Answers.Body: <p>What you're describing falls under the concept of <a href="https://en.wikipedia.org/wiki/Depth_map" rel="nofollow noreferrer">depth map</a> as a subset of computer vision.</p>
  <blockquote>
  <p>In 3D computer graphics and computer vision, a depth map is an image or image channel that contains information relating to the distance of the surfaces of scene objects from a viewpoint. The term is related (and may be analogous) to depth buffer, Z-buffer, Z-buffering, and Z-depth.</p>
  </blockquote>
  <p>The AI task here is called <a href="https://keras.io/examples/vision/depth_estimation/" rel="nofollow noreferrer">Monocular depth estimation</a>. Here's an example Keras code you can run.</p>
  <blockquote>
  <p>Depth estimation is a crucial step towards inferring scene geometry from 2D images. The goal in monocular depth estimation is to predict the depth value of each pixel or inferring depth information, given only a single RGB image as input. This example will show an approach to build a depth estimation model with a convnet and simple loss functions.</p>
  </blockquote>
  <p>Since it's apparently a specialized application, it's not general in the sense of <a href="https://en.wikipedia.org/wiki/Artificial_general_intelligence" rel="nofollow noreferrer">AGI</a>.</p>
  <blockquote>
  <p>Artificial general intelligence (AGI) is a type of artificial intelligence (AI) that matches or surpasses human cognitive capabilities across a wide range of cognitive tasks. This contrasts with narrow AI, which is limited to specific tasks... The timeline for achieving AGI remains a subject of ongoing debate among researchers and experts. As of 2023, some argue that it may be possible in years or decades; others maintain it might take a century or longer; and a minority believe it may never be achieved.</p>
  </blockquote>
  
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Answers.Text: I like the tone of this answer - you are hired.
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Body: <p>I have played around with StyleGAN and now recently familiarized myself with Apple DepthPro. Now, DepthPro models a 2D frame input to 3rd dimension for the input image i.e generates the depth information map.</p>
  <p>But what is this depth information AI based generation called; is it modeling, generating or even perhaps &quot;figuring out&quot;? Also it surely does it better than I could never achieve.</p>
  <p>For reference this YouTube video I made <a href="https://youtu.be/3TdwTyOnRv4" rel="nofollow noreferrer">https://youtu.be/3TdwTyOnRv4</a> and am still struggling with the idea what my part, making this all visible the way I want, is.</p>
  <p>But truthfully I've yet to decide is the video mentioned above AI generated or not too.</p>
  
Tags: <computer-vision>
Title: Does Apple DepthPro model reach AGI level
UserDisplayName: harism
ThreadText: # Does Apple DepthPro model reach AGI level
  
  (Asked by: username_0 on 2024-11-29)
  
  I have played around with StyleGAN and now recently familiarized myself with Apple DepthPro. Now, DepthPro models a 2D frame input to 3rd dimension for the input image i.e generates the depth information map.
  
  But what is this depth information AI based generation called; is it modeling, generating or even perhaps "figuring out"? Also it surely does it better than I could never achieve.
  
  For reference this YouTube video I made <https://youtu.be/3TdwTyOnRv4> and am still struggling with the idea what my part, making this all visible the way I want, is.
  
  But truthfully I've yet to decide is the video mentioned above AI generated or not too.
  
  **Tags:** computer-vision
  
  
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  ## 1 answers
  
  ### Answer by username_1 on 2024-11-29. Score: 4 | Accepted answer
  
  What you're describing falls under the concept of [depth map](https://en.wikipedia.org/wiki/Depth_map) as a subset of computer vision.
  
  > In 3D computer graphics and computer vision, a depth map is an image or image channel that contains information relating to the distance of the surfaces of scene objects from a viewpoint. The term is related (and may be analogous) to depth buffer, Z-buffer, Z-buffering, and Z-depth.
  
  The AI task here is called [Monocular depth estimation](https://keras.io/examples/vision/depth_estimation/). Here's an example Keras code you can run.
  
  > Depth estimation is a crucial step towards inferring scene geometry from 2D images. The goal in monocular depth estimation is to predict the depth value of each pixel or inferring depth information, given only a single RGB image as input. This example will show an approach to build a depth estimation model with a convnet and simple loss functions.
  
  Since it's apparently a specialized application, it's not general in the sense of [AGI](https://en.wikipedia.org/wiki/Artificial_general_intelligence).
  
  > Artificial general intelligence (AGI) is a type of artificial intelligence (AI) that matches or surpasses human cognitive capabilities across a wide range of cognitive tasks. This contrasts with narrow AI, which is limited to specific tasks... The timeline for achieving AGI remains a subject of ongoing debate among researchers and experts. As of 2023, some argue that it may be possible in years or decades; others maintain it might take a century or longer; and a minority believe it may never be achieved.
  
  > **Comments:**
  > **username_0**: I like the tone of this answer - you are hired.  
  
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