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QVAC SDK and Fabric give people and companies the ability to execute inference and fine-tune powerful models on their own terms, on their own hardware, with full control of their data. techcrunch.com/sponsor/tether…

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Tether AI team is building the open-source building block of Intelligence, standardized, stackable, and infinitely scalable

The QVAC SDK is the "LEGO block" of the next era of computing. It’s a modular, local-first framework designed to turn anything—from a simple robot to an industrial server—into a sovereign, autonomous mind. Why build with QVAC? Atomic Intelligence: AI as a raw material embedded directly into your hardware. No Cloud Dependency: 0 latency and total privacy. If the internet breaks, your world keeps thinking. Infinite Scale: A single API for local AI that runs on any device, anywhere. From a child’s toy to the fabric of the universe, if you can dream it, you can build it. Start building the future: docs.qvac.tether.io 🚀

The QVAC SDK puts the "brain" directly into your pocket. From real-time on-device translation to multimodal understanding, build apps that work everywhere, even 30,000 feet in the air. Local AI is here: 💡Offline-First: No cloud, no latency, no "Department of Truth". 💻 Universal API: One codebase for iOS, Android, macOS, and Linux. 🔍 Multimodal: Understanding text, audio, and images without a server. If you can dream it, you can build it. The era of Stable Intelligence has begun. Start building: docs.qvac.tether.io

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Two islands. Two futures. 🏝️ One chose to trust its people with intelligence. The other turned them into the product. QVAC is the foundation for a sovereign future. No central servers, no "Department of Truth," and no surveillance. Just local-first AI that lives on your device, learns with you, and belongs to you. Your data. Your device. Your freedom. Build the right choice: qvac.tether.io

Tether's QVAC SDK has a unified API for LoRA on-device model finetuning. No cloud, no privacy blackholes. Just your hardware.

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QVAC SDK will support in 0.9.0 (gonna be release in ~10 days) LoRA fine-tuning directly on-device, letting developers customize LLMs with their own data without sending anything to the cloud. You just load a base model, point it at your training dataset, and get a lightweight LoRA adapter back — all running locally. The fine-tuned model can then be used for inference immediately, with no extra setup. Why it matters: LoRA (Low-Rank Adaptation) fine-tuning lets you specialize a general-purpose language model for your specific use case — like matching a brand's tone, mastering domain terminology, or following a particular output format — using a fraction of the compute a full fine-tune would require. QVAC handles the entire workflow locally: dataset preparation, training with configurable hyperparameters, checkpoint saving, and seamless inference with the resulting adapter. Your data never leaves the device. The developer experience: Fine-tuning with QVAC is as simple as calling "sdk.finetune()" with your dataset and a few hyperparameters. Training runs entirely on your local hardware, produces a compact LoRA adapter file, and supports pause/resume so you can stop a job and pick it back up without losing progress. The result plugs straight into QVAC's inference pipeline — no model conversion, no deployment step, just immediate local completions with your fine-tuned model. qvac.tether.io

When the industry faces challenges, Tether steps up. 🛡️ We are leading an up to $150M recovery plan alongside the @SolanaFndn to support user recovery and safely relaunch @DriftProtocol Watch the video to see how we're protecting the community and expanding $USDT on Solana. 👇

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Today will be a good day for DeFi

Bare is a super-efficient Javascript runtime built by the Tether/Holepunch team that runs on any platform, operative system and environment. Code once, scale anywhere.

WDK Hackathon semi-finalists 👇

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Tether Backs $134 Million Raise as Stablecoin Infrastructure Expands into Mainstream Use Cases Learn more: tether.io/news/tether-ba…