Re: List of possible deliverables and position papers for AIKR CG

This line of analysis, mapping the family trees and identifying gaps  could
be a good starting point for the work you propose

On Tue, May 30, 2023 at 6:29 PM ProjectParadigm-ICT-Program <
metadataportals@yahoo.com> wrote:

> Another useful paper is:
> Harnessing the Power of LLMs in Practice: A Survey on ChatGPT and Beyond
> https://arxiv.org/abs/2304.13712
>
> The current situation of the proliferation of OpenAi and other original
> creator derived products is starting to look a lot like a collection of
> family trees of Linux distros.
>
> Garrido et alii have provided a good starting point, but there are quite a
> few more family trees.
>
>
> Milton Ponson
> GSM: +297 747 8280
> PO Box 1154, Oranjestad
> Aruba, Dutch Caribbean
> Project Paradigm: Bringing the ICT tools for sustainable development to
> all stakeholders worldwide through collaborative research on applied
> mathematics, advanced modeling, software and standards development
>
>
> On Monday, May 29, 2023 at 01:28:29 PM AST, Paola Di Maio <
> paola.dimaio@gmail.com> wrote:
>
>
> Thank you Milton
> The idea of identifying categories of generative AI is valid, imho
> First step would be to gather the field, ie, make a short summary of
> existing literature (what about this paper, for example?)
> *A Complete Survey on Generative AI (AIGC): Is ChatGPT from GPT-4 to GPT-5
> All You Need? https://arxiv.org/abs/2303.11717
> <https://arxiv.org/abs/2303.11717>*
>
> https://medium.com/@eduardogarrido90/chatgpt-is-not-all-you-need-a-quick-summary-of-the-generative-ai-taxonomy-e2b8b47a9851
> is there anything missing in this paper that our list could add?
>
> Rendering in Stratml would be a separate thing, that  can be done at the
> end (so that the taxonomy ontology can be rendered in any xml format)
> surely Owen can take care of the stratml part when we get there, but imho
> the taxonomy should exist as plain text in the first place
>
> On Mon, May 29, 2023 at 5:24 PM ProjectParadigm-ICT-Program <
> metadataportals@yahoo.com> wrote:
>
> Dear all,
>
> Open AI, Microsoft, Google and Meta have opened Pandora's Box and set in
> motion an unstoppable development push of generative LLMs and generative
> audio and visual AI applications.
>
> Countless experts and the "godfather of AI" have made comments on the
> current state of AI and painted a varied panorama of scenarios ranging from
> doomsday and human race annihilation to AI as replacing domestic assistants
> (in embodied form) and other assistive functions (replacing humans in quite
> a few instances).
>
> There are three issues that will have an impact on further development:
> (1) the sheer size of the data sets and variable count of the programs and
> the amount of computing power required for general all purpose LLM chatbot
> applications;
> (2) in making online search chatbot powered increases the energy
> footprints of online search to the extent that chatbot related activities
> could lead to a 2-3% increase in CO2 emissions and require additional
> investments and space for data centers;
> (3) bias, error and unwanted emergent abilities will severe limit open,
> explainable, accountable, safe and trustworthy utilization in many
> industries and fields, e.g. in health care, social services and judicial
> systems.
>
> There are several approaches now being proposed to tackle all three issues.
>
> The focus on few shot, zero shot, limited domains of discourse and reduced
> equipment and power consumption solutions, and in some scenarios moving the
> computing from the cloud to the edge.
>
> When we look at how humans learn in school, and other levels of education
> it makes sense to use learning materials that are (1) curated/peer
> reviewed, (2) limited in scope by their application or as part of a modular
> approach to a a specific profession or academic discipline, (3) limited in
> size of text or audiovisual content.
>
> The learning from practice and experience component in humans is slightly
> more complicated and is the subject of many overlapping disciplines from
> biology, biochemistry, cognition and neuroscience to psychology, philosophy
> and quantum physics.
>
> I would like to propose making an inventory of categories of generative AI
> applications currently on the market and being developed, where possible
> mapped to their respective utilization in which fields, and listing for
> their utilization current issues that are of concern to their openness,
> explainability, accountability, safety and trustworthiness.
>
> There are several conceptual diagrams for defining artificial intelligence
> and we could pick a limited number for categorization, one for general
> purpose like the one from the high level expert group on AI of the EU to
> some conceptual models used in industry or academe that focus on particular
> general areas or narrow focus fields of application.
>
> Since the open, explainable, accountable, safe and trustworthy use of
> generative AI will require academics, industry, civil society and
> legislators to find common ground in terms of what needs to be addressed,
> this proposal makes sense.
>
> We can use StratML to help make the strategic planning process automated,
> and get support of academia in generating literature and systematic reviews
> of the status quo and state of the art of conceptual models and application
> of generative AI
>
> And because we as a community group are focused on the knowledge
> representation, we make this the defining ingredient for the proposed work
> to be done.
>
> Milton Ponson
> GSM: +297 747 8280
> PO Box 1154, Oranjestad
> Aruba, Dutch Caribbean
> Project Paradigm: Bringing the ICT tools for sustainable development to
> all stakeholders worldwide through collaborative research on applied
> mathematics, advanced modeling, software and standards development
>
>