Build an AI code review pipeline on GitHub Actions with Semgrep, reviewdog and a Python model reviewer. 12 steps, tested code ...

This snapshot packages the Deportation Data Project's processed USCIS FOIA application records for reproducible analysis in Python, R and SQL. It contains 11,206,545 application records, not unique ...

AI agents are convenient, aren't they? But have you ever felt uneasy, wondering if they are actually working correctly, or ...

Nvidia gave us access to its Vera data center CPU for testing against Intel's Granite Rapids-AP and AMD's EPYC Turin.

Speculative decoding is essentially a way to get more out of each pass through a large model by letting the small drafter ...

Mistral AI opened its Responses API in public preview on October 28, giving developers building OpenAI-format agent pipelines ...

This guide explains how to build an "autonomous AI agent" that operates securely in an environment completely isolated from ...

Learn how to get started with the OpenRouter API to call multiple AI models through one API, compare responses, switch models ...

Python libraries that replace hundreds of lines of custom code. LiteLLM, Instructor, Tenacity, and 5 more I use in every ...

Prompt injection test lab: build a 12-step Python harness that scores Claude, GPT, Gemini, Mistral and DeepSeek on 14 OWASP ...

I loaded a large JSON file in Python and watched memory jump from 43 MB to 808 MB. Here’s what happened and how streaming changed everything.

Compromised LiteLLM 1.107.0 packages run a credential stealer at Python startup and can fetch and execute additional code.