Research Results

GenAISafety: Mission, Purpose, and Values Axioms Health and safety are fundamental rights for all workers. Artificial intelligence is a powerful tool to enhance risk prevention and optimize productivity. Sustainability and ethics are essential for a long-term approach to workplace health and safety. Mission GenAISafety's mission is to develop and implement innovative, trustworthy, and sustainable AI solutions to enhance safety, health, and productivity in the workplace. We are committed to creating a new era of safer, more efficient, and more sustainable work environments through the responsible use of AI. Values Innovation: Encouraging creativity and exploring new ideas to solve complex challenges related to occupational health, safety, and prevention. Integrity and Responsibility: Acting ethically and transparently, upholding the highest standards for data security, privacy, and societal and environmental impact. Excellence: Striving for the highest quality standards in our products and services, grounded in deep expertise and continuous improvement. Collaboration: Working in partnership with our clients, partners, and employees to develop tailored and effective solutions. Sustainability: Ensuring our AI solutions are not only effective but also sustainable and aligned with the principles of trustworthy AI. GenAISafety: Revolutionizing Health, Safety, and Environment with Trusted AI In a world where workplace safety is more crucial than ever, GenAISafety stands at the forefront by developing a trustworthy artificial intelligence (AI) platform. Our mission is clear: to transform critical systems related to health, safety, and the environment through advanced technologies that minimize risks and maximize the protection of people and resources. An Ethical and Reliable AI GenAISafety is built on fundamental principles of integrity and transparency. We integrate rigorous standards to ensure that our AI is not only high-performing but also ethical. By addressing algorithmic biases and establishing clear protocols, we guarantee informed and responsible decision-making within our systems. Compliance with Global and Quebec Standards GenAISafety positions itself as a key player in the health, safety, and environment domain by ensuring rigorous compliance with the most demanding standards. Our platform is designed to meet the requirements of Quebec’s regulatory frameworks, including: Occupational Health and Safety Act (LSST): Establishes fundamental principles to ensure worker protection on all worksites. Occupational Health and Safety Regulation (RSST): Details preventive measures to protect workers in various environments. Safety Code for Construction Work (CSTC): A regulation applicable to all construction sites in Quebec, defining specific rules regarding work organization, equipment, and safety measures according to the risk level of the tasks Transforming Data into Action GenAI Safety enables the transformation of research findings into practical and predictive tools. For instance, by applying reactive statistics from CNESST or OSHA to predictive measures, GenAISafety uses accident data to anticipate and reduce future incidents. This demonstrates how scientific research can be directly integrated into AI systems to enhance workplace safety. Prediction and Prevention Generative AI models are capable of analyzing vast datasets to identify emerging trends and risks. Leveraging these capabilities, GenAISafety can create customized, interactive training that incorporates the latest scientific findings, making learning more relevant and effective for health and safety professionals. Ethics and Compliance Applying research-based knowledge must also adhere to strict ethical standards. GenAISafety is committed to obtaining explicit consent for collecting sensitive data, ensuring that information use respects individual rights while integrating the best ethical practices from scientific research. Interdisciplinary Collaboration GenAI fosters close collaboration among researchers, HSE (Health, Safety, and Environment) professionals, and tech developers. This synergy allows valuable insights to be shared on applying AI technologies in workplace safety while addressing associated ethical and regulatory challenges. Continuous Innovation Using GenAI to update scientific knowledge in real-time enables continuous improvement in safety practices. By integrating the latest research into its algorithms, GenAISafety ensures that its solutions remain at the forefront of innovation, meeting the evolving needs of the market. Join a Collaborative AI Project with GenAISafety

