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Archive/ai research

🔬 AI Research

Academic papers, research breakthroughs, and scientific advances in machine learning and AI.

319 articles

Importance:ResearchML in healthcare/genomics

Machine learning in prediction and classification of type 1 diabetes

Genetic prediction of type 1 diabetes is one of the most successful for complex traits. A machine learning approach now improves this further and discovers... Source: nature.com

Importance:ResearchLLM reasoning / diffusion models

LaDiR: Latent Diffusion Enhances LLMs for Text Reasoning

Large Language Models (LLMs) demonstrate their reasoning ability through chain-of-thought (CoT) generation. However, LLM's autoregressive… Source: machinelearning.apple.com

Importance:ResearchAI fairness / debiasing

Solving the “Whac-a-mole dilemma”: A smarter way to debias AI vision models

A new debiasing approach called WRING resolves the "Whac-a-Mole dilemma" of existing debiasing approaches that can create or amplify existing biases. Source: news.mit.edu

Importance:Researchrepresentation learning in healthcare

Advancing Multi-Institutional EHR Studies via Representation Learning

In a groundbreaking development poised to revolutionize medical research across borders, a team of scientists led by Zhou, D., Tong, H., and Wang,... Source: bioengineer.org

Importance:Researchbiological neural networks

Researchers train living rat neurons to perform…

Japanese researchers trained cultured rat cortical neurons to autonomously generate complex temporal signals using a real-time machine learning… Source: inkl.com

Importance:Researchfoundation models, biological aging prediction

Meet MaxToki: The AI That Predicts How Your Cells Age — and What to Do About It

Researchers at Gladstone Institutes have built a temporal foundation model that forecasts cell state trajectories across the human lifespan — and... Source: marktechpost.com

Importance:LaunchAI for astronomy

Carnegie Mellon Launches New Effort To Advance AI-Driven Astronomy

At Carnegie Mellon University, a new initiative will bring together experts in AI, statistics and astrophysics to accelerate that shift. Source: cmu.edu

Importance:Researchbiological neural networks

Wetware AI: Living Brain Cells Trained to Run Chaos Math

Can living neurons replace AI? A new study shows that biological neural networks (BNNs) can be trained to perform reservoir computing. Source: neurosciencenews.com

Importance:Researchbiological computing and neural networks

Biological neural networks may serve as viable alternatives to machine learning models

A research team at Tohoku University and Future University Hakodate has demonstrated that living biological neurons can be trained to perform a supervised... Source: news-medical.net

Importance:Researchscaling laws and AI capabilities

'More is Different': Research shows scale alone does not explain AI's power—specialization and cooperation do

One of the most influential scientific and philosophical viewpoints is "More is Different," introduced in 1972 by Nobel Prize–winning physicist Philip W. Source: techxplore.com

Importance:ResearchML applications

Machine learning uncovers thousands of unknown bacterial immune defense systems

Bacterial immune systems protect against viral invaders called phages by precisely targeting specific phage genetic sequences. Source: news-medical.net

Importance:ResearchML applications

FuXi-Air: air quality forecasting based on emission-meteorology-pollutant multimodal machine learning

Air pollution has emerged as a major public health challenge worldwide. Numerical simulations and single-site machine-learning approaches in air quality... Source: nature.com

Importance:Researchbiological computing

Living Brain Cells Enable Machine Learning Computations

A collaborative research group has shown that biological neurons can be trained to perform a temporal pattern learning task that was previously carried out... Source: asiaresearchnews.com

Importance:ResearchLLM applications in research

AI inspires new research topics in materials science

Researchers at KIT analyze materials science literature; combination of large language models and machine learning indicates trends for future research. Source: eurekalert.org

Importance:Researchphysics-informed ML

Ultra‑robust machine‑learning models run stable molecular simulations at extreme temperatures

Researchers at The University of Manchester have created a physics‑informed machine‑learning model that can run molecular simulations for unprecedented... Source: phys.org

Importance:ResearchPolicy gradient algorithms for language models

Entropy-Preserving Reinforcement Learning

Policy gradient algorithms have driven many recent advancements in language model reasoning. An appealing property is their ability to learn… Source: machinelearning.apple.com

Importance:ResearchAI for drug discovery

AI tool streamlines drug synthesis

Drug discovery is like molecular Tetris. Chemists snap atoms together, adjusting the pieces until everything fits and suddenly, a molecule makes a promising... Source: technology.org

Importance:Researchquantum vs classical ML

Quantum vs classical AI: Traditional models still lead in phishing detection

Quantum machine learning is being explored as the next frontier in cybersecurity, but new research shows it remains far from replacing established... Source: devdiscourse.com

Importance:Researchquantum machine learning theory

Quantum Machine Learning Gains Tighter Performance Guarantees With New Bounds

Scientists at the University of the Basque Country UPV/EHU, in collaboration with researchers at the University of Warwick and Freie Universität Berlin,... Source: quantumzeitgeist.com