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Giskard's LLM Red Teaming
News

LLM Red Teaming: Detect safety & security breaches in your LLM apps

Introducing our LLM Red Teaming service, designed to enhance the safety and security of your LLM applications. Discover how our team of ML Researchers uses red teaming techniques to identify and address LLM vulnerabilities. Our new service focuses on mitigating risks like misinformation and data leaks by developing comprehensive threat models.

Blanca Rivera Campos
Blanca Rivera Campos
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Data Drift Monitoring with Giskard
Tutorials

Data Drift Monitoring with Giskard

Learn how to effectively monitor and manage data drift in machine learning models to maintain accuracy and reliability. This article provides a concise overview of the types of data drift, detection techniques, and strategies for maintaining model performance amidst changing data. It provides data scientists with practical insights into setting up, monitoring, and adjusting models to address data drift, emphasising the importance of ongoing model evaluation and adaptation.

Sagar Thacker
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Classification of AI systems under the EU AI Act
News

EU AI ACT: 8 Takeaways from the Council's Final Approval

The Council of the EU has recently voted unanimously on the final version of the European AI Act. It’s a significant step forward in its efforts to legislate the first AI law in the world. The Act establishes a regulatory framework for the safe use and development of AI, categorizing AI systems according to their associated risk. In the coming months, the text will enter the last stage of the legislative process, where the European Parliament will have a final vote on the AI Act.

Javier Canales Luna
Javier Canales Luna
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