Where Would AI Be Today If Picasa and Google Goggles Had Survived?
Aydın Tiryaki and Gemini 3 Pro (2025)
Some applications shelved in the dusty archives of technology history are not merely discontinued software; they are massive, missed opportunities. If Google had kept Picasa and Goggles alive, collaborating with users instead of shutting them out, Artificial Intelligence today might be running instead of crawling when it comes to “understanding what it sees.”
We are currently living in the era of the AI revolution. Models can write essays and generate code. However, when it comes to understanding the “Visual World,” billion-dollar algorithms still suffer from a shocking blindness. The fact that Google Lens, when pointed at a television screen, identifies the plastic frame and the TV brand instead of the movie scene playing on it, is the simplest proof of this blindness.
So, where did it go wrong? The answer lies in two legendary applications buried in the Google graveyard in the early 2010s: Picasa and Google Goggles.
Goggles and the “Teacher-User” Model
In the early days of smartphones, there was a “magical” app called Google Goggles. When you pointed your camera at the world, it gave you encyclopedic information. However, the real power of Goggles was not in the information it provided, but in the potential information it could receive from the user.
Let me explain with an example from my own experience: From my terrace, I once pointed my phone at three distinct mountains on the horizon. I manually “taught” Goggles the names of these mountains, one by one. Later, when I pointed the camera there again, the system recognized those mountains by the names I had taught it. Goggles recognized my grandfather’s old historic house from all three sides.
The solution to today’s Artificial Intelligence crisis was right there on that terrace. In technical literature, this is called “Supervised Learning.” At that time, Google could have utilized millions of its users as voluntary “data labelers.” We could have entered our local environment, native plants, architectural details, or cultural objects into the system with our own hands, providing the most accurate context. Google closed this door. They demoted the user from the status of a “Teacher” to merely a “Consumer.”
If Goggles had continued with that interactive structure, today’s AI would possess a massive, flawless dataset—crowdsourced and verified by human eyes—rather than relying solely on satellite data or stock photos scraped from the internet.
Picasa: The Power of Curation
A similar loss occurred on the Picasa front. Picasa was an archiving tool where we organized photos on our local drives, tagged faces, and cared enough to create “Gift CDs.” It was an active process.
When they killed Picasa and directed us to Google Photos (the Cloud), we shifted from “Active Curation” to “Passive Storage.” In Picasa, users filtered, edited, and grouped photos; essentially, they cleaned the data. Today, the billions of photos uploaded to the cloud are largely a digital dump. AI tries to learn from this noisy data. Yet, the disciplined users of Picasa were the best instructors to teach AI “what is important and what is not.”
Conclusion: Smart but Not Wise
At the point we have reached today, technologies like Google Lens are very successful at recognizing “objects,” but they fail miserably at reading “intent.”
When I point my camera at a television, the AI cannot deduce that “This user is interested in the content.” Its commercialized algorithm directs it to the simplest, most sellable object: the TV set itself.
If the logic of Goggles and Picasa had survived:
- Users would have taught AI “where to look” over the years.
- AI would have been trained in the reality of the streets, not just in a laboratory environment.
- We would be receiving deep, contextual answers today, rather than the “generic and general” responses we often get.
Tech giants, succumbing to the arrogance of “our algorithms can solve everything,” rejected the wisdom of the human in the field (the user). The “hallucinating,” context-blind AI we experience today is the direct result of this “Lost Collaboration.”
The future may be shaped by compensating for these opportunities we missed in the past. But for now, the technology in our hands “sees,” but unfortunately, it does not fully “understand.”
Aydın Tiryaki and Gemini 3 Pro (2025)
Ankara, December 17, 2025
A Note on Methods and Tools: All observations, ideas, and solution proposals in this study are the author’s own. AI was utilized as an information source for researching and compiling relevant topics strictly based on the author’s inquiries, requests, and directions; additionally, it provided writing assistance during the drafting process. (The research-based compilation and English writing process of this text were supported by AI as a specialized assistant.)
Aydın Tiryaki 