Preservica and Gravity Union Partner to Streamline Long-Term Data Archiving and Governance in Microsoft 365 for Canadian Organizations
preservica.com·1d
🏛️PREMIS Metadata
[$] Libxml2's "no security embargoes" policy
lwn.net·1d
🔓Free and open source
Observability in the Age of AI
blog.buildrappo.com·16h·
Discuss: Hacker News
👁️System Observability
Design Decisions Behind app.build, a Prompt-to-App Generator
neon.com·5h·
Discuss: Hacker News
🌊Streaming Systems
new2
dev.to·17h·
Discuss: DEV
🧠Query Planners
Critical Anatomy-Preserving & Terrain-Augmenting Navigation (CAPTAiN): Application to Laminectomy Surgical Education
arxiv.org·16h
🌀Differential Geometry
💎 Bespoke Opportunity Forge: AI-Powered Job Concierge 📬
dev.to·9h·
Discuss: DEV
🌀Brotli Internals
Opportunistic Osteoporosis Diagnosis via Texture-Preserving Self-Supervision, Mixture of Experts and Multi-Task Integration
arxiv.org·16h
👁️OCR Enhancement
N8N, Local LLM, MCP proxy in 1 compose file
ajeetraina.com·1d·
Discuss: Hacker News
🏠Homelab Orchestration
Opportunity knocks: getting your house in order for the AI action plan
techradar.com·6h
🌊Stream Processing
Seeing is Believing? Mitigating OCR Hallucinations in Multimodal Large Language Models
arxiv.org·16h
🤖Advanced OCR
Stop Chasing “Efficiency AI.” The Real Value Is in “Opportunity AI.”
towardsdatascience.com·1d
🌊Stream Processing
Machine Learning Fundamentals: active learning project
dev.to·1d·
Discuss: DEV
🧠Machine Learning
AMF-MedIT: An Efficient Align-Modulation-Fusion Framework for Medical Image-Tabular Data
arxiv.org·1d
🤖Advanced OCR
ReMAR-DS: Recalibrated Feature Learning for Metal Artifact Reduction and CT Domain Transformation
arxiv.org·1d
📊Learned Metrics
SharePoint Migration Services: A Complete Guide for Seamless Data Transfer
dev.to·2d·
Discuss: DEV
🚚Data Migration
Who are your MCP servers talking to?
dev.to·4h·
Discuss: DEV
📦Container Security
Marker: Convert PDF to Markdown and JSON
github.com·4d·
Discuss: Hacker News
📄PDF Internals
DigitalOcean Fundamentals: API
dev.to·1d·
Discuss: DEV
🔌Interface Evolution
Learning from Anatomy: Supervised Anatomical Pretraining (SAP) for Improved Metastatic Bone Disease Segmentation in Whole-Body MRI
arxiv.org·1d
🧠Machine Learning