificial intelligence computer program that can accurately identify changes in brain structure resulting from repeated head injury. This AI tool uses machine learning to process magnetic resonance imaging (MRI) scans and distinguish between the brains of male athletes ...
SourceNYU Langone Health / NYU Grossman School of Medicine·JournalThe Neuroradiology Journal·TypeExperimental study·DateMay 30, 2023
Rigol DP832 Triple-Output Bench Power Supply
Rigol DP832 Triple-Output Bench Power Supply powers sensors, microcontrollers, and test circuits with programmable rails and stable outputs.
Researchers are exploring the use of large-scale pre-trained vision-language models (PT-VLM) to develop a new methodological framework for harnessing their power. The project aims to identify basic skills required by VisualQA and design methods to augment pre-trained models with additional skills, such as object recognition and spatial...
Researchers identified five subtypes of heart failure using machine learning, including early onset and atrial fibrillation related. These subtypes have different mortality risks, with some patients at higher risk of dying within a year after diagnosis.
SourceUniversity College London·JournalThe Lancet Digital Health·TypeData/statistical analysis·DateMay 26, 2023
Researchers at Carnegie Mellon University argue against granting rights to robots, instead suggesting a Confucian approach of assigning roles to promote teamwork and harmony. This alternative perspective recognizes the moral status of robots as entities capable of participating in rites and contributing to society.
SourceCarnegie Mellon University·JournalCommunications of the ACM·DateMay 25, 2023
Meta Quest 3 512GB
Meta Quest 3 512GB enables immersive mission planning, terrain rehearsal, and interactive STEM demos with high-resolution mixed-reality experiences.
Researchers at the Beckman Institute for Advanced Science and Technology have developed a new framework for super-resolution ultrasound using deep learning, reducing processing speeds from minutes to seconds. The new technology enables real-time blood flow visualization, overcoming challenges faced by conventional methods.
SourceBeckman Institute for Advanced Science and Technology·JournalIEEE Transactions on Medical Imaging·TypeImaging analysis·DateMay 25, 2023
Researchers used AI to identify a compound that kills Acinetobacter baumannii, a bacterium responsible for many drug-resistant infections. The new antibiotic shows promise in combating this growing public health threat.
SourceMassachusetts Institute of Technology·JournalNature Chemical Biology·TypeComputational simulation/modeling·DateMay 25, 2023
Scientists at McMaster University and MIT have used AI to discover a new antibiotic targeting Acinetobacter baumannii, a deadly drug-resistant pathogen. The new antibiotic, abaucin, targets only A. baumannii, reducing the risk of rapid resistance development.
SourceMcMaster University·JournalNature Chemical Biology·TypeComputational simulation/modeling·DateMay 25, 2023
Researchers found that formalin fixation does not significantly alter the polarimetric properties of brain tissue, making it suitable for training machine-learning models. The study suggests that formalin-fixed brain tissue specimens can provide high-quality data for rapid and accurate diagnostic imaging in surgery.
SourceSPIE--International Society for Optics and Photonics·JournalNeurophotonics·DateMay 25, 2023
CalDigit TS4 Thunderbolt 4 Dock
CalDigit TS4 Thunderbolt 4 Dock simplifies serious desks with 18 ports for high-speed storage, monitors, and instruments across Mac and PC setups.
Researchers developed a mobile application to detect Alzheimer's and mild cognitive impairment from speech data. The app achieved high accuracy rates, demonstrating its potential as an early detection tool.
SourceUniversity of Tsukuba·JournalComputer Speech & Language·DateMay 25, 2023
Researchers used AI models to predict effective peptide sequences for safe drug delivery in eye cells, promising new treatments for glaucoma and macular degeneration. The model accurately predicted a peptide sequence that bound to melanin, releasing medications over several weeks.
SourceJohns Hopkins Medicine·JournalNature Communications·DateMay 24, 2023
Researchers create an AI-based approach to predict precipitation intensity and variability, addressing the missing piece of cloud organization in traditional climate models. The new algorithm improves precipitation predictions, including extreme events, and enables better projections of future changes in the water cycle.
