Tether launches Local AI SDK for privacy-focused solutions

Tether (CRYPTO:USDT) has introduced its new software development kit (SDK) called “Local AI,” with a strong emphasis on privacy and modularity. 

According to Paolo Ardoino, Tether’s CEO, the Local AI SDK aims to run on various devices without compromising user data, ensuring that operations are conducted locally. 

Unveiled at the Plan ₿ event on October 26 in Lugano, Switzerland, Local AI was designed to support a wide range of devices, from low-cost smartphones to high-performance systems. 

The technology is versatile enough to function on devices like smart refrigerators and automotive entertainment systems. 

Ardoino explained that the SDK’s primary goal is to allow AI operations to be executed on the device itself, eliminating the need to share private information with external servers or third parties. 

The Local AI SDK employs a peer-to-peer (P2P) data-sharing structure that enables secure transmission of model weights and fine-tuning information between devices. 

This framework enhances its privacy capabilities and reinforces Tether’s commitment to developing privacy-centered solutions. 

Ardoino described this technology as built to accommodate different AI models, such as Marian and Llama, and noted that it would be released as open-source after comprehensive testing phases. 

“Users can perform all tasks locally without worrying about third-party data access,” said Ardoino, highlighting the privacy-first approach behind the new technology. 

During the Plan ₿ event, he showcased a real-time translation app running entirely on-device as an example of the SDK’s practical applications. 

The Local AI SDK’s open-source release is expected to broaden accessibility for developers and users interested in privacy-focused technologies. 

According to Ardoino, the foundation of the SDK was built upon Tether’s open-source project “holepunchto/bare,” which played a vital role in shaping the framework’s structure.

At the time of reporting, the Tether price was $0.9986.