The Three Ages of Data Science: When to Use Traditional Machine Learning, Deep Learning, or an LLM (Explained with One Example)
towardsdatascience.com·1h
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Windows ARM Goes Tier 1
🦀rust, zig, terraform
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AI Wealth Managers and Smart Contracts = Dead People Controlling Money Forever
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Show HN: I built a tool to create custom OCR APIs in minutes, no training needed
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HyperMarkets: Fast, Fair, and Fun Prediction Markets on Hyperliquid Perps
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4 open‑source apps I use to run AI locally
xda-developers.com·1h
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TAI #178: Kimi K2 Thinking Steals the Open-Source Crown With a New Agentic Contender
pub.towardsai.net·1h
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Right-sized AI: Good for business, users, and the planet
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From Zero to LLMOps Hero: Your 101 Guide to Running LLMs in Production
analyticsvidhya.com·1d
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LoReTTA: A Low Resource Framework To Poison Continuous Time Dynamic Graphs
arxiv.org·11h
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How Point Cloud to BIM Helps Surveyors Reduce Costs and Save Time
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🗓️ Docker Learning Journal
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Decentralized Knowledge Graph Augmentation for Semantic Web3 Discovery
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Hybrid Autoencoders for Tabular Data: Leveraging Model-Based Augmentation in Low-Label Settings
arxiv.org·11h
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A Practical Guide to Building AI Agents with Java and Spring AI - Part 2 - Add Memory
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