SourceColumbia University School of Engineering and Applied Science·JournalProceedings of the National Academy of Sciences·DateMay 24, 2023
A study from the University of Chicago uses machine learning to record intricate tongue movements and neural activity, revealing that brain patterns can accurately predict 3D tongue shape. This breakthrough could lead to brain-computer interface-based prosthetics for restoring lost functions of feeding and speech.
SourceUniversity of Chicago·JournalNature Communications·TypeExperimental study·DateMay 24, 2023
A machine learning model trained on clinical text notes can effectively categorize patients into 10 risk groups, allowing for targeted care. The study found that patients in lower-risk groups had lower rates of lung inflammation and were less likely to receive antibiotics or chest X-ray referrals.
SourceAmerican Academy of Family Physicians·JournalThe Annals of Family Medicine·DateMay 23, 2023
GoPro HERO13 Black
GoPro HERO13 Black records stabilized 5.3K video for instrument deployments, field notes, and outreach, even in harsh weather and underwater conditions.
Researchers at Duke University have discovered a class of compounds called argyrodites that could lead to the development of safer and more efficient solid-state batteries. The materials' unique crystalline structures allow for fast ion conduction, making them promising candidates for energy storage applications.
SourceDuke University·JournalNature Materials·TypeExperimental study·DateMay 22, 2023
A team of researchers developed a deep-learning model called WearNet that uses Fitbit data to detect depression and anxiety. The study found that WearNet performed better than state-of-the-art machine learning models in detecting these conditions, producing individual-level predictions.
A new CAR T cell design approach using machine learning and artificial intelligence is being developed to improve cancer treatment. The project aims to create a hybrid knowledge- and data-driven approach to guide the design of immunotherapeutic cells.
This field uses trial-and-error learning with natural selection to solve complex reinforcement learning tasks, but requires significant computational resources. Researchers can enhance its efficiency by improving encoding, sampling, search operators, algorithmic frameworks, and evaluation methods.
SourceIntelligent Computing·JournalIntelligent Computing·DateMay 19, 2023
Researchers used machine learning to identify 'synthetic extreme' DNA sequences that are active in humans but not fruit flies. These rare sequences have potential practical applications in biotechnology and biomedical research.
SourceUniversity of California - San Diego·JournalGenes & Development·TypeComputational simulation/modeling·DateMay 18, 2023
Apple AirPods Pro (2nd Generation, USB-C)
Apple AirPods Pro (2nd Generation, USB-C) provide clear calls and strong noise reduction for interviews, conferences, and noisy field environments.
A new machine learning-based model predicts individual cardiac surgery patient mortality risk with improved performance over current population-derived models. The model uses electronic health records to provide personalized risk assessments, offering a significant advantage over existing benchmarks.
SourceThe Mount Sinai Hospital / Mount Sinai School of Medicine·JournalJournal of Thoracic and Cardiovascular Surgery·TypeData/statistical analysis·DateMay 17, 2023
A machine learning model uses patterns in mineral associations to predict previously unknown mineral occurrences, including geologically important minerals like uraninite and rutherfordine. The model also identified promising areas for critical rare earth element and lithium minerals.
An AI developed at TU Wien has shown to suggest appropriate treatment steps in cases of blood poisoning, outperforming human decisions. The AI can examine time-varying patient conditions and calculate treatment strategies, increasing cure rates by up to 3%. However, legal aspects and liability need discussion.
SourceVienna University of Technology·JournalJournal of Clinical Medicine·DateMay 11, 2023
A new AI algorithm named CoDE-ACS can quickly and accurately rule out heart attacks in patients, improving diagnosis and reducing hospital admissions. The tool has the potential to reduce misdiagnosis and inequalities in diagnosis across different populations.
SourceBritish Heart Foundation·JournalNature Medicine·DateMay 11, 2023
Kestrel 3000 Pocket Weather Meter
Kestrel 3000 Pocket Weather Meter measures wind, temperature, and humidity in real time for site assessments, aviation checks, and safety briefings.
