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You might be missing the forest for the trees. Digital twins are already used today. 3D Scanning adoption is growing quickly across a whole range of industries.

by rsp1984 6y ago

You might be missing the forest for the trees. Digital twins are already used today. 3D Scanning adoption is growing quickly across a whole range of industries. Billions of dollars change hands for AR/VR products and experiences. Also, on the technology side, there's tons that can be done on the edge these days. Those petabytes of data you mention can be crunched down to mere gigabytes before reaching the cloud. Adoption of spatial computing will not be binary "once someone pulls it off". It's going to be gradually, step after step.

mlyle 6y ago
> Digital twins are already used today. 3D Scanning adoption is growing quickly across a whole range of industries. You might be considering a lot broader things to be spatial computing that are short of the sense being considered here. Yes, representing objects and annotating trivial scenes is interesting and is starting to happen today. But free-form automated representation of the environment in ways that the spatial shortcuts we rely upon ("inside", "on top of", etc) can be used, (non-graph) paths of different types can be solved, and actuator kinematics can find and interact with things, etc: it's really hard. AR and VR and being able to interact with object meshes and geometry is a start. But computational geometry and encoding world constraints in a useful way is really hard. We'll snatch some incremental parts from AR and vision research, but we'll need some breakthroughs in the space, too, to do the really cool stuff.
jandrewrogers 6y ago
You are focusing on the trivial narrow case, which is not where the value is. The broad case is reproducing a real-time mirror of some part of the planet in arbitrary detail from data. Reality running on a computer. Nothing you are talking about addresses that. I know all of this tech, I’ve worked with it operationally across many industries. At its core, spatial computing is about queryable reality. 3D scanning of objects, AR/VR, etc are all adjuncts to this. They are ways of consuming the data model or synthesizing non-real parts, not creating the base model of reality. The latter is the hard part, the rest doesn’t matter in the big picture.
- rsp1984 6y ago
  Believe it or not, but I've also been working first hand with this tech for a long time. As in, actually developing the underlying engines. What you describe is a broad vision that may or may not happen at some point in the future. I agree about the queryable reality part but disagree that AR/VR, 3D scanning etc. "don't matter". Because in a lot of real-life use-cases you don't need the "real-time 3D mirror" but instead can get 80% of the value with something 10% as complex.

mlyle 6y ago

> Digital twins are already used today. 3D Scanning adoption is growing quickly across a whole range of industries. You might be considering a lot broader things to be spatial computing that are short of the sense being considered here. Yes, representing objects and annotating trivial scenes is interesting and is starting to happen today. But free-form automated representation of the environment in ways that the spatial shortcuts we rely upon ("inside", "on top of", etc) can be used, (non-graph) paths of different types can be solved, and actuator kinematics can find and interact with things, etc: it's really hard. AR and VR and being able to interact with object meshes and geometry is a start. But computational geometry and encoding world constraints in a useful way is really hard. We'll snatch some incremental parts from AR and vision research, but we'll need some breakthroughs in the space, too, to do the really cool stuff.

jandrewrogers 6y ago

You are focusing on the trivial narrow case, which is not where the value is. The broad case is reproducing a real-time mirror of some part of the planet in arbitrary detail from data. Reality running on a computer. Nothing you are talking about addresses that. I know all of this tech, I’ve worked with it operationally across many industries. At its core, spatial computing is about queryable reality. 3D scanning of objects, AR/VR, etc are all adjuncts to this. They are ways of consuming the data model or synthesizing non-real parts, not creating the base model of reality. The latter is the hard part, the rest doesn’t matter in the big picture.

rsp1984 6y ago
Believe it or not, but I've also been working first hand with this tech for a long time. As in, actually developing the underlying engines. What you describe is a broad vision that may or may not happen at some point in the future. I agree about the queryable reality part but disagree that AR/VR, 3D scanning etc. "don't matter". Because in a lot of real-life use-cases you don't need the "real-time 3D mirror" but instead can get 80% of the value with something 10% as complex.