Current challenge

TL;DR -- We have mentioned technology. The modern world is full of hyped situations, it seems, on a close observation. Somewhat exacerbated by the uncertainties of the times (COVID)? Even prior to the last two years, attention was attracted to claims that were motivated by computer prowess. Companies made choices along that line. There are opinions all around about how technology will influence the future. That will not abate and will be an important of daily decisions and discovery as we go forward. In a sense, it's obligatory to be informed. What does that mean? And, how might 400 years of experience contribute to the necessary reviews and alternative determinations? 

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Autodidacts? Anyone? Or, from another angle, the American experiment? Is its moment now? 

As the story goes, during a period of the plague, Newton spent his time of isolation to play with light beams and to think of falling apples. And, views changed. 

For the past two years, we have been diving into the basis of AI having heard the clamor that seemed non-ceasing. At the same time, we have been assaying the general basis of computing which is the main mode that enables AI's current dancing. But, people are important, too. 

The other day, we watched a video given last spring via Zoom for a conference held by the Stanford Law School on "Future Law." Alan Kay was the speaker. We did a post (Grand Challenge). Alan was at the famous Xerox PARC Lab and invented the Smalltalk language. Too, he has been a professor at California Universities and involved with AI (artificial intelligence). 

We have already pointed to the importance of technology and knowledge going forward. Can a private, small-dimensioned organization contribute to studies and analysis in a manner that brings benefit? That is a discussion that we will be having. In a manner, the plans for the TGS portal run along the lines mentioned by Alan with respect to a research platform. 

Again, with respect to AI needing to respect people, Alan mentioned that the current hype which relates to a particular form of is like the tail doing the wagging. Alan lists a few researchers who are (have been) working in other than the current mode. We could name a lot more. 

Be that as it may, the HBR has been contributing to the discussion for several years now. In 2019, they published a comment by a researcher who suggested that we quit calling every bit of progress AI. Their special issue for Winter 2021 is on the subject of How AI is Changing Work. The topics covered are: Competing with AI; Adopting AI; The future of jobs; Working with machines; Keeping AI from going wrong. For each of these, there is an executive summary. 

Earlier, we had a post titled "How Dumb is AI?" which was courtesy of the IEEE (formerly, Institute of Electrical and Electronic Engineers). IEEE has it fingers in every piece of technology. Earlier, electricity was the focus; now, computation is huge. Recently, we looked at the IEEE.org website and saw no reference to  AI. Today, there was one that pointed to a webinar scheduled for later in January. 

At the same time, another group involved with computing is the ACM (Association for Computing Machinery) which as been around about as long as has the computer. Their site has a few more hits on AI but not as many as there were a few months ago. However, their focus is largely research and not commercial exploitation. The ACM has sponsored a special interest group on AI for decades (SIGAI). 

The point of the post deals with technology as a whole of which computing will be a large part which inevitably leads to issues of intelligence, thereby giving life to artificial intelligence. Our next post (Challenges of technology) deals with the growing presence on the web of content which has been increasing since HTTP came on the scene. We looked at this due to the subject relating to our interest in the great interior of the U.S. which was populated over a long century of frontier experience. 

Remarks: Modified: 01/17/2022

01/04/2022 -- Stanford has a group that talks Singularity. We will look at that more closely. Not to be snarky, but to increase the philosophical view. Academia cannot do this. 

01/17/2022 -- Added newer image. 

How dumb is AI?

TL;DR -- The title may be self-explanatory. Hype has reigned for a while now. Let's correct that. 

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This is the 2nd post of a series and looks at some articles from the recent IEEE Spectrum. First, what is the IEEE? It's the Institute for Electronic and Electrical Engineers, now known by its acronym, which is over 100 years old. An old motto reminded everyone that for all of the technology events of the 20th century, some member of the IEEE was there. That is due to the pervasive influence of power generation and management. With the computer, the tie is even stronger. 

So, the IEEE has had its ups and downs, as does any groups of humans. But, their collection of articles in the Spectrum of October of 2021 was phenomenally on the mark. We will pick a few articles for this post but will look at all of them eventually in our technology focus. The image on the right is from their cover showing a robot (nicely configured) and the headline: Why is AI so dumb? 

Now, AI has been around for more than 1/2 of a century and was almost named as a lark by John McCarthy. It is famous for having generated lots of interest during its life in a cycle of boom and bust. We are currently in a boom where AI is all over. Companies are piling on the heap of people trying to use. We see some success. 

