Scientific Analysis & Insights:

Only GPT-4.03 successfully used Chain-of-Thought reasoning to detect and resolve contradictions. 🔥

Claude 3.7 & Grok 3 had high-speed processing but lacked deep analytical skills. 🏃‍♂️

DeepSeek R1 had the worst performance due to major flaws in logical processing & maintaining information coherency. 🚨

🔬 How AI Models Process Logical Problems:
✅ Text Understanding (NLU & Encoder)
✅ Working Memory Retention
✅ Step-by-Step Deduction (Chain-of-Thought Processing)
✅ Contradiction Resolution (Logical Inference & Conflict Handling)

🚀 Final Verdict:
🥇 GPT-4.03 is the clear winner! This model dominated logical reasoning, accurately solved the puzzle, and even pointed out an inconsistency in the clues! 👏💡

📌 Pro Tip: If you need a model for high-stakes logical analysis and problem-solving, GPT-4.03 is the best pick! 🔥

✨ What’s Next?
The future of LLMs depends on enhancing deep logical reasoning & improving the balance between speed and accuracy! 🌐🤖

💬 What do you think? Which model do you prefer, and why? 🤔🚀

✍️Author:
@Ghiasvand_Engineering
@AddiTech

🔹 What is Generative Design?
Generative design is an AI-driven engineering approach that automatically generates multiple optimized design alternatives based on user-defined inputs like materials, constraints, and performance goals. It mimics nature’s evolution process to find the best possible design.

🔹 How Can It Solve Our Challenges?
✅ Reduces Weight & Material Waste → Optimized structures with less material but higher strength
✅ Speeds Up Product Development → AI explores thousands of designs in hours, not weeks
✅ Cost-Effective Manufacturing → Creates ready-to-produce designs for 3D printing, CNC, and more
✅ Enhances Product Performance → Finds the strongest, lightest, and most efficient designs

🔹 Why is Generative Design the Future?
By automating complex design processes, companies can innovate faster, reduce costs, and create breakthrough products that were previously impossible to design manually.

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𝗔𝗩𝗢𝗜𝗗 𝟯𝗗 𝗣𝗥𝗜𝗡𝗧𝗜𝗡𝗚 𝗘𝗥𝗥𝗢𝗥𝗦 𝗪𝗜𝗧𝗛 𝗦𝗜𝗠𝗨𝗟𝗔𝗧𝗜𝗢𝗡 🖥

At Danish Technological Institute, experts use simulations to optimize additive manufacturing and achieve 'first-time-right' results 📈

Using Simufact software, AM design specialist Andreas Weje Larsen predicts errors like deformation, cracks, shrink lines, and recoater contacts in titanium (Ti6Al4V). Aluminium (AlSi10Mg) is next ⚙️

Below is a test build for AMSIS GmbH, where shrink lines were predicted and later confirmed in the printed part 😊

The goal: Predict and fix errors before printing 👍

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⚡️ Ansys Fluent Meets #SimAI: Revolutionizing Simulation ⚡️

Ansys SimAI, a cloud-enabled generative AI platform, is transforming the engineering landscape by delivering ultra-fast and accurate performance predictions across physics domains like fluid dynamics.

🚀 What makes SimAI powerful?
1) Lightning-fast predictions: Evaluate performance in under a minute — design cycles reduced by 10-100X.
2) Massive design exploration: Quickly test and compare countless design iterations.
3) No-code AI experience: Designed for engineers and designers — no deep learning expertise needed.

One impressive example: SimAI's drag prediction on a new SUV geometry takes less than 1 minute, with an error of less than 0.5% compared to CFD, while maintaining accurate skin friction and wake topology predictions.

🔁 Left: Traditional Fluent CFD | Right: AI Prediction from #SimAI

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🧠 AI-Powered Crash Predictions by NAVASTO | Powered by Autodesk 🕓

Crash simulations that once took hours can now be performed in seconds thanks to the AI technology developed by NAVASTO, a company backed by Autodesk.

Originally built for sensitivity analysis, this AI model now enables real-time crash predictions. A striking example: a Toyota vehicle crashing into a wall, fully simulated with AI, showing accurate deformation and impact behavior all happening in real time.

Why it matters:
• From hours to seconds: real-time crash analysis
• Fast evaluation of multiple design options
• Supports early decision-making
• Reduces physical testing needs

This is a major step forward in engineering workflows, making simulation faster, smarter, and more accessible.

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🔧 Metal 3D Printing and Generative Design Applied to Vehicle Chassis Engineering

This advanced demonstration combines Generative Design algorithms with Directed Energy Deposition (DED) metal 3D printing technology to redefine how we design and manufacture structural automotive components.

Key advancements include:

• 🔻 Up to 10× reduction in part count – minimizing complexity and improving maintainability.
• ⏱️ 60% shorter lead times – accelerating prototyping and production cycles.
• 🪶 Lightweight and modular architecture – enabling enhanced performance and energy efficiency.

By integrating AI-driven design with additive manufacturing, this approach not only improves mechanical performance but also revolutionizes the production process through material efficiency and design optimization.

#Metal3DPrinting #GenerativeDesign #DirectedEnergyDeposition #AdditiveManufacturing #VehicleEngineering #InnovationInMotion #AdvancedManufacturing

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🔍 Autonomous AI Systems: Shaping the Future of Engineering & Intelligent Decision-Making
Imagine an AI system that doesn't just process data but learns, plans, experiments, and generates innovative solutions independently.

These next-generation autonomous systems function in iterative, adaptive cycles, enabling them to:

🔁 Plan and execute complex simulations and optimization workflows
📊 Evaluate results automatically and refine strategies based on outcomes
💡 Generate novel solutions grounded in learned patterns and insights.

All with minimal to no human intervention drastically accelerating innovation across disciplines.

🚀 Key Applications Include:
• Intelligent Data Acquisition through Active Learning
• Automated Hyperparameter Tuning via Bayesian Optimization
• Closed-loop Experimental Design and Model-Driven Discovery

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🚀 A Must-Read Resource for Tech & Engineering Enthusiasts (Ansys Advantage – Issue 2, 2024)

Focus Topic: AI-Powered Simulation & Autonomous Systems in Engineering

This issue provides deep insights into the future of simulation technologies, autonomous AI systems, digital twins, and their real-world industrial applications.

Key Highlights:
🔹 Autonomous AI for Smart Decision-Making
🔹 AI-Driven Simulation & Optimization Workflows
🔹 Digital Twin Development with AI/ML Integration
🔹 Industrial Case Studies from Leading Companies (Tata Steel, Seagate, Automotive, Aerospace)

📥 Access to the full PDF is available in this post.

For more high-value resources in technology, engineering, and AI — stay connected with @AddiTech.

#AI #Engineering #Simulation #DigitalTwin #Optimization #AddiTech

Generative Design ⚙️
Revolutionizing Engineering Through AI

Generative Design is a cutting-edge, AI-driven approach that transforms the way we conceptualize and create engineering solutions. Instead of manually modeling a structure based on past experience or intuition, engineers define the design goals, constraints, material properties, manufacturing methods, and loading conditions and the software explores hundreds or even thousands of optimized design alternatives.

This iterative and exploratory process mimics nature's evolutionary approach, using algorithms to evaluate and evolve solutions based on performance metrics such as strength, weight, durability, and cost-efficiency.

Unlike traditional CAD modeling, where design originates from the engineer’s mind, generative design starts with data — and ends with innovation.

Stay tuned for real-world applications, case studies, and simulation insights into the future of design and manufacturing. 🌐✨

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