Research Results

Mon Portfolio Innovation in Occupational Health and Safety Innovation en santé sécurité du travail Research and Prevention Recherche et prévention Health and Safety Awards: Mario Deshaies' HSE Achievements, Key Performance Indicators (KPI), and Oc Health and Safety Performance HSE Risk Management Consultation Projects Portfolio Inteligence artificielle générative Large Language Models (LLM) Assistants IA avancés IA générative pour la santé au travail Analytique de données Conférences and publications

Contact GenAISafety Do you have any questions about our AI solutions for health, safety and environmental risk management? Would you like to learn more about how GenAISafety can transform your company’s safety or have any comments to share? Feel free to contact us! Our team of experts is available to answer all your questions and guide you in implementing solutions adapted to your needs. Whether for a request for information, a personalized quote or support on a specific project, we are here to help you. Take action now: Contact us and learn how GenAISafety can improve the safety of your operations while increasing compliance and efficiency. We look forward to supporting you on your journey to a safer, more efficient work environment. Let's discuss Discuter sur le Chat E-mail genaisafety@preventera.online Social networks First name Name E-mail Company Message Send Thank you for your submission.

Formules personnalisées Les formules personnalisées de GenAISafety offrent une flexibilité et une puissance inégalées pour exploiter pleinement le potentiel des grands modèles de langage (LLM) dans le domaine de la santé et sécurité au travail (SST). Ces formules permettent aux entreprises de créer des colonnes de calcul sur mesure, intégrant des métriques spécifiques à leur industrie et à leurs besoins en SST.Grâce à l'interface intuitive du workspace OpenAI GenAISafety, les utilisateurs peuvent combiner des données provenant de diverses sources, appliquer des fonctions avancées et créer des indicateurs de performance clés (KPI) personnalisés. Ces formules peuvent, par exemple, calculer des taux d'incidents ajustés au risque, évaluer l'efficacité des mesures préventives ou prédire les tendances en matière de sécurité.De plus, les formules personnalisées peuvent intégrer les résultats des LLM spécialisés en SST, permettant ainsi d'enrichir les analyses avec des insights générés par l'IA. Cette approche hybride, combinant données structurées et intelligence artificielle, offre une vision plus complète et nuancée de la performance en SST, aidant les entreprises à prendre des décisions plus éclairées et à optimiser continuellement leurs stratégies de prévention des risques. Formule Discovery La Formule Discovery de GenAISafety est conçue pour les entreprises qui font leurs premiers pas dans l'utilisation de l'IA générative pour la santé et sécurité au travail (SST). Cette offre d'entrée de gamme permet aux organisations d'explorer le potentiel des grands modèles de langage (LLM) dans le domaine de la SST, tout en bénéficiant d'un encadrement sécurisé. Formule Liberty La Formule Liberty de GenAISafety est une solution intermédiaire conçue pour les entreprises qui souhaitent exploiter pleinement les capacités des grands modèles de langage (LLM) dans le domaine de la santé et sécurité au travail (SST). Cette offre complète permet aux organisations d'intégrer l'IA générative de manière approfondie dans leurs processus de SST, tout en bénéficiant d'un environnement sécurisé et personnalisable Formule Enterprise La Formule Entreprise de GenAISafety est une solution haut de gamme conçue pour les grandes organisations ayant des besoins complexes en matière d'intelligence artificielle générative et de santé et sécurité au travail (SST). Cette offre complète et personnalisable permet aux entreprises d'exploiter pleinement le potentiel des grands modèles de langage (LLM) pour transformer leur approche de la SST. Formule GPT Prevent La Formule GPT Prevent de GenAISafety est une solution spécialisée conçue pour les entreprises qui accordent une importance primordiale à la sécurité et à la conformité dans l'utilisation de l'IA générative pour la santé et sécurité au travail (SST). Cette offre innovante combine des technologies de pointe avec des pratiques de sécurité rigoureuses pour créer un environnement d'IA robuste et