AIF 2026: Twingo meets DigiPHY -- Renault & Granstudio Collaborative Story In this presentation from AIF26, teams from Renault Design and Grand Studio show how automation, virtual reality, and mixed reality are transforming the way vehicles are reviewed, experienced, and developed. Using the Renault Twingo project as a real-world example, they demonstrate how physical and digital design can come together in a scalable workflow that helps teams evaluate decisions earlier and iterate faster. Key topics include: • How Renault evolved VR from a manual, specialist-driven process into a scalable daily design workflow • How automated data preparation embeds visualization expertise directly into the pipeline • Bringing physical and digital vehicle experiences together for immersive design reviews • Using the Twingo project to evaluate HMI, ergonomics, proportions, and interior elements in context • Dynamic benchmarking and fast digital prototyping to support earlier design decisions • Creating more open, software-agnostic workflows through APIs and system integration • How immersive XR supports CMF, interaction design, multidisciplinary collaboration, and user testing “The most expensive mistake is the one that you find out too late in the process.” #AIF26 #Au...

AI models can now help run physical science experiments The Model Hardware Standard (MHS) is a new standard for AI agents to safely operate physical equipment in scientific research and advanced manufacturing. MHS began as a collaboration between Anthropic’s Beneficial Deployments team and HHMI Janelia Research Campus. This video tells the story of how MHS was developed and shows how it can be used to accelerate scientific research. MHS is now in research preview with select partners. Read more about how we're learning what AI can do in the physical world: https://www.anthropic.com/news/model-hardware-standard-research-preview

We're building a way for AI models to connect to any device and run real experiments. Scientists spend a significant amount of their time just getting their devices to communicate with one another. Each device tends to have its own programming interface, and so far there has been no standardized way to integrate them, or to allow them to connect to AI. The Model Hardware Standard (MHS) gives AI models one common way to connect to lab and manufacturing equipment and operate it safely, with limits built into each device. MHS started as a collaboration between Anthropic and HHMI Janelia Research Campus, and is beginning as a research preview with partners across science, robotics and manufacturing.

Model Hardware Standard: AI operating physical equipment The Model Hardware Standard (MHS) is a new standard for AI agents to safely operate physical equipment in scientific research and advanced manufacturing. MHS started as part of a beneficial deployments project between Anthropic and HHMI Janelia Research Campus and is evolving into a wider industry effort. This video shows what MHS is, how it works, and early examples of AI agents operating lab and manufacturing equipment. MHS is now in research preview with select partners. Read more about how we're learning what AI can do in the physical world: https://www.anthropic.com/news/model-hardware-standard-research-preview

Getting Started with the Unreal Engine HMI Template and Data Reduction Pipeline Building automotive HMI in Unreal Engine from scratch means solving the same infrastructure problems every time: ingesting vehicle signals, binding them to UI widgets, rendering maps, configuring mobile render settings, and targeting embedded platforms. UE 5.8 changes that. The new HMI Template provides a ready-to-use foundation for exploring, prototyping, and accelerating HMI development. In this webinar recording, we cover: - Instrument cluster: A fully wired digital cluster that receives live vehicle signals over a standard protocol and renders them in real time. - Maps: A high-performance offline map experience with no cloud dependency and no licensing cost per render that runs on embedded hardware. - Widget library: Every widget used in the instrument cluster, available independently. No C++ required. - Data Reduction Pipeline: Take a heavy UE model from marketing-grade to HMI-ready, optimized for embedded hardware. Ready to get started? The Unreal Engine HMI Template and Data Reduction Pipeline plugins are available by request. Contact us through this form and our team will follow up: https://airtable.com/appVg7uYNxTQihgxH/pageuCnqwni4RoPFH/form #HMI, #AutomotiveHMI, ...

Top 100 Animated Trading Cards Montage | Gauntlet of Gods (ft. @RogetMusic ) Pre-order the Physical Card Game before 9.26: https://creocards.com/collections/gauntlet-of-gods Play the Digital Online Game for Free: https://play.gauntletofgods.com/ Follow your Favorite Artists: https://docs.google.com/spreadsheets/d/1Kdw4qJxNkxttwlSCqgWQSbrcknEfFx308OT2uD4Gw0M/edit?usp=sharing Music by: @RogetMusic Spotify: https://open.spotify.com/artist/4b6Khs68thyzQrWRISZFrT?si=56tlmm_FRUSfeoTohB-IDw Matheus Souza - Violin, Viola Peter Bobinski, Eric Notar - Guitar C.J. Jenkins - Vocals *SPONSORS:* Marvelous Designer: https://www.marvelousdesigner.com/gauntletofgods Rokoko: https://glnk.io/pwnisher KitBash3D: https://kitbash3d.com/pwnisher The Gnomon School: https://bit.ly/GnomonxGOTG2026-Connect-YT Kaft: https://www.kaft.com/tisort?utm_source=affiliate&utm_medium=cpc&acid=139&utm_campaign=pwnisher XPPen: https://bit.ly/xppenxpwnisher JangaFX: http://jangafx.com/events/gauntlet-of-gods Action VFX: https://bit.ly/clint-gaussian-splats Fox Renderfarm: https://bit.ly/4fAg48y Game Design by: AJ Brandon YouTube: https://www.youtube.com/playlist?list=PLlpOSsHmIZE9Q1V5UuzhrM3ZncMJVsnol Spotify: https://open.spotify.com/show/3ajvJw7gKYB8uo1kcJc4Iw *SPONSOR DISCOUNTS:* Rokoko ...

التصميم باستخدام البيانات | 3 - استخدام البيانات | Data Driven Design | 03 - Data Integration في الجلسة الثالثة من سلسلة “التصميم المعماري المدفوع بالبيانات” نستكشف منهجيات وأدوات متقدمة لتحويل البيانات إلى أشكال تصميمية: التصميم الحسابي (Computational Design): مبادئ البناء الخوارزمي للنماذج المعمارية. التصميم الخوارزمي (Algorithmic Design): كتابة خطوات منطقية لإنشاء الأشكال وتحكم إجرائي في عناصر المشروع. التصميم البرامتري (Parametric Design): ربط المتغيرات الهندسية بمعايير قابلة للتعديل الفوري. Grasshopper: استخدام البيانات الحية لقيادة الأشكال والأنماط داخل بيئة Rhino. Ladybug: تحليل بيئي متقدم (ظل، إضاءة، حرارة) داخل Grasshopper. تكامل الإحصاءات مع Python & Grasshopper: استيراد قواعد بيانات (CSV, API) وتغذية النماذج البرامترية بقيم حقيقية. محاكاة Slime Mold في Houdini: نمذجة توزيع الشبكات العضوية وتحسين المسارات باستخدام أدوات VEX وPDG. التوأم الرقمي (Digital Twin): جمع البيانات الحسية الحية من المستشعرات وربطها بالبيئة الافتراضية لمتابعة الأداء. أدوات الذكاء الاصطناعي (AI Tools): استخدام نماذج التعلم الآلي في تحليل الأنماط وتوليد الاقتراحات التصميمية. TestFit: منصة أتمتة تخطيط الوحدات السكنية والتجارية بناءً على معايير السوق والمساحات المتاحة. المصادر والمراجع متوفرة بشكل تفصيلي على حسابنا في GitHub: https://github.com/lAvArt/Data-Driven-Design #التصميم_المد...