Team
Stelline
Project Concept
We are building a development tool to build cross-platform robot skills. The goal is to use crewAI and copilot kit to give developers access to a robots system profile, and generate working code.
Entry
Status: Submitted
Last saved: May 18 at 7:50 PM PDT
Team Roster
Message board not available for this team yet.
Zak Hussain Team Lead RSVP Approved
Founder at Zettaware
Zak laid out the Next.js system, and got he robot system prepped.
I'm a full-stack engineer who believes anyone should be able to program a robot just by talking to it. After pushing myself through multiple hackathons to learn faster, I built Zettaware—a tool that lets you control robots through your browser using plain English instead of complex math. I love connecting AI language models to real-world hardware, and recently built a massive system in just a week to explore whether AI can develop a sense of its own "body." My mission is simple: make robotics accessible to everyone while exploring fascinating questions about what happens when we give AI physical form.Retry
Researching LLM Proprioception & Embodied AI | Building Natural Language Interfaces for Robot Control
Robotics Developer Tools| Researching LLM Proprioception & Embodied AI | Building Natural Language Interfaces for Robot Control
Michael Zhang RSVP Approved
Research scientist at Meta
Michael worked on the crewai imlentation and the python proxy for directly sending results to the bot.
Michael Zhang is a Research Scientist at Meta with over 7 years of experience in cloud computing, machine learning, and augmented reality. He holds a Ph.D. in Computer Science from the University of California, Santa Barbara, and a Master's degree from Northeastern University. Michael has previously worked at prestigious companies such as Microsoft and Apple, where he contributed to innovative solutions and advanced research projects. His skills include software engineering, distributed systems, and data analysis, with a strong background in coding and implementation, particularly in Python and R. Additionally, he has a keen interest in AI engineering and has worked on various machine learning models.
cloud computing, machine learning, augmented reality, software engineering, distributed systems, data analysis, AI engineering, machine learning models
Michael Zhang is currently involved in projects such as Async Tier Core Context Propagation and FeedHack at Meta, focusing on enhancing distributed systems and machine learning frameworks. He is leveraging technologies like Python and R to develop innovative solutions that improve data processing and analysis. Additionally, he is working on various AI engineering initiatives, creating and refining machine learning models to advance augmented reality applications.