Materials Project Database Growth Supports AI-Ready Materials Science Research - Lab Manager
Hi there, little scientist! 👋
Imagine you have a giant toy box full of amazing building blocks, like LEGOs! 🧱 This toy box is called the "Materials Project Database."
Scientists are like super builders, and they're adding more and more cool blocks to this box every day! 🎉
Why? Because they want to teach a smart robot friend, called "AI," how to build new, super-strong, or super-bendy things even faster! 🤖 The more blocks the robot sees, the better it learns to invent new stuff for us, like new kinds of play-doh or super-fast cars! Isn't that neat?
Materials Project Database Growth Supports AI-Ready Materials Science Research Lab Manager
Could not retrieve the full article text.
Read on GNews AI materials →Sign in to highlight and annotate this article
Conversation starters
Daily AI Digest
Get the top 5 AI stories delivered to your inbox every morning.
More about
research
How to Build an AI Content Playbook That Actually Protects Your Voice
Ahnii! You've read the articles warning you not to let AI take over your content. Ruth Doherty's latest piece is one of the best: a clear-eyed breakdown of where AI helps and where it silently destroys your brand. This post shows you how to take that framework and turn it into an actual operating document for your content pipeline. Why a Framework Without a Playbook Doesn't Stick Ruth's core argument is sharp: AI is an efficiency engine, not a strategy engine. Use it for research, structuring, repurposing, and editing. Keep it away from messaging, customer research, and anything that requires your actual point of view. That distinction is easy to agree with. It's harder to enforce on a Tuesday afternoon when you're behind on three social posts and the AI can draft all of them in 90 seconds
Top 10 Best Universities to Study AI in USA 2026 Led by CMU and MIT With Strong Research and Industry Ties - International Business Times Australia
Top 10 Best Universities to Study AI in USA 2026 Led by CMU and MIT With Strong Research and Industry Ties International Business Times Australia
Knowledge Map
Connected Articles — Knowledge Graph
This article is connected to other articles through shared AI topics and tags.
More in Generative UI
Researchers train living rat neurons to perform real-time AI computations — experiments could pave the way for new brain-machine interfaces - Tom's Hardware
Researchers train living rat neurons to perform real-time AI computations — experiments could pave the way for new brain-machine interfaces Tom's Hardware
Researchers train living rat neurons to perform real-time AI computations — experiments could pave the way for new brain-machine interfaces
Researchers train living rat neurons to perform real-time AI computations — experiments could pave the way for new brain-machine interfaces
I Built a GitHub-Style Contribution Calendar That Shows When My AI Works Without Me
GitHub's contribution calendar shows when you coded. But what if half those green squares weren't actually you? I built cc-calendar — a terminal tool that renders a GitHub-style activity graph for your Claude Code sessions. Two rows: YOU (cyan) and AI (yellow). Ghost Days — when AI ran autonomously while you had zero interactive sessions — glow bright. The output $ npx cc-calendar cc-calendar — AI草カレンダー ══════════════════════════════════════════════════ Jan Feb Mar Sun ░░░░░▒░░░ Sun ░▒▒▒▓█▓█▒ Mon ░░░░░░░░░ Mon ░▒▒▒▓██▓░ Tue ░░░░░▒░░░ Tue ░▒▒▒▒▓▓▓░ Wed ░░░░▒░░░░ Wed ░▒▓▒▒▓▓▓░ Thu ░░░░░░██░ Thu ░▓▒▒▒▒▓▒░ Fri ░░░░░░█░░ Fri ░▒░█▒▒▓▒░ Sat ░░░░▒░░█░ Sat ▒░░▒▓▒▓█░ █ You █ AI █ Ghost Day ░▒▓█ = none→light→heavy ▸ Period: 2026-01-10 → 2026-03-01 ▸ Active Days: 48 total ├─ Both active: 8 days ├─ You
Please add New hardware the AMD ai pro R9700 "My GPU"
Please add “AMD Radeon AI PRO R9700” to “My Hardware” Specs: GPU Memory: Volume Memory - 32GB Memory Type - GDDR6 AMD Infinity Push Technology - 64 MB Memory Interface - 256-bit Max Memory Letters - 640 GB/s GPU: AMD RDNA™ 4 Execution Accelerators - 64 Against AI Accelerators - 128 Streams - Processors 4096 Compute Units - 64 Boost Ads - Up to 2920MHz Gameplay - 2350MHz Max Charged Speed - Up to 373.76 GP/s Max Single Precision (FP32 Vector) Performance - 47.8 TFLOPs Max Half Precision (FP16 Vector) Performance - 95.7 TFLOPs Max Half Precision (FP16 Matrix) Performance - 191 TFLOPs Gain Structural Spurtity Max Half-Precision (FP16 Matrix) Performance - 383 TFLOPs Max 8-Bit Performance (FP8 Matrix) (E5M2, E4M3) - 383 TFLOPs 8-Bit Performance (FP8 Matrix) with Structured Spursity (E5M2, E4
Discussion
Sign in to join the discussion
No comments yet — be the first to share your thoughts!