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From Pitcher to Programmer: Hudson Fuller's Journey pt. 1

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Manage episode 482763837 series 3547738
Content provided by A Podcast for Precision Agriculture Geeks. All podcast content including episodes, graphics, and podcast descriptions are uploaded and provided directly by A Podcast for Precision Agriculture Geeks or their podcast platform partner. If you believe someone is using your copyrighted work without your permission, you can follow the process outlined here https://podcastplayer.com/legal.

Hudson Fuller, GK Technology's newest full-time employee and computer science graduate, shares his journey from baseball player to agricultural data specialist working on the ADAPT standard integration.
• Hudson's connection to GK began through family ties and company retreats before pursuing internships during college
• Completed a computer science degree at Dakota State University while playing college baseball
• Created an AI baseball pitch predictor that achieved 80% accuracy in predicting pitch outcomes
• Currently coaches high school baseball and plays for the local amateur team
• Working on implementing the ADAPT standard to unify agricultural data formats across different systems in ADMS
• ADAPT aims to standardize how agricultural data is stored and transferred between different controllers and software
• The standardization is similar to how hydraulic hookups were standardized to allow equipment compatibility
• Different file types (shapefiles, GeoJSON, ISO XML) serve different purposes in storing agricultural data
• Modern controllers can process thousands of data points instantly to vary application rates accurately
Join us for part two of our conversation with Hudson in the next episode of Ag Geek Speak.

  continue reading

Chapters

1. Introduction to Hudson Fuller (00:00:00)

2. Baseball and Computer Science Background (00:04:32)

3. AI Baseball Pitch Predictor Project (00:08:56)

4. Baseball Career and Coaching (00:14:03)

5. Understanding ADAPT Standard (00:15:00)

6. File Types and Data Integration (00:22:17)

7. Episode Wrap-up and Next Steps (00:28:48)

53 episodes

Artwork
iconShare
 
Manage episode 482763837 series 3547738
Content provided by A Podcast for Precision Agriculture Geeks. All podcast content including episodes, graphics, and podcast descriptions are uploaded and provided directly by A Podcast for Precision Agriculture Geeks or their podcast platform partner. If you believe someone is using your copyrighted work without your permission, you can follow the process outlined here https://podcastplayer.com/legal.

Hudson Fuller, GK Technology's newest full-time employee and computer science graduate, shares his journey from baseball player to agricultural data specialist working on the ADAPT standard integration.
• Hudson's connection to GK began through family ties and company retreats before pursuing internships during college
• Completed a computer science degree at Dakota State University while playing college baseball
• Created an AI baseball pitch predictor that achieved 80% accuracy in predicting pitch outcomes
• Currently coaches high school baseball and plays for the local amateur team
• Working on implementing the ADAPT standard to unify agricultural data formats across different systems in ADMS
• ADAPT aims to standardize how agricultural data is stored and transferred between different controllers and software
• The standardization is similar to how hydraulic hookups were standardized to allow equipment compatibility
• Different file types (shapefiles, GeoJSON, ISO XML) serve different purposes in storing agricultural data
• Modern controllers can process thousands of data points instantly to vary application rates accurately
Join us for part two of our conversation with Hudson in the next episode of Ag Geek Speak.

  continue reading

Chapters

1. Introduction to Hudson Fuller (00:00:00)

2. Baseball and Computer Science Background (00:04:32)

3. AI Baseball Pitch Predictor Project (00:08:56)

4. Baseball Career and Coaching (00:14:03)

5. Understanding ADAPT Standard (00:15:00)

6. File Types and Data Integration (00:22:17)

7. Episode Wrap-up and Next Steps (00:28:48)

53 episodes

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