Explanatory Note: Use of Technologies and LLM Models in Product Demos Introduction GenAISafety, a global leader in transforming workplace health and safety (HSE) through generative artificial intelligence, combines advanced technologies to provide innovative and secure solutions. This explanatory note outlines the use of OpenAI technologies as part of our corporate membership, along with the integration of open-source models and benchmarks for security and performance. Use of OpenAI Technologies GenAISafety has established a corporate membership with OpenAI, enabling the use of their cutting-edge technologies under the highest security standards. Key highlights of our use of OpenAI technologies include: Data Security: We exclusively use non-sensitive data for training and developing our models, ensuring the confidentiality and security of information. Compliance: All operations comply with OpenAI’s security regulations and guidelines, ensuring responsible and ethical use of generative AI. Advantages of Generative AI: OpenAI models, such as GPT-4, are integrated into our platform to analyze real-time data, anticipate risks, and provide personalized recommendations to enhance workplace safety. Integration of Open-Source Models In addition to leveraging OpenAI technologies, GenAISafety integrates open-source models to diversify and strengthen its analytical and predictive capabilities. Key Open-Source Foundation Models: Bloom: A multilingual language model developed by Hugging Face, utilized for language comprehension and generation tasks. BERT: A pre-trained model by Google, applied to natural language processing tasks. MISTRAL 7B: A French language model developed by INRIA, designed for specialized applications in French. FALCON 180: A model tailored for advanced language processing tasks. Security and Performance Benchmarks: MMLU (Multimodal Language Understanding): Evaluates multimodal comprehension of models. ACR (Automatic Content Recognition): Assesses the capability for automatic content recognition. BLEUScore: Measures the quality of automated translation. HELM (Human Evaluation of Language Models): Gauges model performance through human evaluations. TRIVIAQA: Tests question-answering capabilities. LMSYS (Language Model System): Evaluates overall performance of language model systems. Purpose of Product Demos The product demos available on [GenAISafety Channels] serve as illustrative examples of our solutions. These demos aim to showcase the capabilities and benefits of our products without involving sensitive or personal data. Compliance with GDPR and Quebec’s Law 25 GenAISafety strictly adheres to the European Union’s General Data Protection Regulation (GDPR) and Quebec’s Law 25 on the protection of personal information. Personal Data Protection: We do not process personal data in demos unless explicitly necessary and with informed consent. We respect individuals’ data protection rights as defined by GDPR and Law 25. Transparency and Information: We clearly inform users about the purpose of data processing, the legal basis, recipients, and retention periods, in accordance with GDPR and Law 25 requirements. Data Security: Appropriate security measures are in place to protect data, including conducting data protection impact assessments when required. These measures comply with Article 32 of the GDPR and Law 25 standards. Incident Notification: Any confidentiality breach involving personal information is promptly reported to Quebec’s Commission d’Accès à l’Information (CAI) and affected users, as per Law 25. Consent and Oversight: We obtain clear and informed consent before collecting or using sensitive data. A designated Data Protection Officer (DPO) ensures compliance. GenAISafety ensures compliance with Quebec’s Law 25 in its product demos by adhering to key requirements and principles outlined in the legislation.

Podcast Channel: Dep Dive GenAISafety Insights GenAISafety positions itself as a leader in workplace health and safety through artificial intelligence. The company offers a range of software suites, including the Agentic SquadrAI Suite, focused on EHS programs and AI multi-agent systems. These solutions cover various aspects such as HSE management, ergonomics, and regulatory compliance. They include tools for risk analysis, simulation, and training, as well as specialized AI agents designed to assist humans in various roles. The "GenAISafety Market Place" features a variety of products, such as EmergiBot, HazardBot, and CompliGuard, each addressing specific needs related to safety and risk prevention. The offering also includes compliance assistance tools aligned with standards like OSHA and CNESST. Channel Description: The GenAISafety Insights podcast channel focuses on the integration of artificial intelligence in workplace health and safety. Each episode explores how advanced technologies, such as generative language models, are transforming safety practices, enhancing accident prevention, and fostering a safer work environment. Topics Covered: Predictive Risk Analysis: How AI can anticipate and prevent incidents. Best Safety Practices: Case studies on the successful application of AI-based solutions across various sectors. Training and Awareness: Educational programs to