Materials research generates vast amounts of data, but the information often exists in manufacturer-specific formats and the terminology is inconsistent, making it difficult to aggregate, compare, and ...
Abstract: Traffic data contains deep domain-specific knowledge, making labeling challenging, and the lack of labeled data adversely impacts the accuracy of learning-based traffic analysis. The ...
Why today’s AI systems struggle with consistency, and how emerging world models aim to give machines a steady grasp of space ...
Credit: VentureBeat made with Flux.2 [klein] on Fal.ai The German AI startup Black Forest Labs (BFL), founded by former ...
The project for which Hulsebos received the grant is called DataLibra, which runs from 2024 to 2029. Over those five years, ...
As agentic and RAG systems move into production, retrieval quality is emerging as a quiet failure point — one that can ...
When data is productized and semantics encoded, you unlock agentic AI at scale. Instead of assistants, you get executors: ...
If the last few years were about experimenting with artificial intelligence, 2026 will be about making it actually work. Retailers have spent a huge amount of money on tools that promise sharper ...
Abstract: As an emerging paradigm for 6G intelligent communications, deep learning (DL) has delivered remarkable performance gains in physical layer communications and has found its way into many ...
CHICAGO, Dec. 23 - In Chicago’s working-class Pilsen neighborhood, a 60s-era oil-fired power plant rises up from an industrial lot behind Dvorak Park, which in warmer weather is packed with children ...
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