We are proud to be the

Title sponsor

Hack for Social Impact

This weekend-long hackathon leverages agent-based technology, giving teams the opportunity to build impactful solutions on real-world problems faced by mission-driven organisations.

November 9, 2024

717 Market St. San Francisco

Schedule

Friday, November 08

Time

Topic

Location

18:30 PST

Intro to Fetch.ai Tech Stack: Learn how to best utilise Fetch.ai to Build Solutions

Saturday, November 09

Time

Topic

Location

08:00 PST

Registration & Breakfast

717 Market St. San Francisco

09:00 PST

Opening Ceremony

717 Market St. San Francisco

10:40 PST

Team Formation

717 Market St. San Francisco

12:00 PST

Lunch

717 Market St. San Francisco

13:00 PST

Hacking Begins

717 Market St. San Francisco

17:30 PST

Dinner

717 Market St. San Francisco

Sunday, November 10

Time

Topic

Location

08:00 PST

Breakfast

717 Market St. San Francisco

12:00 PST

Lunch

717 Market St. San Francisco

16:00 PST

Hacking Ends!!

717 Market St. San Francisco

16:00 PST

Presentations

717 Market St. San Francisco

17:50 PST

Judging

717 Market St. San Francisco

18:00 PST

Closing Remarks

717 Market St. San Francisco

18:10 PST

Awards Ceremony

717 Market St. San Francisco

18:30 PST

Networking and Wrap Up

717 Market St. San Francisco

Introduction

Fetch.ai’s vision is to create a marketplace of dynamic applications. We are empowering developers to build on our platform that can connect services and APIs without any domain knowledge.

Our infrastructure enables ‘search and discovery’ and ‘dynamic connectivity’. It offers an open, modular, UI agnostic, self-assembling of services.

Our technology is built on four key components:

uAgents - uAgents are autonomous AI agents built to connect seamlessly with networks and other agents. They can represent and interact with data, APIs, services, machine learning models, and individuals, enabling intelligent and dynamic decision-making in decentralized environments.

Agentverse - serves as a development and hosting platform for these agents.

Fetchai SDK – seamlessly integrates your AI Agent into Agentverse and empowers dynamic connectivity with the Fetch.ai SDK

Fetch Network - underpins the entire system, ensuring smooth operation and integration.

Challenge statement

In a world where technology is advancing rapidly, Fetch.ai invites you to explore the potential of AI Agents in solving real-world challenges. Your task is to apply intelligent agent-based technology from Fetch.ai to one of the following areas, focusing on critical challenges in translation of important UN Documents, housing development, and environmental sustainability. We encourage you to design projects that incorporate multiple AI Agents to collaborate and enhance the overall effectiveness of your solution.

Complex interactions between land degradation, drought, and people: Create a system of AI Agents that explores the significant implications of land degradation on natural disasters like drought and its effects on economic and social well-being in affected communities. Each agent can specialize in different analytical aspects, such as data collection, impact assessment, and restoration effectiveness evaluation. By collaborating to examine the effectiveness of land restoration initiatives on economic growth and community resilience, your agents can inform strategies for sustainable development and enhance disaster preparedness efforts.

Fast and Accurate AI Translation of Important UN Documents: Develop a suite of AI Agents that tackle the complexities of translating UN documents, which often contain specialized terminology and intricate concepts. Each agent can focus on different aspects of the translation process. By leveraging natural language processing to learn from existing official UN documents, your agents should create efficient translation tools or assist official translators in producing accurate translations, enhancing the accessibility of vital information across diverse languages.

Unraveling the Complexity of Building Codes for Housing Construction: Design a network of AI Agents that addresses the fragmented landscape of California's varied building codes, complicating affordable housing development. Different agents can focus on specific jurisdictions, regulatory compliance, and construction best practices. By organizing and clearly displaying differences in building codes, your agents will aid developers in navigating regulations. This collaborative approach can support policy changes that promote affordable housing solutions and improve overall access to housing.

Additional Information : You can post all your queries in the #innovation-labs channel on Discord.

If you want to learn more about uAgents through articles, please Click Here.

You can find more interesting integrations and example on our gitHub Repo.

In case you missed the Fetch.ai Pre-Hackathon Workshop, here's a link to the presentation and the recording

Watch the recording

Workshop Presentation

Fetch.ai tech stack

Product Overview

Quick start example

This file can be run on any platform supporting Python, with the necessary install permissions. This example shows two agents communicating with each other using the uAgent python library.
Read the guide for this code here ↗

from uagents import Agent, Bureau, Context, Model
    class Message(Model):
        message: str
    
    sigmar = Agent(name="sigmar", seed="sigmar recovery phrase")
    slaanesh = Agent(name="slaanesh", seed="slaanesh recovery phrase")
        
    @sigmar.on_interval(period=3.0)
    async def send_message(ctx: Context):
       await ctx.send(slaanesh.address, Message(message="hello there slaanesh"))
        
    @sigmar.on_message(model=Message)
    async def sigmar_message_handler(ctx: Context, sender: str, msg: Message):
        ctx.logger.info(f"Received message from {sender}: {msg.message}")
    
    @slaanesh.on_message(model=Message)
    async def slaanesh_message_handler(ctx: Context, sender: str, msg: Message):
        ctx.logger.info(f"Received message from {sender}: {msg.message}")
        await ctx.send(sigmar.address, Message(message="hello there sigmar"))
        
    bureau = Bureau()
    bureau.add(sigmar)
    bureau.add(slaanesh)
    if __name__ == "__main__":
        bureau.run()