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Tether introduced a framework enabling large language model training on smartphones.
The system used BitNet architecture and LoRA fine-tuning to reduce compute needs.
Crypto firms increased spending on AI infrastructure and high-performance computing.
Tether released a new artificial intelligence training framework on Tuesday that enables large language models to run and fine-tune on consumer hardware. The system formed part of the company’s QVAC platform and supported smartphones alongside several non-Nvidia processors. Engineers designed the framework to reduce memory requirements, thereby lowering the cost barrier to building and testing language models.
The launch came as crypto infrastructure companies moved deeper into artificial intelligence development and compute markets. Tether, issuer of the largest stablecoin by market capitalization, framed the release as an attempt to decentralize machine-learning capabilities. The firm argued that enabling m
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