Run local AI models like gpt-oss, Llama, Gemma, Qwen, and DeepSeek privately on your computer.

Note: This is a personal essay by Matt Ranger, Kagi’s head of ML In 1986, Harry Frankfurt wrote On Bullshit ( https://en.wikipedia.org/wiki/On_Bullshit ).

via: https://news.ycombinator.com/item?id=46357194

What can you build with one HTML file and an LLM? A lot more than you think. This post shows hard-won patterns from 150+ real tools, showing how to skip frameworks, exploit browser primitives, and build projects fast with copy/pasteable code.

A four-step engineering process for software teams that don’t write code

NornicDB is a high-performance graph database designed for AI agents and knowledge systems. It speaks Neo4j’s language (Bolt protocol Cypher) so you can switch with zero code changes, while adding intelligent features including GPU accelerated embedding search, k-means, and auto TLP with optional LLM inference, plus plugins. - orneryd/NornicDB

Open-source platform to build and deploy AI agent workflows. - simstudioai/sim

Design agent workflows visually on a canvas—connect agents, tools, and blocks, then run them instantly.

A tool to snap pixels to a perfect grid. Designed to fix messy and inconsistent pixel art generated by AI. - Hugo-Dz/spritefusion-pixel-snapper

CLAUDE.md is a high-leverage configuration point for Claude Code.

Learning how to write a good CLAUDE.md (or AGENTS.md) is a key skill for agent-enabled software engineering.

An LLM will perform better on a task when its’ context window is full of focused, relevant context

a system that monitors ~200,000 news RSS feeds in near real-time and clusters related articles to show how stories spread across the web. It uses Snowflake’s Arctic model for embeddings and HNSW for fast similarity search. Each “story cluster” shows who published first, how fast it propagated, and how the narrative evolved as more outlets picked it up.

a system that monitors ~200,000 news RSS feeds in near real-time and clusters related articles to show how stories spread across the web. It uses Snowflake’s Arctic model for embeddings and HNSW for fast similarity search. Each “story cluster” shows who published first, how fast it propagated, and how the narrative evolved as more outlets picked it up.

Course to get into Large Language Models (LLMs) with roadmaps and Colab notebooks.

mlabonne.github.io/blog/

Artificial intelligence is a fast-moving field. I created Ahead of AI to help you keep up with the latest developments and research trends in the fields of machine learning, deep learning, and artificial intelligence.

Verbalized Sampling, a training-free prompting strategy to mitigate mode collapse in LLMs by requesting responses with probabilities. Achieves 2-3x diversity improvement while maintaining quality. Model-agnostic framework with CLI/API for creative writing, synthetic data generation, and dialogue simulation. - CHATS-lab/verbalized-sampling

Open-Source Memory Engine for LLMs, AI Agents

What is Memori Memori enables any LLM to remember conversations, learn from interactions, and maintain context across sessions with a single line: memori.enable(). Memory is stored in standard SQL databases (SQLite, PostgreSQL, MySQL) that you fully own and control.

Why Memori?

One-line integration - Works with OpenAI, Anthropic, LiteLLM, LangChain, and any LLM framework SQL-native storage - Portable, queryable, and auditable memory in databases you control 80-90% cost savings - No expensive vector databases required Zero vendor lock-in - Export your memory as SQLite and move anywhere Intelligent memory - Automatic entity extraction, relationship mapping, and context prioritization

Fara-7B is Microsoft’s first agentic small language model (SLM) designed specifically for computer use.

With only 7 billion parameters, Fara-7B is an ultra-compact Computer Use Agent (CUA) that achieves state-of-the-art performance within its size class and is competitive with larger, more resource-intensive agentic systems.

AI-Powered Data Processing: Use LOTUS to process all of your datasets with LLMs and embeddings. Enjoy up to 1000x speedups with fast, accurate query processing, that’s as simple as writing Pandas code - lotus-data/lotus

LOTUS is an open-source query engine that makes programming as easy as writing Pandas and optimizes your programs for up to 400x speedups.

Research assistant powered by Lotus.

DeepScholar, an openly-accessible DeepResearch system from Berkeley & Stanford.

DeepScholar efficiently processes 100s of articles, demonstrating strong long-form research synthesis capabilities, competitive with OpenAI’s DR, while running up to 2x faster!

Fast, stateless LLM for your shell: qq answers; qa runs commands - iagooar/qqqa