# Simulation Published articles for Simulation. This is one page of public article previews, not the complete archive. Follow Next page to continue. Summaries are not the original full articles. ## How to Use AI Agents to Prepare 3D Scenes for Simulation DevFeed: [How to Use AI Agents to Prepare 3D Scenes for Simulation]() Original publisher: [Read original article]() Author: Tanya Lenz Published: 2026-09-16T23:20:33Z Content type: tutorial Language: en Sources: [NVIDIA Developer](), [NVIDIA Technical Blog]() Topics: [Artificial Intelligence](), [Simulation](), [Physical AI](), [Simulation and Design](), [blender](), [Isaac Sim](), [Omniverse](), [Robotics Simulation](), [Robotics]() Tags: [3d](), [agentic](), [agentic-ai-generative-ai](), [agents](), [ai](), [blender](), [gpt-6-astra](), [how-to](), [isaac-sim](), [nemoclaw](), [nvidia](), [omniverse](), [openai](), [openusd](), [physical-ai](), [robotics](), [robotics-simulation](), [simulation](), [simulation-modeling-design]() ### AI overview This tutorial describes an agentic workflow for preparing Blender 3D scenes for robotics simulation. It covers scene inspection, OpenUSD metadata, physics properties, rendering preflight views, and validation for simulation-ready handoff to NVIDIA Isaac Sim or Isaac Lab. ### Source excerpt Agentic AI workflows can be used to prepare and validate digital twins for physical AI systems. Agents can inspect 3D scenes, author simulation-relevant data in... ## What to Expect at the Zephyr Project Workshop & Meetup (September 24, 2026) - Stuttgart, Germany DevFeed: [What to Expect at the Zephyr Project Workshop & Meetup (September 24, 2026) - Stuttgart, Germany]() Original publisher: [Read original article]() Author: Susan Remmert Published: 2026-09-16T17:57:36Z Content type: news Language: en Sources: [Zephyr Project]() Topics: [Embedded Systems](), [Embedded Software Dev](), [Application Development](), [Testing](), [Simulation](), [Open Source]() Tags: [2026](), [blog](), [command-line](), [community](), [contributors](), [development](), [embedded](), [embedded-systems](), [event](), [events](), [germany](), [meetup](), [open-source](), [sessions](), [simulation](), [technical](), [testing](), [workshop](), [zephyr]() ### AI overview The Zephyr community will hold a hands-on workshop and afternoon meetup in Stuttgart, Germany, on September 24, 2026. The program includes guided exercises, technical presentations, community networking, and discussions of Zephyr-based embedded applications. ### Source excerpt On September 24, the Zephyr community will gather in Stuttgart for a hands-on workshop followed by an afternoon meetup featuring community-led technical presentations. The event is open to experienced contributors, first-time users, students, engineers, and anyone interested in open source embedded development. Attendees may join both sessions or choose either the workshop or the meetup based on their interests. ## Children's Hospital of Philadelphia Uses Open Source AI and MONAI to Model Pediatric Hearts DevFeed: [Children's Hospital of Philadelphia Uses Open Source AI and MONAI to Model Pediatric Hearts]() Original publisher: [Read original article]() Author: Isha Salian Published: 2026-09-15T09:00:42Z Content type: news Language: en Sources: [NVIDIA Blog]() Topics: [MONAI](), [Medical imaging](), [Artificial Intelligence](), [Open Source](), [Machine learning]() Tags: [ai](), [ai-for-good](), [healthcare-and-life-sciences](), [machine-learning](), [medical-imaging](), [monai](), [open-source](), [openusd](), [robotics](), [simulation](), [software]() ### AI overview Children's Hospital of Philadelphia uses open source AI tools built on MONAI to generate anatomically precise pediatric heart models from medical images in seconds. Its teams are applying machine learning to support care for children with congenital heart disease. ### Source excerpt Children's Hospital of Philadelphia is using open source AI tools to model children's hearts in seconds -- with the goal of enabling safer, more precise care for kids with congenital heart disease. ## Resolve Amazon Aurora PostgreSQL lock contention with Database Insights: Part 2 DevFeed: [Resolve Amazon Aurora PostgreSQL lock contention with Database Insights: Part 2]() Original publisher: [Read original article]() Author: