4 ms·

> In a few years we will have an accurate digital twin of the world No, you will not, unless you redefine what "accurate" means.

crubier 7y ago
Google has 3D models of cities nowadays. 20years ago we only had 2D maps. Why do you think this trend will not continue?
- Piskvorrr 7y ago
  Collecting more data scales far better than processing more data into information. That's one bottleneck right there.
  - crubier 7y ago
    While this is true about user data, this is definitely not true in the context of real physical world data. Getting a picture from the tip of a wind turbine blade is done with a drone in the best case, or a rope access technician in the worst (legacy) case. Analyzing this picture with AI to identify anomalies takes a few seconds. That’s one of my company’s use cases. In the same way, ask the google maps team about what scales better: flying real airplanes to capture photographic data, or just processing this data to get 3D models... Edit: typo
- pauljurczak 7y ago
  Google Street View is full of artifacts, it's not even close to being accurate. The same goes for satellite imagery of rugged mountains. I'm not even mentioning the vegetation, snow cover, river levels, etc.
  - crubier 7y ago
    Accuracy is relative to the need. By accurate I mean accurate enough that we can extract actionable information from it. For power plant critical structures we want 0.5mm, updated every 6months. For forest management we want 5m, updated every 2 years. But this increase in spatial and temporal accuracy will keep on going. At some point in the future a small swarm of insect-sized drones will be able to capture a whole forest in a day for a super low cost. And a few people walking with basic smartphones for will be enough to map a whole city. In 1980 you would have said that google maps 3D and google street view would never exist...
    - pauljurczak 7y ago
      Well, you just redefined accurate to "accurate enough that we can extract actionable information from it". Your statement is true now. BTW, I never say never.

crubier 7y ago

Google has 3D models of cities nowadays. 20years ago we only had 2D maps. Why do you think this trend will not continue?

Piskvorrr 7y ago
Collecting more data scales far better than processing more data into information. That's one bottleneck right there.
- crubier 7y ago
  While this is true about user data, this is definitely not true in the context of real physical world data. Getting a picture from the tip of a wind turbine blade is done with a drone in the best case, or a rope access technician in the worst (legacy) case. Analyzing this picture with AI to identify anomalies takes a few seconds. That’s one of my company’s use cases. In the same way, ask the google maps team about what scales better: flying real airplanes to capture photographic data, or just processing this data to get 3D models... Edit: typo
pauljurczak 7y ago
Google Street View is full of artifacts, it's not even close to being accurate. The same goes for satellite imagery of rugged mountains. I'm not even mentioning the vegetation, snow cover, river levels, etc.
- crubier 7y ago
  Accuracy is relative to the need. By accurate I mean accurate enough that we can extract actionable information from it. For power plant critical structures we want 0.5mm, updated every 6months. For forest management we want 5m, updated every 2 years. But this increase in spatial and temporal accuracy will keep on going. At some point in the future a small swarm of insect-sized drones will be able to capture a whole forest in a day for a super low cost. And a few people walking with basic smartphones for will be enough to map a whole city. In 1980 you would have said that google maps 3D and google street view would never exist...
  - pauljurczak 7y ago
    Well, you just redefined accurate to "accurate enough that we can extract actionable information from it". Your statement is true now. BTW, I never say never.