Paolo Ardoino, CEO of blockchain platform Tether, emphasized the importance of localized AI models in ensuring privacy and security following a recent hack of OpenAI.
Ardoino argues that localized AI models are essential for protecting individuals and their privacy. By running AI models locally on devices like smartphones and laptops, users can ensure their data remains secure and independent.
Ardoino highlighted that modern devices have enough processing power to “fine–tune general large language models (LLMs) with users’ own data, keeping enhancements local to the device.” This approach would prevent the need for third-party servers, thereby reducing vulnerability to hacks and improving data security.
In a statement, Ardoino described localized AI models as a “paradigm shift” in user privacy and independence:
“By running directly on the user’s device, be it a smartphone or laptop, these models eliminate the need for third-party servers. This not only ensures that data stays local, enhancing security and privacy, but also allows for offline use.”
This setup allows users to benefit from advanced AI–driven experiences and data analysis while maintaining complete control over their information.
Tether recently announced its expansion into AI, with Ardoino mentioning that the company is “actively exploring” the integration of locally executable models into its AI solutions.
This focus on localized AI models comes in response to a recent security breach experienced by OpenAI. In early 2023, a hacker accessed OpenAI’s internal messaging systems, compromising sensitive information about the company’s AI technologies.
By advocating for localized AI models, Tether aims to prevent similar breaches and enhance user privacy and security.
Summary Review: By advocating for localized AI models, Tether aims to prevent similar breaches and enhance user privacy and security. This approach represents a significant shift in how AI technology can be implemented to safeguard user data and promote independence from centralized servers.
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