fiable. Elle comprend un accès à un OpenAI Workspace GenAISafety de base, préconfiguré avec des LLM spécialisés en SST, couvrant des aspects essentiels tels que la gestion des risques, l'analyse des incidents et la conformité réglementaire. Les utilisateurs bénéficient d'une formation initiale sur l'utilisation responsable de ces outils, ainsi que d'un support technique par email pour guider leurs premiers pas. Cette formule offre une introduction structurée et sécurisée à l'IA générative en SST, permettant aux entreprises de découvrir son potentiel tout en minimisant les risques associés à son adoption. Démo Gratuite Webinaire LLM-SST La Formule Liberty offre un Workspace OpenAI GenAISafety avancé, permettant la création et la gestion de multiples LLM spécialisés en SST. Elle comprend des services de fine-tuning pour adapter les modèles aux spécificités de l'industrie du client, ainsi qu'un apprentissage continu pour maintenir les LLM à jour. Les entreprises bénéficient également d'outils d'analyse de performance et de sécurité, de fonctionnalités SST avancées, et d'une formation approfondie sur l'optimisation et l'utilisation des modèles. Cette formule est idéale pour les organisations cherchant à intégrer pleinement l'IA générative dans leur stratégie de SST, en offrant une solution flexible et puissante pour améliorer la gestion des risques, la conformité réglementaire et la sécurité globale sur le lieu de travail. Audit IA-SST Formation LLM Avancée Au cœur de cette formule se trouve un Workspace OpenAI GenAISafety premium, offrant un environnement sécurisé et flexible pour le déploiement de LLM sur mesure adaptés aux différents départements et fonctions SST de l'entreprise. L'intégration d'un service RAG (Retrieval-Augmented Generation) complet permet d'enrichir continuellement les modèles avec des connaissances spécifiques à l'industrie et à l'entreprise, assurant ainsi des réponses toujours pertinentes et à jour. La Formule Entreprise va au-delà de la simple fourniture de technologie en offrant un accompagnement stratégique personnalisé, une intégration sur mesure avec les systèmes existants, et des programmes de formation avancés. Elle inclut également des outils de gouvernance et de contrôle sophistiqués pour garantir une utilisation éthique et sécurisée de l'IA en SST. Cette solution complète vise à transformer radicalement la gestion de la SST, en permettant aux grandes organisations de créer un environnement de travail plus sûr, plus efficace et plus réactif grâce à l'IA générative. Atelier Stratégique Pilote RAG-SST Au cœur de cette formule se trouve un workspace dédié à la sécurité et à la conformité des LLM (grands modèles de langage). Ce workspace offre : Des modèles pré-entraînés sur les normes de sécurité spécifiques à l'industrie du client, garantissant une compréhension approfondie des réglementations et des meilleures pratiques en SST. Des outils automatisés de détection de biais et de contenu inapproprié, assurant que les sorties des modèles restent éthiques et conformes aux standards de l'entreprise. L'intégration de politiques de sécurité personnalisées directement dans les LLM, permettant une application cohérente des règles de sécurité de l'entreprise. La Formule GPT Prevent met l'accent sur la prévention des risques liés à l'utilisation de l'IA en SST. Elle offre des fonctionnalités avancées telles que : Une évaluation continue des risques liés aux LLM, permettant d'identifier et de mitiger les vulnérabilités potentielles. Des mises à jour régulières des bases de connaissances pour le système RAG (Retrieval-Augmented Generation), assurant que les modèles opèrent toujours avec les informations les plus récentes et pertinentes. Des audits trimestriels de sécurité des modèles, garantissant leur conformité continue aux normes de sécurité les plus strictes. Cette formule est idéale pour les organisations qui cherchent à exploiter le potentiel de l'IA générative en SST tout en maintenant les plus hauts standards de sécurité et de conformité. Elle offre la tranquillité d'esprit nécessaire pour innover en toute confiance dans le domaine critique de la santé et sécurité au travail. Évaluation Risques IA Pilote RAG-SST Obtenir un devis Paragraphe. Cliquez sur « Modifier texte » ou double-cliquez sur la zone de texte pour modifier son contenu. Prénom Nom de famille E-mail Envoyer Merci pour votre envoi !

