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Giskard leads GenAI Evaluation in France 2030's ArGiMi Consortium

The ArGiMi consortium, including Giskard, Artefact and Mistral AI, has won a France 2030 project to develop next-generation French LLMs for businesses. Giskard will lead efforts in AI safety, ensuring model quality, conformity, and security. The project will be open-source ensuring collaboration, and aiming to make AI more reliable, ethical, and accessible across industries.

Blanca Rivera Campos

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Giskard-vision: Evaluate Computer Vision tasks

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Giskard Vision: Enhance Computer Vision models for image classification, object an landmark detection

Giskard Vision is a new module in our open-source library designed to assess and improve computer vision models. It offers automated detection of performance issues, biases, and ethical concerns in image classification, object detection, and landmark detection tasks. The article provides a step-by-step guide on how to integrate Giskard Vision into existing workflows, enabling data scientists to enhance the reliability and fairness of their computer vision systems.

Benoît Malézieux

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Evaluating LLM applications: Giskard Integration with NVIDIA NeMo Guardrails

Giskard has integrated with NVIDIA NeMo Guardrails to enhance the safety and reliability of LLM-based applications. This integration allows developers to better detect vulnerabilities, automate rail generation, and streamline risk mitigation in LLM systems. By combining Giskard with NeMo Guardrails organizations can address critical challenges in LLM development, including hallucinations, prompt injection and jailbreaks.

Blanca Rivera Campos

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Global AI Treaty: EU, UK, US, and Israel sign landmark AI regulation

The Council of Europe has signed the world's first AI treaty marking a significant step towards global AI governance. This Framework Convention on Artificial Intelligence aligns closely with the EU AI Act, adopting a risk-based approach to protect human rights and foster innovation. The treaty impacts businesses by establishing requirements for trustworthy AI, mandating transparency, and emphasizing risk management and compliance.

Stanislas Renondin

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L'Oréal leverages Giskard for advanced Facial Landmark Detection

L'Oréal has partnered with Giskard to enhance its AI models for Facial Landmark Detection. The collaboration focuses on evaluating and comparing various AI models using metrics such as Normalized Mean Error, prediction time, and robustness against image perturbations. It aims to improve the accuracy and reliability of L'Oréal's online services, ensuring superior performance across diverse facial regions and head poses. Co-authors: Alexandre Bouchez (L'Oréal), and Mathieu Martial (Giskard).

Rabah Abdul Khalek

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The EU AI Act published in the EU Official Journal: Next steps for AI Regulation

David Mercado

News

Partnership announcement: Bringing Giskard LLM evaluation to Databricks

Alex Combessie

News

LLMOps: MLOps for Large Language Models

Najia Gul

Blog

Defending LLMs against Jailbreaking: Definition, examples and prevention

Matteo A. D'Alessandro

Blog