AI Tools & Frameworks Directory

Behind a customer's API, a high-quality answer isn't enough. It has to be usable, which means on time. Delivering that consistently is a problem about variance, not speed, and the fixes are counterintuitive. The post Tail Control: The Counterintuitive Engineering of Reliable Agentic Workflows appear...

A concrete bias–variance lesson: why the smallest model had the best cross-validated fit, and how to know when to reach for the big hammer. The post I Pitted XGBoost Against Logistic Regression on 358 Matches. The Boring Model Won. appeared first on Towards Data Science.

A team cut their AI inference bill by more than half. Three months later, customer satisfaction was dropping and the cost savings were tied to the quality loss. Cost-optimization routing layers are a Pareto trap, and here's the detection methodology that catches them in days instead of months. The p...

Using Gemma 4, Ollama, OpenAI Agents SDK, and Tavily MCP to build a lightweight research agent The post From Local LLM to Tool-Using Agent appeared first on Towards Data Science.

Enterprise Document Intelligence [Vol.1 #M1] - The thesis behind every architectural choice in this series The post Amplify the Expert: A Philosophy for Building Enterprise RAG appeared first on Towards Data Science.

I benchmarked raw chat history, vector-only RAG, and a context graph on the same multi-agent conversations. The results exposed a surprising weakness in relational retrieval. The post Vector RAG Isn’t Enough — I Built a Context Graph Layer for Multi-Agent Memory appeared first on Towards Data Scienc...

A reproducible benchmark on latency, cost, and reproducibility, and where agents actually earn their keep. The post The Hot Path Belongs to GBDTs, Agents Own the Cold Path: A Payment-Fraud Benchmark appeared first on Towards Data Science.

Beat the 8GB VRAM limit. Learn how to run three different LLMs on a single 8GB GPU using C++ layer multiplexing and admission control. The post 3 Agents. 3 LLMs. 1 Aging GPU: Engineering Parallel Inference on Bare Metal appeared first on Towards Data Science.

Enterprise Document Intelligence [Vol.1 #7C] - One LLM call ranks the candidates with reasons. The output is one typed object your auditor can defend The post Letting an LLM Pick the Right RAG Page: The Arbiter Pattern at the End of Retrieval appeared first on Towards Data Science.

Activation patching reveals how facts are stored, routed, and read out across transformer layers, and why the residual stream does most of the work The post A Three-Phase Factual Recall Circuit in Gemma-2B and Gemma-12B-IT appeared first on Towards Data Science.

Enterprise Document Intelligence [Vol.1 #7B] - Retrieval is filtering on structured tables: keywords first, TOC second, embeddings last The post Anchor Detection for RAG: Parallel Detectors, Then One LLM Call at the End appeared first on Towards Data Science.

Enterprise Document Intelligence [Vol.1 #7A] - Stop searching strings. Filter line_df and toc_df. Pick anchors small, expand context large The post Retrieval Is Filtering, Not Search: A Mental Model for Enterprise RAG appeared first on Towards Data Science.

From installing Ollama to launching OpenCode with a local model, step by step. The post Build Your Own Local AI Coding Agent with Gemma 4 and OpenCode appeared first on Towards Data Science.

The intuition behind neural networks and why they need activation functions. The post Neural Networks, Explained for Beginners: Start Here If They’ve Confused You appeared first on Towards Data Science.

Understanding ow LLMs interact with the world around them, from returning data to taking action The post Tool Calling, Explained: How AI Agents Decide What to Do Next appeared first on Towards Data Science.

For years, I created date tables with DAX code whenever I didn’t have a way to create them upstream of the data flow. Now I've realised there's another way to do it. Let’s see what the alternatives are and how they compare. The post What Are the Possibilities to Build Date Tables in Self-Service Env...

What data teams need to build with AI to make self-healing data architecture a practical reality The post 7 Crucial Barriers Between Data Teams and Self-Healing Data Architecture appeared first on Towards Data Science.

Why Custom Inference in DeepStream? The post Building a Custom GStreamer Plugin for NVIDIA DeepStream appeared first on Towards Data Science.

Enterprise Document Intelligence [Vol.1 #5quinquies] - Same 1974 scanned PDF, two engines. EasyOCR recovers text. Docling recovers text + sections + figures. The structural gap makes one output usable downstream and the other one a flat string. The post Parse Scanned PDFs for RAG with EasyOCR: Free ...

The PCIe transfer latency is silently bottlenecking your agentic inference. Here is how building a custom device-resident vector search kernel bypasses the CPU to unlock deterministic microsecond tail latencies. The post GPU-Resident Top-K for Agentic RAG: I Built a CUDA Kernel So My Retrieval Step ...

Getting reliable, readable responses out of your LLM, and knowing which tool to reach for The post Structured Outputs with LLMs: JSON Mode, Function Calling, and When to Use Each appeared first on Towards Data Science.

For decades, the existence of the hydrophobic core, a region in the 3D structure of proteins where hydrophobic amino acids reside together, has been considered a general property in proteins. What we have found now may extend that model. In particular, the rest of amino acids also seem to cluster to...

Enterprise Document Intelligence [Vol.1 #6c] - The decisions the parser makes on top of the user string, using the document’s profile: dispatch, activations, full schema, three approaches to deciding what fires, the audit _meta block, and a broker-corpus walkthrough The post Dispatching the Parsed R...

A hands-on guide to setting up image similarity search in Milvus, and why visual replication isn't always enough. The post The Power and Pitfalls of Vector-Based Image Search appeared first on Towards Data Science.