Il en va ainsi, par exemple, de pauses effectuées en tenue de travail mais sans obligation de devoir se conformer aux directives de l’employeur ou de rester à sa disposition permanente.

robotics: The department of AI focused on designing, setting up, and working robots. Robotics brings together AI with engineering to produce equipment effective at performing responsibilities autonomously or semi-autonomously.

k-signifies clustering: An unsupervised learning algorithm that partitions data into K distinct clusters determined by feature similarity. It aims to minimize the variance within Each and every cluster.

zero-shot Understanding: A device learning technique in which a product can understand and classify data from classes it has not viewed during education. This method leverages auxiliary details, including semantic characteristics, to generalize to new types.

Ne respectant pas strictement les trois situations cumulatives posées par l’article L. 3121-one du Code du travail, les temps d’habillage et de déshabillage ne constituent légalement pas un temps de travail effectif.

Le Code du travail le définit comme le temps pendant lequel le salarié est à la disposition de l'employeur et se conforme à ses directives sans pouvoir vaquer librement à des occupations personnelles.

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education information: The dataset accustomed to train a device Understanding design. It is made of input-output pairs the product learns from to produce exact predictions on new, unseen knowledge.

“By combining a pre-properly trained eyesight-language design with a library of interpretability resources, our multimodal method can reply to consumer queries by composing and operating specific experiments on certain designs, continuously refining its approach till it can offer a comprehensive solution.”

overfitting: A modeling error that happens when a machine Understanding model learns the instruction info also well, capturing sounds and outliers. This brings about poor generalization and performance on new, unseen data.

clustering: An unsupervised Mastering system that teams similar information points collectively based mostly on their own characteristics. It is frequently employed for customer segmentation and anomaly detection.

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“We’re not proclaiming perceived functionality and personalization are the one two Proportions that make any difference, but Based on our meta-Investigation, both of these dimensions capture Considerably of what designs individuals’s preferences for AI versus humans throughout a wide array of scientific tests,” Lu concludes.