Sameer Kumar Published: 2026-09-14T16:02:16Z Content type: tutorial Language: en Sources: [AWS Database Blog]() Topics: [Amazon Aurora](), [Amazon CloudWatch](), [PostgreSQL](), [Concurrency](), [Monitoring](), [Database](), [Amazon EC2](), [Architecture & Design](), [Amazon Web Services](), [AWS CloudFormation]() Tags: [advanced-300](), [amazon-aurora](), [amazon-cloudwatch](), [amazon-ec2](), [aws](), [aws-cloudformation](), [concurrency](), [monitoring](), [performance](), [postgresql](), [rds-for-postgresql](), [simulation](), [technical-how-to]() ### AI overview This tutorial explains how to diagnose and resolve lock contention in Amazon Aurora PostgreSQL using Amazon CloudWatch Database Insights. It demonstrates Lock Analysis and the Lock Tree visualization for identifying blocking sessions, then covers immediate fixes, configuration changes, optimistic concurrency control, asynchronous processing, SKIP LOCKED, and row splitting. ### Source excerpt Part 1 showed how row lock contention degrades Amazon Aurora PostgreSQL throughput. In Part 2, use Amazon CloudWatch Database Insights and its Lock Tree to pinpoint blocking sessions, then resolve contention with query termination, timeout parameters, and architectural patterns such as SKIP LOCKED and row splitting that restore throughput. ## IBM Quantum System Two Heads to Switzerland: 120-Qubit Nighthawk r2 at CSCS by End of 2026 DevFeed: [IBM Quantum System Two Heads to Switzerland: 120-Qubit Nighthawk r2 at CSCS by End of 2026]() Original publisher: [Read original article]() Author: Harold Fritts Published: 2026-09-11T16:25:47Z Content type: news Language: en Sources: [StorageReview.com]() Topics: [ibm](), [Quantum Computing](), [Supercomputing](), [Cloud](), [Algorithms](), [Optimization](), [Simulation and Design](), [Hardware]() Tags: [2026](), [ai](), [algorithms](), [amd](), [chemistry](), [cloud](), [collaboration](), [core](), [enterprise](), [financial-services](), [hardware](), [hub](), [ibm](), [infrastructure](), [manufacturing](), [optimization](), [processors](), [quantum](), [quantum-computing](), [science](), [simulation](), [supercomputing]() ### AI overview IBM and Lockheed Martin are establishing a quantum innovation hub at ETH Zurich, centered on an IBM Quantum System Two planned for installation at the Swiss National Supercomputing Centre by the end of 2026. The system will use IBM's 120-qubit Nighthawk r2 processor and support research in areas including chemistry, materials science, optimization, and financial services. ### Source excerpt IBM and Lockheed Martin are setting up a quantum innovation hub at ETH Zurich, and its core is Switzerland's first IBM Quantum System Two, to be installed at the Swiss National Supercomputing Centre (CSCS) in Lugano by the end of 2026. The hub comes out of an offset agreement with armasuisse, Switzerland's Federal Office for The post IBM Quantum System Two Heads to Switzerland: 120-Qubit Nighthawk r2 at CSCS by End of 2026 appeared first on StorageReview.com. ## System helps humans predict when self-driving cars will make mistakes DevFeed: [System helps humans predict when self-driving cars will make mistakes]() Original publisher: [Read original article]() Author: Adam Zewe | MIT News Published: 2026-09-02T15:00:00Z Content type: news Language: en Sources: [MIT AI News]() Topics: [autonomous vehicles](), [Deep learning](), [Artificial Intelligence](), [Robotics](), [Simulation](), [Computer science]() Tags: [aeronautical-and-astronautical-engineering](), [ai](), [artificial-intelligence](), [autonomous-vehicles](), [computer-science-and-artificial-intelligence-laboratory-csail](), [computer-science-and-technology](), [concept-wrapper-network](), [cw-net](), [deep](), [electrical-engineering-and-computer-science-eecs](), [eoin-kenny](), [human-computer-interaction](), [julie-shah](), [laura-major](), [machine-learning](), [mit-schwarzman-college-of-computing](), [momchil-tomov](), [motional](), [research](), [robotics](), [safety](), [school-of-engineering](), [self-driving](), [self-driving-cars](), [simulation](), [transparency]() ### AI overview MIT and Motional researchers developed CW-Net, a method that translates an autonomous vehicle's deep-learning decisions into understandable concepts. Tests found that the explanations