A Year of Progress, A Future of Promise: GenAISafety 2024 Highlights 🚀 LLM 2.0 Explained: Why It’s Better, Faster, and More Accurate Than GPT 🎉 A Year of Progress, A Future of Promise: GenAISafety 2024 Highlights 🚀 Cognitive Safe System framework applied to the PreventionProgram AI (PPAI) Introduction: Transform Workplace Health and Safety with GenAISafety Leitmotif: Every Workplace Accident Can Be Prevented Workplace accident statistics in Quebec reveal concerning trends that highlight the urgency of adopting a proactive approach to workplace health and safety (HSE). Below is an overview of recent data and associated consequences: Increase in Workplace Accidents: Between 2021 and 2022, workplace accidents surged from 93,028 to 149,812—a 61% increase. In 2022, CNESST recorded a total of 190,875 claims for workplace injuries and illnesses, marking a 50% increase from the previous year. Sharp Rise in Occupational Injuries: From 2013 to 2022, the total number of occupational injuries rose by 83.3%, reaching 161,962 cases. This includes a significant 147.5% increase in occupational illnesses. Impact on the Construction Sector: The construction industry has been particularly affected, with 68 deaths recorded in 2023, accounting for approximately 32% of total workplace fatalities. Additionally, CNESST reported 8,676 workplace accidents and 914 occupational illnesses in this sector during the same year. Consequences of Workplace Accidents: Economic Costs: Workplace accidents impose significant costs on businesses and society, including medical expenses, compensation for injured workers, and productivity losses. Social Consequences: These accidents impact not only direct victims but also their families and colleagues, causing lasting psychological trauma and affecting workplace morale. GenAISafety positions itself as a key player in reversing these trends through innovative approaches driven by generative artificial intelligence. This is a story of innovation, vision, and collaboration. Origins and Mission Birth of an Idea: It all began with a clear vision: to use artificial intelligence (AI) to transform how businesses address workplace health and safety. The founders of Preventera and GenAISafety, experts passionate about AI and HSE, identified a significant gap between advanced technologies and traditional prevention practices. Mission: Preventera and GenAISafety aim to harness AI to create safer and healthier workplaces. They seek to foster a culture where safety and technology combine for the greater good. Detailed Milestones of GenAISafety: 2022 to 2024 2022: Development and Research Creation of the HSE Data Hub: Establishment of an integrated data infrastructure to centralize workplace health and safety information. Use of OWL Ontology to Structure Data and Connect Disparate Quebec and International Databases, Including CNESST, IRSST, Standardized International Accidentology Sources, Sector-Specific Industrial Operational Data, and Scientific Studies (e.g., INRS) The OWL ontology provides a robust framework for organizing and linking diverse data sources. It facilitates seamless integration across: Provincial Resources: Databases from Quebec-based organizations such as CNESST and IRSST, capturing regulatory, operational, and risk-related data. International Standards in Accidentology: Harmonization with global frameworks for accident analysis and prevention, ensuring alignment with best practices. Sector-Specific Industrial Data: Incorporating operational datasets from industries such as construction, manufacturing, and energy to tailor solutions to unique sectoral needs. Scientific Research: Leveraging cutting-edge studies from organizations like INRS to inform evidence-based safety practices. This structured approach enhances interoperability, enables advanced analytics, and supports predictive modeling to revolutionize health and safety management in diverse environments. Standardization of HSE concepts to ensure seamless interoperability. Strategic Partnerships: Collaborations with sectoral associations and academic institutions to refine proposed solutions. Initiation of pilot projects in specific sectors, such as construction and energy. R&D Investments: Launch of research on predictive models for HSE using historical data. Development of the first real-time risk analysis algorithms. 