Open Source AI Project

Goten

Goten is designed to enhance the security of neural network training on GPUs.

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Goten is a project focused on bolstering the security measures during the training phase of neural networks, specifically when utilizing Graphics Processing Units (GPUs). In the realm of machine learning and artificial intelligence, the sanctity and privacy of data, along with the proprietary nature of models, are of paramount importance. Goten addresses these concerns by implementing what is known as trusted execution environments (TEEs). TEEs are secure areas within the processor that provide a higher level of security against software attacks, thereby safeguarding the integrity and confidentiality of the data and models involved in the training process.

The core objective of Goten is to ensure that during the training phase, sensitive information and intellectual property related to AI models are securely enclosed within these protected environments. This not only prevents unauthorized access but also mitigates the risk of potential data breaches or intellectual property theft. As AI and machine learning operations become increasingly integral to various sectors, the importance of such security measures has escalated. Goten’s implementation of TEEs on GPUs for neural network training is a significant step towards addressing the burgeoning concerns around AI intellectual property and user privacy, ensuring that stakeholders can conduct their machine learning operations without fear of compromise.

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