Towards the end of last year, Meta released SAM 3, which stands for the third version of its Segment Anything Model. The way it generally works is that it allows you to detect, edit, and experiment with things in images and videos. For example, if you were looking at a video of a street, you could ask it to find all the scooters (which I did below), count the number of pedestrians wearing black pants, blur all the license plates on the cars, and so on.

This is immediately useful for a company like Meta because it allows for object-level modifications across its content creation platforms. So if you took a video of someone dancing and you desperately wanted to give them a bobblehead, SAM 3, I'm told, would allow you to quickly do that. Other AI models, such as Gemini, can also segment, but supposedly the SAM models are better and more precise at this specific task.

Beyond bobblehead videos, the potential of this model seems enormous for real estate, cities, and, of course, many other things. Using the above image as an example, you can quickly imagine SAM 3 being used to count and track modal splits across a city, and then make planning decisions based on real-time data.

People are also using it for real estate purposes. Pair the model with satellite images, and you can ask it to tell you how many houses have a pool, which houses recently had their roof replaced (and have solar panels), how many cars are parked on a street, how many cars are parked at Canadian Tire, and the average building lot coverage in an area.

You could also use it to swap out finishes in a real estate listing (including in videos), and get material/area takeoffs ahead of a construction project. I don't know for sure, but I would also imagine that this model would make a great building condition inspector. Come to think of it, I'd love a SAM 3 that could walk our construction sites and document every little detail!

Of course, a lot of these use cases are already being tackled. But the models are getting that much better. And that will lead to even more innovation.

Cover photo by Above Horizon on Unsplash

In case you missed it, Google released Gemini 3 this past week. And boy is it awesome. The images it creates — see the tweet above — are completely undetectable as the work of AI, and this is just one particular use case. From an overall sentiment standpoint, it is also amazing to see how quickly things have changed for Google. This past summer, the narrative was that AI was going to kill Google's golden goose — its search business. But now all of a sudden, it feels like Google is the king of AI.

I know we all know this, but it's hard not to keep thinking about how profoundly this is all going to change the global economy. Let's take real estate development. Development is a future-oriented business. It's about imagining what the future could be, and then going out and trying to create it. Because of this, I think you could also describe it as an industry of visual persuasion. Renderings, photos, diagrams, and many other tools are used to sell a specific kind of future.

In the olden days, these tools used to cost a lot of money, especially if you were preparing for something like a condominium sales launch. When it came to renderings, we used to have to book the best companies months in advance, and then once work actually started, it would take several weeks of iteration before the final renderings were ready. In parallel to this, you'd also be working on your photography. And because no developer wants to photograph dormant winter trees and sidewalks shellacked in road salt, you also needed to carefully plan ahead for when you'd be taking these.

Then, once you had all your visuals ready, you sent them off to the printers, so that sales brochures and other marketing collateral could be physically printed. It's a long and expensive process. Of course, AI collapses this entire workflow. It dramatically reduces both time and cost (down to an almost zero marginal cost), and opens up a world of unlimited visual possibilities. Want a photograph of a couple walking in New York City in the snow during Christmas? Done.

So what does this mean for development and all of the service providers who help to visualize projects into existence? In my view, it means the low-value-add ones go away. AI easily replaces them. But for the high-value ones who bring incredible creative direction to projects, I think they get better and become even more important. AI is creative rocket fuel. But you still need someone who can direct, who has taste, and who can decide what story the project should tell.

Cover photo by Serhii Hanushchak on Unsplash

Towards the end of last year, Meta released SAM 3, which stands for the third version of its Segment Anything Model. The way it generally works is that it allows you to detect, edit, and experiment with things in images and videos. For example, if you were looking at a video of a street, you could ask it to find all the scooters (which I did below), count the number of pedestrians wearing black pants, blur all the license plates on the cars, and so on.

This is immediately useful for a company like Meta because it allows for object-level modifications across its content creation platforms. So if you took a video of someone dancing and you desperately wanted to give them a bobblehead, SAM 3, I'm told, would allow you to quickly do that. Other AI models, such as Gemini, can also segment, but supposedly the SAM models are better and more precise at this specific task.

Beyond bobblehead videos, the potential of this model seems enormous for real estate, cities, and, of course, many other things. Using the above image as an example, you can quickly imagine SAM 3 being used to count and track modal splits across a city, and then make planning decisions based on real-time data.

People are also using it for real estate purposes. Pair the model with satellite images, and you can ask it to tell you how many houses have a pool, which houses recently had their roof replaced (and have solar panels), how many cars are parked on a street, how many cars are parked at Canadian Tire, and the average building lot coverage in an area.

You could also use it to swap out finishes in a real estate listing (including in videos), and get material/area takeoffs ahead of a construction project. I don't know for sure, but I would also imagine that this model would make a great building condition inspector. Come to think of it, I'd love a SAM 3 that could walk our construction sites and document every little detail!

Of course, a lot of these use cases are already being tackled. But the models are getting that much better. And that will lead to even more innovation.

Cover photo by Above Horizon on Unsplash

In case you missed it, Google released Gemini 3 this past week. And boy is it awesome. The images it creates — see the tweet above — are completely undetectable as the work of AI, and this is just one particular use case. From an overall sentiment standpoint, it is also amazing to see how quickly things have changed for Google. This past summer, the narrative was that AI was going to kill Google's golden goose — its search business. But now all of a sudden, it feels like Google is the king of AI.

I know we all know this, but it's hard not to keep thinking about how profoundly this is all going to change the global economy. Let's take real estate development. Development is a future-oriented business. It's about imagining what the future could be, and then going out and trying to create it. Because of this, I think you could also describe it as an industry of visual persuasion. Renderings, photos, diagrams, and many other tools are used to sell a specific kind of future.

In the olden days, these tools used to cost a lot of money, especially if you were preparing for something like a condominium sales launch. When it came to renderings, we used to have to book the best companies months in advance, and then once work actually started, it would take several weeks of iteration before the final renderings were ready. In parallel to this, you'd also be working on your photography. And because no developer wants to photograph dormant winter trees and sidewalks shellacked in road salt, you also needed to carefully plan ahead for when you'd be taking these.

Then, once you had all your visuals ready, you sent them off to the printers, so that sales brochures and other marketing collateral could be physically printed. It's a long and expensive process. Of course, AI collapses this entire workflow. It dramatically reduces both time and cost (down to an almost zero marginal cost), and opens up a world of unlimited visual possibilities. Want a photograph of a couple walking in New York City in the snow during Christmas? Done.

So what does this mean for development and all of the service providers who help to visualize projects into existence? In my view, it means the low-value-add ones go away. AI easily replaces them. But for the high-value ones who bring incredible creative direction to projects, I think they get better and become even more important. AI is creative rocket fuel. But you still need someone who can direct, who has taste, and who can decide what story the project should tell.

Cover photo by Serhii Hanushchak on Unsplash