help professionals effectively utilize these technological tools. Objective: The podcast aims to educate and inspire health and safety professionals in the workplace by providing practical tools and insights into the latest innovations in AI to improve workplace safety. Deep Dive - GenAISafety Insights est une chaîne de podcast dédiée à l'exploration des impacts de l'intelligence artificielle générative (IA) sur la santé et la sécurité au travail (SST). À travers des discussions approfondies et des témoignages d'experts, le podcast met en lumière comment les technologies avancées transforment les pratiques de prévention, améliorent la gestion des risques et favorisent des environnements de travail plus sûrs. Les sources explorent l'avènement de l'IA agentique, une nouvelle phase de l'intelligence artificielle générative caractérisée par des systèmes autonomes et proactifs. Elles soulignent son potentiel de transformation dans divers secteurs, notamment la santé et sécurité du travail (SST), en automatisant des tâches complexes, en améliorant la prise de décision et en optimisant les processus. Un focus particulier est mis sur GenAISafety et SquadrAI Hugo AI CoSS, des solutions exploitant l'IA agentique pour la prévention des risques, la conformité réglementaire et l'amélioration de la sécurité sur les lieux de travail. Les textes mettent en avant les avantages d'une adoption rapide de ces technologies et décrivent les étapes pour leur conceptualisation et intégration dans les entreprises. Des études de cas concrets illustrent l'impact tangible de l'IA agentique sur la productivité et la réduction des coûts. Les sources explorent comment l'intelligence artificielle agentique (IA agentique) transforme la santé et sécurité au travail (SST) en automatisant des processus clés et en offrant des capacités d'analyse et de prédiction avancées. Cette technologie, caractérisée par son autonomie et sa proactivité, permet une surveillance continue des risques, une identification optimisée des dangers, et une aide à la décision précieuse pour les équipes de SST souvent confrontées à un manque de ressources. L'IA agentique s'appuie sur divers algorithmes d'apprentissage automatique et utilise des technologies spécifiques comme la vision par ordinateur, les capteurs et la robotique pour améliorer la prévention des accidents et la gestion des urgences. Malgré ses nombreux avantages, son intégration soulève des défis techniques, organisationnels et éthiques qui nécessitent une attention particulière. Les sources explorent l'application de l'intelligence artificielle, notamment les grands modèles de langage (LLM), à la sécurité industrielle et à la gestion de la santé et sécurité au travail (SST). Un accent particulier est mis sur les méthodes d'entraînement optimales des LLM, les défis liés à la qualité et à la collecte des données HSE, ainsi que les meilleures pratiques pour la préparation et l'évaluation de ces données. Diverses technologies et techniques d'entraînement avancées, y compris les modèles multimodaux et l'apprentissage avec peu ou pas d'exemples, sont présentées. Enfin, les sources abordent les considérations éthiques, la protection des données et présentent des solutions logicielles spécifiques pour la transformation et l'analyse des données HSE. 🚧 The Future of OHS Management: From Traditional Systems to GenAISafety 🚧 Occupational Health and Safety (OHS) management has undergone a significant transformation, moving from traditional systems to SaaS-based solutions, and now embracing the revolutionary power of GenAISafety. 🔍 What’s Driving This Evolution? Traditional OHS systems laid the groundwork with structured frameworks like the PDCA cycle. SaaS introduced flexibility, scalability, and real-time monitoring. Now, GenAISafety is redefining the game with AI-driven, agentic systems capable of predictive analytics, dynamic workflows, and autonomous decision-making. 💡 Why GenAISafety Stands Out: Automation Beyond Expectations: AI handles complex safety tasks proactively. Predictive Insights: Anticipate and prevent incidents before they occur. Dynamic Adaptability: Adjusts in real-time to changing workplace needs. Seamless Integration: Works across ecosystems for holistic safety management. 