{"id":25629,"date":"2025-12-02T20:00:20","date_gmt":"2025-12-02T20:00:20","guid":{"rendered":"https:\/\/www.criptofacil.com\/es\/?p=25629"},"modified":"2025-12-02T17:22:09","modified_gmt":"2025-12-02T17:22:09","slug":"tether-lanza-solucion-que-permite-entrenar-modelos-de-ia-en-celulares-y-portatiles","status":"publish","type":"post","link":"https:\/\/www.criptofacil.com\/es\/tether-lanza-solucion-que-permite-entrenar-modelos-de-ia-en-celulares-y-portatiles\/","title":{"rendered":"Tether lanza soluci\u00f3n que permite entrenar modelos de IA en celulares y port\u00e1tiles"},"content":{"rendered":"<p><strong>Tether Data<\/strong> present\u00f3 hoy el <strong>QVAC Fabric LLM<\/strong>, un nuevo entorno de ejecuci\u00f3n y ajuste de modelos de lenguaje que permite realizar inferencia y fine-tuning directamente en dispositivos del d\u00eda a d\u00eda. En otras palabras, la soluci\u00f3n permite <strong>entrenar modelos de Inteligencia Artificial (IA) de forma simplificada.<\/strong><\/p>\n<p><strong>Fine-tuning<\/strong> consiste en el proceso de entrenar un <strong>modelo de IA<\/strong> ya preentrenado con un conjunto de <strong>datos m\u00e1s peque\u00f1o y espec\u00edfico para convertirlo en un especialista en una tarea o dominio particular.<\/strong><\/p>\n<p>La plataforma funciona en <strong>GPUs de consumo, port\u00e1tiles e incluso smartphones<\/strong>, eliminando la necesidad de servidores especializados o infraestructura en la nube.<\/p>\n<p>De acuerdo con el <a href=\"https:\/\/tether.io\/news\/tether-data-introduces-qvac-fabric-llm-the-edge-first-llm-inference-runtime-and-generalized-llm-lora-fine-tuning-framework-for-modern-ai-models-on-heterogeneous-gpus-smartphones-laptops-and-server\/\">comunicado<\/a>, publicado este martes (2), con el <strong>QVAC Fabric LLM<\/strong>, la empresa introduce un modelo unificado capaz de ejecutar y personalizar LLMs en una amplia variedad de sistemas operativos. <strong>El framework opera en Windows, macOS, Linux, iOS y Android.<\/strong> Es decir, ahora es posible entrenar y adaptar modelos localmente, sin enviar datos a proveedores externos.<\/p>\n<ul>\n<li>Lee tambi\u00e9n: <a href=\"https:\/\/www.criptofacil.com\/es\/bitcoin-hoy-02-12-2025-la-fed-inyecta-liquidez-en-el-mercado-y-el-btc-sube-a-usd-87-000\/\">Bitcoin Hoy 02\/12\/2025: la Fed inyecta liquidez en el mercado y el BTC sube a USD 87.000<\/a><\/li>\n<\/ul>\n<h2>Tether lanza soluci\u00f3n con foco en modelos de IA<\/h2>\n<p>Uno de los principales destaques es el<strong> soporte para entrenamiento en GPUs m\u00f3viles<\/strong>, incluyendo chips Qualcomm Adreno y ARM Mali. Seg\u00fan afirm\u00f3 Tether, es <strong>la primera vez que un framework de producci\u00f3n ofrece capacidades completas de ajuste de modelos en hardware<\/strong> t\u00edpico de tel\u00e9fonos inteligentes.<\/p>\n<p>La funcionalidad abre camino para <strong>aplicaciones de IA<\/strong> que aprenden con informaci\u00f3n almacenada en el propio dispositivo y <strong>funcionan incluso sin una conexi\u00f3n estable a internet.<\/strong><\/p>\n<p>La plataforma tambi\u00e9n<strong> ampl\u00eda el alcance del ecosistema de llama.cpp<\/strong> al incorporar rutinas de fine-tuning para modelos recientes como Llama3, Qwen3 y Gemma3. Estos modelos pasan a ser ajustables en un <strong>flujo estandarizado<\/strong>, independientemente del hardware utilizado.<\/p>\n<p>El sistema abarca equipos AMD, Intel, NVIDIA, Apple Silicon y procesadores m\u00f3viles. En la pr\u00e1ctica, esto <strong>descentraliza la infraestructura antes concentrada en GPUs de alto rendimiento.