Thursday Dec 07, 2023

250. What Does YELL-O! My Pee Frequently Analyst GPT have to do with the We Get Around Network Forum?

What Does YELL-O! My Pee Frequently Analyst GPT have to do with the We Get Around Network Forum?

Thursday, December 7, 2023

Commentary by

Dan Smigrod
Founder and Managing Editor
We Get Around Network Forum | WGAN-TV Podcast | WGAN Forum Podcast
Atlanta, Georgia USA

Hi All,

Bridging the gap between Matterport and related digital twin platforms, cameras and solutions; and frequently peeing might seem far-fetched, but they intersect in an unexpected way in my latest passion project.

What does my YELL-O! My Pee Frequently Analyst, a GPT tool designed to graphically analyze and track urination patterns, have to do with the WGAN Forum?

The answer lies in leveraging AI for personal and professional growth. YELL-O! was born from my personal health journey, aiming to provide clear, meaningful, data-driven insights into my frequent urination habits.

YELL-O!
 provides 14+ different types of graphs from a pee time data file (.xlsx). The graphs and analysis offer a comprehensive data-driven view of my urination patterns. This is super-helpful for both my understanding and consultations with my Urologist and Physician Assistant (PA).

Some backstory: the detailed analytics provided by YELL-O! include various metrics, from the "Number of Pee Times Per Day" to more complex analyses such as "Day-to-Day Variability" and "Comparative Analysis Pre and Post Treatment."

This level of detail is invaluable in my ongoing treatment for frequent urination and in identifying potential trigger foods, events, and other factors that contribute to my frequent peeing. The data analytics help me and my Urology team understand the impact of the Percutaneous Tibial Nerve Stimulation (PTNS) treatment and my medications in context to various triggers.

YELL-O! represents the intersection of AI with personal health, mirroring my aspirations for the WGAN Forum.

Yes. Clearly oversharing. But discussing my journey with frequent urination is crucial in understanding the motivation behind creating YELL-O! and its connection to developing AI solutions for the WGAN Forum.

This personal passion project parallels the development of a GPT for the WGAN Forum, which aims to automatically address queries based on an extensive database of 98,400+ posts covering 17,450+ topics since August 2014, including 200+ live, one-hour WGAN-TV Podcast interview/demo episodes and 250+ episodes of the WGAN Forum Podcast. That’s a lot of content to help the WGAN community succeed faster.

These two AI applications, though similar in concept, differ in their dataset scale. YELL-O! analyzes a single day/time peeing data file, whereas the WGAN Forum GPT will process huge datasets from the We Get Around Network ForumWGAN-TV Podcast and WGAN Forum Podcast.

The creation of these GPTs has facilitated a better understanding of how to effectively communicate and collaborate with the WGAN Forum tech team on our ambitious GPT project for the WGAN Forum.

Our vision is that the WGAN Forum AI Assistant (GPT) will automatically provide fast answers to member queries, drawing from the rich, dynamic knowledge base of the WGAN ForumWGAN-TV Podcast and WGAN Forum Podcast.

This automation aims to enhance the experience for the 15,000+ unique monthly visitors and 8,900+ registered WGAN Forum members, demonstrating the significant value of joining and engaging with the WGAN Forum community.

This creates more helpful and useful content (content powers our flywheel for scaling the We Get Around Network Forum and WGAN-TV Podcast that attracts WGAN Sponsors).

I would still expect WGAN Forum members to “weigh-in” with their thoughts to questions that are automatically answered by the WGAN Forum AI Assistant, but sometimes fact seeking questions just need a quick fact-based answer.

The ultimate goal is to create an environment where questions are promptly and accurately answered, to help foster a thriving WGAN Forum community.

As the capabilities of ChatGPT evolve, the scope of questions that can be addressed by the WGAN Forum AI Assistant will broaden. WGAN Forum members seeking specific advice, like creating floor plans from Matterport digital twins for very large spaces, will receive tailored, insightful responses, based on the collective wisdom of the community from various WGAN Forum discussions.

To achieve this, we have outlined a phased approach:

1. Manual Operation: Initially, I will run the WGAN Forum AI Assistant against the dataset, manually posting the responses. This will help refine our prompt structuring approach.
2. Automation of Data Reading: Next, we'll automate the WGAN Forum AI Assistant to access and interpret the WGAN Forum datasets.
3. Automated Responses: The WGAN Forum AI Assistant will then be programmed to automatically post answers to WGAN Forum questions.
4. Broader Topic Posting: Finally, we aim to expand the capabilities of the WGAN Forum AI Assistant to cover a wider range of topics.

Conclusion

The process of developing the YELL-O! My Pee Frequently Analyst GPT is helping the development process for the WGAN Forum AI Assistant.

This project not only demonstrates the versatility of GPT-powered tools in diverse applications but also underscores the potential of AI in enhancing faster answers to WGAN Forum member posts, community engagement and knowledge sharing within the WGAN Forum.

The YELL-O! project is more than a health management tool; it's a gateway to a more interconnected and intelligent digital ecosystem within the WGAN Forum, enriching both personal experiences and collective wisdom.

What passion project are you creating that is both unrelated - and related - to your profession?

---

[Note: OpenAI's ChatGPT4 assisted Dan Smigrod in writing this commentary. The accompanying illustration was created by DALL-E3.]

Comments (0)

To leave or reply to comments, please download free Podbean or

No Comments

© 2024 All rights Reserved. WGAN-TV Podcast and WGAN Forum Podcast are divisions of TERRIFIC! Inc. www.WeGetAroundNetwork.com | www.WGAN-TV.com

Podcast Powered By Podbean

Version: 20240320