Mostly, though, we can say that it's far from expectation's ideal in terms of real modes of gain. Hence, the interest of the TGS, Inc. Every group needs some focus. We are taking technology in the perspective of people with 400 years of history under their belt. We have already started to look at these long threads of cultural experience and discussing how we need such in today's world. Expect that effort to continue. 

In particular, we can look at historic fact. Genealogists have used the computer from the beginning. Then, we saw the genetic analysis project gain footing and ground. On the other hand, there are many open questions yet unanswered. In fact, they have not even been asked. When you see commercial outfits piling on something, watch out. AI is like that; so, too, can be genealogy efforts; as well, we can look at the whole of the industry, given enough time. 

But, back to the Spectrum. There were several articles, such as the one looking at AI history. There we see that two views predominated: symbolic and connectionist. Of late, the press has favored the latter which got out of bed finally due to increases in computational prowess. We worked in this, hence the interest. Prior to that, the symbolic approach made some headway. IEEE had a brief history. There are more in-depth looks that we can purview. Specifically, the most recent work has been on tying these two approaches together. That is, as smart people have always done, the work will continue, in the spotlight or out of it. 

Unfortunately, the spotlight perturbs things greatly. One might think that turning the damn thing off is how to go, except for those who want to act and play reality rather than do hard science and engineering. So, in that guise, lets look at three of the articles. 

• An Inconvenient Truth About AI - IEEE calls this the third wave. In each one, the advances were noticeable. This time, we saw the AI win games thought to be too difficult for computers. Everywhere almost, we see AI systems handling customer queries for better or for worse. There are other examples of the good and the bad. Briefly, this technology is not ready for big-time replacement of humans and their talents. So, why the hype? This will need discussion. 
• 7 Revealing Ways AIs Fail - Some of the attributes are discussed, such as brittleness, inherent bias, lack of common sense, and failure to handle mathematics as we would expect. In this latest round, huge stacks of data that came from the computer's existence allowed a focus on AI training itself. Some success got people to thinking of autonomous modes which did not really pan out as expected. But, typical to human endeavors, it took a while for the realizations to hit home. We all know the little engine that could. Just how little is the AI engine? Pun. 
• Deep Learning's Diminishing Returns - One ignored factor has been that these new approaches are expensive in several ways. There is the hardware and then the energy. Then, there was the complexity that was latent. Scaling up is not an option. This AI thrust was leveraged by the general economic boost of the past decade. Profligate ways of business became almost the vogue which is not sustainable. As problems of the technology got more visible, the costs and their issues got attention. So, there is 'deep' here; the whole thing is in a morass with no real plan for extrication. The business and social aspects of AI will be an interesting bit of study. Even magic has its price. 

How does this topic relate to the TGS, Inc.? Technology, going forward, will be only more complicated and with troublesome ramifications on people. The U.S.? Has led in technology for a long while. Too, technology involves people across the board. Now, our interest can and will be several. Consider though, the U.S. history over the past 400 years has some meaning and significance, in terms of technology and society. This post looks at one topic of very many from a viewpoint that is not very well known publicly. There is a lack of places to go to find proper information. This is a general problem whose severity is only now becoming known. But, these issues could have been foreseen. Were. Again, our focus is going forward in a mode that lift people out of the various mires, some of which are historic in scope, others are being created every day, some times by technological errors. 

As an aside, something needing attention deals with truth and what it is. We will help with this discussion, especially from a position that takes note of the need for truth engineering. Technology is core to the issues of truth, though the issues have been in human culture for as long as we can recall. The smaller world created by technology is more of an exacerbating influence than that of any type of mitigation.  

Remarks: Modified: 12/03/2021

10/30/2021 -- Add the TL;DR.  

12/03/2021 -- After some research, this seems in order. Will use this to set a basis: Practical issues of AI. 

Alchemy and AI

TL;DR -- This post is about Dreyfus and his arguments about what computers can and cannot do from a philosophical position. Dreyfus was a student at Harvard. He taught at MIT and Berkeley. The post provides links to some of his material in the interest of future work related to technology. 

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We have a technological focus to pay attention to. Of late, the main topics have related to the xNNN/LLM approach that has been called "generative." In November of 2022, OpenAI released ChatGPT upon the public. It got acclaim and criticism. The former is still there as companies rush to make money on the idea, even though AI has had a troubled past in some cases. 