<\/strong><\/p>\n<h2>\u201cInteligencia Infinita. Antifr\u00e1gil. Ubicua\u201d<\/h2>\n<p>El movimiento <strong>tiene implicaciones directas para empresas que manejan datos sensibles<\/strong>. Con la posibilidad de ajuste local, los departamentos internos pueden <strong>adaptar modelos en la propia infraestructura corporativa<\/strong>, cumpliendo requisitos de seguridad y conformidad sin depender de plataformas externalizadas. El proceso <strong>reduce costos operativos y distribuye la carga de procesamiento<\/strong> entre los dispositivos ya existentes en la compa\u00f1\u00eda.<\/p>\n<p>El<strong> CEO de Tether<\/strong>, Paolo Ardoino, destac\u00f3 que la iniciativa busca <strong>ampliar el acceso a las herramientas de IA y reducir la dependencia de proveedores centralizados<\/strong>. Seg\u00fan \u00e9l, el QVAC Fabric LLM coloca a usuarios y organizaciones en control del procesamiento, la personalizaci\u00f3n y los datos involucrados en el entrenamiento.<\/p>\n<blockquote><p>\u201cInteligencia Infinita. Antifr\u00e1gil. Ubicua. La base para un futuro de IA descentralizado e imparable\u201d, tuite\u00f3 Ardoino.<\/p><\/blockquote>\n<p><img decoding=\"async\" class=\"size-full wp-image-338439 aligncenter\" src=\"https:\/\/www.criptofacil.com\/wp-content\/uploads\/2025\/12\/Ardoino.png\" alt=\"Fonte: Paolo Ardoino\/X\" width=\"439\" height=\"292\" \/><\/p>\n<p>El <strong>software fue puesto a disposici\u00f3n de forma abierta bajo la licencia Apache 2.0<\/strong>, acompa\u00f1ado de binarios multiplataforma y adaptadores en Hugging Face. La empresa informa que el proceso inicial de fine-tuning se realiza con pocos comandos. Esto <strong>reduce barreras<\/strong> para la creaci\u00f3n de aplicaciones personalizadas.<\/p>\n<ul>\n<li>Lee tambi\u00e9n: <a style=\"font-size: 16px\" href=\"https:\/\/www.criptofacil.com\/es\/tras-4-semanas-de-salidas-los-etf-de-criptomonedas-atraen-usd-1-000-millones\/\">Tras 4 semanas de salidas, los ETF de criptomonedas atraen USD 1.000 millones<\/a><\/li>\n<\/ul>\n","protected":false},"excerpt":{"rendered":"<p>Tether Data present\u00f3 hoy el QVAC Fabric LLM, un nuevo entorno de ejecuci\u00f3n y ajuste de modelos de lenguaje que permite realizar inferencia y fine-tuning directamente en dispositivos del d\u00eda a d\u00eda. En otras palabras, la soluci\u00f3n permite entrenar modelos de Inteligencia Artificial (IA) de forma simplificada. Fine-tuning consiste en el proceso de entrenar un [&hellip;]<\/p>\n","protected":false},"author":87,"featured_media":25630,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"_acf_changed":false,"inline_featured_image":false,"site-sidebar-layout":"default","site-content-layout":"","ast-site-content-layout":"default","site-content-style":"default","site-sidebar-style":"default","ast-global-header-display":"","ast-banner-title-visibility":"","ast-main-header-display":"","ast-hfb-above-header-display":"","ast-hfb-below-header-display":"","ast-hfb-mobile-header-display":"","site-post-title":"","ast-breadcrumbs-content":"","ast-featured-img":"","footer-sml-layout":"","theme-transparent-header-meta":"default","adv-header-id-meta":"","stick-header-meta":"","header-above-stick-meta":"","header-main-stick-meta":"","header-below-stick-meta":"","astra-migrate-meta-layouts":"set","ast-page-background-enabled":"default","ast-page-background-meta":{"desktop":{"background-color":"var(--ast-global-color-4)","background-image":"","background-repeat":"repeat","background-position":"center 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