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Poll for manufacturing teams: Biggest material selection challenge right now? A) Cost pressure B) Sustainability compliance C) Performance requirements D) Supply availability Our Engine's 20 specialist AI agents—from Cost & Procurement to Material Analyst—turn scanned mater...

🔧 Calling all makers! We're launching #MaterialHacks — a recurring series featuring YOUR best discoveries. Swapped plywood for reclaimed pallet wood? Found a clever workaround in your workshop? Tag us + #MaterialHacks. Best submissions get featured. What could you build nex...

AI is discovering new materials. Robots are testing them. But here's the exciting part for YOU: Think of it like this — scientists are writing new ingredients. The Engine lets you cook with them TODAY. Snap a photo of any material → 20 AI agents → product concepts, CAD files...

Launching today: #MaterialHacks — a recurring community spotlight series. We want to see your best material swap, clever workaround, or surprising test result from the lab or workshop. Tag us + #MaterialHacks. Top submissions get featured. First spotlight drops next week. ...

🎓 DT & STEM teachers — what material problem are your students wrestling with right now? Maybe they've found something interesting and don't know what to make from it? Share below! We'll feature the best challenges and walk through how 20 AI specialist agents would analyse t...

AI discovers materials. Robots validate them. But who turns them into products? The Material-to-Product Engine: scan a material → 20+ AI agents analyse it → get product concepts, CAD files, engineering drawings & manufacturing plans. 42+ products designed from real scans. #A...

Federal agencies are prioritizing advanced materials & energy resiliency funding. For sustainability consultants: the green materials pipeline is about to accelerate. Our 20+ AI agents already turn scanned sustainable materials into full product concepts with manufacturing pla...

AI-discovered materials could transform clean energy — but only if they reach sustainable products. The Material-to-Product Engine includes a Sustainability Analyst among 20+ agents. Scan a material → get product concepts, manufacturing plans & CAD files with environmental im...

Novel material validated in the lab → now what? Upload a photo to the Material-to-Product Engine. 20+ AI agents — Material Analyst, Chemical Engineer, Technology Scout, CAD/CAM — deliver product concepts, STEP/STL files & supply chain options. From discovery to deployment. #...

🔧 What Would You Build? #1 Got offcuts, salvage, or mystery materials lying around your workshop? Share a photo below! We'll vote on which one our 20 AI agents should turn into a real product — complete with CAD files, engineering drawings & a manufacturing plan. Drop your ...

Next-gen research fellows are merging AI, robotics & neuroscience with materials discovery. The Material-to-Product Engine mirrors this: 20 specialist agents analyse scanned materials → product concepts, STEP/STL CAD, engineering drawings & manufacturing plans. 42+ products d...

What if surplus material wasn't a write-off but a design input? 42 products designed from scanned materials. 20 AI specialists including Cost & Procurement built into every output — STEP files, drawings, manufacturing plans. Material-first design changes the supply chain equ...

42 products designed from scanned materials — every one assessed by a Sustainability Analyst agent before production. From the Garden Hose Station to the Hybrid Workstation, circular economy thinking is built into the engineering. Evidence-based sustainable design, at scale. ...

5 scanned materials/components. One AI engine. 84-page engineering report. 8 innovation pathways. Watch the Material-to-Product Engine turn warehouse leftovers into the HydraLift Pro — a 500kg hydraulic platform cart with IoT monitoring, smart safety systems, and a full path to manufacture. Not what to build. How to build it better. mp-engine.com #ManufacturingAI, #CircularEconomy, #Industry40, #SmartManufacturing, #AIEngineering, #AI

5 images of warehouse scrap → 84-page Tier 4 engineering report → 8 innovation pathways mapped. The Material-to-Product Engine designed a mobile hydraulic platform from pallet racking + a used pump, then identified IoT monitoring, smart hydraulics, CFRP weight reduction & Industry 4.0 fleet management. Not just what to build. What technologies to integrate. Utility: 8.2/10 | 61% carbon reduction | 0.92 innovation confidence. #ManufacturingAI #CircularEconomy #IntegratedManufacturing

Every #AI #CAD tool starts from a prompt. The Material-to-Product Engine starts from 3–5 photos of the materials you already have. One session → CAD, BOM, 3 build tiers, regulatory flags, patent check, sustainability analysis. No CAD licence. Mobile-first. Nobody else does this. mp-engine.com #MPEngine #AIEngineering #MakerMovement #DeepTech #ManufacturingAI #NoCADRequired #ProductDesign

Some interesting results from our internal testing of the three LLMs we use: @AnthropicAI , @OpenAI and @GeminiApp . @AnthropicAI is the fastest across the board — especially on throughput where it's 2-3x faster than competitors. It also handles concurrency best, with little degradation (1.1s single vs 1.0s avg under concurrency). @OpenAI is competitive on complex prompts (slightly faster than @AnthropicAI wall-clock, but fewer output tokens — 297 avg vs 548 avg). Its concurrency is nearly as good as @AnthropicAI. @Gemini is significantly slower on everything, especially complex prompts (20.6s vs 5.6s). Under concurrency it degrades badly (4.9s wall time vs 1.4s versus 1.5s for the others). Combined with the persistent 503s, it's not ready for our critical-path agents. #IndustrialStrategy, #AI, #Innovation, #GovTech, #RandD, #DeepTech, #Manufacturing, #ClaudeAI, #ChatGPT, #Gemini, #MaterialEngine

@mp_engine @AnthropicAI @OpenAI @GeminiApp We think @GeminiApp will catch up at some point. Or could it be that it is slow because it’s popular?…🤔

5 images, few clicks and you just compressed several weeks to several months of product R&D to minutes. That simple.... #IndustrialStrategy, #AI, #Innovation, #GovTech, #R&D #DeepTech, #Manufacturing

If you #teach #engineering, #design, or #product #development — ask yourself: are your #students #learning to work for an #industry, or #learning to #create one? There's a difference. And there's now a tool for the second. @mp_engine Full article here --> x.com/mp_engine/stat… #HigherEd, #Engineering, #ProductDesign, #AI, #DeepTech, #RandD