The research identifies two primary models for this integration: the element model and the process model. The element model focuses on the five key aspects of evaluation: who, what, when, how, and why ...

A key lesson was to measure what matters. From the outset, we defined clear success metrics—latency reduction, resource efficiency and cost improvement.

Big data integration process faced structural heterogeneity and semantic heterogeneity problems. Ontology is an explicit specification of a conceptualization, which is the core of semantic web ...

EPFL researchers have developed new software—now spun-off into a start-up—that eliminates the need for data to be sent to third-party cloud services when AI is used to complete a task. This could ...

On Wednesday, Databricks released Dolly 2.0, reportedly the first open source, instruction-following large language model (LLM) for commercial use that has been fine-tuned on a human-generated data ...

The results suggest that training models on less, but higher-quality, data can lower computing costs. The Allen Institute for Artificial Intelligence (Ai2), a research nonprofit, is releasing a family ...

Motif-2-12.7B-Reasoning is positioned as competitive with much larger models, but its real value lies in the transparency of how those results were achieved. The paper argues — implicitly but ...

The prevailing Lambda Cold Dark Matter (LCDM) model, based on the Big Bang and subsequent inflation, faces challenges including the inability to explain the universe's homogeneity and the singularity ...