corpus.blog
41554 blogs · [ { "id": "01a0df45-4dda-71df-a2d3-fcd020941f67", "title": "AI Slop Is Already in Your Training Dataset. I Tested Three Ways to Spot It.", "url": "https://towardsdatascience.com/ai-slop-is-now-in-your-training-dataset-i-tested-three-ways-to-spot-it/", "published_at": "2026-09-26T15:00:02+00:00" }, { "id": "01a0df45-4dda-71df-a2d3-fcd021119207", "title": "Your LLM Has a Curved Space of Paragraphs", "url": "https://towardsdatascience.com/your-llm-has-a-curved-space-of-paragraphs/", "published_at": "2026-09-26T12:00:01+00:00" }, { "id": "01a0df45-4dda-71df-a2d3-fcd021c24542", "title": "10 Things I’m Learning Beyond AI to Become More Technologically Fluent", "url": "https://towardsdatascience.com/10-things-im-learning-beyond-ai-to-become-more-technologically-fluent/", "published_at": "2026-09-25T15:30:01+00:00" }, { "id": "01a0df45-4dda-71df-a2d3-fcd022b14af3", "title": "Your Model's MSE Is Lying to You: Part II", "url": "https://towardsdatascience.com/your-models-mse-is-lying-to-you-part-ii/", "published_at": "2026-09-25T14:00:02+00:00" }, { "id": "01a0df45-4dda-71df-a2d3-fcd02392adcc", "title": "RAG Isn't an Agent — I Built the Layer Between Retrieval and Action", "url": "https://towardsdatascience.com/rag-isnt-an-agent-i-built-the-layer-between-retrieval-and-action/", "published_at": "2026-09-25T12:30:01+00:00" }, { "id": "01a0df45-4dda-71df-a2d3-fcd023d87bf7", "title": "Jev vs. LLMs: When AI Moves from Generation to Decision-Making", "url": "https://towardsdatascience.com/jev-vs-llms-when-ai-moves-from-generation-to-decision-making/", "published_at": "2026-09-25T11:00:01+00:00" }, { "id": "01a0d483-a22f-7142-8471-a7a8a7e4d191", "title": "How to Maximize Your Coding Agent Subscriptions", "url": "https://towardsdatascience.com/how-to-maximize-your-coding-agent-subscriptions/", "published_at": "2026-09-24T15:30:01+00:00" }, { "id": "01a0d483-a22f-7142-8471-a7a8a85b20be", "title": "Beyond RAGs: Building Actually Truthful AI Harnesses", "url": "https://towardsdatascience.com/beyond-rags-building-actually-truthful-ai-harnesses/", "published_at": "2026-09-24T14:00:01+00:00" }, { "id": "01a0d483-a22f-7142-8471-a7a8a8a4b234", "title": "Towards Spec-Driven Test Automation: Part 1", "url": "https://towardsdatascience.com/towards-spec-driven-test-automation-part-1/", "published_at": "2026-09-24T12:30:02+00:00" }, { "id": "01a0d483-a22f-7142-8471-a7a8a9860b50", "title": "When the Correct Answer Is Nothing, What Does Your Pipeline Return?", "url": "https://towardsdatascience.com/when-the-correct-answer-is-nothing-what-does-your-pipeline-return/", "published_at": "2026-09-24T11:00:01+00:00" }, { "id": "01a0d483-a22f-7142-8471-a7a8aa3de672", "title": "I Trained a Tiny Network to Compress Data. It Drew a Pentagon.", "url": "https://towardsdatascience.com/i-trained-a-tiny-network-to-compress-data-it-drew-a-pentagon/", "published_at": "2026-09-23T15:30:01+00:00" }, { "id": "01a0d483-a22f-7142-8471-a7a8aad2c1f8", "title": "From Words to Vectors: What Happens in Between?", "url": "https://towardsdatascience.com/from-words-to-vectors-what-happens-in-between/", "published_at": "2026-09-23T14:00:01+00:00" }, { "id": "01a0d483-a22f-7142-8471-a7a8ab8cee28", "title": "How GRPO Trains Small Language Models with Verifiable