The Next AI Bottleneck Isn’t the Model: It’s the Inference System
Enterprise AI systems are entering a phase where inference design matters as much as model capability itself.
The post The Next AI Bottleneck Isn’t the Model: It’s the Inference System appeared first on Towards Data Science.
The Counterintuitive Networking Decisions Behind OpenAI’s 131,000-GPU Training Fabric
A critical analysis of MRC's three counterintuitive design decisions, the networking mathematics that make them work, and what they mean for the rest of the AI infrastructure community.
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What happened when I migrated a 10K+ line project into an AI-native workflow
The post I Let CodeSpeak Take Over My Repository appeared first on Towards Data Science.
Building an Evaluation Harness for Production AI Agents: A 12-Metric Framework From 100+ Deployments
A 12-metric evaluation framework for production AI agents — covering retrieval, generation, agent behavior, and production health. Drawn from 100+ enterprise deployments.
The post Building an Evaluation Harness for Production AI Agents: A 12-Metric Framework From 100+ Deployments appeared first on T...
A 4.5-hour journey from idea to working fitness app with LLM agents
The post From Vibe Coding to Spec-Driven Development appeared first on Towards Data Science.
Proxy-Pointer Framework for Structure-Aware Enterprise Document Intelligence
Hierarchical understanding and comparison of contracts, research papers, and more
The post Proxy-Pointer Framework for Structure-Aware Enterprise Document Intelligence appeared first on Towards Data Science.
Your First WebAssembly Program and Web App (Written, Tested, and Deployed Entirely in the Web Browser)
Compiling and running C code with Emscripten and GitHub Codespaces — no local installation required.
The post Your First WebAssembly Program and Web App (Written, Tested, and Deployed Entirely in the Web Browser) appeared first on Towards Data Science.
Learning Word Vectors for Sentiment Analysis: A Python Reproduction
How to build sentiment-aware word representations from IMDb reviews using semantic learning, star ratings, and linear SVM classification
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A step-by-step guide to understanding distributed data, lazy logic, and your first DataFrame.
The post PySpark for Beginners: Mastering the Basics appeared first on Towards Data Science.
A practitioner's argument that meeting summarizers fail in the same way regressions fail when you skip the part where you ask what the data can support.
The post LLM Summarizers Skip the Identification Step appeared first on Towards Data Science.
From tokenisation to evaluation : how modern language models actually work in practice
The post The Must-Know Topics for an LLM Engineer appeared first on Towards Data Science.
RAG Is Blind to Time — I Built a Temporal Layer to Fix It in Production
Three weeks into testing, a learner told me my AI tutor gave her the wrong answer.
Not obviously wrong — just outdated enough to mislead.
That was the moment I realized something most RAG systems quietly ignore: they have no sense of time. My system retrieved the most similar document, not the most ...
The AI Agent Security Surface: What Gets Exposed When You Add Tools and Memory
Standard prompt attacks are merely the beginning. A structured framework to map and mitigate the backend attack vectors of agentic workflows.
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When Customers Churn at Renewal: Was It the Price or the Project?
A practitioner's guide to causal attribution when two churn drivers arrive at once.
The post When Customers Churn at Renewal: Was It the Price or the Project? appeared first on Towards Data Science.
Unified Agentic Memory Across Harnesses Using Hooks
How hook implementation gives Claude Code, Codex, and Cursor persistent memory via Neo4j, without locking you into any one of them.
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How Major Reasoning Models Converge to the Same “Brain” as They Model Reality Increasingly Better
Because there's only one reality to model!
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I Rewrote a Real Data Workflow in Polars. Pandas Didn’t Stand a Chance.
From 61 seconds to 0.20 seconds — and the mental model shift I didn't expect
The post I Rewrote a Real Data Workflow in Polars. Pandas Didn’t Stand a Chance. appeared first on Towards Data Science.
When the Uncertainty Is Bigger Than the Shock: Scenario Modelling for English Local Elections
A scenario analysis case study on calibrated uncertainty, historical error, and why some models are most useful when they refuse to forecast.
The post When the Uncertainty Is Bigger Than the Shock: Scenario Modelling for English Local Elections appeared first on Towards Data Science.
Timer-XL: A Long-Context Foundation Model for Time-Series Forecasting
Exploring the inner workings of a decoder-only Transformer foundation model
The post Timer-XL: A Long-Context Foundation Model for Time-Series Forecasting appeared first on Towards Data Science.
Discrete Time-To-Event Modeling – Predicting When Something Will Happen
Part 1: The basics — discretization of time, censoring and the life table
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