Re: Two challenges related to KR of scientific papers and books

If you want an natural language notation for math, you might be interested in EasyMath from work in the late nineties:

> EzMath provides an easy to learn notation for embedding mathematical expressions in Web pages. The notation is inspired by how expressions are spoken aloud together with a few abbreviations for conciseness (e.g. x^y denotes x raised to the power y).

 
See:

 https://www.w3.org/People/Raggett/EzMath/
 https://www.w3.org/People/Raggett/EzMath/EzMathPaper.html

Sadly, the browser plugin is now defunct as it relies on an interface long abandoned by modern browsers.  It wouldn’t be that hard (one week's work) to reimplement it as a JavaScript library using the HTML CANVAS element as its target.

However, that is a million miles from work on AI agents like Minerva.

Minerva is a sophisticated deep learning based system. It starts from general purpose large language model (PaLM) and refines it with training against a mathematical dataset, producing impressive results.

 https://arxiv.org/pdf/2206.14858.pdf

However, the approach described in the paper (linked above) is limited to agents with a single purpose. For agents designed for general purposes, we need a more flexible approach. That is why I am proposing work on direct manipulation of latent semantics, along with mimicking the way that the brain separates different kinds of knowledge across different parts of the cortex. The idea is to combine intuitive (System 1) thinking with deliberative, analytic thinking (System 2).  Minerva only supports the former.

> On 21 Nov 2022, at 10:00, Paola Di Maio <paola.dimaio@gmail.com> wrote:
> 
> You and I are on different planets, and speak different languages :-)

So it seems. :-)

Dave Raggett <dsr@w3.org>