Assessing the Risks of Large Language Models: DeepKeep’s Generative AI Risk Assessment Module
The increasing adoption of Large Language Models (LLMs) in various industries has raised concerns about their security, trustworthiness, and privacy. To address these issues, DeepKeep, a leading provider of AI-native trust, risk, and security management, has launched its Generative AI Risk Assessment module. This module is designed to secure LLMs and computer vision models by identifying potential vulnerabilities and threats to model security.
DeepKeep’s Generative AI Risk Assessment module provides a comprehensive ecosystem approach to identifying risks associated with model deployment.
The Generative AI Risk Assessment module offers a thorough examination of AI models, ensuring high standards of accuracy, integrity, fairness, and efficiency. It provides a range of scoring metrics for evaluation, including penetration testing, identifying the model’s tendency to hallucinate, and assessing toxic, offensive, harmful, unfair, unethical, or discriminatory language.
Identifying Weak Spots in AI Models
One of the key features of DeepKeep’s Risk Assessment module is its ability to identify weak spots in AI models. For example, when applying the module to Meta’s LLM LlamaV2 7B, the findings pointed to a weakness in English-to-French translation. This highlights the importance of evaluating model resilience, particularly during its inference phase, to provide insights into the model’s ability to handle various scenarios effectively.
Evaluating model resilience is crucial to ensure high standards of transparency and integrity.
Empowering Businesses with Confidence
“The market must be able to trust its GenAI models, as more and more enterprises incorporate GenAI into daily business processes,” says Rony Ohayon, DeepKeep’s CEO and Founder. “Evaluating model resilience is paramount, particularly during its inference phase in order to provide insights into the model’s ability to handle various scenarios effectively. DeepKeep’s goal is to empower businesses with the confidence to leverage GenAI technologies while maintaining high standards of transparency and integrity.”
Securing AI Applications with DeepKeep’s AI Firewall
DeepKeep’s Generative AI Risk Assessment module secures AI applications alongside its AI Firewall, enabling live protection against attacks on AI applications. Detection capabilities cover a wide range of security and safety categories, leveraging DeepKeep’s proprietary technology and cutting-edge research.
ROUGE and METEOR are natural language processing (NLP) techniques for evaluating machine learning outputs. Scores range between 0-1, with 1 indicating perfection.
