#javascript #api #ethereum #swarm #whisper

https://github.com/ChainSafe/web3.js

#go #golang #ethereum #swarm #bee

https://github.com/ethersphere/bee

#csharp #docker #kubernetes #swarm

https://github.com/dockersamples/example-voting-app

#csharp #demo #docker #docker_compose #example #kubernetes #sample #swarm

This voting app is a simple example of a distributed application that runs on multiple Docker containers. To use it, you need to download Docker Desktop and ensure you have the latest version of Docker Compose. The app uses Python, Node.js, and .NET, with Redis for messaging and Postgres for storage. You can run the app using `docker compose up` and access it at http8080 for voting and http8081 for results. The benefit to the user is that this app demonstrates how different technologies can work together in a distributed system, making it easier to understand and set up similar applications.

https://github.com/dockersamples/example-voting-app

#javascript #agentic_ai #agentic_engineering #agentic_framework #agentic_rag #agentic_workflow #ai_assistant #ai_tools #anthropic_claude #autonomous_agents #claude_code #codex #huggingface #jules #mcp_server #model_context_protocol #multi_agent #multi_agent_systems #npx #swarm #swarm_intelligence

Claude-Flow v2.7 is an enterprise AI platform with hive-mind swarms, 25 natural language skills, 100+ tools, and AgentDB integration for 96x-164x faster semantic search and 4-32x less memory use. Install via `npx claude-flow@alpha init` after Claude Code, then use commands like `swarm "build API"` for quick tasks or hive-mind for projects. It boosts your coding speed with 84.8% problem-solving rate, automation, GitHub tools, and persistent memory—saving you hours on complex development.

https://github.com/ruvnet/claude-flow

#python #agent_memory #financial_forecasting #future_prediction #knowledge_graph #llms #multi_agent_simulation #public_opinion_analysis #python3 #social_prediction #swarm_intelligence

MiroFish is a simple AI tool that predicts anything by creating a digital world from your data like news, policies, or stories. Upload seed info and describe what you want to predict; it builds thousands of smart agents with personalities and memories to interact, simulate futures, and give you a detailed report plus chat access. You benefit by testing decisions risk-free—like policy impacts or story endings—making smart choices or fun ideas win through safe, accurate previews.

https://github.com/666ghj/MiroFish

#python #agents #ai #ai_agents #ai_engineering #computer_vision #course #deep_learning #from_scratch #generative_ai #llm #machine_learning #mcp #nlp #python #reinforcement_learning #rust #swarm_intelligence #transformers #tutorial #typescript

This is a free MIT learning guide for AI engineering with 428 lessons in 20 phases. It teaches you AI from the math up, then moves into machine learning, deep learning, LLMs, agents, tools, safety, and production. Each lesson helps you build useful code or AI tools, not just read theory. You can start at the right level, follow a clear path, and keep reusable artifacts for real work. The benefit is simple: you learn how AI actually works and gain practical skills you can use to build and ship better AI systems.

https://github.com/rohitg00/ai-engineering-from-scratch