New feature helps B2B marketers audit AEO readiness, identify intent gaps, and optimize pages for AI-driven search ...
How much of the energy consumed in an AI chip is spent doing something useful? This question affects everything from software ...
Abstract: Quantum computing promises to solve difficult optimization problems in chemistry, physics and mathematics more efficiently than classical computers. However, it requires fault-tolerant ...
This repository contains the source code for the paper titled "Eraser: Eliminating Performance Regression on Learned Query Optimizer." Eraser is a plugin deployed on top of learned query optimizers ...
Database optimization has long relied on traditional methods that struggle with the complexities of modern data environments. These methods often fail to efficiently handle large-scale data, complex ...
from qdrant_nlp import NaturalLanguageInterface nlp = NaturalLanguageInterface(client) # Instead of this complex query: client.search( collection_name="products ...
Abstract: Query Optimization is considered to be one of the most important challenges in database management. Existing built-in query optimizers are very complex and rely on various approximations and ...
Modern database systems rely on cost-based query optimizers to come up with good execution plans for input queries. Such query optimizers rely on cost models to estimate the costs of candidate query ...
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