2023: Launch of New Products and Leadership Development Data Integration and Structuring: Finalization of the Preventera DataHub, featuring visualization tools to identify emerging trends and risks. Adoption of interoperable solutions to streamline regulatory compliance and declarations. Appointment of Mario Deshaies as Visionary Innovation Strategy Officer (VISO): Strengthening GenAISafety's strategic vision to transform HSE standards. Highlighting a combined human and AI approach to anticipate and prevent risks. Development of the GenAISafety LLM Suite: Creation of over 100 fine-tuned AI tools based on large language models (LLMs) tailored to 10 industrial sectors. Integration of local (LSST, RSST) and international (CSA, ISO) standards and regulations. Participation in International Events: Presentation of solutions at conferences such as the Grand Rendez-vous in HSE and other forums focused on AI innovation. 2024: Significant Achievements and Strategic Launches Launch of the GenAISafety Suite: Introduction of comprehensive solutions for proactive prevention tailored to small and large enterprises. Coverage across 10 industries, including manufacturing, construction, agribusiness, and energy. Global HSE Marketplace: Deployment of the first marketplace dedicated to AI-based HSE solutions. Facilitating access to innovative tools for businesses aiming to enhance their safety and compliance. Collaboration with Regional Innovation Hubs: Integration of Quebec’s regional hubs to develop personalized solutions addressing local sectoral needs. Resource pooling to provide accessible solutions for SMEs. Participation in ALL IN 2024: Showcasing GenAISafety innovations on a global stage. Interactive demonstrations of HSE use cases, including predictive analysis and AI conversational agents. Deployment of Real Solutions: Testing and validation of tools in real industrial environments. Collaboration with partner companies to measure direct impacts on risk reduction. Impact of These Milestones on GenAISafety’s Vision Transforming HSE: A successful transition to AI-based approaches, enhancing efficiency and safety. Greater adoption by SMEs through accessible and user-friendly tools. Quebec’s Leadership: Strengthening Quebec’s position as a global leader in HSE innovation. Attracting foreign investments through unique initiatives like the Marketplace and Regional Hubs. Key Goals for 2025-2030: 30% reduction in workplace accidents in Quebec. Projected savings of $2 billion for the Quebec economy through improved prevention. Leadership in global HSE solutions powered by AI. With these ambitious milestones and goals, GenAISafety is poised to sustainably transform workplace health and safety, not just in Quebec but worldwide.

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.

The era of proactive accident prevention and health well-being in the workplace, driven by the precision and power of generative AI. GenAISafety © AI-Powered Workplace Accident Prevention and Employee Well-Being GenAISafety Events GenAISafety & GPT-4o Thu, Jan 16 Conférence en ligne Jan 16, 2025, 8:30 AM – 3:30 PM Conférence en ligne Jan 16, 2025, 8:30 AM – 3:30 PM Conférence en ligne Optimisation des processus HSE grâce à GenAISafety et GPT-4o : Évaluation avancée des risques et conformité réglementaire Buy Tickets Mastery en Générative AI et LLM pour la Sécurité et la Gestion des Risques en entreprise Fri, Jan 17 En ligne ou sur place chez le client Jan 17, 2025, 8:00 AM – Feb 28, 2025, 11:30 AM En ligne ou sur place chez le client Jan 17, 2025, 8:00 AM – Feb 28, 2025, 11:30 AM En ligne ou sur place chez le client Le programme est conçu pour guider les apprenants à travers une maîtrise progressive des concepts de l'IA générative, en utilisant une approche structurée . See All RSVP Lancement Officiel – Suite GenAISafety : Agentic SquadrAI Quebec 2025 Fri, Jan 17 Zoom GenAISafety Event Jan 17, 2025, 10:00 AM – 11:00 AM Zoom GenAISafety Event Jan 17, 2025, 10:00 AM – 11:00 AM Zoom GenAISafety Event Lancement Officiel – Suite GenAISafety : Agentic SquadrAI Quebec 2025 🔹 Rejoignez-nous pour une révolution en santé et sécurité au travail (SST) ! GenAISafety est fier de vous présenter Agentic SquadrAI