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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 integrates with LiteLLM to simplify LLM agent testing

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[Release notes] Giskard integrates with LiteLLM: Simplifying LLM agent testing across foundation models

Giskard's integration with LiteLLM enables developers to test their LLM agents across multiple foundation models. The integration enhances Giskard's core features - LLM Scan for vulnerability assessment and RAGET for RAG evaluation - by allowing them to work with any supported LLM provider: whether you're using major cloud providers like OpenAI and Anthropic, local deployments through Ollama, or open-source models like Mistral.

Blanca Rivera Campos

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AI Liability in the EU: Business guide to Product (PLD) and AI Liability Directives (AILD)

The EU is establishing an AI liability framework through two key regulations: the Product Liability Directive (PLD), taking effect in 2024, and the proposed AI Liability Directive (AILD). The PLD introduces strict liability for defective AI systems and software, while the AILD addresses negligent use, though its final form remains under debate. Learn in this article the key points of these regulations and how they will impact businesses.

Stanislas Renondin

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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

Stanislas Renondin

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L'Oréal leverages Giskard for advanced Facial Landmark Detection

Rabah Abdul Khalek

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

David Mercado

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Partnership announcement: Bringing Giskard LLM evaluation to Databricks

Alex Combessie

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