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

Web Search MCP Server for use with Local LLMs A TypeScript MCP (Model Context Protocol) server that provides comprehensive web search capabilities using direct connections (no API keys required) with multiple tools for different use cases.

Features Multi-Engine Web Search: Prioritises Bing > Brave > DuckDuckGo for optimal reliability and performance Full Page Content Extraction: Fetches and extracts complete page content from search results Multiple Search Tools: Three specialised tools for different use cases Smart Request Strategy: Switches between playwright browesrs and fast axios requests to ensure results are returned Concurrent Processing: Extracts content from multiple pages simultaneously

“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.

A technique for deterministic labeling from stochastic models, with benchmarked Golang implementation.

An AI Model Just Compressed An Entire Encyclopedia Into A Single, High-Resolution Image.

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.

This Nature Neuroscience article discusses the emerging role and potential applications of large language models (LLMs) in accelerating research and advancing understanding within the field of neuroscience.