6 ms·

Being able to measure our successes and failures is the first step towards better algorithms :) This is always exciting. I don't think anyone thought that vanil

Being able to measure our successes and failures is the first step towards better algorithms :) This is always exciting. I don't think anyone thought that vanilla CNN architectures were all that would ever be needed. This paper which received an honorable mention this year from NeurIPS conference first attempts to convert the image to a 3d scene before detecting objects. https://arxiv.org/pdf/1906.01618.pdf https://arxiv.org/pdf/1906.01618.pdf

rhizome 7y ago
The thing about AI/CV and other interpretation simulators is that there is always a quantization of nature in the end result. This is why the Uncanny Valley exists, "Uncanny Valley" being a term that refers to the difference between nature and the model itself, and I'm pretty sure it can't be engineered out of the technology. That is, the simulator can not picture an object from any angle, only an angle greater than its mathematical-precision limits. Analog vs. digital doesn't always have to be about audio. ;) So, "construct an internal 3D model of [something in the natural world]" will always be deficient, and any conclusions derived from these models will always have inherent errors (even before you get to algo bias). Self-driving cars, airport face-reading gates, Pixar blockbusters...their models can never represent reality in anything but a temporarily-convincing way. Those that affect policy and peoples' lives (aka not-entertainment) will always come up with the wrong conclusion sometimes, sometimes fatally. https://en.wikipedia.org/wiki/Uncanny_valley https://en.wikipedia.org/wiki/Uncanny_valley
- nl 7y ago
  > This is why the Uncanny Valley exists, "Uncanny Valley" being a term that refers to the difference between nature and the model itself That is incorrect. From the Wikipedia page you references: as the appearance of a robot is made more human, some observers' emotional response to the robot becomes increasingly positive and empathetic, until it reaches a point beyond which the response quickly becomes strong revulsion. However, as the robot's appearance continues to become less distinguishable from a human being, the emotional response becomes positive once again and approaches human-to-human empathy levels > The thing about AI/CV and other interpretation simulators is that there is always a quantization of nature in the end result. That's just not true in any meaningful sense. Computer vision can process images with a higher resolution than the human eye can distinguish. > So, "construct an internal 3D model of [something in the natural world]" will always be deficient, and any conclusions derived from these models will always have inherent errors Humans do this too (hence optical illusions). There's no reason to think that machine models can't surpass human models (and in some domains they already do). All models are wrong, but some are useful.
  - mistrial9 7y ago
    humans do not have only one state, one performance criteria or one mood.. on the other hand, of course sensors can read data that humans cannot, for some set of hardware and inputs. I like the comment above. It is too early for large generalization.
  - rhizome 7y ago
    >as the robot's appearance continues to become less distinguishable from a human being, the emotional response becomes positive once again and approaches human-to-human empathy levels The gap implied by "approaches" is where the problems occur, and how that gap is dealt with is where inherent bias in the process(es) fits. >Computer vision can process images with a higher resolution than the human eye can distinguish. The problem is not in the resolution, but the "process" part. Also, "resolution" is not the right word to pivot the situation on, since we'd have to be comparing a digital system with an analog one. >All models are wrong, but some are useful. Useful I'll give you, but for life and death decisions? It's not going to help me evade downvotes, but...not so much.

rhizome 7y ago

The thing about AI/CV and other interpretation simulators is that there is always a quantization of nature in the end result. This is why the Uncanny Valley exists, "Uncanny Valley" being a term that refers to the difference between nature and the model itself, and I'm pretty sure it can't be engineered out of the technology. That is, the simulator can not picture an object from any angle, only an angle greater than its mathematical-precision limits. Analog vs. digital doesn't always have to be about audio. ;) So, "construct an internal 3D model of [something in the natural world]" will always be deficient, and any conclusions derived from these models will always have inherent errors (even before you get to algo bias). Self-driving cars, airport face-reading gates, Pixar blockbusters...their models can never represent reality in anything but a temporarily-convincing way. Those that affect policy and peoples' lives (aka not-entertainment) will always come up with the wrong conclusion sometimes, sometimes fatally. https://en.wikipedia.org/wiki/Uncanny_valley https://en.wikipedia.org/wiki/Uncanny_valley

nl 7y ago
> This is why the Uncanny Valley exists, "Uncanny Valley" being a term that refers to the difference between nature and the model itself That is incorrect. From the Wikipedia page you references: as the appearance of a robot is made more human, some observers' emotional response to the robot becomes increasingly positive and empathetic, until it reaches a point beyond which the response quickly becomes strong revulsion. However, as the robot's appearance continues to become less distinguishable from a human being, the emotional response becomes positive once again and approaches human-to-human empathy levels > The thing about AI/CV and other interpretation simulators is that there is always a quantization of nature in the end result. That's just not true in any meaningful sense. Computer vision can process images with a higher resolution than the human eye can distinguish. > So, "construct an internal 3D model of [something in the natural world]" will always be deficient, and any conclusions derived from these models will always have inherent errors Humans do this too (hence optical illusions). There's no reason to think that machine models can't surpass human models (and in some domains they already do). All models are wrong, but some are useful.
- mistrial9 7y ago
  humans do not have only one state, one performance criteria or one mood.. on the other hand, of course sensors can read data that humans cannot, for some set of hardware and inputs. I like the comment above. It is too early for large generalization.
- rhizome 7y ago
  >as the robot's appearance continues to become less distinguishable from a human being, the emotional response becomes positive once again and approaches human-to-human empathy levels The gap implied by "approaches" is where the problems occur, and how that gap is dealt with is where inherent bias in the process(es) fits. >Computer vision can process images with a higher resolution than the human eye can distinguish. The problem is not in the resolution, but the "process" part. Also, "resolution" is not the right word to pivot the situation on, since we'd have to be comparing a digital system with an analog one. >All models are wrong, but some are useful. Useful I'll give you, but for life and death decisions? It's not going to help me evade downvotes, but...not so much.