📌 The 2026 Goal Tracker: How I Built a Data-Driven Vision Board Using Python, Streamlit, and Neon

🗂 Category: PRODUCTIVITY

🕒 Date: 2026-01-15 | ⏱️ Read time: 8 min read

Designing a centralized system to track daily habits and long-term goals

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📌 Do You Smell That? Hidden Technical Debt in AI Development

🗂 Category: ARTIFICIAL INTELLIGENCE

🕒 Date: 2026-01-15 | ⏱️ Read time: 14 min read

Why speed without standards creates fragile AI products

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📌 Maximum-Effiency Coding Setup

🗂 Category: PROGRAMMING

🕒 Date: 2026-01-16 | ⏱️ Read time: 9 min read

Learn how to be a more efficient programmer

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📌 Cutting LLM Memory by 84%: A Deep Dive into Fused Kernels

🗂 Category: LARGE LANGUAGE MODELS

🕒 Date: 2026-01-16 | ⏱️ Read time: 18 min read

Why your final LLM layer is OOMing and how to fix it with a custom…

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📌 From RGB to Lab: Addressing Color Artifacts in AI Image Compositing

🗂 Category: ARTIFICIAL INTELLIGENCE

🕒 Date: 2026-01-16 | ⏱️ Read time: 13 min read

A multi-tier approach to segmentation, color correction, and domain-specific enhancement

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📌 The Great Data Closure: Why Databricks and Snowflake Are Hitting Their Ceiling

🗂 Category: DATA SCIENCE

🕒 Date: 2026-01-16 | ⏱️ Read time: 13 min read

Acquisitions, venture, and an increasingly competitive landscape all point to a market ceiling

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📌 Data Poisoning in Machine Learning: Why and How People Manipulate Training Data

🗂 Category: MACHINE LEARNING

🕒 Date: 2026-01-17 | ⏱️ Read time: 14 min read

Do you know where your data has been?

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📌 A Geometric Method to Spot Hallucinations Without an LLM Judge

🗂 Category: LARGE LANGUAGE MODELS

🕒 Date: 2026-01-17 | ⏱️ Read time: 7 min read

Imagine a flock of birds in flight. There’s no leader. No central command. Each bird…

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📌 The Hidden Opportunity in AI Workflow Automation with n8n for Low-Tech Companies

🗂 Category: ARTIFICIAL INTELLIGENCE

🕒 Date: 2026-01-18 | ⏱️ Read time: 14 min read

How to use n8n with multimodal AI and optimisation tools to help companies with low…

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📌 Why Healthcare Leads in Knowledge Graphs

🗂 Category: DATA SCIENCE

🕒 Date: 2026-01-18 | ⏱️ Read time: 9 min read

How science, regulation, collaboration, and public funding shaped the world’s most mature semantic infrastructure

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📌 Bridging the Gap Between Research and Readability with Marco Hening Tallarico

🗂 Category: AUTHOR SPOTLIGHTS

🕒 Date: 2026-01-19 | ⏱️ Read time: 6 min read

Diluting complex research, spotting silent data leaks, and why the best way to learn is…

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📌 Using Local LLMs to Discover High-Performance Algorithms

🗂 Category: LARGE LANGUAGE MODELS

🕒 Date: 2026-01-19 | ⏱️ Read time: 10 min read

How I used open-source models to explore new frontiers in efficient code generation, using my…

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📌 Time Series Isn’t Enough: How Graph Neural Networks Change Demand Forecasting

🗂 Category: DATA SCIENCE

🕒 Date: 2026-01-19 | ⏱️ Read time: 11 min read

Why modeling SKUs as a network reveals what traditional forecasts miss

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📌 You Probably Don’t Need a Vector Database for Your RAG — Yet

🗂 Category: LARGE LANGUAGE MODELS

🕒 Date: 2026-01-20 | ⏱️ Read time: 14 min read

Numpy or SciKit-Learn might meet all your retrieval needs

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📌 Why Package Installs Are Slow (And How to Fix It)

🗂 Category: DATA ENGINEERING

🕒 Date: 2026-01-20 | ⏱️ Read time: 7 min read

How sharded indexing patterns solve a scaling problem in package management

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📌 Does Calendar-Based Time-Intelligence Change Custom Logic?

🗂 Category: DATA SCIENCE

🕒 Date: 2026-01-20 | ⏱️ Read time: 8 min read

Let’s look at calculating the moving average over time

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