Rewards", "url": "https://towardsdatascience.com/how-grpo-trains-small-language-models-with-verifiable-rewards/", "published_at": "2026-09-23T12:30:01+00:00" }, { "id": "01a0d483-a22f-7142-8471-a7a8ac19c4d4", "title": "How to Make Your First World Model from Scratch", "url": "https://towardsdatascience.com/how-to-make-your-first-world-model-from-scratch/", "published_at": "2026-09-23T11:00:02+00:00" }, { "id": "01a0d483-a22f-7142-8471-a7a8ac3fb2da", "title": "Break Your Own RAG Pipeline Before Users Do", "url": "https://towardsdatascience.com/break-your-own-rag-pipeline-before-users-do/", "published_at": "2026-09-22T15:30:01+00:00" }, { "id": "01a0d483-a22f-7142-8471-a7a8ac79a1fc", "title": "Build a Speaker-Recognition App with Claude Code", "url": "https://towardsdatascience.com/build-a-speaker-recognition-app-with-claude-code/", "published_at": "2026-09-22T14:00:02+00:00" }, { "id": "01a0d483-a22f-7142-8471-a7a8ac888a75", "title": "4 Ways to Use AI on a PhD Thesis", "url": "https://towardsdatascience.com/4-ways-to-use-ai-on-a-phd-thesis/", "published_at": "2026-09-22T12:30:01+00:00" }, { "id": "01a0d483-a22f-7142-8471-a7a8ad52b316", "title": "An Introduction to Jev", "url": "https://towardsdatascience.com/an-introduction-to-jev/", "published_at": "2026-09-22T11:00:01+00:00" }, { "id": "01a0d483-a22f-7142-8471-a7a8addfb18d", "title": "A New Kind of Model for AI Decision-Making?", "url": "https://towardsdatascience.com/a-new-kind-of-model-for-ai-decision-making/", "published_at": "2026-09-21T15:30:02+00:00" }, { "id": "01a0d483-a22f-7142-8471-a7a8ae885b24", "title": "GPT-6 Astra Just Hit OpenAI's Highest Cybersecurity Risk Level", "url": "https://towardsdatascience.com/gpt-6-astra-just-hit-openais-highest-cybersecurity-risk-level/", "published_at": "2026-09-21T14:00:01+00:00" }, { "id": "01a0d483-a22f-7142-8471-a7a8af4c030e", "title": "Google Offered $10M for a Dying Airline's Data. How Can You Value Yours?", "url": "https://towardsdatascience.com/google-offered-10m-for-a-dying-airlines-data-how-can-you-value-yours/", "published_at": "2026-09-21T12:30:02+00:00" }, { "id": "01a0d483-a22f-7142-8471-a7a8afc948a9", "title": "Your AI Assistant Wrote the Code. Who Checked the Defaults?", "url": "https://towardsdatascience.com/your-ai-assistant-wrote-the-code-who-checked-the-defaults/", "published_at": "2026-09-21T11:00:02+00:00" }, { "id": "01a0d483-a22f-7142-8471-a7a8b0b2386e", "title": "GraphRAG: A Practitioner's Guide to 6 Advanced Architectural Patterns", "url": "https://towardsdatascience.com/graphrag-a-practitioners-guide-to-6-advanced-architectural-patterns/", "published_at": "2026-09-20T15:00:01+00:00" }, { "id": "01a0d483-a22f-7142-8471-a7a8b1129188", "title": "CBAM Paper Walkthrough: The Double-Attention Mechanism", "url": "https://towardsdatascience.com/cbam-paper-walkthrough-the-double-attention-mechanism/", "published_at": "2026-09-20T13:00:01+00:00" }, { "id": "01a0d483-a22f-7142-8471-a7a8b1ef8eb8", "title": "One Vendor, Four Spellings: How Deterministic Stages Beat Similarity Scores", "url": "https://towardsdatascience.com/one-vendor-four-spellings-how-deterministic-stages-beat-similarity-scores/", "published_at": "2026-09-19T15:00:01+00:00" }, { "id": "01a0d483-a22f-7142-8471-a7a8b2bb7bf5", "title": "AI Made Me 5x Faster. It