Date To Be Announced

Compute for the People, by the People

Build a distributed compute network where everyday machines power secure and verifiable workloads.

⏱️ In 6 days, you’ll create an MVP showing how jobs can be submitted, scheduled, verified, and collected across a network of nodes.

🌟 Receive guidance from expert mentors who will support you throughout the challenge.

🤝 Collaborate with others or work independently to bring your groundbreaking ideas to life.

🧑‍💻 This challenge is geared toward experienced builders in decentralized compute—if that’s you, show us what you can do.

🧑‍💻 Secure your spot now and start building the future of decentralized compute infrastructure.

Enroll now!

About Decentralized Computing

Decentralized computing is reshaping the future of infrastructure. Instead of relying on centralized cloud providers, compute power is distributed across networks of independent, volunteer machines. These networks allow anyone to contribute their idle CPU/GPU resources and enable developers to run workloads at scale—securely, verifiably, and with global reach.

As demand for AI and high-performance computing grows, decentralized compute networks are emerging as a scalable, cost-effective, and censorship-resistant alternative. They power AI inference, machine learning jobs, and general computation—without the bottlenecks of centralized systems.

This hackathon is your opportunity to help shape that future. You'll explore how to design the foundational components of a distributed network, where tasks are submitted, executed, and verified in real-time, across a mesh of globally connected nodes.

CHALLENGE

Build a decentralized compute platform where volunteer machines contribute resources and jobs run securely and verifiably across the network.

We’re looking for innovators to help build the next wave of decentralized compute infrastructure — inspired by systems like io.net. Think of a network where anyone can contribute unused CPU/GPU on their personal machine, and job submitters can run distributed workloads across the network in a trustworthy, efficient, and developer-friendly way.

Your mission is to deliver an MVP that demonstrates the core flow:

• Volunteer machines (“nodes”) register themselves and report resource availability

• Jobs are scheduled and executed across multiple nodes

• Results are verified and collected reliably

• A clean interface (CLI, API, or dashboard) exists to submit, monitor, and retrieve jobs

Potential Features to Include

Below are features & modules you can include (core + advanced):

Core MVP

• Worker Agent: runs on any machine (Linux, macOS, Windows), reports available resources, pulls jobs, executes in sandbox (Docker rootless / WASM).

• Coordinator/Control Plane: schedules tasks, manages job lifecycle, verifies outputs.

• Verification: k-of-n redundancy (e.g., send job to 3 nodes, accept if 2 match).

• CLI / API: submit jobs, check status, fetch logs, download results.

• Dashboard: simple web view of nodes, jobs, metrics.

Advanced

• Credits/Economics: token or credit system where submitters “pay” and workers “earn.”

• Reputation System: track node reliability, uptime, accuracy.

• Fault Tolerance: reschedule jobs if a node disconnects mid-task.

• Observability: Prometheus metrics, Grafana dashboards, live logs.

• Data Locality Optimization: smarter scheduling based on region / bandwidth.

• Security Enhancements: job signing, encrypted inputs, secret management.

• ZK Proofs / TEEs: explore zero-knowledge proofs or trusted execution environments for verifiable compute.

Recommendations for Developers

Scope management

• Focus on end-to-end flow (job submission → execution → verification → result retrieval).

• Keep architecture modular: Coordinator (jobs/scheduling), Worker Agent (execution), Interfaces (CLI/UI).

Tech stack suggestions

• Coordinator: Go or Node.js with Postgres/Redis for queue + state

• Worker Agent: Rust or Go daemon with Docker rootless or WASM runtime.

• Networking: Start with HTTPS polling (simpler than P2P); consider libp2p/WebRTC if time allows.

• Storage: MinIO (S3-compatible) or even plain filesystem + signed uploads.

• Interfaces: CLI in Go/Node; web dashboard in React/Next.js.

Workloads to demo

• Deterministic: file hashing, wordcount, checksum validation.

• Semi-deterministic: text embeddings or image resizing with fixed seeds.

Presentation advice

• Run two jobs: one simple + one ML-related.

• Demonstrate failure recovery (kill a node during job).

• Visualize progress on the dashboard.

Talent Scouting

In addition to the competition, we will be scouting top performers for potential full-time roles on our engineering team.

We’re particularly interested in talent with experience in:

• P2P / Distributed Systems: Rust or Go, libp2p, scheduling, content-addressed storage

• Security / Isolation: sandboxing, OS hardening, code signing, TEEs/attestation

• Economics / Smart Contracts: incentives, payments, reputation, slashing

• Edge Client Engineering: cross-platform agents, auto-updates, GPU support

• Backend & Developer Experience: APIs, SDKs, job specs, portals, observability

Note: Participation in the hackathon does not guarantee employment or a job offer. Candidates selected for interviews or further opportunities will be contacted directly.

What to submit?

📋 Basic Information

• Project Title

• Short Description

• Long Description

• Technology & Category Tags

📸 Cover Image and Presentation

• Cover Image

• Video Presentation

• Slide Presentation

💻 App Hosting & Code Repository

• Public GitHub Repository

• Demo Application Platform

• Application URL

For further details and guidance, please visit Submission Guidelines

lablab.ai

Topic: Hackathon Submissions Process

▶️ Watch Video

Judging Criteria

Application of Technology

How effectively the chosen model(s) are integrated into the solution.

Presentation

The clarity and effectiveness of the project presentation.

Business Value

The impact and practical value, considering how well it fits into business areas.

Originality

The uniqueness & creativity of the solution, highlighting approaches and ability to demonstrate behaviors.

Hackathon Details

Join lablab.ai hackathon and innovate using the latest models in the market. Discover all the relevant details below.

🗓️ Where and when

The start date of the hackathon is mentioned according to the date specified on the hackathon page, cover and schedule. The hackathon will take place on the lablab.ai platform and lablab.ai Discord server.

🦸🏼‍♂️ Who can join?

This hackathon is designed for builders with experience in decentralized computing.

😅 What about teams?

If you don't have a team, don't worry! You can connect with other participants from all over the world on our dashboard or Discord server. We also recommend checking out our Discord server to find teammates and bounce around ideas. You can join the server here.

🛠️ How to participate

The hackathon will take place online on lablab.ai platform and lablab.ai Discord Server. Please register for both in order to participate. To participate click the "Enroll" button at the bottom of the page and read our Hackathon Guidelines and Getting Started Guide.