helped safety drivers and nonexpert users better predict vehicle behavior. ### Source excerpt A new method, called CW-Net, translates the reasoning process of an autonomous vehicle's AI system into understandable concepts that explain its behavior. ## Isle of Food Combines Island Exploration and Cooking in a Virtual Reality Restaurant Simulation DevFeed: [Isle of Food Combines Island Exploration and Cooking in a Virtual Reality Restaurant Simulation]() Original publisher: [Read original article]() Author: Luis Aviles Published: 2026-08-26T22:57:20Z Content type: opinion Language: en Sources: [UploadVR]() Topics: [Simulation](), [Virtual reality]() Tags: [3d-printer](), [customers](), [games](), [simulation](), [vr-gaming]() ### AI overview The article reviews Isle of Food, a virtual reality cooking and ingredient-collecting simulation on a tropical island. It describes gathering resources, preparing recipes, serving customers, customizing the restaurant, and progressing through experience points and new recipes. ### Source excerpt Isle of Food takes a novel approach to a cooking simulation game by having you explore an island for food to prepare for your guests. ## Qiskit Fermions: a modular toolbox for fermionic systems DevFeed: [Qiskit Fermions: a modular toolbox for fermionic systems]() Original publisher: [Read original article]() Published: 2026-08-24T14:30:00Z Content type: release Language: en Sources: [IBM Research]() Topics: [Quantum Computing](), [Software](), [Simulation](), [Open Source]() Tags: [open-source](), [quantum](), [quantum-computing](), [quantum-enablement](), [quantum-research](), [quantum-software](), [release](), [simulation](), [software]() ### AI overview IBM introduces Qiskit Fermions, an open-source modular toolbox for expressing fermionic operators and circuits, defining fermion-to-qubit mappings, and compiling fermionic workflows into quantum circuits. The package preserves fermionic structure until transpilation and supports quantum simulation workflows in areas including quantum chemistry, condensed-matter physics, and materials science. ### Source excerpt A new research tool for expressing fermionic operators, circuits, and mappings--and for building efficient fermionic algorithms. ## Coding Challenge #133 - Particle Playground DevFeed: [Coding Challenge #133 - Particle Playground]() Original publisher: [Read original article]() Author: John Crickett Published: 2026-08-22T08:01:30Z Content type: tutorial Language: en Sources: [Coding Challenges]() Topics: [Simulation](), [Cellular automaton](), [coding](), [creative coding](), [Graphics](), [Canvas]() Tags: [canvas](), [coding](), [creative-coding](), [graphics](), [programming](), [real-time](), [simulation]() ### AI overview A coding challenge guides readers through building a 2D particle playground with two simulation engines: a force-based particle system and a cellular automaton. The project combines materials such as sand, water, and fire with a fireworks display whose embers can ignite the material grid. ### Source excerpt This challenge is to build your own particle playground. ## GeoPT helps AI models simulate how objects respond to physical forces DevFeed: [GeoPT helps AI models simulate how objects respond to physical forces]() Original publisher: [Read original article]() Author: Alex Shipps | MIT CSAIL Published: 2026-08-10T19:25:00Z Content type: news Language: en Sources: [MIT AI News]() Topics: [AI Models](), [Simulation](), [AI Research](), [Computer Science and Artificial Intelligence Laboratory (CSAIL)](), [Robotics]() Tags: [3-d-imaging](), [ai](), [ai-models](), [artificial-intelligence](), [computational-fluid-dynamics-cfd](), [computer-graphics](), [computer-modeling](), [computer-science-and-artificial-intelligence-laboratory-csail](), [computer-science-and-technology](), [crash-simulation](), [design](), [electrical-engineering-and-computer-science-eecs](), [geometric-pre-training](), [geopt](), [haixu-wu](), [human-computer-interaction](), [kaiming-he](), [manufacturing](), [minghao-guo](), [mit-csail](), [mit-eecs](), [mit-schwarzman-college-of-computing](), [neural-physics-simulation](), [paper](), [physics](), [physics-aware-ai](), [physics-foundation-models](), [research](), [robotics](), [school-of-engineering](), [self-supervised-learning](), [simulation](), [surrogate-modeling](), [synthetic-dynamics](), [transformer-based-simulators](), [wojciech-matusik]() ### AI