Academic papers, research breakthroughs, and scientific advances in machine learning and AI.
319 articles
PACMAN is an AI-based control framework designed to manage fusion systems safely, making critical decisions within milliseconds. Its speed is meant to help prevent instabilities that could disrupt or damage fusion reactors. Source: phys.org
A collaboration linking MIT research with IBM's technology stack aims to accelerate how AI and quantum computing move from lab to real-world use. Details on specific projects or timelines were not provided. Source: news.mit.edu
Australian research agency CSIRO, through its Data61 unit, has developed a defense technique designed to protect machine learning models from adversarial attacks. The method works like a vaccine, exposing models to manipulated inputs in advance so they become more resistant to malicious interference. Source: zdnet.com
Researchers are exploring whether AI models can identify Parkinson's patients likely to experience more rapid disease progression. Early detection of high-risk patients could help tailor treatment and monitoring strategies. Source: news.med.miami.edu
A study presents a method for predicting concrete strength using domain-specific feature engineering paired with the explainable machine learning model LightGBM. The approach aims to improve prediction accuracy while keeping the model's decisions interpretable for engineers. Source: nature.com
Google AI has introduced EnvHarness, a programmable layer designed to convert static agent environments into dynamic, adaptive training worlds. The tool aims to give AI agents more realistic and flexible conditions to learn from during training. Source: marktechpost.com
Researchers are exploring federated learning as a way to train large language models across distributed data sources without centralizing or sharing sensitive information. The approach could help address privacy concerns tied to training AI on private datasets. Source: bioengineer.org
Researchers introduced 'Code-as-World,' an agentic system that converts real-world video footage into executable MuJoCo physics programs. The approach uses an iterative loop to translate visual scenes into code-based simulations that can be run and manipulated as physics models. Source: marktechpost.com
A large-scale study analyzing data from 500,000 pregnancies worldwide found that AI models can identify risk indicators early in pregnancy. The findings suggest AI-based screening could support earlier intervention and better outcomes for mothers and babies. Source: labroots.com
A new research approach called Agent Seer synthesizes test scenarios by having AI systems interpret and understand written specifications. The method aims to automate scenario creation for validating complex software behavior. Source: machinelearning.apple.com
Researchers used machine learning to map how the immune system's response evolves over time in patients with sepsis. The approach could help identify critical shifts in immune activity that inform treatment timing. Source: news-medical.net
Researchers warn that widely used benchmarks for evaluating AI models in drug discovery may contain hidden flaws, potentially inflating or misrepresenting performance results. This raises concerns about the reliability of current leaderboards used to compare AI systems in pharmaceutical research. Source: chemistryworld.com
Scientists used gas chromatography-mass spectrometry (GC-MS) together with machine learning to identify a chemical signature linked to bladder cancer in urine samples. The approach could pave the way for a non-invasive diagnostic tool. Source: chromatographytoday.com
Researchers propose a generalizable multiple-instance learning approach designed to work reliably across different computational pathology tasks. The method targets improved consistency when analyzing medical imaging data at scale. Source: nature.com
A new AI system can spot subtle warning signs of incoming solar storms up to nine hours earlier than previous methods. Earlier detection could give power grids and satellite operators more time to prepare for disruptions. Source: universetoday.com
Researchers have developed an AI-based framework to optimize the operation of solid oxide electrolysis cells, a technology used for efficient hydrogen production. The approach aims to boost performance and stability of these energy systems. Source: techxplore.com
A study demonstrates how machine learning can go beyond simple chlorophyll measurements to estimate diagnostic phytoplankton pigments using multispectral ocean-color satellite data. This offers a more detailed picture of marine ecosystem health. Source: astrobiology.com
A new research review examines how machine learning can improve the delivery of 360° video content across 5G and future B5G networks. It highlights emerging use cases as well as technical hurdles still facing widespread adoption. Source: link.springer.com
A new machine learning method has helped scientists detect previously unseen patterns in DNA methylation data. The findings could deepen understanding of how epigenetic changes influence gene activity. Source: phys.org
Researchers used a machine learning model to screen roughly 500,000 possible perovskite materials for solar cell applications. The approach narrowed the pool down to just 38 promising candidates for further study. Source: azom.com