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🚀 Tether Announces Launch of Open-Source AI Project

According to PANews, Tether's CEO Paolo Ardoino has announced the upcoming launch of a new project named Tether.ai on his X platform account.

Ardoino described Tether.ai's core product, 'Personal Infinite Intelligence,' as a fully open-source AI Runtime. This AI Runtime is designed to operate on any hardware or device without the need for API keys, eliminating centralized points of failure. It is also fully modular and composable. Notably, the AI Runtime will integrate WDK, presumed to be Tether's development kit, to support payments using stablecoin USDT and Bitcoin.

Ardoino envisions that Tether's AI technology aims to eventually build a peer-to-peer network consisting of billions of AI agents.


#Tether #TetherAI #OpenSource #AI #PersonalInfiniteIntelligence #AI_Runtime #Stablecoin #USDT #Bitcoin #PeerToPeer #AIAgents #BTC
🚀 Tether AI Team to Announce Groundbreaking Achievement This Week

Tether CEO Paolo Ardoino has announced that the Tether AI team is set to unveil a significant achievement this week. According to NS3.AI, Ardoino emphasized the groundbreaking nature of the upcoming release, highlighting its potential impact on the industry. Details about the achievement remain undisclosed, but the announcement has generated anticipation within the crypto community.

#TetherAI #PaoloArdoino #groundbreaking #crypto #achievement #NS3AI #AIannouncement
🚀 Tether AI Team Unveils Enhanced QVAC Fabric with Cross-Platform Capabilities

Tether CEO Paolo Ardoino has announced the release of a new version of QVAC Fabric by the Tether AI team. According to ChainCatcher, this update integrates the BitNet LoRA framework, enabling the training and inference of large models with billions of parameters on consumer-grade GPUs and smartphones.

The updated QVAC Fabric LLM marks the first instance of BitNet LoRA fine-tuning and inference running cross-platform on AMD, Intel, Apple Metal, and mobile GPUs. On flagship devices, GPU inference speed has increased by 2 to 11 times compared to CPUs, while memory usage has been reduced by up to 90% compared to full-precision models. The Tether team has successfully fine-tuned models with up to 3.8 billion parameters on flagship smartphones such as Pixel 9, S25, and iPhone 16, and achieved fine-tuning of models with up to 13 billion parameters on the iPhone 16. The related code has been made open-source on GitHub.


#TetherAI #QVACFabric #BitNetLoRA #AI #LLM #CrossPlatform #GPU #MobileAI #OpenSource #MachineLearning #DeepLearning #AIInnovation #AIModels #SmartphoneAI #TechNews