overview Researchers at MIT CSAIL and Tsinghua University developed GeoPT, a pre-training approach that uses 3D simulations of mechanical interactions to help AI models learn physics more efficiently. The article reports that models using the approach reached peak performance twice as fast and trained on up to 60 percent less data than leading models. ### Source excerpt "GeoPT" helps AI models understand the basics of physics so they can simulate how objects respond to things like wind and water more efficiently and accurately. ## Чем запомнилась ICRA 2026: Reinforcement Learning, генерация сложных сценариев поведения и будущее робототехники DevFeed: [Чем запомнилась ICRA 2026: Reinforcement Learning, генерация сложных сценариев поведения и будущее робототехники]() Original publisher: [Read original article]() Author: egavolk (Яндекс) Published: 2026-08-04T08:00:45Z Content type: article Language: ru Sources: [Яндекс - Как мы делаем Яндекс / Статьи]() Topics: [Reinforcement learning](), [Robotics](), [Simulation](), [Machine learning]() Tags: [2026](), [icra](), [ml](), [reinforcement-learning](), [rl](), [robotics](), [simulation](), [tag-511fbf58fd45](), [tag-6faff4be08e9](), [tag-d704a344cc75](), [tag-dace475544fb]() ### AI overview The article reviews notable trends, papers, and engineering trade-offs discussed at ICRA 2026, with emphasis on reinforcement learning, autonomous-vehicle perception and planning pipelines, simulation, rare edge-case generation, and robotic learning. It also discusses award-winning work on manipulation, humanoid robots, and camera-conditioned policy learning. ### Source excerpt Привет, Хабр! В начале июня в Вене прошла главная международная конференция по робототехнике и автономным системам -- International Conference on Robotics and Automation (ICRA). В этом году среди участников была и наша команда автономного транспорта Яндекса. Топиков, которые обсуждаются на ICRA, много, потому что она не только об ML -- она скорее о робототехнике в целом. Например, есть секции о механизмах и дизайне, а также о медицинских роботах. Было немало и чисто инженерных работ. Ключевой топик докладов на конференции -- RL, он же Reinforcement Learning, обучение с подкреплением. Также нас интересовали статьи по классическому пайплайну автономного автомобиля: perception + prediction + planner + simulation. Новые подходы к Robotic Learning тоже интересны, так как их можно перенести на задачи автономного транспорта. Меня зовут Егор Волков, я занимаюсь претрейном модели планирования движения в автономном транспорте Яндекса. Вместе со мной на конференцию ездил Максим Спорышев -- руководитель службы поведения и предсказания движения. В этой статье мы собрали самые интересные тренды, доклады и инженерные развилки, которые заметили на ICRA 2026, -- от Reinforcement Learning и генерации редких edge-кейсов до того, куда вообще двигается ML в робототехнике. Читать далее ## Velxio: An open-source browser-based simulator for ESP32 and other embedded boards DevFeed: [Velxio: An open-source browser-based simulator for ESP32 and other embedded boards]() Original publisher: [Read original article]() Author: John Lee Published: 2026-07-31T00:00:00Z Content type: article Language: en Sources: [Blog on Developer Portal]() Topics: [ESP32](), [Simulation](), [Open Source](), [Web app](), [browser](), [AI Agent]() Tags: [ai](), [arduino](), [article](), [blog](), [browser](), [education](), [esp32](), [open-source](), [projects](), [simulation](), [web-app]() ### AI overview The article introduces Velxio, an open-source browser-based simulator for embedded projects. It describes real firmware execution on emulated hardware, support for multiple boards and components, analog and digital co-simulation, development workflows, and self-hosting. ### Source excerpt This article introduces Velxio, an open-source, browser-based embedded simulator that runs real ESP32 firmware on emulated hardware. It explains how the simulator works under the hood, demonstrates LED, Wi-Fi, MQTT, and sensor based projects, and highlights support for multiple boards across the ESP32 family. ## SceneSmith uses collaborative AI agents to create 3D environments