/* === MOBILE OPTIMIZATION === */ /* ============================================ MOBILE OPTIMIZATION v1 Optimized for Android & iOS ============================================ */ /* === CORE VIEWPORT === */ html { font-size: 16px; -webkit-text-size-adjust: 100%; text-size-adjust: 100%; overflow-x: hidden; } body { overflow-x: hidden; -webkit-font-smoothing: antialiased; -moz-osx-font-smoothing: grayscale; } /* === PREVENT HORIZONTAL SCROLL === */ *, *::before, *::after { box-sizing: border-box; max-width: 100vw; } .gh-viewport { overflow-x: hidden; } /* === TOUCH TARGETS (WCAG 2.5.5) === */ a, button, input, select, textarea, label { min-height: 44px; min-width: 44px; } .gh-navigation-menu a, .gh-navigation-actions a, .gh-icon-button, button { padding: 10px 12px; min-height: 44px; min-width: 44px; display: flex; align-items: center; justify-content: center; } /* === NAVIGATION MOBILE === */ .gh-navigation-inner { padding: 0 1rem; flex-wrap: nowrap; gap: 0.5rem; } .gh-navigation-brand { flex-shrink: 0; min-width: unset; } .gh-navigation-logo { font-size: 1.25rem; } .gh-burger { display: flex !important; width: 44px; height: 44px; flex-shrink: 0; } .gh-burger svg { width: 24px; height: 24px; } /* === TYPOGRAPHY SCALE (MOBILE) === */ h1 { font-size: clamp(1.75rem, 6vw, 3rem) !important; } h2 { font-size: clamp(1.4rem, 5vw, 2.25rem) !important; } h3 { font-size: clamp(1.2rem, 4vw, 1.5rem) !important; } .article-title, .gh-article-title { font-size: clamp(1.5rem, 7vw, 2.5rem) !important; letter-spacing: -0.02em; } .gh-container-title h1 { font-size: clamp(1.75rem, 8vw, 3rem) !important; } /* === FEED / CARDS MOBILE === */ .gh-feed { grid-template-columns: 1fr !important; gap: 1.25rem !important; padding: 1rem 0 !important; } .gh-card { border-radius: 12px; flex-direction: column; } .gh-card-wrapper { padding: 1.25rem !important; } .gh-card-title { font-size: 1.125rem !important; line-height: 1.35; } .gh-card-excerpt { font-size: 0.875rem !important; -webkit-line-clamp: 2 !important; } .gh-card-meta { flex-wrap: wrap; gap: 0.5rem; } /* === SINGLE POST MOBILE === */ .gh-article-header { padding: 2.5rem 0 1.5rem !important; } .article { padding: 1.5rem 1rem 3rem !important; } .gh-article-excerpt { font-size: 1rem !important; } .gh-article-meta { flex-wrap: wrap; gap: 0.75rem; font-size: 0.8125rem; } .gh-content p { font-size: 1rem !important; line-height: 1.75 !important; } .gh-content h2 { font-size: 1.375rem !important; margin: 2rem 0 0.75rem !important; } .gh-content h3 { font-size: 1.125rem !important; margin: 1.5rem 0 0.5rem !important; } .gh-content blockquote { padding-left: 1rem !important; font-size: 1.0625rem !important; } .gh-content pre { padding: 1rem !important; font-size: 0.8125rem !important; border-radius: 8px !important; margin: 1.5rem -0.5rem !important; overflow-x: auto !important; -webkit-overflow-scrolling: touch; } .gh-content code { font-size: 0.8125rem !important; } .gh-content ul, .gh-content ol { padding-left: 1.25rem !important; } .gh-content li { font-size: 1rem !important; line-height: 1.65 !important; margin-bottom: 0.5rem !important; } /* === CONTAINERS === */ .gh-container { padding: 0 1rem !important; } .gh-outer { padding: 1.5rem 0 !important; } /* === FOOTER MOBILE === */ .gh-footer-inner { grid-template-columns: 1fr !important; gap: 1.5rem !important; padding: 0 1rem !important; } .gh-footer-menu { flex-wrap: wrap !important; gap: 1rem !important; } .gh-footer-bar { flex-direction: column !important; gap: 0.75rem !important; text-align: center !important; } /* === NEWSLETTER MOBILE === */ .newsletter-cta { padding: 1.5rem 1rem !important; border-radius: 12px !important; margin: 1.5rem 0 !important; } .newsletter-cta h3 { font-size: 1.375rem !important; } .newsletter-form { flex-direction: column !important; gap: 0.75rem !important; } .newsletter-form input, .newsletter-form button { width: 100% !important; font-size: 1rem !important; } /* === DARK MODE TOGGLE MOBILE === */ .dark-mode-toggle { bottom: 1.5rem !important; right: 1.5rem !important; width: 44px !important; height: 44px !important; } /* === IMAGES MOBILE === */ .gh-content img, .article img { max-width: 100vw !important; height: auto !important; border-radius: 8px !important; margin: 1.5rem -1rem !important; } /* === PREVENT OVERSCROLL === */ html, body { overscroll-behavior: none; } /* === CONTAINER TITLE MOBILE === */ .gh-container-title { padding: 2rem 0 1.5rem !important; } .gh-container-title h1 { font-size: 1.75rem !important; line-height: 1.2 !important; } /* === LISTS MOBILE === */ .gh-article .gh-canvas + .gh-content ul, .gh-article .gh-canvas + .gh-content ol, article.gh-article .gh-content ul, article.gh-article .gh-content ol { padding-left: 1.25rem !important; margin: 1rem 0 !important; } .gh-article .gh-canvas + .gh-content li, article.gh-article .gh-content li { font-size: 1rem !important; line-height: 1.65 !important; margin-bottom: 0.5rem !important; } .gh-article .gh-canvas + .gh-content > li, article.gh-article .gh-content > li { font-size: 1rem !important; padding-left: 1.25rem !important; } /* === ARTICLE TITLE (SINGLE) === */ .gh-article-title.is-title { font-size: clamp(1.5rem, 6vw, 2.25rem) !important; } /* Tablet */ @media (min-width: 600px) and (max-width: 900px) { .gh-feed { grid-template-columns: repeat(2, 1fr) !important; } } /* Small screens */ @media (max-width: 380px) { h1 { font-size: 1.5rem !important; } .gh-card-title { font-size: 1rem !important; } .gh-card-excerpt { font-size: 0.8125rem !important; } .gh-content p { font-size: 0.9375rem !important; } .newsletter-cta h3 { font-size: 1.25rem !important; } .dark-mode-toggle { width: 40px !important; height: 40px !important; } } /* === REDUCED MOTION === */ @media (prefers-reduced-motion: reduce) { *, *::before, *::after { animation: none !important; transition: none !important; } }
IA

