Category: Machine Learning

K1x plans to use this new funding to expand its use of ML and genAI across its products. Credit: Katawaredokii/Shutterstock.com. K1x, a US-based AI-native private market tax data platform, has raised $175 million in growth funding. The financing was led by Sumeru Equity Partners, with participation from existing investor Edison Partners. Access deeper industry intelligence […]

Sysdig has released its 2026 Cloud-Native Security and Usage Report. It shows that organizations are moving from human-driven security operations to machine-speed detection and response. The findings are based on an analysis of billions of software packages and hundreds of thousands of cloud identities. Sysdig claims that security teams are adapting to faster attack cycles […]

Data collection and curation The complete dataset including all physicochemical properties, loading metrics, cytotoxicity values, and composition details of all 75 nanocarriers is provided in Supplementary Table S1. This dataset included a wide variety of nanocarriers, including polymeric nanoparticles, lipid-based systems, inorganic nanoparticles, metal-organic frameworks, and hybrid composites. Information captured for every entry includes: Structural […]

Asm we have obtained considerable knowledge about the data and can easily build models. To find an appropriate ML model for our proposed system, this study conducts two experiments on datasets using the sklearn and keras libraries of python. sklearn and keras are Python libraries that are used to train ML and Deep learning models, […]

The program funds overseas postdoctoral research for UAE nationals in the field of AI. The Mohammed bin Zayed University of Artificial Intelligence has launched the Ruwwad AI Scholars (RAIS) Fellowship, a fully funded two-year postdoctoral program for UAE nationals who have recently completed their Ph.D. The initiative supports advanced research placements at international institutions with […]

For centuries, war has been seen as a failure of human foresight. Diplomats respond, militaries prepare, and academics analyze, but conflict is rarely accurately predicted in advance. Now, that may be changing. Advances in deep learning neural networks are moving competitive predictions from guesswork to more accurate, data-driven predictions. The focus is no longer on […]

dataset For pre-training, we selected 189 compounds from 10 MoA classes (ATPase, Aurora Kinase, HDAC, JAK, HSP, PARP, protein synthesis, topoisomerase, tubulin polymerization inhibitor, and retinoid receptor agonist, see distribution in Table SM1) at 10uM, similar to Harrison et al.52 They were randomly distributed into eight 384-well plates seeded with human osteosarcoma U2OS cells. Each […]

Project Maven, officially the Algorithmic Warfare Cross-Functional Team (AWCFT), was established in a memorandum signed by Deputy Secretary of Defense Robert O. Work on 26 April 2017. The memorandum directed the Department of Defense to accelerate the integration of big data, machine learning, and computer vision into intelligence workflows, beginning with the processing, exploitation, and […]

Overall strategies The aim of this work is to apply strategies of optimal pattern recognition to problems for atomistic machine learning. We will begin in the “Pattern recognition based on the method of Langbein and flexible descriptor sets” section by explaining these strategies in the abstract, applied to a generic set of invariant features, to […]

Dataset The dataset used in this study originates from a retrospective cohort of residents from four DomusVi nursing homes in Spain. Ethical approval for the study was granted by the relevant institutional committee (Code: 2023/576). The database contains information from 2,608 residents and includes 4,718,828 activity records collected over a 13-year period (2011–2024). Each entry […]