Criticism range over a wide domain. For one thing, students got to using it to do their work. Again, companies have been using it where "fiction" is not an unlikely find. For instance, where PR doesn't have a firm basis. So, people came up with analogs, such as "lies" or "hallucinations" to describe the careless output. Well, actually, sophisticated, albeit misdirected, mathematics was doing the work. 

A sister approach became quite adept at creating "fake" photos that could fool people. And, movies being a moving stream of photos, there were "fake" videos.  

Since then, there is a newer version of ChatGPT. It has scored well on some tests. But, at the hard problems where guts and smarts are necessary, we still see low scoring. No one, in their right mind, would trust their lives being run by these new deals. Though, management decisions now are setting up the future for just that event. 

Of all of the issues at hand, that is the one that really bears some attention due to its potential for errors. Oh yes, bias has come up in discussion as it seems to be inherent to the approach. There are many things to discuss, as said. 

In the below, we will use "AI" to mean "artificial intelligence," in toto. We coined AIn't about two years ago with respect to the adulation being given xNNN (and its manipluative ways) which is only one aspect of what has been considered to be important to AI.  

So, is any of the critical opinions other than new? You bet. The following is a summary. 

• Hubert L. Dreyfus (1929-2017) is one example. He studied transcendental and existential phenomonology at Harvard and in Europe. He talked to some of the greats (Heidegger, Sartre, ...). He also was a professor at MIT which was the hotbed of the early development of AI. As we will see, he and AIers did not agree. 
• While at MIT Dreyfus wrote "Alchemy and Artificial Intelligence" which was published by RAND and is available at the DOD site. Later, this paper became a book, What Computers Can't do. 
• 
  Later Dreyful publish an update since AI had made seeming progress. His new title was What Computers still Can't do. There is a "preview" available copy of this book at GDocs. In the commentary, there is this great quote about this work: ... was widely attacked but quietly studied. Dreyfus's arguments are still provocative and focus our attention once again on what it is that makes human beings unique.
• Hubert Dreyfus's views on artificial intelligence (at Wikipedia) has a great summary of the discussions and related themes. John McCarthy, early AI pioneer, mentioned that Dreyfus had good concerns, however his presentation and argument style was offputting. Which, in McCarthy' opinion was too bad as some necessary discussions were not to be. 

And, that is where we are now. Dreyfus's ideas will figure in coming work. Too, one
thing that might be the result of this cycle of AI which has had several is that AI might now continue into the future as something that is recognized though without proper definition. It means different things to different people. But, over these decades, there have been many cases of AI involvment in progress and effective work. In fact, it's daily on the computer horizon and touches operational situations more than we might realize. 

Remarks: Modified: 08/23/2023

08/23/2023 --

README and more

TL;DR -- README! Such a minor thing. It's age old. We don't seem to know where it started. But, it relates to the world of code. It's nice that GitHub, old ways being new with the internet and worldwideweb. In any case, now AI has put its wannabe head into code from various positions. We have payed sporadic attention and thought that it deserves a more regular focus. 

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We have mentioned GitHub (Wikipedia overview) several times since around the 2020 timeframe. Our latest post was motivated by an email feed from the GitHub team that related to an article on those who maintain code. That role was always seen as less important than the "cowboy" roles of the developer. 

Stopping a minute. GittHub is an on-line example of what can be termed code management. This type of facility/utility evolved over the years until it's a fairly robust addition to good business practices. Some have used CMS for this type of work. However, we have had lots of posts about Content Mangement and will continue. AI modes will require extra efforts at curating. So, stay tuned.  

Now, back to the "cowboy" (apologies to the real type). Guess what? Lots of developers put stuff out and strutted off the stage like the stud. Oh, btw, this is an old guy writing who has seen this stuff for decades. And, after strutting off, the stud left the errant traces of his work for other to clean up after. Much like the mother after her kids. 

Mixed metaphors, I know. But continuing. I'm working with a project that will try to incorporate AI modes (we'll be more specific later) into a new system which is supposed to revolutionize the economy, as a whole. Large piece of pie to bite from. Anyway, I will still blog though I'll be going to other blogs and linking from those back to here. 

Another bit of interest? GitHub and OpenAI have been working for awhile on a Copilot which is supposed to aid in developmenr or general code management. This joint work started in 2021 which was a year before the general release of ChatGPT. BTW, if you are wondering what this is about, see a brief history of GPT. The author writes about research on AI (mainly machine learning). 