Suite – GenAISafety Quebec 2025, une série d’agents intelligents autonomes conçus pour la SST See All Buy Tickets GPT-4o et GenAISafety La date et l'heure sont à définir Conférence en ligne La date et l'heure sont à définir Conférence en ligne La date et l'heure sont à définir Conférence en ligne GPT-4o et GenAISafety : Révolutionnez votre HSE avec l'IA multimodale de pointe Details GenAISafety© Welcome to GenAISafety.online, a global leader in transforming Occupational Health and Safety (OHS) through generative artificial intelligence. In a world where workplace safety is becoming increasingly complex, GenAISafety innovates by enabling businesses to shift from a reactive approach to a proactive one. Our GenAISafety suite solutions anticipate risks, analyze real-time data, and provide personalized recommendations to enhance safety. With GenAISafety, generative AI becomes a key asset in protecting your employees, strengthening compliance, and reducing costs related to workplace accidents. We put safety at the heart of every strategic decision. Transforming Workplace Safety with Trusted AI Solutions. Secure Your Workforce, Boost Productivity, and Achieve Zero Accidents with GenAISafety Transforming Occupational Health and Safety with AI Harness the power of GenAISafety© to anticipate, predict, and mitigate risks, strengthen compliance, and create a safer workplace with AI-driven analytics and automation that impact your safety culture. In today’s fast-changing business landscape, ensuring employee well-being is key to operational success. Workplace injuries can impact productivity, legal compliance, and your reputation. GenAISafety transforms safety management by shifting from reactive to proactive strategies. Powered by advanced AI and analytics, GenAISafety predicts risks, prevents incidents, and integrates seamlessly into your safety protocols. As we look towards 2027, industry-specific GenAISafety models offer unmatched precision in risk management, enabling sustainable and responsible AI deployment. GenAISafety is the future of AI-driven safety—ensuring compliance, boosting efficiency, and protecting your workforce. GenAISafety Technologies Development Subscribe to Our Newsletter | Abonnez-vous à notre newsletter Enter your email adress Merci pour votre envoi ! Merci pour votre envoi ! Contact us "Contact us using this form. We will get back to you as soon as possible. Prénom Nom E-mail Envoyer Merci pour votre envoi !

Technologies Technologies GenAISafety’s cutting-edge technologies stand out for their ability to address the complex needs of health, safety, and environmental (HSE) risk management. Powered by advanced artificial intelligence algorithms, GenAISafety integrates a variety of technologies, from image annotation to video generation to GPU acceleration. Here’s a detailed look at the key technologies: Image and Video Annotation Platforms for AI and Computer Vision Projects Synthetic Data GPU Acceleration Image and Video Annotation Platforms for AI and Computer Vision Projects Synthetic Data GPU Acceleration Technology: Image and video annotation platforms Example: CVAT (Computer Vision Annotation Tool) Explanation: These platforms, often open-source, allow the creation of annotated data sets for AI models to recognize and analyze risks in work environments. They are essential for training algorithms to detect incidents and potential dangers. Technology: Synthetic data generation solutions Example: Amazon SageMaker Ground Truth Explanation: Using synthetic data to address the lack of real-world data in certain industrial sectors. This allows modeling complex safety scenarios while adhering to data privacy standards. Technology: CUDA, cuDNN Example: NVIDIA A100, GeForce RTX series 30/40 Explanation: GPU acceleration allows the processing of large amounts of data and real-time simulations. This is crucial for applications like the recognition of dangerous objects or modeling high-risk workflow streams. Advanced Chatbots Federated Learning Data Processing Advanced Chatbots Technology: Transformers, Retrieval-Based Models Example: ChatGPT, Claude Explanation: Chatbots can be used to answer employee questions about safety protocols and provide real-time assistance on the ground in case of emergency. Federated