AMIE (Articulate Medical Intelligence Explorer) is a research AI system developed by Google Research and DeepMind, designed to engage in diagnostic medical conversations. Built upon the Gemini 2.0 Flash model, AMIE integrates a state-aware reasoning framework that allows it to adapt its responses based on the evolving context of a clinical dialogue. This enables AMIE to intelligently request, interpret, and reason about visual medical information, such as skin photos, ECGs, and lab results, enhancing its diagnostic capabilities. In evaluations using Objective Structured Clinical Examinations (OSCEs), AMIE demonstrated performance comparable to or exceeding that of primary care physicians in areas like diagnostic accuracy, multimodal data interpretation, and communication skills. While AMIE shows promise in augmenting clinical decision-making, further research and validation are required before real-world deployment.

AMIE

amie

A multimodal AI diagnostic agent that conducts clinical conversations and interprets medical images for accurate diagnoses.

AlphaEvolve is an evolutionary AI coding agent developed by Google DeepMind, designed to autonomously discover and optimize complex algorithms across various domains. Leveraging the capabilities of Gemini 2.5 Flash and Pro models, AlphaEvolve employs an ensemble approach that balances computational throughput with solution quality. It utilizes an evolutionary framework where large language models generate candidate algorithms, which are then evaluated and refined through automated processes. This system has achieved notable successes, including surpassing the 56-year-old Strassen algorithm for matrix multiplication and optimizing data center scheduling, leading to significant efficiency gains. AlphaEvolve's ability to generate provably novel and correct algorithms marks a significant advancement in AI-driven scientific discovery.

AlphaEvolve

alphaevolve

A Gemini-powered AI coding agent that autonomously discovers and optimizes complex algorithms.

Google's AI Co-Scientist is a multi-agent system built on Gemini 2.0, designed to function as a virtual scientific collaborator. It assists researchers by generating novel hypotheses, designing experiments, and analyzing complex datasets. The system employs specialized agents that mimic the scientific method through processes like generation, reflection, and ranking. In collaboration with institutions like Stanford University and Imperial College London, the AI Co-Scientist has demonstrated its ability to identify novel biological mechanisms and potential therapeutic targets, showcasing its potential to accelerate scientific and biomedical discoveries.

Google AI Co-Scientist

google-ai-co-scientist

A multi-agent AI system that collaborates with scientists to generate hypotheses and accelerate biomedical research.

Agent Network Protocol (ANP) is an open-source communication protocol designed to facilitate secure, decentralized interactions among AI agents. It aims to become the 'HTTP of the Agentic Web Era' by providing a standardized framework that enables agents to connect, communicate, and collaborate efficiently. ANP's architecture comprises three layers: the Identity Layer for decentralized authentication using W3C DID standards, the Meta-Protocol Layer for dynamic protocol negotiation, and the Application Layer for semantic-based capability descriptions. This structure ensures interoperability, scalability, and secure communication across diverse AI systems.

Agent Network Protocol

agent-network-protocol

An open-source protocol enabling secure, decentralized communication among AI agents.

Hugging Face's Open Computer Agent is an open-source AI tool designed to perform web-based tasks by emulating human interactions within a virtual Linux desktop environment. Powered by vision-language models like Qwen2-VL-72B and frameworks such as smolagents and E2B Desktop, it can navigate websites, fill out forms, and retrieve information based on natural language prompts. Operating through a browser interface, the agent simulates mouse and keyboard actions to execute tasks. While still in its experimental phase, it showcases the potential of AI agents in automating routine digital activities.

Hugging Face Open Computer Agent

hugging-face-open-computer-agent

An open-source AI agent that automates web tasks by simulating user interactions in a virtual Linux environment.

Google's Agent Development Kit (ADK) is an open-source framework designed to simplify the creation, deployment, and management of AI agents. Optimized for Google's Gemini models yet model-agnostic, ADK supports various agent types, including LLM-powered agents, workflow controllers, and custom agents. It offers features like multi-agent orchestration, tool integration, session management, and built-in evaluation tools. ADK facilitates flexible deployment options, including local environments, Google Cloud's Vertex AI Agent Engine, and Cloud Run, making it suitable for a wide range of AI applications.