Again, back to the subject. Today's mail pointed to this discussion: How are AI coding tools changing the way developers work? This is from the maintainers group referenced above. In reading the text of the discussion, there were some things that stood out. One was this: AI might not write a book, but it can write a good paragraph. 

Before proceeding, though, a couple of words. Yes, one can drive a small nail with a sledge hammer. But, it's a mismatch of need and what's being used to fulfill the need. Too, AI (GenAI, in particular) is hugely chewing up resources. For what? They need large data centers that requires an unwarranted amount of energy. Too, they need water for cooling. And, more. They're noisy. They make the landscape other than desirable. Go look at those that surround the lovely Virginia countryside of Dulles (IAD). 

So, reading the article was interesting. I went to look at their site and saw that this group started to publish in April of 2023. That would have been when the reality of ChatGPT and its kin was sinking in which was a mere five months after the release. As a reminder, OpenAI went viral and got millions of people to sign up for the free ttrial. Too, lots of folks bought in, including companies. 

All of that will eventually be analyzed. I started last year in another context: Knowledge Systems Center, Sperry Univac. As mentioned in the last post, I have been off helping to support a project as it gets off the ground. So, there are pending tasks that will be picked up again. 

Now, the effort at GitHub is called The ReadME Project. Coders have used a README forever, it seems. Software usually had this text file that included some documentation, or information about using the software, and more. So, does Wikipeda say anything about the README? Yes. 

Now back to the GitHub project. Here is a little bit of the notices sent since they started. AI itself has only come into focus the past few of these. 

• 06/26/2024 - AI is here. How is it changing the way developers work?
• 05/23/2024 - Maintainer Month: The joy of open source
• 04/17/2024 - Getting started in a career in platform engineering
• 03/12/2024 - Intelligent uses for AI in coding
• 02/13/2024 - Best practices for open source maintainers
• 01/09/2024 - Creating technical content
• ...
• 08/01/2023 - Getting started with edge computing | The ReadME Project Q&A
• 07/13/2023 - How to make your first open source contribution
• 07/10/2023 - How to handle programming paradigm shifts | The ReadME Project Q&A
• ...
• 06/13/2023 - Non-code contributors: The unsung heroes of open source
• 05/25/2023 - Elevating contributors into maintainership | The ReadME Project Q&A
• 05/09/2023 - Is it still "open source" if you don't accept contributions?

For an old timer, seeing all of this progress is a pleasure. There are several caveats which come from doing this for years including stints in the plush offices dealing with management and its science (if there is such). Evidence of this is becoming apparent to me. People, the key resource, are being driven to distraction and worse being slaves of automation. Oh, I would write more and will. Not just now. 

This year, I saw USDOD mention that people and their intuition ought to be the focus, not the computational twin that is a wannabe, many times over. All of this may seem new. It's not and has been going on for a long while. What's new? We can't hide the realities so much under proprietary cloaks when the evidence are huge monoliths traipsing along our skyline and blocking our rightful views ;>). 

Remarks: Modified: 12/28/2024

12/28/2024 -- See updates in GB, XIV, 1 for 2024 updates. 

AI not solely ML

TL;DR -- AI is more than ML. For one thing, people need to be included. A bucket-of-bits oracle never was the goal for reasonable folks. 

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AI was pirated by the machine learning people. Forget AGI. AI is good enough if we remember that "intelligence" is more than we have seen represented on the planet. 

    Artificial intelligence, not solely machine learning

Too forward thinking? Nope. We will get to discussing "truth engineering" at some point. ML optimizes without caring. 

Engineeing and economics go hand in hand. 

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Aside: After posting the above article, there was a comment from Tomek which touts being an "AI" company. Will look into this further, but Tomek Venture came up with "whois" as well as several others who have Tomek as a name. With respect to the extension ".ai", Wikipedia is a good source. Have not been paying attention, though I did run into this earlier), ".ai" has been a popular extension, since 2009, for its possible association with "AI" the subject of the above article. Tomek is leveraging on that with an automated interface. Perhaps, will look at it further. Otherwise, doing a survey of this type of activity would be more beneficial as it's going to get more prevalent. GitHub's pilot is an example of enablers. To think, in 2012, I was looking at coding manually. Still will. See Content vs configuration. For now, AI, of all sorts digital, arises from buckets-of-bits whose latest magical behavior with respect to text processing has no intent behind it. We're talking a "stochastic parrot" (in the words of some) and similar. That does not mean that meaning may not formulate from the mix, whether good or bad. But, reasoning as enlightenment liked to tout? Not. On the other hand, knowledge-based approaches do a better approximation, with a good example being knowlege-based engineering (KBE).  

