Scientists at Massachusetts Institute of Technology have devised a way for large language models to keep learning on the fly—a step toward building AI that continually improves itself.

AI inference is pushing computing demand to the edge, and that is making adaptive reuse an option again for data center developers ...

Adaptive Biotechnologies Highlights New Data at 2025 ASCO Annual Meeting and EHA 2025 Congress Demonstrating How clonoSEQ® MRD Assessment is Optimizing Patient Care ...

Better data annotation—more accurate, detailed or contextually rich—can drastically improve an AI system’s performance, adaptability and fairness.

By Don Strickland, Product Manager for Legrand’s Data, Power, and Control division The explosion of AI workloads is redrawing the data center blueprint in real time. Models are larger, compute ...

Control of synthetic polymer solution phase behavior is crucial for soft materials engineering. Recent experiments on styrene-isoprene block–random copolymers [Taylor, L. W. Macromolecules 2024, 57, ...

Acceldata, a leading provider of data observability and agentic data management solutions, is announcing a new capability designed to amplify the power of agentic reasoning within the company's xLake ...

Information compression is shown to pack the size of data accumulated in advanced documents. We have proposed a block adaptive model (BAM) compression strategy to pack the size of image while keeping ...

Databricks, a company that helps big businesses build custom artificial intelligence models, has developed a machine-learning trick that can boost the performance of an AI model without the need ...

Alireza Doostan is leading a major effort for real-time data compression for supercomputer research. A professor in the Ann and H.J. Smead Department of Aerospace Engineering Sciences at the ...