Real-time stock volatility prediction with deep learning on a time-series DB
🔬Deep Learning
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DynBERG: Dynamic BERT-based Graph neural network for financial fraud detection
arxiv.org·1d
🤖Transformers
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How Datadog Built a Custom Database to Ingest Billions of Metrics Per Second
blog.bytebytego.com·18h
🗄️Database Engines
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Radar Trends to Watch: November 2025
oreilly.com·22h
🎭Program Synthesis
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News for October 2025
ptreview.sublinear.info·1d
✅Property Testing
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Show HN: I analyzed 44 OSS dev tools revenue model matters more than stars
🌐Open Source
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Replication redefined: How we built a low-latency, multi-tenant data replication platform
datadoghq.com·1d
🤝Paxos
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Why Your AI Agent Keeps Failing in Production (And How to Fix It)
pub.towardsai.net·2d
🤝Paxos
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Hans-Juergen Schoenig: Counting Customers in PostgreSQL
cybertec-postgresql.com·1d
🗄️Database Internals
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MariaDB vs. PostgreSQL: Understanding the Architectural Differences That Matter
🗄️Databases
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What to Do When Your Credit Risk Model Works Today, but Breaks Six Months Later
towardsdatascience.com·15h
⚡Incremental Computation
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Inside Zendesk’s dual AI leap: From reliable agents to real-time intelligence with GPT-5 and HyperArc
venturebeat.com·1d
💬Prompt Engineering
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The Infrastructure of Modern Ran king Systems, Part 2: The Data Layer - Fueling the Models with Feature and Vector Stores
shaped.ai·2d
🧮Vector Databases
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Going From Reactive to Predictive Incident Response with AIOps
hackernoon.com·12h
⚡Performance Engineering
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Building Data Tools That Work
🔧Data Engineering
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