Also Made Me 5x Worse at My Job.", "url": "https://towardsdatascience.com/ai-made-me-5x-faster-it-also-made-me-5x-worse-at-my-job/", "published_at": "2026-09-19T13:00:01+00:00" }, { "id": "01a095f1-33bf-726e-af24-c2ae0ac69eff", "title": "One Capital Letter Was Silently Breaking My AI Support Bot, and It Wasn't in the New Model", "url": "https://towardsdatascience.com/one-capital-letter-was-silently-breaking-my-ai-support-bot-and-it-wasnt-in-the-new-model/", "published_at": "2026-09-12T14:00:02+00:00" }, { "id": "01a09556-22ef-715e-b7bf-704b11064ef2", "title": "Stop Managing Alarms: An Incident-First Blueprint for Telecom AIOps", "url": "https://towardsdatascience.com/stop-managing-alarms-an-incident-first-blueprint-for-telecom-aiops/", "published_at": "2026-09-12T11:00:02+00:00" }, { "id": "01a094b0-7de4-72df-8db4-619d5b2b7d5f", "title": "Coding Agents Don't Need Longer History — They Need Intent Continuity", "url": "https://towardsdatascience.com/coding-agents-dont-need-longer-history-they-need-intent-continuity/", "published_at": "2026-09-11T15:30:01+00:00" }, { "id": "01a094b0-7de4-72df-8db4-619d5bcf136c", "title": "Software Design in the Age of AI", "url": "https://towardsdatascience.com/software-design-in-the-age-of-ai/", "published_at": "2026-09-11T14:00:02+00:00" }, { "id": "01a094b0-7de4-72df-8db4-619d5bf9ee41", "title": "The 95% Illusion: Why Your Confidence Interval Isn't What You Think It Is", "url": "https://towardsdatascience.com/the-95-illusion-why-your-confidence-interval-isnt-what-you-think-it-is/", "published_at": "2026-09-11T12:30:02+00:00" }, { "id": "01a094b0-7de4-72df-8db4-619d5c3248b9", "title": "Demystifying Anthropic's J-Space: A Mathematical Primer", "url": "https://towardsdatascience.com/demystifying-anthropics-j-space-a-mathematical-primer/", "published_at": "2026-09-11T11:00:02+00:00" }, { "id": "01a08c58-019b-73f1-b5be-3f5d38fa591d", "title": "How to 5x Your Communication Effectiveness with Claude Code", "url": "https://towardsdatascience.com/how-to-5x-your-communication-effectiveness-with-claude-code/", "published_at": "2026-09-10T15:30:01+00:00" }, { "id": "01a08c58-019b-73f1-b5be-3f5d39ddf220", "title": "What SHAP Can't Explain About Agentic AI Fraud", "url": "https://towardsdatascience.com/what-shap-cant-explain-about-agentic-ai-fraud/", "published_at": "2026-09-10T14:00:01+00:00" }, { "id": "01a08c58-019b-73f1-b5be-3f5d3a8df501", "title": "Optimizing LLM Inference Costs in Multi-Agent Systems with Adaptive Model Routing", "url": "https://towardsdatascience.com/optimizing-llm-inference-costs-in-multi-agent-systems-with-adaptive-model-routing/", "published_at": "2026-09-10T12:30:01+00:00" }, { "id": "01a08c58-019b-73f1-b5be-3f5d3b4885be", "title": "Who Questions What Works: When Should We Retest Our Assumptions?", "url": "https://towardsdatascience.com/who-questions-what-works-when-should-we-retest-our-assumptions/", "published_at": "2026-09-10T11:00:01+00:00" }, { "id": "01a08c58-019b-73f1-b5be-3f5d3bcf0811", "title": "Getting started with dbt", "url": "https://towardsdatascience.com/getting-started-with-dbt/", "published_at": "2026-09-09T15:30:01+00:00" }, { "id": "01a08c58-019b-73f1-b5be-3f5d3c70111d", "title": "The Symmetry That Breaks Neural Network