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From: Mild Shock <janburse@fastmail.fm>
Newsgroups: sci.logic
Subject: Linear Algebraic Approaches to Logic Programming (Was: NVIDIA Jetson
 Orin controlled by Prolog)
Date: Fri, 3 Jan 2025 22:30:25 +0100
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Hi,

Maybe one can get a better grip of an intimate
relationship, simply by some hands on?

Linear Algebraic Approaches to Logic Programming

Katsumi Inoue (National Institute of Informatics, Japan)

Abstract: Integration of symbolic reasoning and machine
learning is important for robust AI.  Realization of
symbolic reasoning based on algebraic methods is promising
to bridge between symbolic reasoning and machine learning,
since algebraic data structures have been used in machine
learning. To this end, Sakama, Inoue and Sato have defined
notable relations between logic programming and linear
algebra and have proposed algorithms to compute logic
programs numerically using tensors.  This work has been
extended in various ways, to compute supported and stable
models of normal logic programs, to enhance the efficiency
of computation using sparse methods, and to enable abduction
for abductive logic programming.  A common principle in
this approach is to formulate logical formulas as vectors/
matrices/tensors, and linear algebraic operations are
applied on these elements for computation of logic programming.
Partial evaluation can be realized in parallel and by 
self-multiplication, showing the potential for exponential
speedup.  Furthermore, the idea to represent logic programs
as tensors and matrices and to transform logical reasoning
to numeric computation can be the basis of the differentiable
methods for learning logic programs.

https://www.iclp24.utdallas.edu/invited-speakers/

Mild Shock schrieb:
> Hi,
> 
> Ok this one is only 250 bucks for a TPU:
> 
> Introducing NVIDIA Jetson Orin™ Nano Super
> https://www.youtube.com/watch?v=S9L2WGf1KrM
> 
> Now I am planning to do the following:
> 
> Create a tensor flow DSL.
> 
> With these use cases:
> 
> - Run the tensor flow DSL locally in
>    your Prolog system interpreted.
> 
> - Run the tensor flow DSL locally in
>    your Prolog system compiled.
> 
> - Run the tensor flow DSL locally on
>    your Tensor Processing Unit (TPU).
> 
> - Run the tensor flow DSL remotely
>    on a compute server.
> 
> - What else?
> 
> Maybe also support some ONNX file format?
> 
> Bye