definitions, problem spaces, methods

Dave asks for definitions, Adeel asks why is this CG called AI KR CG
Milton now wants to see KR bible

I ll comment quickly and take this opportunity to create a new diagram
<https://docs.google.com/document/d/1lYn8-YUvIS_k1rezgqdR0DX2BLTRYpvkJpmvYjAEpng/edit?usp=sharing>
since answering these questions can serve as reorientation also for folks
who joined recently

1. Dave, definitions for KR are to be found in the many textbooks and
papers, some of which are linked to our pages (need to reorganise pointers
to resources). KR is an established field. I cannot answer all your
personal questions that relate to the field. if you study the books,(take
my course?) you'll find your answers. most graduate courses do not contain
answers to new research questions, this is why we become researchers
You need to study the references and pick a definition that fits what you
are trying to do. The example you pointed to yesterday (some ML that
identifies deepfakes) uses KR, thanks for bringing it up. Why dont you dig
up the code and analyze and look into how this NN uses KR to solve the
deepfake problem? That would be very interesting-

2.Adeel, this CG is called AI KR because it addresses the problems caused
by lack of KR in ML. It was started because some years ago, AI went mad
with NN/ML without KR and I started getting nighmares of a world run by
unintelligent machines (you should have seen the papers in top conferences,
I was in agony)  This CG pointed out that KR needs to be in the picture to
make AI intelligence
 We have succeeded. KR is now back in the AI/ML learning picture
The topics we have discussed here are being picked up by researchers (yes,
plagiarized and published under their own name) Universities have started
looking for PhD students in the field of KR applied to AI/ML
I am glad something has been achieved.
 There are gaps to be filled, contributions to be made

3. Milton, the KR bible/s  have been written decades ago, then forgotten
We may be able to add future chapters, KR now needs to be understood and
practiced in the context of these powerful new technologies coming out from
labs. NN coupled with KR (hybrid) are the way forward
This is what people have been working on thirty years ago already
Your idea to start relating the work of this CG to knowledge representation
challenges is good, maybe we can find some use cases in other CGs (I am a
member of a couple of other CGs and have shared on the list a few posts
where the problems they were trying to address are clearly related to KR
that we could look at

PDM