for robot training DevFeed: [SceneSmith uses collaborative AI agents to create 3D environments for robot training]() Original publisher: [Read original article]() Author: Alex Shipps | MIT CSAIL Published: 2026-07-13T18:50:00Z Content type: news Language: en Sources: [MIT AI News]() Topics: [AI research agents](), [robot grasping simulation](), [Simulation](), [vlm](), [Artificial Intelligence](), [Computer Science and Artificial Intelligence Laboratory (CSAIL)]() Tags: [3-d](), [3d](), [adversarial-machine-learning](), [agents](), [ai-agents](), [artificial-intelligence](), [computer-science-and-artificial-intelligence-laboratory-csail](), [computer-science-and-technology](), [electrical-engineering-and-computer-science-eecs](), [foundation-models](), [general-purpose-robotics](), [gpt-5-2](), [machine-learning](), [mit-csail](), [mit-eecs](), [mit-schwarzman-college-of-computing](), [national-science-foundation-nsf](), [nicholas-pfaff](), [research](), [robot-simulations](), [robotics](), [robots](), [russ-tedrake](), [scene-generation](), [scenesmith](), [school-of-engineering](), [simulation](), [simulation-ready-indoor-scenes](), [virtual-playgrounds](), [vision-language-models-vlms](), [zero-shot-policy]() ### AI overview MIT CSAIL and Toyota Research Institute researchers developed SceneSmith, a system that uses three collaborative AI agents to create realistic 3D environments for robot training. The scenes can be loaded into physics simulation software, allowing robots to practice tasks before real-world testing. ### Source excerpt "SceneSmith" system uses collaborative AI agents to create realistic 3D environments of places like kitchens, hotels, and living rooms, where robots can simulate everyday chores. ## AR And VR In Java: ARKit, ARCore, And A Virtual Room You Can Debug DevFeed: [AR And VR In Java: ARKit, ARCore, And A Virtual Room You Can Debug]() Original publisher: [Read original article]() Author: Shai Almog Published: 2026-07-12T00:00:00Z Content type: release Language: en Sources: [CodeName One]() Topics: [Java](), [Emulator](), [Simulation](), [Android](), [GPU](), [iOS]() Tags: [android](), [debug](), [emulator](), [event-driven](), [gltf](), [gpu](), [ios](), [java](), [release](), [simulation](), [simulator]() ### AI overview A Codename One release adds portable AR support over ARKit and ARCore, stereo rendering and 360 media support, and a simulated AR backend. Developers can test tracking, planes, anchors, hit testing, and related event-driven code in a virtual room within the simulator. ### Source excerpt World tracking, plane detection, anchors, stereo rendering and 360 panoramas, with a simulated AR room so the whole loop is debuggable in the simulator. ## Outlier Handling at Scale in Experimentation DevFeed: [Outlier Handling at Scale in Experimentation]() Original publisher: [Read original article]() Author: Margarida Moreira da Silva Published: 2026-07-01T13:44:26Z Content type: article Language: en Sources: [Booking.com Data Science]() Topics: [experiments](), [data](), [Simulation](), [Ground truth / benchmark quality](), [plotting]() Tags: [data](), [experimentation](), [experiments](), [false-positive](), [outlier-detection](), [simulation](), [variance]() ### AI overview The article examines how extreme values affect experimentation at Booking.com. It describes permutation tests and simulated A/A experiments for diagnosing distorted p-value distributions, and reports that increasing outlier magnitude and frequency can cause test failures. ### Source excerpt At Booking.com, thousands of experiments run simultaneously across highly heterogeneous users, from individual travellers to large travel agencies. This means our experiment data regularly contains legitimate but extreme values. When these go unhandled, they distort the statistical conclusions we draw, leading us to scale ideas that don't create value, or to discard ones that do. So, we need outlier handling methods that are reliable, automated, and applicable across diverse metrics without manual intervention. The Problem When extreme values are present in experiment data, they can compromise the estimation of average treatment effects (ATE), leading to unreliable test results and reduced statistical power. Even a single observation can inflate variance