🚀 Learn More: Discover how GenAISafety can help your business achieve smarter, safer, and more adaptive OHS solutions Future of OHS Management GenAISafety, une entreprise spécialisée en sécurité au travail assistée par intelligence artificielle, présente un nouvel outil: un ensemble de 100 scénarios d'accidents tirés d'une base de données combinant les technologies HSE-HumanX et ViAI Prévention. Ces scénarios, principalement liés aux engins mobiles en milieu industriel, servent à illustrer les risques et à proposer des mesures préventives. Un algorithme d'apprentissage automatique, basé sur des données historiques d'accidents et des capteurs IoT, est décrit pour prédire les zones à risque dans les entrepôts. L'objectif est d'améliorer la sécurité en identifiant les comportements et les conditions dangereuses avant qu'un accident ne survienne. Finalement, un tableau résume 100 prédictions d'accidents avec recommandations. Citations Clés « AI AIEthicsGuard est un système conçu pour assurer une gouvernance et une gestion éthique des systèmes d’intelligence artificielle (IA). » « Son objectif principal est d’aider les organisations à identifier, mesurer, gérer et atténuer les risques liés à l’IA afin d’assurer une utilisation transparente, responsable et sécurisée de ces technologies. » « AIEthicsGuard repose sur quatre fonctions essentielles pour la gestion des risques liés à l’IA : Gouverner, Cartographier, Mesurer, Gérer. » Conclusion AI AIEthicsGuard se présente comme un cadre structurant essentiel pour les organisations souhaitant adopter l'IA de manière éthique et sécurisée dans le domaine de la SST. En intégrant les principes du AI RMF et en fournissant des applications concrètes, il vise à maximiser les avantages de l'IA tout en minimisant les risques potentiels. Ces extraits proviennent de GenAISafety, un chef de file en santé et sécurité au travail alimenté par l'IA, et se concentrent sur la prévention des risques liés aux chariots élévateurs. Ils mettent en évidence les coûts économiques et humains importants des accidents impliquant ces engins et présentent une approche novatrice basée sur une ontologie sémantique pour la gestion des risques industriels. L'article détaille comment GenAISafety intègre l'IA pour standardiser les connaissances en SST, optimiser la gestion des risques, et s'intégrer aux outils numériques existants. De plus, il offre 100 prédictions basées sur un graphe de connaissances SST, couvrant des aspects tels que les facteurs humains, les technologies sécuritaires, la formation, les normes, et l'aménagement des zones de travail. Enfin, il met en lumière des modèles prédictifs avancés et une analyse des facteurs de risque, démontrant comment l'IA peut être utilisée pour anticiper et prévenir les accidents de chariots élévateurs. Forklift Safety: AI Prevention and Recommendations These excerpts come from GenAISafety, a leader in AI-powered occupational health and safety, focusing on forklift risk prevention. They highlight the significant economic and human costs of forklift-related accidents and introduce an innovative approach based on a semantic ontology for industrial risk management. The article explains how GenAISafety integrates AI to standardize OHS knowledge, optimize risk management, and seamlessly integrate with existing digital tools. Additionally, it provides 100 AI-driven predictions based on a knowledge graph, covering key aspects such as human factors, safety technologies, training, regulations, and workplace layout. Finally, the article showcases advanced predictive models and risk factor analysis, demonstrating how AI can anticipate and prevent forklift accidents. Welcome back, everybody, to the Deep Dive. This time, we're taking a close look at how AI is changing the game and workplace safety, especially in those hands-on fields like construction and manufacturing. Yeah, some really big changes happening. We're basing this Deep Dive on a couple of super interesting reports. Oh, yeah, which ones? One is called SafeScan360, Transforming Workplace Safety Through AI-Powered Risk Management. OK. And the other is Squadra a Hugo Cos, Examples of Work Situations and OHS Risk Management Développez votre vision de la santé corporative propulsez par l'IA Chaîne de Communication SquadrAI Kinosys – Propulsez Votre Vision de la Santé Corporative avec l’IA La chaîne de communication SquadrAI Kinosys repose sur une architecture intelligente et interconnectée, facilitant une gestion proactive et personnalisée de la santé en entreprise. Grâce à l’intégration de l’intelligence artificielle (IA), SquadrAI crée un écosystème de collaboration fluide entre les employés, les gestionnaires, les professionnels de la santé et les chercheurs. Commencer Kinosys, en tant que solution innovante propulsée par l'intelligence artificielle, répond aux défis du mieux-être organisationnel au Québec. En mettant l'accent sur les saines habitudes de vie, la conciliation travail-vie personnelle, les pratiques de gestion et l'environnement de travail, Kinosys offre une approche intégrée pour améliorer la santé globale des employés. Grâce à des outils d'IA avancés, Kinosys facilite la détection précoce des risques psychosociaux, propose des interventions personnalisées pour promouvoir le bien-être numérique et soutient les organisations dans la mise en place de pratiques favorisant un équilibre sain entre vie professionnelle et personnelle. En adoptant Kinosys, les entreprises québécoises peuvent ainsi créer un environnement de travail plus sain, réduire l'absentéisme et renforcer l'engagement de leurs employés, tout en répondant aux enjeux contemporains du monde du travail.

