How We Got Here

Reverse engineers images to uncover the chain of events that led to them.

Available with ChatGPT Plus

I’ve seen a lot of GPTs that do interesting things with image recognition and DALL•E, like analyzing an image to understand the scene and then recreating it from scratch as a painting.

But I wanted to do something different, like, “what if we could guess the stories behind the pictures?”. Obviously it’s for laughs, so this GPT is called “How We Got Here” and it theorizes a possible chain of events that took place before the picture to result in what you see. It works for any given scene or an object, but because of OpenAI’s restrictions it will refuse to comment on images of famous people.

Here’s an example:

1. A parliament session started with the introduction of a controversial bill: The Mandatory Karaoke Performance Act.
2. The opposition leader, known for his baritone renditions of “My Way”, vehemently opposes the bill, fearing unfair advantages for tenors.
3. During the debate, an amendment is proposed: All speeches must be sung to the tune of popular folk songs.
4. The finance minister, a secret shower-singer, is thrilled and immediately begins to belt out budget allocations in A-minor.
5. The amendment passes by one vote, thanks to a swing voter who misunderstood the motion, thinking it was about free concert tickets.
6. The session escalates as a counter-amendment is suggested: All sung speeches must be auto-tuned for fairness.
7. Chaos ensues when the auto-tune machine malfunctions, making everyone sound like rogue robots.
8. In a bid to shut down the malfunctioning device, a scramble erupts, with one member accidentally broadcasting his vocal warm-up scales live on national television.
9. The image captures the exact moment when the tech-savvy intern is summoned to fix the auto-tuner, while the rest try to cover up the incident by looking deeply concerned about fiscal policies.

Try How We Got Here with your own photos.