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Fix(Docs): Missing images in tutorials #110

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2 changes: 1 addition & 1 deletion docs/_sources/education/blogs/moving_ai_beyond_its_narrow_view_of_intelligence.md.txt
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Expand Up @@ -41,7 +41,7 @@ We expect that any decision-making system should be able to apply logical rules
really not be there, since our network only needs 3 neurons to compute on
such knowledge:

<img src="https://raw.githubusercontent.com/IBM/LNN/master/docs/source/education/blogs/raining_implies_wet.png" alt="It is raining Implies the grass is wet" width="320" class="aligncenter">
<img src="https://raw.githubusercontent.com/IBM/LNN/master/docsrc/source/education/blogs/raining_implies_wet.png" alt="It is raining Implies the grass is wet" width="320" class="aligncenter">

Logic also allows us to build high-level decision makers that can reason about
outcomes given only partial information about the world. Lets add some more
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2 changes: 1 addition & 1 deletion docs/_sources/introduction.md.txt
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Original file line number Diff line number Diff line change
@@ -1,6 +1,6 @@
# Logical Neural Networks

<img src="https://raw.githubusercontent.com/IBM/LNN/master/docs/images/lnn_structure.png" alt="LNN structure" width="400" class="aligncenter"/>
<img src="https://raw.githubusercontent.com/IBM/LNN/master/docsrc/images/lnn_structure.png" alt="LNN structure" width="400" class="aligncenter"/>

The LNN is a form of recurrent neural network with a 1-to-1 correspondence to a set of logical formulae in any of
various systems of ___weighted, real-valued logic___, in which evaluation performs logical inference. The graph
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2 changes: 1 addition & 1 deletion docs/education/blogs/moving_ai_beyond_its_narrow_view_of_intelligence.html
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Expand Up @@ -394,7 +394,7 @@ <h2 id="why-a-logical-representation-is-important">
really not be there, since our network only needs 3 neurons to compute on
such knowledge:
</p>
<img alt="It is raining Implies the grass is wet" class="aligncenter" src="https://raw.githubusercontent.com/IBM/LNN/master/docs/source/education/blogs/raining_implies_wet.png" width="320"/>
<img alt="It is raining Implies the grass is wet" class="aligncenter" src="https://raw.githubusercontent.com/IBM/LNN/master/docsrc/source/education/blogs/raining_implies_wet.png" width="320"/>
<p>
Logic also allows us to build high-level decision makers that can reason about
outcomes given only partial information about the world. Lets add some more
Expand Down
2 changes: 1 addition & 1 deletion docs/introduction.html
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Expand Up @@ -264,7 +264,7 @@ <h1 id="introduction--page-root">
</a>
</h1>
<img alt="LNN structure" class="aligncenter" src="https://raw.githubusercontent.com/IBM/LNN/master/docs/images/lnn_structure.png" width="400"/>
<img alt="LNN structure" class="aligncenter" src="https://raw.githubusercontent.com/IBM/LNN/master/docsrc/images/lnn_structure.png" width="400"/>
<p>
The LNN is a form of recurrent neural network with a 1-to-1 correspondence to a set of logical formulae in any of
various systems of
Expand Down
2 changes: 1 addition & 1 deletion docsrc/source/education/blogs/moving_ai_beyond_its_narrow_view_of_intelligence.md
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -41,7 +41,7 @@ We expect that any decision-making system should be able to apply logical rules
really not be there, since our network only needs 3 neurons to compute on
such knowledge:

<img src="https://raw.githubusercontent.com/IBM/LNN/master/docs/source/education/blogs/raining_implies_wet.png" alt="It is raining Implies the grass is wet" width="320" class="aligncenter">
<img src="https://raw.githubusercontent.com/IBM/LNN/master/docsrc/source/education/blogs/raining_implies_wet.png" alt="It is raining Implies the grass is wet" width="320" class="aligncenter">

Logic also allows us to build high-level decision makers that can reason about
outcomes given only partial information about the world. Lets add some more
Expand Down
2 changes: 1 addition & 1 deletion docsrc/source/introduction.md
View file
Open in desktop
Original file line number Diff line number Diff line change
@@ -1,6 +1,6 @@
# Logical Neural Networks

<img src="https://raw.githubusercontent.com/IBM/LNN/master/docs/images/lnn_structure.png" alt="LNN structure" width="400" class="aligncenter"/>
<img src="https://raw.githubusercontent.com/IBM/LNN/master/docsrc/images/lnn_structure.png" alt="LNN structure" width="400" class="aligncenter"/>

The LNN is a form of recurrent neural network with a 1-to-1 correspondence to a set of logical formulae in any of
various systems of ___weighted, real-valued logic___, in which evaluation performs logical inference. The graph
Expand Down