VertebrAI Prenez soin de votre dos, naturellement et intelligemment. À propos de VertebrAI Chez VertebrAI, nous utilisons l'intelligence artificielle pour aider à la gestion et au soulagement des douleurs chroniques au dos. Notre mission est d'offrir des outils personnalisés, des conseils pratiques et des programmes interactifs afin d'améliorer la qualité de vie de nos utilisateurs. Que vous soyez un patient à la recherche de solutions non invasives ou un professionnel de santé souhaitant enrichir vos pratiques, VertebrAI est là pour vous accompagner à chaque étape. Pourquoi SquadrAI pour VertebrAI est Révolutionnaire ? Approche Holistique : SquadrAI couvre tous les aspects de la douleur dorsale, du diagnostic au soutien psychologique. Personnalisation Maximale : Chaque patient bénéficie d'un parcours adapté à ses besoins spécifiques. Collaboration en Temps Réel : Les agents interagissent et échangent des données pour ajuster en permanence les soins. Optimisation des Ressources Médicales : SquadrAI réduit la charge administrative des professionnels, leur permettant de se concentrer sur les soins directs. Notre histoire Notre histoire Chez VertebrAI, nous croyons que la gestion de la douleur dorsale peut être révolutionnée grâce à la technologie et à l'innovation. Fondée par des experts en santé et en intelligence artificielle, notre mission est de fournir aux patients et aux professionnels de santé des outils intuitifs et efficaces pour améliorer la qualité de vie. Nous avons commencé notre aventure avec une simple idée : utiliser l'IA pour offrir des solutions personnalisées à chaque individu souffrant de douleurs chroniques au dos. Aujourd'hui, VertebrAI est un acteur clé dans le domaine de l'autogestion de la douleur, aidant des milliers de personnes à retrouver mobilité et confort. Notre équipe Notre équipe est composée de spécialistes de divers horizons : médecins, kinanthropologues, kinésithérapeutes, ingénieurs IA et développeurs passionnés par l'innovation médicale. Ensemble, nous collaborons pour concevoir des outils qui mettent l'humain au cœur de la technologie. Chaque membre apporte son expertise pour s'assurer que VertebrAI reste à la pointe du progrès et répond aux besoins réels des utilisateurs. 1. Approche Personnalisée et Centrée sur le Patient Chaque programme de gestion de la douleur est adapté aux besoins spécifiques du patient grâce à des évaluations précises (ODI, SF-12) et une surveillance continue de l'évolution des symptômes. Pourquoi ? La douleur dorsale varie d'un individu à l'autre. L'IA s'ajuste en temps réel aux progrès du patient. Découvrir Notre équipe SquadrAI pour VertebrAI SquadrAI est l’architecture intelligente qui alimente VertebrAI, un écosystème d’agents IA spécialisés dans la gestion de la douleur vertébrale. Ces agents travaillent en synergie pour offrir un soutien complet aux patients, aux professionnels de santé, aux intervenants et aux chercheurs. L'objectif est de fournir des solutions personnalisées et adaptatives, améliorant ainsi la qualité de vie des patients tout en optimisant le temps et les ressources des praticiens. 1. V-Guide (Agent Patient – Suivi et Éducation) 1. V-Guide (Agent Patient – Suivi et Éducation) Rôle : V-Guide accompagne le patient tout au long de son parcours de soin. Il sert de coach virtuel pour l'autogestion de la douleur. Fonctionnalités : Suivi des douleurs via un journal interactif. Recommandations quotidiennes d’exercices et de postures. Évaluation de la progression à l'aide des questionnaires SF-12 et ODI. Conseils personnalisés en fonction de l’évolution des symptômes. 2. V-Scan (Agent Clinicien – Diagnostic et Analyse) 2. V-Scan (Agent Clinicien – Diagnostic et Analyse) Rôle : Cet agent assiste les cliniciens en analysant les résultats d’imagerie médicale (IRM, radios) et en identifiant des anomalies structurelles. Fonctionnalités : Intégration des données biomédicales. Aide au diagnostic grâce à des modèles prédictifs basés sur des millions de cas similaires. Génération de rapports détaillés pour les consultations. Détection des signes de douleur chronique ou aiguë. 3. V-Link (Agent Intervenant – Communication et Coordination) 3. V-Link (Agent Intervenant – Communication et Coordination) Rôle : V-Link facilite la communication entre les patients et les intervenants (kinésithérapeutes, ostéopathes). Fonctionnalités : Planification et synchronisation des rendez-vous. Partage des progrès du patient en temps réel. Coordination des plans de rééducation. Adaptation des exercices en fonction des retours des praticiens. 4. V-Research (Agent Recherche – Données et Innovation) 4. V-Research (Agent Recherche – Données et Innovation) Rôle : V-Research collecte des données anonymisées et participe aux projets de recherche pour faire avancer la compréhension de la douleur dorsale. Fonctionnalités : Analyse des données cliniques pour identifier des tendances. Contribution à des études longitudinales sur les douleurs chroniques. Recommandations d'approches thérapeutiques basées sur les dernières publications scientifiques. Génération d’hypothèses pour essais cliniques. 