nowfound

AI · May 19, 2026

Sigma Node

Sigma Node powers AI with decentralized bandwidth

What it does

Sigma Node is a decentralized AI infrastructure network that turns idle bandwidth into a scalable data and connectivity layer for AI agents, RAG systems, and real-time AI applications. By connecting distributed nodes through token incentives, Sigma Node helps users monetize unused resources while enabling developers and enterprises to access cost-efficient, verifiable, and resilient AI data infrastructure.

Does a similar job

all alternatives →
  • Netmind Power2023 · ▲272

    The decentralised machine learning and AI platform

  • DR
    Decentralized robots (and things) orchestration system2025 · docs.p2p.industries · ▲69

    Hi HN, we build an open-source operating system extension for orchestrating robot swarms fully decentralized. This first beta version allows you to create fully decentralized robot swarms. The system will set up a wireless mesh network and run a p2p networking stack on top of it, such that nodes can interact with each other through various abstractions using our SDKs (Rust, Python, TypeScript) or a CLI. We hope this is a step toward better inter-robot communication (and a fun project if you have a few Raspberry Pis lying around). Our mesh network is created by B.A.T.M.A.N.-adv and we’ve…

  • AgihaloJan 2026 · agihalo.com · ▲68

    LLM Router for A.I Agent & Saas with x402

  • Decentralized Data Exchange Protocol2019 · ▲85

    Bringing Data and AI together for the Web3 Data Economy

  • ChainGPT AI HubDec 2025 · pad.chaingpt.org · ▲60

    Crypto, AI Tools, Web3, Trading, Smart Contracts

  • ChainMind—Decentralized Intelligence NetJun 2026 · chainmind.com.ng · ▲3

    Decentralized AI network powered by real computers worldwide

More ai this month

the category →
  • I trained a 125M-parameter transformer to autocomplete piano performances in real time (~108 notes/sec on an iPhone 15). The idea is basically GitHub Copilot or Tabnine, except instead of prompting it with code, you prompt it by playing a few notes on a MIDI piano. The model then continues what you played, entirely on-device. The app is free if anyone wants to try it. Happy to answer questions about the model, training, Core ML, or the many things that didn't work.

    AI · 18d ago · simedw.com

  • Astute585

    Automate your B2B brand going viral, with new media creators

    AI · 19d ago · company-app.joinastute.com

  • Grok Bot547

    AI teammates that you can give real work to

    AI · 26d ago · x.ai

  • Hey HN, Henry from Cactus here! We previously released Cactus Needle, a 14MB agentic LLM for tool call, device use, and structured extraction for phones, wearables, smart homes, small robots and microcontrollers. We got really great feedback here, and have now incorporated the suggestions to release Needle 2. The whole model is a single 14MB binary that runs a full session in 28MB of RAM; 45m parameters at 2bit compression. Needle hits 500 tokens/sec decode speed on a Raspberry Pi 5, sits between 400-1,500 tokens/sec on VR devices like Meta Quest 3S and Apple Vision Pro, and ranges…

    AI · 28d ago · cactuscompute.com

  • Monid475

    One wallet, every paid tool your agent needs

    AI · 7d ago · monid.ai

  • Turn website visitors into qualified pipeline

    AI · 20d ago · clarasdr.ai

Launched alongside, May 2026

the whole month →
  • Brew 905

    Like Claude design for email marketing

    AI · May 2026 · brew.new

  • Parallel agents, diff reviewer, and multi-model comparisons

    Dev tools · May 2026 · kilo.ai

  • StoreClaw805

    Grow your store profits with agents that know how to sell

    AI · May 2026 · storeclaw.ai

  • Give your agent a real number and voice to make calls.

    AI · May 2026 · pollyreach.ai

  • NW

    Hey HN, Henry here from Cactus. We open-sourced Needle, a 26M parameter function-calling (tool use) model. It runs at 6000 tok/s prefill and 1200 tok/s decode on consumer devices. We were always frustrated by the little effort made towards building agentic models that run on budget phones, so we conducted investigations that led to an observation: agentic experiences are built upon tool calling, and massive models are overkill for it. Tool calling is fundamentally retrieval-and-assembly (match query to tool name, extract argument values, emit JSON), not reasoning. Cross-attention…

    Life & fun · May 2026 · github.com

  • FM

    Dev tools · May 2026 · github.com