Tether Unveils A Technology That Breaks The Conventions Of AI training

Tether has just propelled the AI market to a whole new level. The company unveils a framework capable of training models directly on smartphones. This breakthrough shakes up the industry standards. But not only that! It also paves the way for more accessible artificial intelligence.

Here is how Tether makes training AI models possible on smartphones

Tether introduces a system based on the BitNet architecture and LoRA fine-tuning. This combination significantly reduces computing power and memory optimization. Result: a language model can run on a simple smartphone.

The numbers are particularly striking. An AI model with one billion parameters is indeed trained in less than two hours. Tests even show capabilities up to 13 billion. This performance relies on 1-bit models, much lighter than classical architectures.

But that’s not all! The memory gain also reaches 77.8%. This changes the game for machine learning and deep learning. Developers no longer need high-end GPUs. The framework also runs on multiple chips, including Apple, AMD, and Qualcomm.

Inference also gains in speed. Mobile GPUs outperform CPUs with performance up to 11 times higher. This technical leap brings AI closer to everyday life. The fact is that model training leaves data centers to settle in users’ pockets.

AI: towards a decentralized infrastructure without Cloud or Nvidia

This innovation goes beyond simple technical prowess. It effectively redefines AI infrastructure as it reduces dependence on cloud giants and Nvidia GPUs. Decentralized AI thus becomes a credible scenario.

The system favors federated learning. Data remains on the device. Data processing gains in privacy. Each user thus participates in distributed computing without exposing their information.

This model aligns with the logic of “edge computing”. AI runs as close as possible to the user. This approach limits costs and speeds up processing. It also opens new use cases for mobile applications.

Tether’s initiative therefore confirms a broader trend. AI is moving closer to users and away from data centers. This evolution could redefine the balance between Big Tech and decentralized actors.