5. V-Connect (Agent Communautaire – Soutien et Motivation) 5. V-Connect (Agent Communautaire – Soutien et Motivation) Rôle : V-Connect crée une communauté virtuelle de patients souffrant de douleurs similaires pour favoriser l'échange d’expériences et le soutien psychologique. Fonctionnalités : Groupes de soutien virtuels et forums. Organisation de webinaires avec des spécialistes. Gamification du parcours de soin pour maintenir la motivation des patients. Rappels pour les exercices et suivi de la progression collective. V-Ergo – Agent Ergonomie et Kinésiologie V-Ergo – Agent Ergonomie et Kinésiologie V-Ergo est l'agent IA dédié à l'optimisation du mouvement, de la posture et à la prévention des douleurs vertébrales dans l'écosystème SquadrAI de VertebrAI. Spécialiste en ergonomie et kinésiologie, V-Ergo analyse les postures, les gestes quotidiens et les habitudes physiques des patients pour prévenir et corriger les déséquilibres musculo-squelettiques. VertebrAI VertebrAI Play Video Share Whole Channel This Video Facebook Twitter Pinterest Tumblr Copy Link Link Copied Search video... Now Playing Ressources Spécifiques pour VERTEBR AI Bases de Données et Étapes du Chemin de Guérison 03:08 Play Video Now Playing Vertebr AI. Questions organisées par catégorie de patients et types de maux de dos, 03:00 Play Video

GenAISafety AI concepts GenAISafety use approaches and techniques aimed at ensuring the safe and responsible development and deployment of generative AI systems. Based on the search results, here are some key concepts related to GenAISafety: Safety by Design Framework: T his involves incorporating safety and ethical considerations from the early stages of AI development. It includes four key elements for delivering safe and reliable generative AI systems. Adversarial Testing: This is a proactive approach to identify and mitigate potential risks in GenAI models before they are broadly available. It involves systematically evaluating models with malicious or inadvertently harmful inputs across various scenarios. Scaled Adversarial Data Generation: This technique creates diverse test sets containing potentially unsafe model inputs to stress-test model capabilities under adverse circumstances. Automated Test Set Evaluation: This allows for rapid evaluation of thousands of model responses across a wide range of potentially harmful scenarios. Community Engagement: This is crucial for identifying "unknown unknowns" and seeding the data generation process for safety testing. Rater Diversity: Safety evaluations rely on human judgment, which is shaped by community and culture. Prioritizing diversity in raters helps account for different cultural perspectives on safety. Specialized Enterprise LLMs: Using industry-specific models with relevant frameworks and customer-specific rules can enhance precision and safety for business needs. Guardrails-First Mindset : Implementing strong governance mechanisms and guardrails for responsible AI use helps protect against misuse and security threats. Employee Training Initiatives : Raising AI awareness among employees through training helps in understanding the technology's possibilities and limitations, fostering trust and proper usage. Strict Data Privacy: Ensuring data privacy across the enterprise is crucial, especially in industries handling sensitive personal information. Ethical and Fairness Considerations Ethical and Fairness Considerations AI Ethics: AI ethics are a priority for GenAISafety, ensuring that the technology is developed and deployed responsibly. The system considers privacy, fairness, and the well-being of workers, aligning with broader ethical standards in AI. Ethical and Fairness Considerations Ethical and Fairness Considerations Algorithmic Fairness: GenAISafety implements algorithmic fairness principles to ensure that its safety recommendations are equitable and do not favor one group of workers over another. This focus on fairness is critical for maintaining trust and compliance in safety management. Data and Analytics Concepts Data and Analytics Concepts Transfer Learning: Transfer learning in GenAISafety allows the system to apply knowledge gained from one industry or safety scenario to improve performance in another. This capability enhances the system’s adaptability across different environments and industries. Data and Analytics Concepts Data and Analytics Concepts Cloud Computing: GenAISafety leverages cloud computing to store and process large volumes of safety data, ensuring scalability and accessibility from multiple locations. This infrastructure supports the platform’s ability to handle extensive datasets and complex analyses efficiently. Data and Analytics Concepts Data and Analytics Concepts Data Mining: GenAISafety uses data mining techniques to extract valuable insights from large