Averaging", "url": "https://towardsdatascience.com/the-symmetry-that-breaks-neural-network-averaging/", "published_at": "2026-09-09T14:00:02+00:00" }, { "id": "01a08c58-019b-73f1-b5be-3f5d3c752ea6", "title": "When One Process Becomes Too Much: Splitting a Pipeline into MCP Services", "url": "https://towardsdatascience.com/when-one-process-becomes-too-much-splitting-a-pipeline-into-mcp-services/", "published_at": "2026-09-09T12:30:02+00:00" }, { "id": "01a08c58-019b-73f1-b5be-3f5d3c791a26", "title": "10 Statistical Traps We Often Overlook", "url": "https://towardsdatascience.com/10-statistical-traps-we-often-overlook/", "published_at": "2026-09-09T11:00:02+00:00" }, { "id": "01a0823c-ddcd-71c3-9cc4-1963193e2688", "title": "How to Maximize GPT-6 Astra", "url": "https://towardsdatascience.com/how-to-maximize-gpt-6-astra/", "published_at": "2026-09-08T18:00:35+00:00" }, { "id": "01a08219-daca-703a-a7d4-eadf61e65ed5", "title": "The Model Validation Playbook for GenAI: Lessons from Banking", "url": "https://towardsdatascience.com/the-model-validation-playbook-for-genai-lessons-from-banking/", "published_at": "2026-09-08T17:34:37+00:00" }, { "id": "01a08219-daca-703a-a7d4-eadf6264de9f", "title": "A Beginner’s Guide to World Models", "url": "https://towardsdatascience.com/a-beginners-guide-to-world-models/", "published_at": "2026-09-08T17:27:42+00:00" }, { "id": "01a08219-daca-703a-a7d4-eadf62a1179b", "title": "Introducing ShipAI", "url": "https://towardsdatascience.com/introducing-shipai/", "published_at": "2026-09-08T13:41:29+00:00" }, { "id": "01a08219-daca-703a-a7d4-eadf637f2aa2", "title": "Context Windows Don’t Know What’s Still True — I Built a Validity Layer That Does", "url": "https://towardsdatascience.com/context-windows-dont-know-whats-still-true-i-built-a-validity-layer-that-does/", "published_at": "2026-09-08T11:00:01+00:00" }, { "id": "01a08219-daca-703a-a7d4-eadf63952149", "title": "I Vibe-Coded an App in Just Two Hours (And Regretted It the Next Day)", "url": "https://towardsdatascience.com/i-vibe-coded-an-app-in-just-two-hours-and-regretted-it-the-next-day/", "published_at": "2026-09-07T14:00:01+00:00" }, { "id": "01a08219-daca-703a-a7d4-eadf645094fc", "title": "Why Most Multi-Agent Systems Fail Even When Evaluation Passes", "url": "https://towardsdatascience.com/why-most-multi-agent-systems-fail-even-when-evaluation-passes/", "published_at": "2026-09-07T12:00:01+00:00" }, { "id": "01a08219-daca-703a-a7d4-eadf64c21389", "title": "Text Watermarking in Python: Catch Whoever Copies Your Writing", "url": "https://towardsdatascience.com/text-watermarking-in-python-catch-whoever-copies-your-writing/", "published_at": "2026-09-06T14:00:01+00:00" }, { "id": "01a08219-daca-703a-a7d4-eadf64dcc40b", "title": "Linear Discriminant Analysis (LDA) in Real-Life: Dimensionality Reduction in a Real-Estate Dataset", "url": "https://towardsdatascience.com/linear-discriminant-analysis-lda-in-real-life-dimensionality-reduction-in-a-real-estate-dataset/", "published_at": "2026-09-06T12:00:02+00:00" }, { "id": "01a08219-daca-703a-a7d4-eadf6568f562", "title": "Why Transformers Need Positional Encoding For Time Series: A Visual Guide", "url": "https://towardsdatascience.com/why-transformers-need-positional-encoding-for-time-series-a-visual-guide/", "published_at": "2026-09-05T15:00:01+00:00" }, { "id": "01a08219-daca-703a-a7d4-eadf6606a430", "title": "Dynamical