Learning Technology: Cryptography algorithms, Secure Multi-Party Computation Example: TensorFlow Explanation: Allows the training of models on decentralized data without compromising the confidentiality of sensitive information, thereby ensuring compliance with regulations such as GDPR. Data Processing Technology: Autoencoders, GANs Example: Mostly AI, Syntho Explanation: Generate synthetic data sets to simulate complex HSE (Health, Safety, Environment) scenarios, facilitating testing and optimizing prevention systems. Transformers, GPT, BERT Exemple : ChatGPT, GPT-3, BERT echnologie : Transformers spécialisés Exemple : GitHub Copilot, Amazon Q Developer Audio/Music Generation Text Generation Technology: Transformers, GPT, BERT Example: ChatGPT, GPT-3, BERT Explanation: These models generate coherent text for safety documents, such as incident reports, recommendations, or training manuals. Code Generation Technology: Specialized Transformers Example: GitHub Copilot, Amazon Q Developer Explanation: Automates the creation of scripts and processes for monitoring safety data and generating compliance reports. Audio/Music Generation Technology: WaveNet, GANs Example: Jukebox, AIVA Explanation: Compose alert sounds or audio prompts adapted to workplace environments. This includes the use of voice recognition for security systems in noisy environments. PodCast. Sand Box AI PodCastt. LLM 2.0 Explained 🚀 LLM 2.0 Explained: Why It’s Better, Faster, and More Accurate Than GPT 🎉 A Year of Progress, A Future of Promise: GenAISafety 2024 Highlights 🚀 Cognitive Safe System framework applied to the PreventionProgram AI (PPAI) Pour concevoir un grand modèle de langage (LLM) GenAISafety, plusieurs outils et langages sont couramment utilisés : Langages de programmation Python est de loin le langage le plus utilisé pour le développement de LLM, en raison de sa simplicité et de la richesse de son écosystème pour l'apprentissage automatique. Les bibliothèques Python populaires incluent : PyTorch TensorFlow Hugging Face Transformers Infrastructure de calcul GPUs NVIDIA : Essentiels pour l'entraînement rapide des modèles TPUs Google : Optimisés pour les workloads d'apprentissage profond Plateformes cloud : AWS, Google Cloud, Azure offrent des ressources de calcul évolutives Frameworks d'apprentissage profond Les frameworks les plus couramment utilisés sont : PyTorch : Très populaire pour sa flexibilité et son approche dynamique TensorFlow : Développé par Google, offre de bonnes performances et un déploiement facile Préparation et gestion des données Apache Spark : Pour le traitement de grands volumes de données Databases NoSQL : Pour stocker et gérer efficacement les vastes corpus de textes Outils spécialisés Hugging Face : Fournit des modèles pré-entraînés et des outils pour le fine-tuning NVIDIA Megatron-LM : Optimisé pour l'entraînement de très grands modèles sur des clusters GPU Outils de suivi et visualisation Weights & Biases : Pour suivre les expériences et visualiser les résultats TensorBoard : Outil de visualisation intégré à TensorFlow GenAISafety Suite: A Technology Framework Cutting-edge technologies for GenAISafety suites based on SaaS, BaaS and AI app stores Summary of Product Deliverables for GenAISafety 1. SaaS (Software as a Service) The GenAISafety Suite is based on a SaaS model to provide generative AI solutions for risk management and safety via the cloud. The characteristics of this deliverable include: Real-time access: Companies can use generative AI tools directly from the cloud, eliminating the need to manage complex infrastructure. Continuous updates: Security tools and AI models are constantly improved and updated automatically to protect against new risks. Scalability: The SaaS architecture easily adjusts to meet growing data management needs. Cost-effectiveness: The subscription model reduces upfront costs, offering advanced security tools without significant investment. 2. Backend as a Service (BaaS) The Backend as a Service (BaaS) provides a secure infrastructure to support GenAISafety's generative AI applications. This service includes: Optimized development environment: It allows developers to focus on security features with ready-to-use solutions for storage, authentication, and APIs. Enhanced security: BaaS ensures secure management of sensitive data related to workplace safety. AI Integration: It facilitates the rapid deployment of AI models for real-time risk assessments and automated decisions based on predictive analytics. API Accessibility: BaaS offers APIs and SDKs tailored for seamless integration into various security systems. 