Changes between Version 17 and Version 18 of Other/Summer/2024/lLM


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Timestamp:
Jul 24, 2024, 7:27:55 PM (4 months ago)
Author:
Jonathan123
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  • Other/Summer/2024/lLM

    v17 v18  
    22https://www.orbit-lab.org/wiki/Other/Summer/2024/lLM?action=edit#
    33
    4 **Project Goal**: To create a functional smart-space for Internet-of-Things(IoT) and Machine Learning (ML) research. "Maestros," which are RaspberryPi 3B+s with various sensors, will collect a variety of multi-modal data formats (ex. temperature, humidity, RGB, motion, video, audio, etc). This data, then, will be stored on the a WINLAB server, and can be remotely connected to and experimented with using SSH.
     4**Project Goal**: To create a functional smart-space for Internet-of-Things(IoT) and Machine Learning (ML) research. "Maestros," which are RaspberryPi 3B+s with various sensors, will collect a variety of multi-modal data formats (ex. temperature, humidity, RGB, motion, video, audio, etc). This data, then, will be stored on the WINLAB server, and can be remotely connected to and experimented with using SSH.
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    66After collecting this data, these "Maestros" will enable LLM creation and model development to create a multi-modal, machine learning-powered smart space for cities and a variety of environments.
    … …  
    1161163. **Termination Control**: We also worked on adding more specific termination control for Maestros. Previously, running the end_experiment script would terminate all Maestros, or at least attempt to do so. Hence, even if only one was running, it would try and connect to each every Maestro, of which there are more than 30 total, and this process was inefficient. Hence, we wanted to add a feature that could shut off specified Maestros and give the user more control and efficient workflow when interacting with the Maestros. It is still a work in progress, with tr, and it should be finalized by the upcoming week.
    117117
    118 4. **GitHub Documentation**
     1184. **GitHub Documentation** We worked on documentation with the installations of the dependencies. Even though imaging was considered the best method to have all Maestros with the required dependencies to run, using the other method, installing dependencies from a fresh Raspberry Pi SD card, is still important to understand how the working Maestros came to be and to have a reference on how to create your own working Maestro for experimentation.
    119119
    120120Week 4