System Transfer Learning with Reduced Order Models", "url": "https://towardsdatascience.com/dynamical-system-transfer-learning-with-reduced-order-models/", "published_at": "2026-09-05T13:00:01+00:00" }, { "id": "01a08219-daca-703a-a7d4-eadf6639309e", "title": "Optimal Traffic Allocation Under Heterogeneous Variant Cost", "url": "https://towardsdatascience.com/optimal-traffic-allocation-under-heterogeneous-variant-cost/", "published_at": "2026-09-04T15:30:02+00:00" }, { "id": "01a08219-daca-703a-a7d4-eadf66bb2603", "title": "Disaggregation Is a Thousand-GPU Problem", "url": "https://towardsdatascience.com/disaggregation-is-a-thousand-gpu-problem/", "published_at": "2026-09-04T14:00:02+00:00" }, { "id": "01a08219-daca-703a-a7d4-eadf66ee4e4f", "title": "The Power BI Developer's Survival Guide to Microsoft Fabric", "url": "https://towardsdatascience.com/the-power-bi-developers-survival-guide-to-microsoft-fabric/", "published_at": "2026-09-04T12:30:02+00:00" }, { "id": "01a08219-daca-703a-a7d4-eadf67206ea5", "title": "How to Run 10+ Claude Code Sessions Without a Powerful Computer", "url": "https://towardsdatascience.com/how-to-run-10-claude-code-sessions-without-a-powerful-computer/", "published_at": "2026-09-04T11:00:02+00:00" }, { "id": "01a08219-daca-703a-a7d4-eadf67e36d8b", "title": "My Model Worked Perfectly. Then I Tried to Make It Useful.", "url": "https://towardsdatascience.com/my-model-worked-perfectly-then-i-tried-to-make-it-useful/", "published_at": "2026-09-03T15:30:01+00:00" }, { "id": "01a08219-daca-703a-a7d4-eadf684fcae7", "title": "Tables in PDFs for RAG: Don’t Flatten the Grid", "url": "https://towardsdatascience.com/tables-in-pdfs-for-rag-dont-flatten-the-grid/", "published_at": "2026-09-03T14:00:01+00:00" }, { "id": "01a08219-daca-703a-a7d4-eadf689f54e5", "title": "Changing One Prompt Can Affect 50 Others — I Built a Prompt Dependency Graph to Find What Needs Retesting", "url": "https://towardsdatascience.com/changing-one-prompt-can-affect-50-others-i-built-a-prompt-dependency-graph-to-find-what-needs-retesting/", "published_at": "2026-09-03T12:30:01+00:00" }, { "id": "01a08219-daca-703a-a7d4-eadf695f7b95", "title": "How to Solve the Right Problem in the Age of Agentic AI", "url": "https://towardsdatascience.com/how-to-solve-the-right-problem-in-the-age-of-agentic-ai/", "published_at": "2026-09-03T11:00:01+00:00" }, { "id": "01a08219-daca-703a-a7d4-eadf6a5ee7f4", "title": "Avoiding Entity Key Drift in a Data Lake: Step 2, When Fuzzy Matching Stops Working", "url": "https://towardsdatascience.com/avoiding-entity-key-drift-in-a-data-lake-step-2-when-fuzzy-matching-stops-working/", "published_at": "2026-09-02T15:30:02+00:00" }, { "id": "01a08219-daca-703a-a7d4-eadf6af3e847", "title": "A RAG That Says “Not in This Document” Has to Show Four Kinds of Evidence", "url": "https://towardsdatascience.com/a-rag-that-says-not-in-this-document-has-to-show-four-kinds-of-evidence/", "published_at": "2026-09-02T14:00:02+00:00" }, { "id": "01a087ac-de76-724b-9fc5-476f76b9d75d", "title": "Linklog | When Data Lies: Finding Optimal Strategies for Penalty Kicks with Game