#AI simulation
634 related articles
·3 min
Scholé Scenarios: AI-Powered Scenario Simulations That Take Corporate Training from Knowing to Doing
Scholé Scenarios is an AI-driven scenario-based learning tool that simulates real customer interactions with adaptive learning to help sales and service teams bridge the gap between knowing and doing.
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·3 min
Crankwave: A Detailed Look at the Open-Source Engine Sound Simulation and Baking Tool
An in-depth look at Crankwave, an MIT-licensed open-source engine sound simulator and audio baking tool supporting JSON config, WASM execution, deterministic baking, and simulator-free playback for game developers.
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·4 min
Agentic Engineering: How AI Agents Are Reshaping Physics Simulation and Robotics Development
Deep dive into the agentic engineering paradigm from NVIDIA's SIGGRAPH demo—from vibe coding to controlled workflows, and how Omniverse libraries empower AI Agents for physics simulation and robotics.
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·3 min
AI Training Guide for Virtual Basketball Courts: 3D Generation, Physics Simulation & Generative AI Paths Explained
A detailed guide on three technical paths for training virtual basketball court AI models: 3D scene generation (NeRF/Gaussian Splatting), Unity/Unreal simulation, and generative AI fine-tuning.
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·3 min
Mecanum Wheel Motion Simulation Platform: A Detailed Guide to Low-Cost VR Haptic Solutions
A detailed look at a Mecanum wheel-based omnidirectional motion simulation platform using VR trackers for 3-DOF motion simulation and recentering correction — a viable low-cost VR immersion solution.
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·3 min
SCAIL 2 Deep Dive: Character Replacement, Physics Simulation & Object Permanence Performance Analysis
In-depth testing of SCAIL 2 video generation AI across character replacement, physics simulation, object permanence, and more—covering reference image prep, ComfyUI workflows, and real results.
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·3 min
AI-Powered Abaqus Simulation: With vs. Without Skills — The Results Are Worlds Apart
No Skills: AI gets units wrong, assembly fails, zero results. With Skills: AI generates batch stress contour plots end-to-end. A deep dive into the general model + domain skill methodology for AI-driven CAE simulation.
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·4 min
AI-Driven HFSS Simulation: Codex Automates AEDT Modeling and Solving via MCP
Learn how Codex or Claude Code uses AEDT MCP to connect with Ansys HFSS, automating Wilkinson power divider modeling, solving, and post-processing end-to-end.
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·3 min
OpenAI Codex Powers Black Hole Simulation: 1000x Algorithm Speedup Brings First-Ever Black Hole Video Within Reach
The EHT team used OpenAI Codex to speed up black hole plasma simulation algorithms by 1000x, from ten days to minutes. Learn how Codex is enabling the first-ever black hole video.
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Deep Dives·3 min
Why Is AI Agent Testing So Hard? How Simulation Testing Cracks the Infinite Input Space Problem
AI Agents face infinite input spaces and non-deterministic outputs. Learn how simulation testing systematically validates Agent reliability through scenario generation, environment simulation, and behavior evaluation.
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Tech Frontiers·3 min
Simulation Reshaping AI Testing: A New Paradigm for Systematically Validating AI Application Reliability
Explore how simulation solves AI testing challenges, covering scenario simulation, large-scale regression testing, and multi-agent verification to build reliable AI systems.
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·3 min
The Fascinating Real-World Counterparts of OpenAI Gym Reinforcement Learning Environments
Exploring how OpenAI Gym RL environments map to real-world scenarios, from CartPole to MountainCar, covering design principles and the sim-to-real transfer challenge.
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·3 min
How to Prepare for Technical Interviews: Practical Strategies for Tackling Open-Ended System Design Questions
Anxious about open-ended system design questions in tech interviews? Learn what interviewers really evaluate, plus practical strategies including structured frameworks, the Feynman Technique, and mock practice.
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·3 min
How Hexapod Robots Achieve Walking and Self-Leveling: Core Technical Analysis
Deep dive into the technical challenges of hexapod robot walking with self-leveling, covering gait planning, inverse kinematics, IMU feedback, and real-time control system integration.
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·3 min
Stanford CS234 Reinforcement Learning Too Hard to Self-Study? Group Learning Is the Key to Breaking Through
Addressing the high barriers, isolation, and lack of practical feedback faced by Stanford CS234 RL self-learners, with actionable advice on group learning strategies, community resources, and project-driven approaches.
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·4 min
AI Large Language Models + MCP Protocol: A Hands-On Tutorial for Fully Automated Unity Digital Twin Construction
Learn how AI LLMs paired with MCP servers can fully automate Unity digital twin construction without manual operations. Covers MCP setup, Claude Code integration, and auto-generated conveyor scenes.
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·3 min
APAC Dataset: First-Person Stereo Vision Robot Training Data for Real-World Work Environments
APAC Egocentric Stereo dataset covers real work scenes like garages, factories, and construction sites with stereo vision, depth, and hand tracking for robot training.
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·3 min
Training a Robot Dog with Real Dog Videos: A Technical Breakdown of Video-Driven Reinforcement Learning
A deep dive into how real dog videos can train robot dogs for locomotion control, covering pose estimation, motion retargeting, PPO reinforcement learning, and the challenges ahead.
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·3 min
reinfors Adds CarRacing Environment: Rust Backend Delivers 20x Reinforcement Learning Speedup
Open-source reinfors v0.3.0 adds CarRacing with a Rust backend, achieving 20x faster stepping than Gymnasium. Features overlapping train/sample execution via collect_stream, compatible with PyTorch and JAX.
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·3 min
The Technical Truth Behind the Robot Hurdles Race: How Reinforcement Learning Makes Embodied AI Move as Naturally as Humans
Analyzing the core tech behind the humanoid robot hurdles race: how reinforcement learning enables natural movement, what controllers really do, and the Sim-to-Real pipeline driving embodied AI forward.
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