Welcome to GenAISafety, the leader in AI-powered workplace safety.
GenAISAFETY LAB : Preuve de Concept
La section "Preuve de Concept" de GenAISAFETY LAB est dédiée à l’exploration, la création et l’évaluation de solutions innovantes basées sur l’IA générative dans le domaine de la santé et sécurité au travail. En se concentrant sur des environnements à risques, cette section a pour mission de démontrer l’efficacité et la faisabilité de nouvelles technologies pour la prévention et la réduction des incidents professionnels.
GenAISafety Lab Demo-(PoC, ou "Proof of Concept"
GenAISafety Lab Demo-(PoC, ou "Proof of Concept"
Flame et PoC-1oo problématiques de lésions professionnelles au Québec
PoC-Rapport Structuré pour la Création de 10 Preuves de Concept (PoC) en Santé et Sécurité dans le Secteur Horticole
GenAISafety_PoC- Appliqué à deux projets de GenAISafety Continuum et GenAISafety Mutuelles
The Safety Lab Demo channel showcases Prevention Program AI (PPAI), a key tool in the GenAISafety suite.
Designed to transform risk prevention in the workplace, PPAI leverages artificial intelligence to tailor and optimize safety programs based on the specific needs of high-risk sectors.
Through interactive demonstrations, the channel illustrates how PPAI helps safety managers and companies anticipate risks, adjust safety protocols, and enhance compliance in health, safety, and environment (HSE). With PPAI, the GenAISafety suite offers a proactive, intelligent solution to reduce workplace incidents and promote a modern, data-driven safety culture.
GenAISafety Lab Demo-Prevention Program AI (PPAI
GenAISafety Lab Demo-Prevention Program AI (PPAI
Prevention Program AI (PPAI)-Démo -PPAI peut assurer une contextualisation factuelle en adoptant une approche de validation continue
Prevention Program AI (PPAI)-Démo -Creation d'un algorithme visant à réduire les milieux de travail sécuritaires
Prevention Program AI (PPAI)-Démo -Creation d'un algotithme visant à réduire les milieux de travail sécuritaires
Prevention Program AI (PPAI)-Démo -Gestion de Contexte pour des Réponses Personnalisées et Précises
PPAI-Établis une liste de 100 invites utilisateurs et propose des exemples de réponses pour assurer la personnalisation de PPAI
PPAI-personnaliser PPAI au contexte de l'industrie manufacturière automobile (SCIAN 31-33
PPAI-100 Questions pour la Santé et Sécurité du Travail - Secteur Bâtiment et Travaux Publics (CNESST)
ProgrammedePrévention.Prevention program Étapes pour Créer un Programme de Prévention en Utilisant des Données Analytiques Multimodales
ProgrammedePrévention.Prevention program.Méthode et Processus pour Générer un Programme de Prévention avec l'IA
ProgrammedePrévention.L'évaluation des risques d'effondrement lors des travaux d'excavation et de remblayage
ProgrammedePrévention. table de données structurées pour l'analytique avancé et l'IA pour chacun des formulaires (exemple inspection audits, etc
ProgrammedePrévention.Prevention program.procédure sécuritaire sur les travaux de pose d'acier d'armature
ProgrammedePrévention.Prevention program.Sommaire
ProgrammedePrévention.Prevention program..Programme de Prévention avec l'IA- détails des sections
ProgrammedePrévention.conformité aux nouvelles réglementations en vigueur pour 2023 dans le Code de sécurité pour les travaux de construction (CSTC) et plan d'action
Summary for each video in the Prevention Program AI (PPAI)-Demo channel:
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100 Health and Safety Questions - Construction and Public Works Sector (CNESST)
This video presents 100 questions users can ask related to health and safety requirements for the construction and public works sector, meeting the specific needs of workers and managers. -
Creating an Algorithm to Improve Workplace Safety
Introduction to an algorithm designed to analyze workplace risks and propose preventive strategies to enhance employee safety. -
Structured Data Set for Horticultural Companies (Mutual Prevention Program)
Overview of a structured dataset with 100 user prompts tailored for horticultural companies, aiming to strengthen safety practices in this sector. -
System Prompts for Mutual Prevention Program Managers in Horticulture
Demonstration of 100 system prompts designed to help managers in the horticultural sector manage and monitor workplace safety practices. -
Examples of Guardrails for Safety and Compliance
Exploration of built-in "guardrails" that ensure the AI's responses align with safety and compliance standards. -
Training on Health and Safety Data
A look at how health and safety data is used to train the AI model, improving the relevance and accuracy of its responses in safety contexts. -
Ensuring Accuracy and Reliability of HSE Information
Explanation of the mechanisms to guarantee that AI-provided information in health, safety, and environment (HSE) is accurate and fact-based. -
Context Management for Precise and Personalized Responses
This video demonstrates how the AI adjusts its responses based on context to deliver personalized and relevant information for various users and workplace situations. -
Managing AI Hallucinations
Introduction to techniques used to minimize “hallucinations” in AI, or inaccurate or inconsistent responses, ensuring reliability in safety advice. -
System Prompts for Workers
Presentation of a set of system prompts specifically designed for workers to help them ask questions and receive precise information on workplace safety. -
User Prompts for Priority Groups (CNESST)
A list of 50 user prompts designed to explore the needs of sectors classified as priority by CNESST in health and safety, specifically for groups 1, 2, and 3. -
System Prompts for Employers in the Horticulture Sector
Demonstration of 100 system prompts for employers in the horticulture sector, helping them to better manage workplace safety. -
Advanced Algorithm Structured in Steps
Explanation of a structured algorithm for PPAI, outlining data inputs and outputs, reports, and AI processing for precise recommendations. -
Customizing Prevention Programs for High-Risk Sectors
A list of 50 user prompts, organized around five economic sectors according to NAICS, to adapt prevention programs to each sector's specific risks. -
Contextualization and Continuous Data Validation
Description of PPAI's ability to continuously validate HSE information, ensuring the relevance and accuracy of responses. -
Prevention Program Requirements and How PPAI Responds
Overview of the key requirements of a prevention program and how PPAI can address them, providing solutions that meet safety regulations. -
Chain of Thought (CoT) Workflow to Structure Reasoning
Introduction to the Chain of Thought (CoT) methodology in PPAI, a process to structure AI reasoning for more accurate and logical safety responses. -
Guardrail System to Ensure Consistency and Compliance
Explanation of the guardrails in PPAI to ensure that the AI’s advice adheres to health and safety standards and regulations.