Inpher SecurAI: Enhancing Large Language Model Inference with Confidential Computing
In the rapidly evolving landscape of Generative Artificial Intelligence (AI), organizations are exploring applications to enhance productivity and unlock substantial business benefits. However, utilizing AI for applications like code development, content creation, anomaly detection, automation, healthcare analytics or personalization often involves handling sensitive data and intellectual property. The visibility of this data specifically through prompts and completions shared with a model service provider raises serious governance concerns, often hindering organizations from fully leveraging AI capabilities.
In this paper, we will look at the advantages of using generative AI, in this case ChatGPT or other Large Language Models (LLMs), ethically and responsibly by leveraging Trusted Execution Environments (TEEs) and Inpher SecurAI. Inpher SecurAI ensures that both the prompt and the completion are secured during model inference, thus enabling large organizations to solve the sensitive data challenge.
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