Body: <p>I want to make a kind of robotic brain, i.e. a big neural network, which includes an NLP model (for understanding human voice), real-time object recognition system (so that it can identify particular objects), a face recognition model (for identifying faces), etc.</p>
  <p>Is possible to build a huge neural network in which we can combine all these separate models together, so we can use all 3 model's capabilities at same time in parallel?</p>
  <p>For example, if I ask the robot, using the microphone, &quot;Can you see that table or that boy?&quot;, the robot would start recognizing the objects and faces, then answer me back by speaking if it could identify them or not.</p>
  <p>If this is possible, can you kindly share your idea how can I implement this? Or is there any better to make such AI (e.g. in TensorFlow)?</p>
  
Comments.ContentLicense: CC BY-SA 4.0
Comments.CreationDate: 2021-05-24T11:23:42.647Z
Comments.Text: I got the same idea. Did you find any papers/researches on combining several different neuron networks?
Comments.UserDisplayName: Yijiang Dong
Comments.ContentLicense: CC BY-SA 4.0
Comments.CreationDate: 2021-05-24T12:25:38.687Z
Comments.Text: It seems that you want to build something like the robot [_Sophia_](https://en.wikipedia.org/wiki/Sophia_(robot)), which can recognize objects and faces, and answering you by speaking out loud. According to [Ben Goertzel](https://www.linkedin.com/pulse/sophias-ai-ben-goertzel/), Sophia was partially built on top of [OpenCog](https://opencog.org/), so maybe that's the software tool you are looking for, but note that this tool does not use just neural networks.
Comments.UserDisplayName: nbro
Tags: <neural-networks><deep-learning><tensorflow><reference-request><robots>
Title: Can we combine multiple different neural networks in one?
UserDisplayName: Rahul Vansh
ThreadText: # Can we combine multiple different neural networks in one?
  
  (Asked by: username_0 on 2018-10-15)
  
  I want to make a kind of robotic brain, i.e. a big neural network, which includes an NLP model (for understanding human voice), real-time object recognition system (so that it can identify particular objects), a face recognition model (for identifying faces), etc.
  
  Is possible to build a huge neural network in which we can combine all these separate models together, so we can use all 3 model's capabilities at same time in parallel?
  
  For example, if I ask the robot, using the microphone, "Can you see that table or that boy?", the robot would start recognizing the objects and faces, then answer me back by speaking if it could identify them or not.
  
  If this is possible, can you kindly share your idea how can I implement this? Or is there any better to make such AI (e.g. in TensorFlow)?
  
  **Tags:** neural-networks, deep-learning, tensorflow, reference-request, robots
  
  > **Comments:**
  > **username_1**: I got the same idea. Did you find any papers/researches on combining several different neuron networks?  
  > **username_2**: It seems that you want to build something like the robot [_Sophia_](https://en.wikipedia.org/wiki/Sophia_(robot)), which can recognize objects and faces, and answering you by speaking out loud. According to [Ben Goertzel](https://www.linkedin.com/pulse/sophias-ai-ben-goertzel/), Sophia was partially built on top of [OpenCog](https://opencog.org/), so maybe that's the software tool you are looking for, but note that this tool does not use just neural networks.  
  
  ---
  
  ## 0 answers
  
  