Category: Machine Learning

the loudest conversation about AI and work Focus on what disappears. A more pressing problem within IT is one that is quietly proliferating. As AI capabilities spread across the stack, work is broken down into new, poorly defined skill requirements, such as prompt engineering here, orchestration there, and model evaluation somewhere in between. None of […]

Redis further expands its presence in the machine learning software stack with the launch of Redis Feature Form, a managed feature store for production machine learning. Following Redis’ acquisition of Featureform, this release unifies feature definition, orchestration, versioning, and servicing into a single platform. The system is designed to help machine learning teams move models […]

Zhang, J., Fei, Y., Sun, L. & Zhang, Q. C. Advances and opportunities in RNA structure experimental determination and computational modeling. Nat. Methods 19, 1193–1207 (2022). Article  Google Scholar  Wang, W., Su, B., Peng, Z. & Yang, J. Integrated experimental and AI innovations for RNA structure determination. Nat. Biotechnol. 44, 205–214 (2026). Article  Google Scholar  […]

As a disruptive technology resulting from the deep integration of artificial intelligence and material science, AI + new materials are driving a paradigm revolution in material research and development, shifting from the “empirical trial – and – error” approach to “intelligent creation.” With the qualitative leap of large AI models in understanding complex structures, generating […]

image: Important research information for AACR Abstract 4003 view more Credit: University of Texas MD Anderson Cancer Center Path-IO is a machine learning platform that incorporates pathology data to predict how non-small cell lung cancer patients will respond to immunotherapy. Unlike molecular approaches, Path-IO uses pathological data that is already routinely collected from patients. Path-IO […]

In the continuous pursuit of seamless human-machine interfaces and wearable electronics, the critical challenge of mechanical mismatch in the interface between flexible devices and human skin remains a formidable barrier. This mismatch not only compromises sensor adhesion and comfort, but also significantly reduces signal fidelity and energy harvesting efficiency during dynamic body movements. To address […]

Written by Adam Zeve Inside a giant autonomous warehouse, hundreds of robots roam the aisles, collecting and delivering goods and fulfilling a steady stream of customer orders. In this congested environment, even a small traffic jam or a small collision can snowball into massive speed reductions. To avoid this avalanche of inefficiencies, researchers at MIT […]

The following article is written by Pankaj Goyal, Co-Founder and COO of AutoNXT The global battery industry is undergoing a major transformation due to the fusion of advanced manufacturing technology and intelligent technology. As global battery demand continues to grow rapidly, exceeding 1 terawatt hour (TWh) in 2024, manufacturers are under pressure to improve performance, […]

image: Biologically inspired auxetic triboelectric nanogenerators exploit negative Poisson’s ratio to resolve interfacial mechanical mismatches. A “conformal self-adaptation” mechanism with bond curvature maximizes contact area and signal stability on curved surfaces. The optimized structure improves the bending mode energy conversion efficiency by a factor of 3.2 compared to the non-auxetic control and ensures robust energy […]

Website development service for manufacturing industry eLuminous Technologies has developed a scalable ML-powered price prediction platform for a Texas-based industrial equipment trading company. The solution uses Python, web scraping, and advanced algorithms to aggregate real-time data from the market to provide accurate and transparent pricing amidst manufacturing sector challenges such as inconsistent valuations and manual […]