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Original Subject established by Chinese Scientists [Extenics] (Re: LRM moving from FOM to TCS [Lean Prover])

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Hi,

Now "white science" might have more leaning
towards Causal AI. But sometimes I have the
feeling Generative AI is the "yellow science"

now. DeepSeek left handedly inventing the
notation M(a,b) for matrix representation of
a dual number a + b e:

M(a,b) = a I + b E

And then discussing variants like:

E = [[ 0 1 ]
      [ 0 0 ]]

Or this variant like:

E = [[ 1 -1 ]
      [ 1 -1 ]]

I am in mild shock! Then I am reading the small print:

Prof. Cai Wen, Institute of Extenics and Innovative Methods, Guangzhou,
https://fs.unm.edu/DualNumbers.pdf

What is Extenics? Any ideas?

Have Fun!

Bye

Mild Shock schrieb:
 > Hi,
 >
 > Large Reasoning Models (LRM) seem to move from
 > Foundation of Mathematics (FOM) to Theoretical
 > Computer Science (TCS). FOM typically gives
 >
 > you "white science" mathematics, with sets and
 > infinity, if you are lucky a little recursion
 > theory. Fun fact TCS is even more "white".
 >
 > Interesting paper in as far:
 >
 > Lean Meets Theoretical Computer Science:
 > Scalable Synthesis of Theorem Proving Challenges
 > in Formal-Informal Pairs
 > Terry Jingchen Zhang et. al. - 2025
 > https://arxiv.org/abs/2508.15878v1
 >
 > One swallow does not make a summer?
 >
 > But its probably a necessary step. The above
 > paper using Busy Beaver and Interger Constraints
 > as examples. What logical frameworks do even
 >
 > apply, is it enough to have a "total function"
 > theory layer, or does TCS need more. TCS can
 > be heavy on all sort of discrete and
 >
 > non-discrete mathematics.
 >
 > Bye
 >
 > Mild Shock schrieb:
 >  > Hi,
 >  >
 >  > Geoffrey E. Hinton, the Nobel Prize winner
 >  > for AI. He was already beating the drums
 >  > for ReLU in 2010:
 >  >
 >  > HRectified Linear Units Improve Restricted Boltzmann Machines
 >  > Geoffrey E. Hinton & Vinod Nair - 2010
 >  > https://www.cs.toronto.edu/~fritz/absps/reluICML.pdf
 >  >
 >  > Because ANNs (Artificial Neural Networks) were originally
 >  > designed with other functions, e.g. with Logistic function:
 >  >
 >  > An artificial neuron is a mathematical function conceived
 >  > as a model of a biological neuron in a neural network.
 >  > https://en.wikipedia.org/wiki/Artificial_neuron
 >  >
 >  > If you populate additive factor graphs with log P,
 >  > you basically get multiplicative factor graphs.
 >  > So an ANN can express belief networks, right?
 >  >
 >  > Bye
 >  >
 >  > P.S.: What is all the hype about Causal AI, and
 >  > the Ladder of Causation à la Judea Pearl?
 >  >
 >  > Causal AI – the next gen AI
 >  > Prof. Sotirios A. Tsaftaris - 2025
 >  > https://www.youtube.com/watch?v=IelslFzdsYw
 >

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