Optimizing Data Transfer in Distributed AI/ML Training Workloads
A deep dive on data transfer bottlenecks, their identification, and their resolution with the help of NVIDIA Nsight™ Systems – part 3
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Achieving 5x Agentic Coding Performance with Few-Shot Prompting
Learn to leverage few-shot prompting to increase your LLMs performance
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TDS Newsletter: Beyond Prompt Engineering: The New Frontiers of LLM Optimization
Let's zoom in on recent approaches that push AI-powered workflows to the next level
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Building a Self-Healing Data Pipeline That Fixes Its Own Python Errors
How I built a self-healing pipeline that automatically fixes bad CSVs, schema changes, and weird delimiters.
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Using Local LLMs to Discover High-Performance Algorithms
How I used open-source models to explore new frontiers in efficient code generation, using my MacBook and local LLMs.
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Time Series Isn’t Enough: How Graph Neural Networks Change Demand Forecasting
Why modeling SKUs as a network reveals what traditional forecasts miss
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The Hidden Opportunity in AI Workflow Automation with n8n for Low-Tech Companies
How to use n8n with multimodal AI and optimisation tools to help companies with low data maturity accelerate their digital transformation.
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A Geometric Method to Spot Hallucinations Without an LLM Judge
Imagine a flock of birds in flight. There’s no leader. No central command. Each bird aligns with its neighbors—matching direction, adjusting speed, maintaining coherence through purely local coordination. The result is global order emerging from local consistency. Now imagine one bird flying with th...
Cutting LLM Memory by 84%: A Deep Dive into Fused Kernels
Why your final LLM layer is OOMing and how to fix it with a custom Triton kernel.
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The 2026 Goal Tracker: How I Built a Data-Driven Vision Board Using Python, Streamlit, and Neon
Designing a centralized system to track daily habits and long-term goals
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Topic Modeling Techniques for 2026: Seeded Modeling, LLM Integration, and Data Summaries
Seeded topic modeling, integration with LLMs, and training on summarized data are the fresh parts of the NLP toolkit.
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From ‘Dataslows’ to Dataflows: The Gen2 Performance Revolution in Microsoft Fabric
Dataflows were (rightly?) considered "the slowest and least performant option" for ingesting data into Power BI/Microsoft Fabric. However, things are changing rapidly and the latest Dataflow enhancements changes how we play the game
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Under the Uzès Sun: When Historical Data Reveals the Climate Change
Longer summers, milder winters: analysis of temperature trends in Uzès, France, year after year.
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How I used n8n to build AI study partners for learning Mandarin: vocabulary, listening, and pronunciation correction.
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Optimizing Data Transfer in Batched AI/ML Inference Workloads
A deep dive on data transfer bottlenecks, their identification, and their resolution with the help of NVIDIA Nsight™ Systems - part 2
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Automatic Prompt Optimization for Multimodal Vision Agents: A Self-Driving Car Example
Walkthrough using open-source prompt optimization algorithms in Python to improve the accuracy of an autonomous vehicle car safety agent running on OpenAI's GPT 5.2
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Federated Learning, Part 1: The Basics of Training Models Where the Data Lives
Understanding the foundations of federated learning
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Beyond the Flat Table: Building an Enterprise-Grade Financial Model in Power BI
A step-by-step journey through data transformation, star schema modeling, and DAX variance analysis with lessons learned along the way.
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Beyond Prompting: The Power of Context Engineering
Using ACE to create self-improving LLM workflows and structured playbooks
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Retrieval for Time-Series: How Looking Back Improves Forecasts
Why Retrieval Helps in Time Series Forecasting We all know how it goes: Time-series data is tricky. Traditional forecasting models are unprepared for incidents like sudden market crashes, black swan events, or rare weather patterns. Even large fancy models like Chronos sometimes struggle because the...
Faster Is Not Always Better: Choosing the Right PostgreSQL Insert Strategy in Python (+Benchmarks)
PostgreSQL is fast. Whether your Python code can or should keep up depends on context. This article compares and benchmarks various insert strategies, focusing not on micro-benchmarks but on trade-offs between safety, abstraction, and throughput — and choosing the right tool for the job.
The post Fa...
I Evaluated Half a Million Credit Records with Federated Learning. Here’s What I Found
Why privacy breaks fairness at small scale—and how collaboration fixes both without sharing a single record
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