Autonomous Agents Hackathon

SuperAGI is hosting Twitter space before the Hackathon, having an open discussion on AI Agents with AI experts from SuperAGI, Weaviate, Llamaindex, and lablab.ai

Join the discussion on Twitter on @_superAGI page!

Twitter Space Talk!

Hackathon Kick-Off

The founders at NewNative and lablab.ai will introduce participants to our mission and the opportunities you have as a member of the lablab.ai community

NewNative Introduction

Introduction to SuperAGI: Exploring AI Agents

AI Agents Explained: A Talk by Logan Kilpatrick (from OpenAI)

Vector Databases & AI Agents: A Talk by Etienne Dilocker, Weaviate

Let's go through the Technologies for the Hackathon and how you can learn it.

Technology and Challenge

We will guide you through the website, and Discord community - to make sure you will succeed at the Hackathon

Hackathon Guide

Weaviate Workshop: 45-Minute Session with Mentors on Discord

AWS Workshop with Goutam Kurumella

Open Q&A with mentors

Live Q&A: Meet the Auto-GPT Team

Join us for an insightful Q&A session with Vasek Mlejnsky of E2B and the expert mentors from lablab.ai!

Book Your Slot with Industry Experts! Collaborate with Mentors from Arize, Lablab.ai, LlamaIndex, SuperAGI, and Weaviate to Finalize Your Concepts and Ideas!

Mentorship Sessions

Arize Workshop on Discord: Troubleshooting Retrieval Augmented Generation

Q&A Session with GPT Engineer Anton Osika

Submission Deadline

Finnalists Pitching and Winners Announcament Stream

We are trying a new way to combine static reasoning and dynamic agents to fulfill user requests.

Jarvis AI

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Introduction:
We proudly introduce Jarvis, a groundbreaking system we've developed, which revolutionizes the way tasks are approached and accomplished.


Core Features:
1. Natural Programming Syntax for Jarvis. We have curated a unique YAML-based syntax for Jarvis which incorporates elements like 'If Condition', 'Loop Condition', and more. This allows Jarvis to leverage these constructs in conjunction with tools to execute tasks specified by users. Unlike traditional programming languages, Jarvis' syntax is simpler, closely mirrors natural language, and is therefore more intuitive and user-friendly. We envision that its potential extends to being integrated within Low Code platforms in the future. Compared to the reasoning and planning models of other agents, this programmability grants Jarvis unmatched flexibility. It broadens the spectrum of task paths Jarvis can explore and harness – showcasing the true power of code.


2. Skill System based on Task Execution. Given the aforementioned feature, every successfully executed task can be encapsulated as a 'skill' within Jarvis. To ensure the effective utilization and training of Jarvis, we introduce two pivotal roles: Trainers: These individuals operate within a secure environment, utilizing resources like superagi and babyagi. They act as mentors, guiding Jarvis autonomously, helping it acquire and refine various skills. Agents: These entities are equipped to employ reviewed and trained skills of Jarvis to address real-world tasks.


Vision:
Our aspiration with Jarvis is to bridge the gap between complex task execution and ease of programming. By harnessing the simplicity of natural language and the power of code, we aim to create a future where advanced tasks are as simple as giving a command. 

Jarvis, a lightweight virtual machine system designed for AI, which change the way user tasks are approached and accomplished.

"Jarvis AI team on Autonomous Agents Hackathon Hackathon"

Team Idea

Submission