Theory", "url": "https://towardsdatascience.com/when-data-lies-finding-optimal-strategies-for-penalty-kicks-with-game-theory/", "published_at": "2026-03-11T12:00:00+00:00" }, { "id": "01a087ac-dccd-7076-9336-9f1c7113b8f3", "title": "Linklog | A Visual Guide to How Diffusion Models Work", "url": "https://towardsdatascience.com/a-visual-guide-to-how-diffusion-models-work/", "published_at": "2025-02-06T12:00:00+00:00" }, { "id": "01a0823a-ed4d-73ae-b535-6a0004e4ac62", "title": "Anecdotes from 11 Role Models in Machine Learning", "url": "https://towardsdatascience.com/anecdotes-from-11-role-models-in-machine-learning-d01bc0d65dcd", "published_at": "2021-09-21T00:00:00+00:00" }, { "id": "01a0d4e4-45a0-70ae-99a5-93adad7718b0", "title": "GPT-J, an open-source 6 billion parameter NLP AI model", "url": "https://towardsdatascience.com/cant-access-gpt-3-here-s-gpt-j-its-open-source-cousin-8af86a638b11", "published_at": "2021-08-06T19:11:22+00:00" }, { "id": "01a0d4eb-fba8-72f2-9452-08ab4262830e", "title": "Merzmensch’s roundup of Google Colab notebooks", "url": "https://towardsdatascience.com/12-colab-notebooks-that-matter-e14ce1e3bdd0", "published_at": "2020-03-09T17:56:24+00:00" } ] posts Claim your blog
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2026

AI Slop Is Already in Your Training Dataset. I Tested Three Ways to Spot It.original ↗
26 Sept 2026
Your LLM Has a Curved Space of Paragraphsoriginal ↗
26 Sept 2026
10 Things I’m Learning Beyond AI to Become More Technologically Fluentoriginal ↗
25 Sept 2026
Your Model's MSE Is Lying to You: Part IIoriginal ↗
25 Sept 2026
RAG Isn't an Agent — I Built the Layer Between Retrieval and Actionoriginal ↗
25 Sept 2026
Jev vs. LLMs: When AI Moves from Generation to Decision-Makingoriginal ↗
25 Sept 2026
How to Maximize Your Coding Agent Subscriptionsoriginal ↗
24 Sept 2026
Beyond RAGs: Building Actually Truthful AI Harnessesoriginal ↗
24 Sept 2026
Towards Spec-Driven Test Automation: Part 1original ↗
24 Sept 2026
When the Correct Answer Is Nothing, What Does Your Pipeline Return?original ↗
24 Sept 2026
I Trained a Tiny Network to Compress Data. It Drew a Pentagon.original ↗
23 Sept 2026
From Words to Vectors: What Happens in Between?original ↗
23 Sept 2026
How GRPO Trains Small Language Models with Verifiable Rewardsoriginal ↗
23 Sept 2026
How to Make Your First World Model from Scratchoriginal ↗
23 Sept 2026
Break Your Own RAG Pipeline Before Users Dooriginal ↗
22 Sept 2026
Build a Speaker-Recognition App with Claude Codeoriginal ↗
22 Sept 2026
4 Ways to Use AI on a PhD Thesisoriginal ↗
22 Sept 2026
An Introduction to Jevoriginal ↗
22 Sept 2026
A New Kind of Model for AI Decision-Making?original ↗
21 Sept 2026
GPT-6 Astra Just Hit OpenAI's Highest Cybersecurity Risk Leveloriginal ↗
21 Sept 2026
Google Offered $10M for a Dying Airline's Data. How Can You Value Yours?original ↗
21 Sept 2026
Your AI Assistant Wrote the Code. Who Checked the Defaults?original ↗
21 Sept 2026
GraphRAG: A Practitioner's Guide to 6 Advanced Architectural Patternsoriginal ↗
20 Sept 2026
CBAM Paper Walkthrough: The Double-Attention Mechanismoriginal ↗
20 Sept 2026
One Vendor, Four Spellings: How Deterministic Stages Beat Similarity Scoresoriginal ↗
19 Sept 2026
AI Made Me 5x Faster. It Also Made Me 5x Worse at My Job.original ↗
19 Sept 2026
One Capital Letter Was Silently Breaking My AI Support Bot, and It Wasn't in the New Modeloriginal ↗
