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Willy Messerschmitt – Experience in the design of metal aeroplanes (1943)
calum-douglas.com·9h·
Discuss: Hacker News
Every Public Facing Organisation Should Run a Provenance Service
djoker.dev·7h·
Discuss: Hacker News
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Visual DOS 2024 Tech Preview
antijingoist.itch.io·1h·
Discuss: Hacker News
Google's AI pointed him to a customer service number. It was a scam
yahoo.com·5h·
Discuss: Hacker News
First Descendant Devs in Hot Water Over AI Ads Impersonating Streamers
techpowerup.com·6h·
Discuss: Hacker News
Google is killing the open web
wok.oblomov.eu·10h·
Discuss: Lobsters, Hacker News
First exclusive feature for open ESP32 Wi-Fi stack: standards-compliant meshing
esp32-open-mac.be·7h·
Discuss: Hacker News
proposal: mark/punish ai imagery
lobste.rs·2d·
Discuss: Lobsters
🤖AI
The AI future is too scary even for James Cameron. Where can the Terminator franchise go from here?
theguardian.com·8h·
Discuss: Hacker News
"Why I Built an AI Terminal with Mermaid Themes (And Why Developer Tools Should Spark Joy) 🧜‍♀️"
rinawarptech.com·2d·
Discuss: DEV, Hacker News
Designing for Engaging Communication Between Parents and Young Adult Children Through Shared Music Experiences
arxiv.org·18h
Abundance-Aware Set Transformer for Microbiome Sample Embedding
arxiv.org·18h
G-CUT3R: Guided 3D Reconstruction with Camera and Depth Prior Integration
arxiv.org·18h
From Misunderstandings to Learning Opportunities: Leveraging Generative AI in Discussion Forums to Support Student Learning
arxiv.org·18h
PersonaTwin: A Multi-Tier Prompt Conditioning Framework for Generating and Evaluating Personalized Digital Twins
arxiv.org·18h
Personalized Face Super-Resolution with Identity Decoupling and Fitting
arxiv.org·18h
Visual Perception Engine: Fast and Flexible Multi-Head Inference for Robotic Vision Tasks
arxiv.org·18h
UbiQTree: Uncertainty Quantification in XAI with Tree Ensembles
arxiv.org·4d
🤖AI
Learning Differentiable Reachability Maps for Optimization-based Humanoid Motion Generation
arxiv.org·18h
When Punctuation Matters: A Large-Scale Comparison of Prompt Robustness Methods for LLMs
arxiv.org·18h