We are proud to be the
October 18, 2024
City View at Metreon San Francisco, CA
14:30 PDT
Hackers Check-in
City View at Metreon San Francisco, CA
16:00 PDT
Opening Ceremony
City View at Metreon San Francisco, CA
17:00 PDT
Hacking Begins
City View at Metreon San Francisco, CA
18:10 PDT
Learn about Fetch.ai
City View at Metreon San Francisco, CA
24:00 PDT
Hacking Continues
City View at Metreon San Francisco, CA
10:00 PDT
Fetch-a-Boba and Build with Fetch.ai
City View at Metreon San Francisco, CA
14:30 PDT
One on One Coffee Chat with Sana (CDO)
City View at Metreon San Francisco, CA
12:00 PDT
Hacking Ends
City View at Metreon San Francisco, CA
14:30 PDT
Closing Ceremony
City View at Metreon San Francisco, CA
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:
Agents - AI Agents are independent decision-makers that connect to the network and other agents. These agents can represent data, APIs, services, ML models and people.
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
Explore the potential of intelligent agent-based technology with Fetch.ai, which provides a simple framework for creating your own AI Agents that can communicate with one another. This challenge invites you to develop innovative solutions that address real-world issues across various industries. Whether you choose to focus on finance, education, healthcare, customer service, content creation or more, your goal is to leverage Fetch.ai AI Agents to build applications.
To further enhance your applications, participants are encouraged to integrate Google Cloud services for building custom Machine Learning models, image analysis, text analysis and sentiment detection. These tools can complement Fetch.ai's AI Agents by providing advanced AI-driven insights
You can kick-start your development process by integrating pre-built AI Agents from Agentverse into your applications, and watch your ideas come to life. If you don’t find the exact agent you need on Agentverse, feel free to create and deploy your own to the platform. Get ready to innovate and push the boundaries of what's possible!
Additional Resources You can find the description of available Fetch.ai AI Agents here and you can search for these Agents in the Explorer tab on Agentverse.
If you want to learn more about uAgents through articles, please Click Here.
You can post all your queries in the #innovation-labs channel on Discord.
Fetch.ai tech stack
Product Overview
This flowchart can get you to where you want to be:
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()Important links
Examples to get you started:
Judging Criteria
Winner Team Fetch.Ai Beyond Boundaries AI Agent Prize
2000 USD, Internship Interview plus 50 Agents, 1M Messages and 200K Seconds of computation time on Agentverse for 1 month
Second Prize
Smartest AI Agent Prize
1000 USD Cash Prize
plus
Internship Interview
Third Prize
Best use of Fetch.Ai Tech
Support
Support will be available at the hackathon, and you can also reach out to the core dev team who will be able to support you via Discord ↗
Judges
Sana Wajid
Chief Development Officer
Elliot Bertram
Business Development Director
Mark Losey
CTO at FlockX
Attila Bagoly
Head Of AI
Mentors
Sanket Kulkarni
Developer Advocate
Tanay Godse
Developer Advocate
Chinmay Mahagaonkar
Developer Advocate
Vedita Deshpande
Developer Advocate
Kush Agarwal
Developer Advocate
Shivam Hasurkar
Developer Advocate
Sai Mounika Pateti
Ambassador
Ready to get started with Fetch.ai Platform?