datasets, uncovering trends and correlations that could indicate emerging safety risks. This information is critical for proactive risk management. Application-Specific Concepts Application-Specific Concepts GANs (Generative Adversarial Networks): GenAISafety may use GANs to generate synthetic data for training its models, especially in scenarios where real-world data is scarce or sensitive. This approach helps in creating robust AI models that can handle a wide range of safety scenarios. Ethical and Fairness Considerations Ethical and Fairness Considerations Explainable AI: To build trust and ensure transparency, GenAISafety employs explainable AI techniques that allow users to understand how the AI arrived at a particular safety recommendation. This transparency is vital for user confidence and regulatory compliance. Ethical and Fairness Considerations Ethical and Fairness Considerations Bias in AI: GenAISafety actively monitors and addresses potential biases in its AI models to ensure fair and unbiased safety recommendations. This practice is essential in providing equitable safety solutions across diverse workplace environments. Data and Analytics Concepts Data and Analytics Concepts Edge Computing: Edge computing is used in GenAISafety to process data locally on-site, reducing latency and ensuring that safety alerts and interventions are timely. This capability is particularly important in environments where immediate response is critical. Data and Analytics Concepts Data and Analytics Concepts Big Data: Handling and analyzing massive datasets is a core capability of GenAISafety. The system leverages big data to consider a wide range of variables and make informed safety recommendations based on comprehensive analysis, leading to more accurate and reliable outcomes. Application-Specific Concepts Application-Specific Concepts Edge AI: GenAISafety employs Edge AI by deploying AI models directly on edge devices, ensuring that safety interventions can occur in real-time without relying solely on central servers. This capability is crucial for immediate response in critical situations. Application-Specific Concepts Application-Specific Concepts Robotics: In industries where automation is prevalent, GenAISafety integrates with robotics to ensure that robots operate safely and do not introduce new risks into the workplace. This integration is essential for maintaining a safe environment in highly automated settings.

LLM SAND BOX STUDIO LLM Sandbox Studio pour la SST : Innovez en toute sécurité LLM Sandbox Studio is a secure, isolated workspace designed to prepare, train, test, and optimize large language models while ensuring data confidentiality and adherence to safety and ethical standards. 🛠️ Développer et personnaliser Adaptez des LLM pré-entraînés pour vos besoins spécifiques en SST Créez des applications innovantes pour la prévention des risques 🔒 Garantir la confidentialité Travaillez avec vos données sensibles en toute sécurité Respectez les normes de sécurité et de confidentialité 💡 Tester et optimiser Expérimentez avec différents modèles et paramètres Affinez vos applications pour des performances optimales 📊 Analyser et prévoir Générez des insights précieux à partir de vos données SST Anticipez les risques grâce à l'analyse prédictive 🔌 Intégrer facilement Louez des applications LLM prêtes à l'emploi Intégrez rapidement l'IA dans vos processus existants Avec LLM Sandbox Studio, transformez votre approche de la SST grâce à l'IA, sans compromis sur la sécurité. LLM Sandbox Studio Quick View AIAdoptionAnalyst Quick View AIEthicsGuard Quick View PrivacyGuardian AI Quick View GenAITestDrive Quick View GenAISafety PoC Quick View Agent IA – SafetyGPT-Ethica Quick View HSE Prompt Architect Quick View DataForgeAI Quick View PromptCraftPro Quick View ModelInsightAnalyzer Quick View SecureTrainLab

Privacy Policy - Use of Personal Data Compliance with Law 25 At GenAISafety, protecting your personal information is a priority. Our privacy policy complies with the provisions of Law 25 on the protection of personal information, in effect in Quebec. This page explains how we collect, use, and protect your data, particularly when you register for events through our site. 1. Collection of Personal Data When you register for an event organized by GenAISafety, we collect certain personal information to process your registration. In accordance with Law 25, we obtain your explicit consent before collecting any data. The information collected may include: Your full name Your email address Your phone number Job-related information (title, company, etc.) 2. Use of Data The personal data we collect is used solely for: Processing your registration and providing you with event-related information. Contacting you about the event (confirmation, updates, reminders). Improving our services and tailoring our events to your needs. Your data will never be shared or sold to third parties without your explicit consent, except when required by law. 3. Data Protection and Security We implement strict security measures to protect your personal data, in compliance with Law 25: Data encryption during transmission and storage. Restricted access to authorized personnel only within our organization. Regular security policies to ensure ongoing protection. 