3. AI Application Stores GenAISafety leverages AI application stores to expand its capabilities and provide ready-to-use AI solutions. The deliverables include: Pre-validated AI solutions: Access to AI tools that have already been tested and comply with safety and ethical standards. Customization: Users can select and adapt AI models, such as those used for bias detection and risk verification. Efficiency: Companies can quickly implement generative AI applications, thus reducing development time. Certifications and standards: The AI application stores offer certified tools that comply with security standards, ensuring the reliability of deployed solutions. Summary of Product Deliverables for GenAISafety SaaS (Software as a Service) . BaaS (Backend as a Service) AI Application Stores Obtenir un devis Paragraphe. Cliquez sur « Modifier texte » ou double-cliquez sur la zone de texte pour modifier son contenu. Prénom Nom de famille E-mail Envoyer Merci pour votre envoi !

Transformations Technologiques : Projets d'IA Générative chez GenAISafety Transformez votre approche de la sécurité au travail : Découvrez nos solutions innovantes! Chaine Preventera-sommaire et clients Chaine Preventera-sommaire et clients Play Video Share Whole Channel This Video Facebook Twitter Pinterest Tumblr Copy Link Link Copied Search video... Now Playing AI Safeguard Pioneers Revolutionizing 02:44 Play Video Now Playing ABOUT PREVENT-ERA 00:52 Play Video

Training Methods for LLMs at GenAISafety At GenAISafety, the training of large language models (LLMs) is based on advanced techniques designed to ensure optimal performance in risk management related to workplace safety, environment, and health. Here’s an overview of the training methods we use to develop LLMs tailored to the specific needs of our clients: 1. Pre-training on Specialized HSE Data At GenAISafety, we leverage the innovative Preventera HSE DataHub platform to revolutionize health, safety, and environmental (HSE) risk management. Our solution uses artificial intelligence (AI) to centralize, organize, and analyze vast datasets from multiple sources, while ensuring compliance with standards such as ISO 45001 and ISO 31000 2. Supervised and Semi-Supervised Training We apply a hybrid approach of supervised and semi-supervised training, combining: Supervised training: Models are trained using annotated examples to ensure high accuracy in specific scenarios, such as risk identification and accident prevention. Semi-supervised training: We utilize partially annotated datasets to enable models to gain flexibility in analyzing less structured data, while maintaining consistency in their predictions. 3. Reinforcement Learning We also use reinforcement learning, where models receive feedback on their performance and adjust their predictions accordingly. This method allows optimization of results in complex environments, taking into account changing regulations and working conditions. 4. Fine-tuning on Client-Specific Data We tailor our LLMs to the specific needs of each organization through a fine-tuning phase on company-specific data. This process improves the relevance of the model's responses and ensures that the proposed solutions are aligned with the organization's internal safety policies. 5. Integration of Retrieval-Augmented Generation (RAG) At GenAISafety, we integrate Retrieval-Augmented Generation (RAG) into our language models (LLMs) to enhance the accuracy and relevance of the generated responses. This approach combines real-time information retrieval from internal or external knowledge bases with AI generation, allowing the model's contextual responses to be enriched. Here’s how we effectively implement RAG: 6. Security and Ethics Our models are trained with a focus on security and ethics, including: Reduction of algorithmic biases Respect for data privacy (compliance with regulations such as GDPR) Transparency and explainability of decisions made by the models