Additional examples for the first discussion
Give DALL.E a piece of WL code that produces a graphics and that is not straightforward to predict in detail. It is interesting (and entertaining) to see how it ‘understands’ the code and predicts what the result could look like.

DALL·E 2 prompt

Analyze the following code carefully and make an artistic rendering of how you think the result would look like:

The Wolfram Language input code and its output graphics

ListDensityPlot[Abs[Fourier[Table[1/LCM[i,j],{i,256},{j,256}]]],​​Mesh->False]

DALL-E AI prediction from reading the input code

The Wolfram Language input code and its output graphics

In[]:=
ContourPlotAbs[1/(x+Iy)-Floor[1/(x+Iy)]],​​ {x,-1.1,1.1},{y,-1.1,1.1},Exclusions->None,PlotPoints->50,​​ColorFunction->Function[Blend[{Pink,Black},#]]

DALL-E AI prediction from reading the input code

The Wolfram Language input code and its output graphics

In[]:=
ListContourPlot[Table[Random[],{36},{36}],ColorFunction->Function[Blend[{Darker[Yellow],Darker[Brown]},#]],​​InterpolationOrder->4,Frame->False]
Out[]=

DALL-E AI prediction from reading the input code

The Wolfram Language input code and its output graphics

In[]:=
ListContourPlot[Table[If[EvenQ[#],1,0]&[(n+m)(n-m+1)/2],{n,25},{m,25}],ColorFunction->Function[Blend[{Purple,Darker[Green]},(Cos[2Pi#]+1)/3]],​​InterpolationOrder->1,Frame->False,PlotRange->All]
Out[]=

DALL-E AI prediction from reading the input code

The Wolfram Language input code and its output graphics

In[]:=
ContourPlot[Evaluate[(#==0)&/@ReIm[Product[(x+Iy)-(RandomReal[]+IRandomReal[]),{60}]]],​​{x,0,1},{y,0,1},​​(*usemanyplotpointstoachievehighresolution*)​​PlotPoints->100,PlotRange->All,​​FrameTicks->None,Frame->False,​​ContourStyle->{Red,Blue}]
Out[]=

DALL-E AI prediction from reading the input code

The Wolfram Language input code and its output graphics

In[]:=
ContourPlot[Arg[ArcTan[Tan[(x+Iy)^(-1)]]],​​{x,-2/Pi,2/Pi},{y,-1/Pi,1/Pi},​​PlotPoints->100,ContourLines->False,Exclusions->None,​​PlotRange->All,ColorFunction->Function[Blend[{Orange,Blue},Abs[Sin[12#]]]],​​AspectRatio->Automatic,Contours->100]

DALL-E AI prediction from reading the input code

The Wolfram Language input code and its output graphics

intersectionPicture[δ_,opts___]:=​​Show[{(*thecontourplot*)​​ContourPlot[(y-Pi/((x-δ)^2+1)Sin[12(x-δ)])​​(x-Pi/((y-δ)^2+1)Sin[12(y-δ)]),​​{x,-Pi,Pi},{y,-Pi,Pi},​​PlotPoints->100,Contours->{0},ContourLines->False,​​PlotRange->All,FrameTicks->None],​​(*y=y(x)curve*)​​ParametricPlot[{x,Pi/((x-δ)^2+1)Sin[12(x-δ)]},​​{x,-Pi,Pi},PlotRange->All,PlotPoints->100,​​PlotStyle->{Blue,Thickness[0.01]}],​​(*x=x(y)curve*)​​ParametricPlot[{Pi/((x-δ)^2+1)Sin[12(x-δ)],x},​​{x,-Pi,Pi},PlotRange->All,PlotPoints->100,​​PlotStyle->{Yellow,Thickness[0.01]}]},opts,Frame->False];​​​​intersectionPicture[Pi/2]
Out[]=

DALL-E AI prediction from reading the input code

The Wolfram Language input code and its output graphics

With[{n=14},​​Module[{M,α},​​(*matrixtobediagonalizedforvariousΦ*)​​Set@@{M[α_],N[makeLhsMatrix[n,Φ]]};​​(*showgraphicofeigenvalues*)​​Graphics[{Thickness[0.002],PointSize[0.003],Lighter[Red],​​(*mirroratΦ=1/2*)​​{#,Apply[{#1,1-#2}&,#,{-2}]}&[Line/@Transpose[​​Table[Re[{#,Φ}]&/@Sort[Eigenvalues[M[Φ]]],​​{Φ,0.,1/2.,1/2./(n-1)^2}]]]}/.​​(*forbettervisibilityonscreen*)​​Line[l_]:>Point/@l,AspectRatio->1,​​Background->Yellow,PlotRange->All]]]
Out[]=