12 Sept 2026
Stop Managing Alarms: An Incident-First Blueprint for Telecom AIOpsoriginal ↗
12 Sept 2026
Coding Agents Don't Need Longer History — They Need Intent Continuityoriginal ↗
11 Sept 2026
Software Design in the Age of AIoriginal ↗
11 Sept 2026
The 95% Illusion: Why Your Confidence Interval Isn't What You Think It Isoriginal ↗
11 Sept 2026
Demystifying Anthropic's J-Space: A Mathematical Primeroriginal ↗
11 Sept 2026
How to 5x Your Communication Effectiveness with Claude Codeoriginal ↗
10 Sept 2026
What SHAP Can't Explain About Agentic AI Fraudoriginal ↗
10 Sept 2026
Optimizing LLM Inference Costs in Multi-Agent Systems with Adaptive Model Routingoriginal ↗
10 Sept 2026
Who Questions What Works: When Should We Retest Our Assumptions?original ↗
10 Sept 2026
Getting started with dbtoriginal ↗
9 Sept 2026
The Symmetry That Breaks Neural Network Averagingoriginal ↗
9 Sept 2026
When One Process Becomes Too Much: Splitting a Pipeline into MCP Servicesoriginal ↗
9 Sept 2026
10 Statistical Traps We Often Overlookoriginal ↗
9 Sept 2026
How to Maximize GPT-6 Astraoriginal ↗
8 Sept 2026
The Model Validation Playbook for GenAI: Lessons from Bankingoriginal ↗
8 Sept 2026
A Beginner’s Guide to World Modelsoriginal ↗
8 Sept 2026
Introducing ShipAIoriginal ↗
8 Sept 2026
Context Windows Don’t Know What’s Still True — I Built a Validity Layer That Doesoriginal ↗
8 Sept 2026
I Vibe-Coded an App in Just Two Hours (And Regretted It the Next Day)original ↗
7 Sept 2026
Why Most Multi-Agent Systems Fail Even When Evaluation Passesoriginal ↗
7 Sept 2026
Text Watermarking in Python: Catch Whoever Copies Your Writingoriginal ↗
6 Sept 2026
Linear Discriminant Analysis (LDA) in Real-Life: Dimensionality Reduction in a Real-Estate Datasetoriginal ↗
6 Sept 2026
Why Transformers Need Positional Encoding For Time Series: A Visual Guideoriginal ↗
5 Sept 2026
Dynamical System Transfer Learning with Reduced Order Modelsoriginal ↗
5 Sept 2026
Optimal Traffic Allocation Under Heterogeneous Variant Costoriginal ↗
4 Sept 2026
Disaggregation Is a Thousand-GPU Problemoriginal ↗
4 Sept 2026
The Power BI Developer's Survival Guide to Microsoft Fabricoriginal ↗
4 Sept 2026
How to Run 10+ Claude Code Sessions Without a Powerful Computeroriginal ↗
4 Sept 2026
My Model Worked Perfectly. Then I Tried to Make It Useful.original ↗
3 Sept 2026
Tables in PDFs for RAG: Don’t Flatten the Gridoriginal ↗
3 Sept 2026
Changing One Prompt Can Affect 50 Others — I Built a Prompt Dependency Graph to Find What Needs Retestingoriginal ↗
3 Sept 2026
How to Solve the Right Problem in the Age of Agentic AIoriginal ↗
3 Sept 2026
Avoiding Entity Key Drift in a Data Lake: Step 2, When Fuzzy Matching Stops Workingoriginal ↗
2 Sept 2026
A RAG That Says “Not in This Document” Has to Show Four Kinds of Evidenceoriginal ↗
2 Sept 2026
Linklog | When Data Lies: Finding Optimal Strategies for Penalty Kicks with Game Theoryoriginal ↗
11 Mar 2026

2025

Linklog | A Visual Guide to How Diffusion Models Workoriginal ↗
6 Feb 2025

2021

Anecdotes from 11 Role Models in Machine Learningoriginal ↗
21 Sept 2021
GPT-J, an open-source 6 billion parameter NLP AI modeloriginal ↗
6 Aug 2021

2020

Merzmensch’s roundup of Google Colab notebooksoriginal ↗
9 Mar 2020