Governanza de la IA Física: cuando los modelos de lenguaje empiezan a mover brazos robóticos

Gemini Robotics-ER, robots basados en LLMs y marcos como NIST AI RMF: qué está pasando con la gobernanza de sistemas de IA que interactúan con el mundo físico y por qué importa para la seguridad.

Fernando Luis

— 1 min read

La inteligencia artificial que interactúa con el mundo físico — robots, sensores, maquinaria industrial — plantea un desafío de gobernanza que no tiene equivalente en el software tradicional. No basta con que un modelo entienda instrucciones: hay que definir quién responde cuando esas instrucciones se convierten en movimiento.

El mercado lo está tomando en serio. Según Grand View Research, la IA física movió 81.640 millones de dólares en 2025 y se proyecta que alcanzará los 960.380 millones en 2033. La International Federation of Robotics instaló 542.000 robots industriales solo en 2024, el doble que hace una década. Estamos ante una escala que ya no permite ignorar las preguntas de control.

Cómo funciona un robot con un LLM por cerebro

Google DeepMind lanzó Gemini Robotics en marzo de 2025 y lo actualizó a Gemini Robotics-ER 1.6 en abril de 2026. La idea central es sencilla: usar un modelo de lenguaje multimodal como cerebro de un robot.

Un robot clásico sigue reglas programadas: "si el sensor indica X, ejecutar acción Y". Un robot basado en un LLM recibe una instrucción en lenguaje natural ("doblega esta hoja de papel por la mitad") y tiene que:

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