A Rensselaer researcher has used artificial intelligence to discover novel van der Waals (vdW) magnets with large magnetic moments. These two-dimensional vdW magnets have the potential to advance science and technology in data storage, spintronics, and quantum computing.
SourceRensselaer Polytechnic Institute·JournalAdvanced Theory and Simulations·TypeComputational simulation/modeling·DateMay 11, 2023
Researchers used AI to analyze speech patterns of patients with Parkinson's disease, finding they spoke in shorter sentences with more verbs and fewer common nouns. The study suggests potential early detection methods for the condition through conversational analysis.
SourceNagoya University·JournalParkinsonism & Related Disorders·DateMay 11, 2023
New research from ESMT Berlin suggests that using machine-based predictions can improve overall accuracy of human decisions, but also increase the likelihood of certain errors and the human's cognitive effort. The study highlights the importance of collaboration between humans and machines to maximize complementary strengths.
SourceESMT Berlin·JournalManagement Science·DateMay 11, 2023
A new advanced artificial intelligence system has been developed in the UK that can accurately identify protein patterns within individual cells. The HCPL system uses a deep-learning model to quickly and accurately determine subcellular structures where proteins are present.
SourceUniversity of Surrey·JournalCommunications Biology·DateMay 10, 2023
Researchers found that machine-learning models trained with descriptive data label rule violations more harshly than humans, leading to potential serious implications in the real world. This study highlights the need for careful consideration of data labeling and training methods to ensure fairness and accuracy in AI decision-making.
SourceMassachusetts Institute of Technology·JournalScience Advances·DateMay 10, 2023
Creality K1 Max 3D Printer
Creality K1 Max 3D Printer rapidly prototypes brackets, adapters, and fixtures for instruments and classroom demonstrations at large build volume.
A team of researchers has developed an AI tool called CRANK-MS that uses neural networks to analyze biomarkers in patients' bodily fluids and predict Parkinson's disease onset with an accuracy of up to 96%. The tool may help identify early warning signs for the disease, which can be challenging to diagnose.
SourceUniversity of New South Wales·JournalACS Central Science·TypeObservational study·DateMay 9, 2023
A team of researchers developed an unsupervised entity alignment framework to improve knowledge graph search, avoiding human labor. The framework outperformed most competitors on precision and recall, scoring higher overall across multiple datasets.
SourceIntelligent Computing·JournalIntelligent Computing·TypeExperimental study·DateMay 9, 2023
Researchers developed EmbryoNet, an automated image analysis software that uses AI to detect and classify developmental defects in fish embryos. The software outperforms human experts in terms of speed and accuracy, making it a valuable tool for investigating the mechanisms of drug action and studying embryonic development.
SourceUniversity of Konstanz·JournalNature Methods·DateMay 8, 2023
Garmin GPSMAP 67i with inReach
Garmin GPSMAP 67i with inReach provides rugged GNSS navigation, satellite messaging, and SOS for backcountry geology and climate field teams.
Researchers develop a new online learning algorithm that enables the training of larger spiking neural networks with six million neurons. This allows for faster and more efficient processing of tasks such as speech recognition and object detection.
Dr. Miaomiao Zhang's research aims to automate late mechanical activation detection from cardiac magnetic resonance images using machine learning and AI techniques. This could lead to more accurate placement of CRT electrodes and improved patient outcomes.
SourceUniversity of Virginia School of Engineering and Applied Science·DateMay 8, 2023
A new video anomaly detection algorithm (COVAD) uses content-based attention to focus on objects in frames, improving performance over baseline models. The algorithm also refines the memory module for normal behavioral patterns.
SourceBeijing Zhongke Journal Publising Co. Ltd.·JournalVirtual Reality & Intelligent Hardware·DateMay 8, 2023
Researchers from Integrated Biosciences developed an AI platform to discover novel senolytic compounds, a class of molecules targeting age-related processes. The platform identified three highly selective and potent compounds with favorable medicinal chemistry properties.
SourceTen Bridge Communications·JournalNature Aging·TypeComputational simulation/modeling·DateMay 5, 2023