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.

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

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.

Run Qwen LLMs locally in your browser with WebGPU. Zero installation, instant AI chat.

An open-source, code-first Go toolkit for building, evaluating, and deploying sophisticated AI agents with flexibility and control. - google/adk-go

“AI-Trader: Can AI Beat the Market?” Live Trading: https://hkuds.github.io/AI-Trader/ - HKUDS/AI-Trader

Five AIs battle for NASDAQ 100 supremacy. Zero human input. Pure competition.

New computer model helps reveal how the brain both adapts and misfires, laying the groundwork for more precise treatments for mental health disorders.

The exact same AI-coded page everyone else makes.

Hyperlink is a local-first AI agent that understands your files privately—PDFs, notes, transcripts, and more. No internet required. Data stays secure, offline, and under your control. A Glean alternative built for personal or regulated use.

Lessons learned from building RAG systems for Usul AI and enterprise clients, processing over 13 million pages.

Local LLMs prioritize privacy over security. Our research reveals a 95% backdoor injection success rate. If you’re running a local LLM for privacy and security, you need to read this

As more and more of us use Large Language Models (LLMs) for daily tasks, their potential biases become increasingly important. We investigated whether today’s leading models, such as those from OpenAI, Google, and others, exhibit ideological leanings. Our results reveal that LLMs are not ideologically uniform. Different models displayed distinct “personalities”, with some favouring progressive, libertarian, or regulatory stances, for example, while others frequently refused to answer.

An honest to god, non-algorithmic reverse chrono list of tech news that passes my signal-to-noise tests, updated hourly. A lightweight a page design as I’ve been able to keep; simple, clean, fast. No commercial features or aspirations - this is a passion project, something I’ve been fooling around with on and off for decades.

There’s a “Top” view too with an LLM edited front page & summary, and categorized views for a large number of topics - see the Directory. A few more buried features to explore, but the fundamental use case is pop in, scan, exit - fast and concise.

This repository contains various advanced techniques for Retrieval-Augmented Generation (RAG) systems. The rag-cookbooks GitHub repository provides a collection of Jupyter notebooks offering tutorials, best practices, and practical use cases for implementing Retrieval Augmented Generation (RAG) systems.

The impact of AI on the workforce will be influenced by what different institutions throughout society—including businesses, nonprofit institutions, worker organizations, colleges and universities, and government—choose to do to guide its development and use.

Psst, kid, want some cheap and small LLMs? This blog post provides a comprehensive guide on how to set up and use llama.cpp, a C++ library, to efficiently run large language models (LLMs) locally on consumer hardware.