Python can run Mojo now

The post explores how Python can now call Mojo code, offering a promising way to speed up Python functions with a simple compiled language. While still early and showing some rough edges like overflow issues, Mojo demonstrates significant performance gains in examples like prime counting, making it an exciting tool for Python developers seeking faster execution.

https://koaning.io/posts/giving-mojo-a-spin/

dnsimg - storing images in txt records

The author experiments with storing images in DNS TXT records by converting image data to hex, splitting it into 2048-character chunks, and creating a protocol-like method for retrieval and reconstruction. The process demonstrates both the feasibility and practical limitations of this approach, including DNS record size constraints and the need for custom scripts to upload, fetch, and re...

https://asherfalcon.com/blog/posts/2

miniDiffusion

A reimplementation of Stable Diffusion 3.5 in pure PyTorch.

https://github.com/yousef-rafat/miniDiffusion

MiniMax-AI

The world's first open-weight, large-scale hybrid-attention reasoning model.

https://github.com/MiniMax-AI/MiniMax-M1

This Secret Math Equation let the US Government Spy on Anyone

The article provides a hands-on coding guide to the Dual EC DRBG cryptographic backdoor, showing how the NSA-designed algorithm allowed attackers with secret knowledge to predict random outputs and decrypt secure communications. It explains the math behind the backdoor, demonstrates its practical exploitation in Python, and highlights the real-world risks of insecure random number genera...

https://leetarxiv.substack.com/p/dual-ec-backdoor-coding-guide

coleam00 / local-ai-packaged

Run all your local AI together in one package - Ollama, Supabase, n8n, Open WebUI, and more!

https://github.com/coleam00/local-ai-packaged

Understanding and Coding the KV Cache in LLMs from Scratch

The article explains how KV (Key-Value) caching in large language models (LLMs) speeds up text generation by storing and reusing intermediate computations, significantly improving inference efficiency. It provides a step-by-step, from-scratch code implementation of a KV cache, highlighting both its computational benefits and increased memory requirements during production use.

https://magazine.sebastianraschka.com/p/coding-the-kv-cache-in-llms

llm-memorization

Give your local LLM a real memory with a lightweight, fully local memory system — just like a human recalling past discussions. 100% offline. 100% under your control.

https://github.com/victorcarre6/llm-memorization

MCP Explained: How to Expose Your API to AI Models

The video explains how to use the Model Context Protocol (MCP) to connect your APIs and external tools with AI language models like ChatGPT or Claude, enabling them to interact with real-world data and services. It covers two main architectural patterns for MCP integration, provides practical Python code examples, and offers tips for building scalable, maintainable MCP servers for AI app...

https://www.youtube.com/watch?v=r0QIuI1wpes

Complete Guide to Build and Deploy an AI Agent with Docker Containers and Python

The video is a comprehensive tutorial on building and deploying an AI agent using Python and Docker containers, covering everything from Docker fundamentals to integrating FastAPI, Postgres, LangChain, and LangGraph for multi-agent systems. It walks viewers through local development, containerization, and deployment to platforms like Railway and DigitalOcean, enabling scalable, productio...

https://www.youtube.com/watch?v=KC8HT0eWSGk

Pixeltable

AI Data infrastructure providing a declarative, incremental approach for multimodal workloads.

https://github.com/pixeltable/pixeltable

zen-mcp-server

The power of Claude Code + Gemini Pro / Flash / O3 / Grok / OpenRouter / Ollama / Custom Model / All Of The Above working as one.

https://github.com/BeehiveInnovations/zen-mcp-server

sourcerer

Sourcerer is a CLI-based cloud storage explorer that provides a unified interface for developers and DevOps engineers to view and manage files across multiple cloud providers like GCP Storage, Azure Storage, AWS S3, and S3-compatible services.

https://github.com/the-impact-craft/sourcerer

openai-agents-python

A lightweight, powerful framework for multi-agent workflows.

https://github.com/openai/openai-agents-python

Avoiding PostgreSQL Pitfalls: The Hidden Cost of Failing Inserts

This article discusses how failing inserts in PostgreSQL, particularly due to unique constraint violations in a Django application, can cause significant performance issues and database overhead. It recommends using ON CONFLICT DO NOTHING in PostgreSQL or Django's bulkcreate with ignoreconflicts=True to prevent these problems.

https://johnnymetz.com/posts/postgresql-failing-insert/

Beyond htmx: building modern Django apps with Alpine AJAX

The article demonstrates how to use Alpine.js and AJAX with Django to create interactive, client-side web applications that efficiently handle dynamic data updates without full page reloads. It provides practical examples and code snippets for integrating Alpine.js with Django views, serializers, and templates to enhance user experience through seamless frontend-backend communication.

https://www.loopwerk.io/articles/2025/alpine-ajax-django