Google Agent Development Kit

google-agent-development-kit

A modular framework for building, deploying, and managing AI agents across diverse workflows.

Google's Agent2Agent (A2A) protocol is an open standard designed to facilitate seamless communication and collaboration between AI agents developed by different organizations using various frameworks. A2A provides a standardized method for agents to discover each other's capabilities, negotiate interaction modalities, and securely collaborate on tasks without exposing internal states or proprietary tools. Built on existing technologies like HTTP, JSON-RPC 2.0, and Server-Sent Events (SSE), A2A supports both synchronous and asynchronous interactions, enabling agents to handle complex, long-running tasks efficiently. The protocol emphasizes security, interoperability, and scalability, making it suitable for enterprise-grade applications.

Google A2A

google-a2a

An open protocol enabling AI agents to communicate and collaborate across diverse systems securely.

Crawl4AI is an open-source, LLM-friendly web crawler and scraper designed to streamline web data extraction for AI agents and data pipelines. It offers features such as asynchronous crawling, structured data output in formats like JSON and Markdown, and integration capabilities with large language models. Crawl4AI supports advanced extraction strategies, including LLM-based methods, and provides tools for handling dynamic content, making it a versatile solution for developers seeking efficient and customizable web scraping solutions.

Crawl4AI

crawl4ai

An open-source, LLM-friendly web crawler and scraper optimized for AI agents and data pipelines.

Dcup is an open-source, self-hostable Retrieval-Augmented Generation (RAG) platform designed to help developers and teams build scalable, AI-powered retrieval pipelines. It enables seamless integration with data sources like Google Drive, Dropbox, and AWS, and supports advanced search capabilities including LLM re-ranking, summary indexing, and hybrid search using OpenAI embeddings and Qdrant vector storage. With its intuitive Retrieval API and modular architecture, Dcup simplifies the process of ingesting, indexing, and retrieving data, making it ideal for AI applications requiring efficient and accurate information retrieval.

Dcup

dcup

An open-source RAG-as-a-Service platform for building scalable, AI-powered retrieval pipelines.

HeyGem.ai is an open-source video synthesis tool developed by GuijiAI, designed for Windows systems. It enables users to create realistic digital avatars by precisely cloning their appearance and voice. The platform supports text and voice-driven virtual avatars, high-definition video synthesis, and multilingual support. Operating fully offline, HeyGem.ai ensures user privacy and offers a customizable solution for various applications, including content creation, education, and virtual assistance.

HeyGem.ai

heygem-ai

An open-source tool for creating realistic digital avatars with precise appearance and voice cloning, operating fully offline.

JobHuntr.fyi is a native macOS desktop application that leverages Ollama-powered AI to automate job applications on LinkedIn. Operating entirely on-device, it ensures user privacy while providing features like semantic filtering, tailored cover letter generation, and direct messaging to hiring teams. The app supports functionalities such as auto-apply, application queuing, and progress tracking, aiming to streamline the job search process with high personalization and efficiency.

JobHuntr.fyi

jobhuntr-fyi

A macOS app that automates personalized job applications using on-device AI, enhancing job search efficiency.

Codex CLI is an open-source, terminal-native AI coding assistant developed by OpenAI. Designed for developers who prefer working directly in the terminal, it integrates OpenAI's latest models (like o4-mini) to perform tasks such as reading, modifying, and executing code within a local environment. Codex CLI supports multimodal inputs, allowing users to pass text, screenshots, or diagrams to generate or edit code accordingly. It offers three distinct approval modes—Suggest, Auto Edit, and Full Auto—providing flexibility in how autonomous the agent operates. The tool emphasizes security by running in a sandboxed, network-disabled environment and ensures that your source code remains on your machine unless explicitly shared. With zero-setup installation and compatibility with macOS, Linux, and experimental support for Windows via WSL, Codex CLI aims to streamline the development workflow by bringing powerful AI capabilities directly to the command line.

Codex CLI

codex-cli

Open-source terminal-based AI coding assistant that reads, writes, and executes code locally with multimodal input support.

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