We have done this blog, in concert with 7'oops7, since 2007. We started Fedaerated in 2009. Then, in 2010, we started the TGS blog (last post, Technology assessments ...). For the Thomas Gardner Society, Inc. (TGS), as well, we had some publications (Gardner's Beacon). In 2015, we went over to Quora and have been there since. Various excursions were related to using other modes, such as WordPress.
But, we're back to Google and its Blogger. Why? Of all of the xnn/LLM systems that we looked at (granted, the survey was not exhaustive), we liked Bard the best. So, we'll work in that environment. At the same time, we'll touch all of the to other resources on a regular basis. It's just that we'll use this for publishing where we want to support mobile devices.
Of late, we have tried LinkedIn's approach which we look at below. There we published the first of a series. We just completed the third piece what is expected to be five pieces. What we call AIn't is the motive. Truth engineering has been on our table for a long while but was problematic. What did it mean and for what motive is it necessary and why just this?
2023 brought the answer to the questions. Answers have been embedded within these posts all of this time. So, the effort was right on. Let's just say that I was being exhaustive in a way that can only be understood in the academic sense as being highly multidisciplinary. I was retired and had the time and the interest and the ability.
There is no hubris in that comment; rather, it's a nod to a continuation of what I was doing anyway - advanced computional systems - without having the time to be thorough. So, it's time to pull all of the factors together so that we can analyze and perhaps predict and propose changes. For me, being successful at the complete survey of the western civilization's influence on the world is enough of a motive. However, the world is large, so we need to bring into the discussion all other cultures.
Notice that the TGS is based upon the history of the U.S. as an offshoot of the U.K. Be that as it may, we know that New England was not alone. Too, we know the prior history of these regions. Albeit, lessons learned or not over 400 years require attention. BTW, the U.S. started 250 years ago, almost, so that event will get regular mention.
Okay, after seeing ChapGPT and noting the issues, I began discussion with Larry Walker who had run the Knowledge Systems Center for Sperry Univac for which I worked. The focus on "knowledge" was strong for both of us. That was not what we were seeing with the machine learning systems being pushed out. We can discuss that at any level. For now, these posts will be setting the stage for discussions that are pending and necessary.
I became aware of ChatGPT in February of 2023 which was late. I wrote several posts on it and its cohorts and other topics that relate. But, in December, I published on LinkedIn the 1st of a series. It was also presented in PDF and at WordPress. The title: Artificial intelligence, not solely machine learning (AI, not solely ML). The 2nd of the series continued the theme: Knowlege and truth.
Neither of these seemed to be of importance of the work that went into xNN/LLM. Why say that? It's been by career to work with these issues operationally (real time, industrial environments); at the same time, my private work (autodidact, by nature) covered the bases with respect to what's at play and of scope. Essentially, "theoretical" is my middle name.
I just finished the 3rd of the series: Physicalness and mathematics. There will be one more (4th) that deals with the emergence, and surgence, of machine learning during the past two decades. As well, we have to look at data and decisions as a key topic with regard to computing and technology. That is, people, in general, need to know. Experts? We'll address their issues, too. After the 4th, we'll do a 5th which will deal with "What's next?" with all of this stuff.
The series is based upon experience in KBE as it functioned as the basis for truth engineering. So, it's more oriented toward those operationally involved with engineering and science. I'll turn around and write this series (condensed) for the general public.
So, here is the series:
- 1st - AI, not solely machine learning (Blog post, Linkedin**)
- 2nd - Knowledge and truth (Blog post, Linkedin**)
- 3rd - Physicalness and mathematics (Blog post, LinkedIn**)
- 4th - ML’s emerge/surge and data/decisions ()
- 5th - Where do we go from here?
Notes:
* "truth engineering" coined by David E. Jakstis in discussion of a white paper by John M. Switlik on their joint work with computational modeling for fabrication of forgings and castings.
** This is open to public read. Some Linkedin pages may require account.
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In tems of history, the U.S. D.O.D. supported early work in artificial intelligence. As well, data science was a common program. It is of interest to future discussion to point to the recent guidelines for digital enginering. We have made reference to "digital twin" which is an important concept that must be brought into the discussion related to advanced computing. We will have this document a major piece of our bibliography.
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| Digital engineering |
Remarks: Modified: 02/04/2024
02/04/2024 -- Linked this to 7'oops7 (AI, not ML solely) which will bear directly on the 777 project underlying KBE which relates to truth engineering as AI when it matures. Notice: Shattered dreams.
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