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이미지 제공: Conny Schneider

Trust in our Technology: Your Safety, Our Responsibility

Federated Learning

At Tyrell Inc., we've embraced Federated Learning to provide our users with the most personalized AI experience while maintaining a high level of privacy. This approach allows us to train an AI model across multiple decentralized edge devices holding local data samples, without exchanging them. In this way, each user's private data remains on their own device, thus preserving privacy and security.

sLLM Learning

sLLM, or Secure Large Language Model learning, is a significant part of our approach to AI development. Instead of collecting and processing vast amounts of personal data in a central location, sLLM Learning enables the AI to learn from minimal dialogue data stored locally on the user's device. This reduces the risk of data breaches and keeps the user's private information secure.

De-identification Tech

Tyrell Inc. employs advanced de-identification techniques using Generative Adversarial Network (GAN) technology. This method ensures that any data we use to improve our services is stripped of personally identifiable information. It adds an extra layer of security, as even if the data were somehow accessed, it would be extremely difficult to trace back to the original user.

Vertical LLM Learning

As part of our commitment to protect user data, we have implemented Vertical LLM (Large Language Model) Learning. With this technique, our AI learns from de-identified data originating from the user's device, effectively maintaining the privacy of the user's personal information. It helps to strike the right balance between customization and privacy, as it enables the AI to learn and adapt based on the user's interactions, all while protecting their personal data.

이미지 제공: Rene Böhmer

Guarding Your Privacy in the AI Age

We believe that these approaches are crucial for maintaining our users' trust, as they not only allow us to provide personalized AI services, but also ensure that we are doing so in a manner that prioritizes their privacy and security.

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