DALL-E AI prediction from reading the input code

The Wolfram Language input code and its output graphics

{ℋ0,ℋ1}=With[{n=12},Table[(#1+Transpose[#1]&)[Table[If[i>j,0.,2Random[]-1],{i,n},{j,n}]],{2}]];​​​​minEigenvalueDistance[ℋ_?MatrixQ]:=Module[{evs=Eigenvalues[ℋ],n=Length[ℋ]},Min[Table[Min[Table[Abs[evs〚i〛-evs〚j〛],{j,i+1,n}]],{i,1,n-1}]]]​​​​ParametricPlot3D[{αrCos[αφ],αrSin[αφ],-Log[minEigenvalueDistance[N[(1-αrExp[αφ])ℋ0+αrExp[αφ]ℋ1]]]},{αr,0,2.5},{αφ,0,2π},BoxRatios{1,1,0.6},PlotRange{All,All,{-1,5}},PlotStyle->Directive[GrayLevel[0.3],Specularity[Red,10]],Mesh->None]
Out[]=

DALL-E AI prediction from reading the input code

The Wolfram Language input code and its output graphics

(*makeoneelementarypartofthesignpost*)​​post[α_,dir_,ortho_,size_]:=​​Module[{dir1,orthoh,ortho1,bi,p1,p2,p3,p4,p5,p6,p7,p8,p9,​​s1=1,s2=0.3,s3=0.2,s4=1.2,h1,h2,h3,h4,h5},​​(*directionthenewsignwillpointto*)​​dir1=Normalize[dir];​​(*firstorthogonaldirection*)​​ortho1=Normalize[Normalize[ortho]+Normalize[Cross[dir,ortho]]];​​(*secondorthogonaldirection*)​​bi=Normalize[Cross[dir1,ortho1]];​​h1=s2sizeortho1;h2=s2sizebi;​​h3=s3sizeortho1;h4=s3sizebi;​​h5=s1sizedir1;​​p1=α+h1;p2=α+h2;p3=α-h1;p4=α-h2;​​p5=α+h3+h5;p6=α+h4+h5;p7=α-h3+h5;​​p8=α-h4+h5;p9=α+s4sizedir1;​​(*polygonsformingthenextgeneration*)​​Polygon/@{{p1,p4,p8,p5},{p4,p3,p7,p8},{p3,p2,p6,p7},​​{p2,p1,p5,p6},{p5,p9,p8},{p8,p7,p9},​​{p6,p7,p9},{p5,p6,p9}}]​​​​(*thestartpart*)​​postHierarchy[0]={post[{0.,0.,0.},{0.,0.,1.},{1.,0.,0.},1]};​​​​(*addnewpartsatthesides*)​​postHierarchy[i_]:=postHierarchy[i]=(post@@newData[#,0.4^i])&/@Flatten[(Take[#,4]&/@postHierarchy[i-1])];​​​​(*iteratetheprocess*)​​newData[poly_Polygon,size_]:=​​Module[{f=poly[[1]],ortho,dir,p},ortho=(f[[1]]+f[[2]])/2-(f[[3]]+f[[4]])/2;​​p=(f[[3]]+f[[4]])/2+0.2ortho;​​dir=-Cross[f[[1]]-f[[2]],f[[1]]-f[[4]]];​​{p,dir,ortho,size}]
In[]:=
Show[Graphics3D[{EdgeForm[Thickness[0.001]],Table[postHierarchy[i],{i,0,4}]}]]
Out[]=

DALL-E AI prediction from reading the input code

The Wolfram Language input code and its output graphics

polys=Map[2(#-1/2)&,MeshPrimitives[MengerMesh[3,3],{2}],{-2}];​​​​twist[{x_,y_,z_}]:=RotationTransform[Pi/2z,{0,0,1}][{x,y,z}];​​​​twist[Polygon[l_]]:=Polygon[twist/@l]​​​​Graphics3D[twist/@polys]

DALL-E AI prediction from reading the input code

CITE THIS NOTEBOOK

DALL-E AI artistic renderings predicted from graphics-generating code: Part II​
by Michael Trott​
Wolfram Community, STAFF PICKS, January 29, 2024
​https://community.wolfram.com/groups/-/m/t/3112314