- DeepKeep introduces GenAI Risk Assessment module for enhancing trust in AI models.
- CEO Rony Ohayon emphasizes robust evaluation during model inference phase.
- Module identifies vulnerabilities in Meta’s LLM LlamaV2 7B for prompt manipulation sensitivity.
- Comprehensive ecosystem approach covers deployment risks and application weaknesses.
- Features include penetration testing, bias assessment, and real-time AI Firewall protection.
Main AI News:
DeepKeep’s latest innovation, the GenAI Risk Assessment module, aims to fortify trust in AI models amid their widespread integration into daily business operations. Rony Ohayon, CEO and founder of DeepKeep, emphasizes the critical need for robust model evaluation during the inference phase. This phase is pivotal in ensuring that AI systems can effectively handle diverse scenarios with resilience and reliability. DeepKeep is dedicated to equipping enterprises with the confidence to harness GenAI technologies while upholding transparency and integrity standards.
DeepKeep’s Risk Assessment module, applied to Meta’s LLM LlamaV2 7B for prompt manipulation sensitivity analysis, revealed vulnerabilities in English-to-French translations. Employing a comprehensive ecosystem approach, the module identifies deployment risks and pinpoints weaknesses within AI applications. It boasts a meticulous evaluation framework that includes a spectrum of scoring metrics. These metrics aid security teams in optimizing GenAI deployment processes, ensuring adherence to stringent quality benchmarks.
Key functionalities of DeepKeep’s GenAI Risk Assessment module encompass penetration testing to gauge system vulnerabilities, detection of model hallucination tendencies, and identification of potential data leakage risks. Additionally, the module evaluates language for toxicity, offensiveness, and unfair biases. DeepKeep integrates cutting-edge AI Firewall technology to provide real-time protection against cyber threats targeting AI applications. This innovative solution leverages DeepKeep’s advanced research and technology capabilities to safeguard AI deployments across diverse security and safety domains.
Conclusion:
This launch of DeepKeep’s GenAI Risk Assessment module marks a significant advancement in AI security practices. By addressing vulnerabilities and enhancing transparency in AI model deployments, DeepKeep aims to instill greater confidence among enterprises leveraging GenAI technologies. This proactive approach not only mitigates risks associated with AI applications but also sets a new standard for ensuring integrity and reliability in the evolving AI market landscape.