enough to mask a real effect or produce a spurious one. In practice, this means we risk shipping changes that appear positive but are not, or killing promising features because noise masked their real effect. At Booking.com's scale, this increase in false conclusions quickly compounds into a meaningful impact on customer experience and business outcomes. A Diagnostic Tool: the Permutation Test One way to assess whether extreme values are distorting results is the permutation test. By permuting over experiment data, we generate hundreds of simulated AA experiments where we know the ground truth: there is no real effect. Plotting the resulting p-values, we expect a uniform distribution. If it instead looks skewed, the underlying data distribution is compromising the validity of results. Plot 1: P-value distributions from simulated A/A tests. Clean normally-distributed estimated effects produce a uniform distribution (left), while the presence of extreme outliers results in skewed p-values (right), indicating a distorted false positive rate.Simulation Evidence: What Drives Failure? We ran AA permutation tests across a range of simulated data distributions to understand when they fail (i.e. not show a uniform p-value di ## A better way to model the behavior of metal alloys DevFeed: [A better way to model the behavior of metal alloys]() Original publisher: [Read original article]() Author: Zach Winn | MIT News Published: 2026-06-19T18:00:00Z Content type: news Language: en Sources: [MIT AI News]() Topics: [Simulation](), [Machine learning](), [datasets]() Tags: [artificial-intelligence](), [chemical-engineering](), [chemistry](), [computer-modeling](), [computer-science-and-technology](), [daniel-xiao](), [datasets](), [dmse](), [killian-sheriff](), [lewis-r-owen](), [machine-learning](), [materials-science-and-engineering](), [mit-materials-science-and-engineering](), [models](), [phase-diagrams](), [predicting-new-materials](), [predictions](), [research](), [rodrigo-freitas](), [school-of-engineering](), [simulation](), [yifan-cao]() ### AI overview MIT researchers developed a machine-learning approach that uses diverse training datasets to model chemically complex metal alloys and predict their material properties more accurately across different conditions. ### Source excerpt MIT researchers' approach captures subtle atomic patterns, improving predictions of material properties. ## Gamification 2.0. Beyond Points and Badges: Designing for Players, Not Metrics. Chapter 5: Implementation DevFeed: [Gamification 2.0. Beyond Points and Badges: Designing for Players, Not Metrics. Chapter 5: Implementation]() Original publisher: [Read original article]() Author: Montgomery Singman Published: 2026-06-09T03:26:13Z Content type: tutorial Language: en Sources: [UX Magazine]() Topics: [implementation](), [User experience (UX)](), [App]() Tags: [app](), [building](), [complex-systems](), [core](), [creative](), [design](), [expression](), [games](), [implementation](), [interface](), [leaderboard](), [loops](), [management](), [multiplayer](), [puzzle](), [rpg](), [sandbox](), [simulation](), [strategy](), [ux]() ### AI overview This chapter presents a practical framework for implementing Gamification 2.0. It recommends choosing a dominant game genre that matches an app's core activities, aligning that genre with user psychology, and designing satisfying intrinsic interaction loops before adding points, badges, or other extrinsic rewards. ### Source excerpt Part 5 of the "Gamification Series." A framework for developers: from theory to practice Everything I've outlined so far is meaningless if you can't apply it. So let me give you a practical framework for actually implementing Gamification 2.0. Step 1: Stop copying mechanics; choose a genre Your first question isn't "What gamification mechanics should The post Gamification 2.0. Beyond Points and Badges: Designing for Players, Not Metrics. Chapter 5: Implementation appeared first on UX Magazine. ## Metastability in Recovery: Cascading Recovery with a Loop DevFeed: [Metastability in Recovery: Cascading Recovery with a Loop]() Original publisher: [Read original article]() Author: Aleksey Charapko Published: 2026-05-02T20:53:18Z Content type: article Language: en Sources: [Aleksey Charapko]() Topics: [systems]() Tags: [blog-post](), [engineering](), [metastabiilty](), [other-thoughts](), [recovery](), [simulation](), [systems]() ### AI overview The article explains how ambiguous assumptions and cross-system interactions can make recovery difficult or impossible in interconnected systems. It focuses on cascading recovery, where one system's recovery increases workload for dependent systems and can create amplified feedback loops. ### Source excerpt My last metastable blog post discussed the interactions between systems and components and how they can lead to metastable failures. Specifically, I looked at interactions between systems/components and how signals can be misinterpreted by different systems due to ambiguity -- a timeout may mean a transient fault that can be fixed by retrying, but it [...] ## Netflix's VOID: Fixing the Physics Problem in Video Editing DevFeed: [Netflix's VOID: Fixing the Physics Problem in Video Editing]() Original publisher: [Read original article]() Author: RisingStack Engineering Published: 2026-04-06T22:41:15Z Content type: article Language: en Sources: [RisingStack]() Topics: [AI Models](), [Artificial Intelligence](), [diffusion-transformers](), [Netflix](), [Simulation]() Tags: [ai](), [ai-models](), [diffusion](), [netflix](), [simulation](), [training](), [video]() ### AI overview The article explains Netflix's VOID model for removing objects from videos while also recomputing their downstream physical effects. It describes VOID as a counterfactual video-generation system using video diffusion and training data produced with physics simulation and human-object interaction data. ### Source excerpt There's a familiar trick in modern video editing with AI - taking an object out, slapping some new background in, - and calling it good. It does the trick for simple things, but it all falls apart the moment the object actually starts to move or interact with anything. Take a domino chain for example, [...] The post Netflix's VOID: Fixing the Physics Problem in Video Editing appeared first on RisingStack Engineering. ## Project Genie: Experimenting with infinite, interactive worlds DevFeed: [Project Genie: Experimenting with infinite, interactive worlds]() Original publisher: [Read original article]() Author: Diego Rivas Published: 2026-01-29T17:01:05Z Content type: release Language: en Sources: [Google DeepMind News]() Topics: [World models](), [Artificial Intelligence](), [Google AI](), [Simulation](), [Web app]() Tags: [3d](), [ai](), [experimental](), [google](), [google-ai](), [none](), [prototype](), [research](), [research-prototype](), [simulation](), [web](), [web-app](), [world-model]() ### AI overview Google is opening Project Genie to Google AI Ultra subscribers in the U.S. The experimental research prototype, powered by Genie 3, Nano Banana Pro and Gemini, lets users create, explore and remix interactive worlds. ### Source excerpt Google AI Ultra subscribers in the U.S. can try out Project Genie, an experimental research prototype that lets you create and explore worlds. ## Introducing RSC Explorer DevFeed: [Introducing RSC Explorer]() Original publisher: [Read original article]() Published: 2025-12-19T00:00:00Z Content type: tutorial Language: en Sources: [Dan Abramov]() Topics: [React](), [Protocol (disambiguation)](), [Single-page application (SPA)](), [JSON](), [Streaming](), [Simulation]() Tags: [build](), [json](), [protocol](), [react](), [simulation](), [streaming]() ### AI overview This article introduces RSC Explorer, a browser-based tool for examining how React Server Components serialize and deserialize React trees through the RSC protocol. It demonstrates JSON-like server stream data, client-side JSX reconstruction, and streaming behavior. The tool is a single-page application that runs locally in the browser and uses React's actual RSC protocol packages. ### Source excerpt My new hobby project. ## Some Fun Software Facts DevFeed: [Some Fun Software Facts]() Original publisher: [Read original article]() Author: Hillel Wayne Published: 2025-12-10T18:45:37Z Content type: article Language: en Sources: [Newsletter feed for Hillel Wayne's Newsletter]() Topics: [Software](), [Algorithms, Complexity](), [Simulation](), [ASCII](), [Vim](), [Cloudflare]() Tags: [algorithms](), [ascii](), [cloudflare](), [simulation](), [software](), [vim]() ### AI