4. Access, Modification, and Deletion of Your Data In accordance with Law 25, you have the right to: Access your data: You may request to view the personal information we hold about you at any time. Modify or correct your data: If your information is incorrect or outdated, you can request updates. Request deletion of your data: You have the right to ask for your personal data to be deleted, except where the law requires us to retain it. To exercise these rights, please contact us at: [contact email] 5. Consent and Confidentiality When you register, we ask for your explicit consent to collect and use your data. We guarantee that the default settings on our site are configured to ensure the highest level of privacy. 6. Limiting Data Collection We commit to limiting the collection of your data to the information strictly necessary for event registration. We do not collect any superfluous information. 7. Data Breach Notification In the event of a data breach, we have procedures in place to quickly notify affected individuals and the relevant authorities, in compliance with the requirements of Law 25. 8. Updates and Effective Date This policy will be regularly updated to reflect new provisions of Law 25, including those set for September 2024, when users will be able to request access to all personal data we hold on them. For any questions or requests related to this policy, please contact us at: info@prevenera.online Last Updated: 20.09.2024

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Job Offer: AI Engineer for GenAISafety's SquadrAI Company Overview: GenAISafety is an innovative leader in developing artificial intelligence solutions for occupational health and safety. Our mission is to improve safety, health, and productivity in the workplace through the responsible use of AI. At GenAISafety, we believe in responsible innovation, excellence, collaboration, integrity, empathy, and sustainable impact.Our SquadrAI team, a specialized unit at the heart of our ecosystem, combines expertise in Health, Safety and Environment (HSE), Artificial Intelligence (AI), industrial safety, and AI ethics to create cutting-edge solutions.Position: AI Engineer specializing in LLM for workplace safety Mode: Freelance Location: Montreal, Quebec (hybrid)Job Description: As an AI Engineer within SquadrAI, you will be responsible for developing and optimizing our language models (LLMs) specialized in occupational risk prevention. Your main tasks will include: Developing LLMs for the manufacturing sector: Design predictive risk analysis models for production equipment and processes Implement adaptive safety procedure generation systems Optimizing LLMs for the construction sector: Develop models for analyzing construction plans to identify potential risks Create real-time monitoring systems for safety conditions on construction sites Adapting LLMs for the health sector: Design models for analyzing medical records to identify occupational risks Develop systems for predicting and preventing biological and chemical risks Advanced HSE data management: Implement curation and annotation processes for multimodal HSE data Apply bias reduction techniques in training datasets Integrating ethics and safety into LLMs: Develop transparency and explainability mechanisms for model decisions Design systems for detecting and mitigating algorithmic biases Innovation in AI for OHS: Participate in research and development of new LLM architectures adapted to OHS Contribute to the continuous improvement of the Preventera HSE DataHub platform Required Skills: Expertise in deep learning, NLP, and Transformer architectures Proficiency in Python and AI frameworks (PyTorch, TensorFlow) Experience in LLM optimization (fine-tuning, PEFT, RAG) Knowledge of ethical issues related to AI in health and safety Ability to work in a multidisciplinary team within SquadrAI Professional French and English What We Offer: Opportunity to work on innovative projects with high social impact with the SquadrAI team Access to the latest AI and OHS technologies Collaboration with experts in HSE and ethical AI Continuous training and participation in international conferences Competitive compensation To apply, send your CV and a cover letter detailing your relevant experience for these assignments to careers@preventera.online with the subject "SquadrAI Application - AI Engineer".Join SquadrAI at GenAISafety and help shape the future of workplace safety through AI. Rejoignez notre équipe Prénom Nom de famille E-mail Téléphone Occupation Rédigez votre message ici... Date de commencement Lien vers CV/profil LinkedIn Postuler Merci. Nous vous recontacterons.