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2,281 papers
Full Changelog: https://github.com/attogram/fantastic-octo-giggle/compare/0001...0002 42 and the Open Error Foundation: An Academic Interpretation Abstract The relationship between 42 and the Open Error Foundation (i.o.) can be understood as more than a recurring joke, reference, or organizational number. It can functi...
Artificial intelligence (AI) has emerged as a transformative force in plant genetics and genetic engineering, addressing long-standing challenges in trait complexity, breeding cycle duration, and genome-editing precision. The convergence of machine learning, deep learning, and multi-omics integration enables the decodi...
Full Changelog: https://github.com/attogram/fantastic-octo-giggle/compare/0001...0002 42 and the Open Error Foundation: An Academic Interpretation Abstract The relationship between 42 and the Open Error Foundation (i.o.) can be understood as more than a recurring joke, reference, or organizational number. It can functi...
This Zenodo record is a permanently preserved version of a PREreview. You can view the complete PREreview at https://prereview.org/reviews/22851045. Summary - This study examines digital financial service adoption among 663 active microfinance borrowers in Ranchi district, Jharkhand, using a TAM/UTAUT-based survey admi...
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This Zenodo record is a permanently preserved version of a PREreview. You can view the complete PREreview at https://prereview.org/reviews/22851045. Summary - This study examines digital financial service adoption among 663 active microfinance borrowers in Ranchi district, Jharkhand, using a TAM/UTAUT-based survey admi...
Change in v1.2.3 (19 September 2026). The Availability-of-data statement is corrected, and nothing else is. It said the deposited database contains 175 records, and it quoted a version DOI alongside the concept DOI. Both had gone stale: the database now holds 210 records, and the version DOI quoted — 10.5281/zenodo.228...
Dataset. The verified reference database and calculation script behind the narrative review Bioelectrical Parameters of Living Systems (Rohera, 2026). Three manuscripts by the same author draw on this database: the narrative review named above (concept DOI 10.5281/zenodo.22829923), a companion review of the electrical...
This part sets out how each of the four scoreboards of Europe's AI position is built: venture capital, GPU-cluster compute, model output and inference prices. On money and compute Europe's shares are 6.1 percent of 2025 global AI venture capital as the EU27, about 12 percent once the UK, Switzerland and Norway are coun...
The AI based pipeline enabled accurate, generalisable, and explainable assessment of abdominal aortic aneurysm patients, including both pre-EVAR evaluation and post-EVAR follow up.
The gap between AI's research promise and clinical readiness is highlighted, which underscores the need for localvalidation, post-market surveillance, and adequate user training as AI tools become incorporated into diagnostic prostate MRI workflows.
This narrative, practice-oriented review maps the 2024-2025 landscape of AI-enabled prescribing in opioid use disorder (OUD) care, where the evidence base is most developed, while noting cautious extension to other substance use disorders (SUDs), and proposes safeguards that keep AI explainable, equitable, transferable...
It is suggested that AI safety in healthcare should be understood as a socio-technical governance process rather than a fixed technical property and a High-Reliability Organisation approach may provide a useful framework for early risk detection and continuous oversight.
MIT Statistics and Data Science Center Director Alexander (Sasha) Rakhlin shares important considerations for departments and institutions.
GPT-Lab
· gpt-lab.eu
Oct 8, 2026
Exploring how generative AI could make machine vision more accessible to businesses. The post GenEye in a Box: Making Machine Vision Something You Can Just Ask For appeared first on GPT-Lab.
By rethinking how large cloud computing systems operate, Associate Professor Christina Delimitrou seeks to make data centers more energy efficient.
Training AI agents with reinforcement learning can be challenging because their tools, context, and decision-making are managed by complex frameworks. Agent Lightning connects existing agents to RL training, making it easier to improve them without rebuilding them. The post Agent Lightning v1.0: A 3,500-Line Lightweight Agentic RL Framework for Training Agents with Real Harnesses appeared first on Microsoft Research.
An ongoing survey tracks the latest AI accelerator systems to keep hardware relevant for Lincoln Laboratory staff and sponsors.
Jennifer Neville did not want to go into computer science—but that’s exactly where she landed. Neville discusses the starts and stops that led to her professional sweet spot and her work identifying “surprising failures” making it hard for AI to handle complexity. The post What AI gets wrong and what failure teaches us appeared first on Microsoft Research.
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