overview A year-end newsletter shares miscellaneous software facts, including a Game of Life implementation of Tetris, leap-second handling, Vim's computational capabilities, ASCII history, impractical faster algorithms, Cloudflare's lava-lamp randomness, and historical sorting-algorithm details. ### Source excerpt Last newsletter of the year! First some news on Logic for Programmers. Thanks to everyone who donated to the feedchicago charity drive! In total we raised $2250 for Chicago food banks. Proof here. If you missed buying Logic for Programmers real cheap in the charity drive, you can still get it for $10 off with the holiday code hannukah-presents. This will last from now until the end of the year. After that, I'll be raising the price from $25 to $30. Anyway, to make this more than just some record keeping, let's close out with something light. I'm one of those people who loves hearing "fun facts" about stuff. So here's some random fun facts I accumulated about software over the years: In 2017, a team of eight+ programmers successfully implemented Tetris as a game of life simulation. The GoL grid had an area of 30 trillion pixels and implemented a full programmable CPU as part of the project. Computer systems have to deal with leap seconds in order to keep UTC (where one day is 86,400 seconds) in sync with UT1 (where one day is exactly one full earth rotation). The people in charge recently passed a resolution to abolish the leap second by 2035, letting UTC and UT1 slowly drift out of sync. Vim is Turing complete. The backslash character basically didn't exist in writing before 1930, and was only added to ASCII so mathematicians (and ALGOLists) could write /\ and \/. It's popular use in computing stems entirely from being a useless key on the keyboard. Galactic Algorithms are algorithms that are theoretically faster than algorithms we use, but only at scales that make them impractical. For example, matrix multiplication of NxN is normally O(N^2.81). The Coppersmith Winograd algorithm is O(N^2.38), but is so complex that it's vastly slower for even 10,000 x 10,000 matrices. It's still interesting in advancing our mathematical understanding of algorithms! Cloudflare generates random numbers by, in part, taking pictures of 100 lava lamps. Mergesort is older than bubblesor ## Are Two Heads Better Than One? DevFeed: [Are Two Heads Better Than One?]() Original publisher: [Read original article]() Author: Nolen Royalty (eieiogames@gmail.com) Published: 2025-12-09T00:00:00Z Content type: tutorial Language: en Sources: [eieio.games]() Topics: [Simulation](), [math]() Tags: [math](), [simulation]() ### AI overview This article analyzes a coin-flipping game in which two independent players each lie 20% of the time. It explains that adding the second player does not improve the 80% accuracy achieved by trusting the first player, because disagreements provide no useful information when both players are equally trustworthy. ### Source excerpt A look at the surprising probabilities behind a simple coin flipping game ## Integrating External Libraries into NuttX Applications DevFeed: [Integrating External Libraries into NuttX Applications]() Original publisher: [Read original article]() Author: John Lee Published: 2025-11-19T00:00:00Z Content type: tutorial Language: en Sources: [Blog on Developer Portal]() Topics: [NuttX](), [Library](), [Simulation](), [ESP32-C6](), [RISC-V](), [x86]() Tags: [blog](), [compilation](), [cross-compilation](), [esp32-c6](), [guide](), [how-to](), [libraries](), [library](), [nuttx](), [practitioner](), [risc-v](), [simulation](), [x86]() ### AI overview This guide explains how to integrate an external application library into NuttX using a static library and cross-compilation. It covers building the library on x86, testing it in the NuttX simulation environment, and cross-compiling it for RISC-V to run on the ESP32-C6. ### Source excerpt This guide demonstrates how to integrate external libraries into NuttX applications using static libraries and cross-compilation. Learn how to build a library on x86, integrate it into the NuttX simulation environment, and cross-compile for RISC-V targets like the ESP32-C6, all without moving your entire codebase into the NuttX directory structure. [Next page]()