Remarks: Modified: 12/30/2023

12/30/2023 -- Added image. 

A year ago

TL;DR -- A year ago, the world was three months past the release of ChatGPT with millions signing up. What did that event pertail? We spent several months reviewing the various options as well as looking again at the history from Dartmouth onward. In this new year, one can sense a change. Will there be less hype? 

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By this time last year, we were catching up on machine learning. Much later, we wrote the first of a series: Artificial intelligence, not solely machine learning (or AI, not solely ML) We put a "Papers" folder to publish articles with respect to xNN/LLM. That's refers to the neural net approach plus the large language model. John was involved with advanced computing his whole career and did lots of algorithmic work including those related to artificial intelligence and to what was then known as evolutionary computing including machine learning. His finals decades were oriented toward modeling with a focus on engineering support.   

So the following is a recap of the past year. After finding out about ChatGPT, we started discussions of the Director, Larry L. Walker, of the Sperry Univac Knowledge Systems Center (KSC). After some reflection, we planned a series of articles that would cover the history of computing and the related mathematics. The first thing that we published dealt with the decisions behind the KSC and with its accomplishments. The title was: Sperry Univac Pioneers Application of Artificial Intelligence – 1985-1987. 

After that, Larry wrote of his experiences with computing from the early days of Control Data and to his knowledge systems (expert systems) work. Meanwhile, Larry and John discussed the technology involved with Knowledge-based engineering (KBE) which was central to Boeing's 777 program. Throughout the year, the research looked into what happened with KBE at Boeing, in subsequent years, and in the world, in general. 

We have had some posts here on these subjects which we will collect. Late last year, the ACM Communications had an article by Thomas Haigh that looked at the history of AI and argued that there had been no AI Winter up to 1980 though the popular press seems to say that there was. In this regard, Larry talked of his having seen the AI winter of 1990. In the latest ACM Comm, Prof. Haigh published another article. This one is titled How the AI Boom Went Bust which agrees with Larry's assessment. 

So, letting John chime in, he has seen no AI Winter. KBE? It is still part of some CAD systems. Now, we can argue that it is not to the expectation that was there in the 1990s. John would agree. However, in doing a quick survey, there are many other names that KBE continued as. The theme with that is to not associate with a failed system. But, digging deeply, most of the continuals that John saw reference KBE as being in their history. 

Personally, for him? He worked KBE from the late 1980s until 2005 when he retired. Then, his focus became truth engineering which was spawned at Boeing and has continued in a research mode. Now, AI was created by mathematicians one of whom (John McCarthy) coined the term. Dartmouth was the site of a meeting on the subject in the 1950s. And, all along since the 1950s, there have been periods of excitement as people contemplate some creature emerging from the fog of computing ala Science Fiction's take on the matter. 

Being adult about the situation? A closer look, under the covers, shows the mathematics at play. Yes, it is sophisticated. Taming the hype cycles will require some maturity. Part of that will be grasping that mathematics and bringing it out to public view. 

Since that first paper on AI and ML, there have been two more which present the important factors that need to be discussed. A fourth one is in the works. After that, the focus will be on a discussion that is practical in scope. John will offer one example which comes from the KBE work. 

Essentially, some in the discipline of data science have been traveling the right path. Actually, there are many examples of computational systems providing benefits via services that we can respect as they offer results that have value. 

The theme of utmost importance will be determined by people as the technology progress. And, the universal themes seems to have been conjured up through the efforts of a few. Local themes have been given little attention. AI gives us a chance for a better balance; in fact, such a balance would improve all humans affairs, including science. 

Remarks: Modified: 02/13/2024

02/13/2024 --  Added image. 

The Stargate Project

TL;DR -- Stargate, of late, is an example of so many things. Already, after a few days, the sides are being drawn. We are neutral with our technology focus. Kant, of the western pantheon, will be seen as important contributor to the proper analysis to settle some of the issues. Expected downturns, along several axes, ought to be part of the discussion, as well. We see a major communication gap between marketing (and the world of business) and basic science (including its application via engineering). 

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Note: This goes along with our interest in the 250th of the U.S. plus one of our sons who contributed: Josiah Willard Gibbs. A tie? Gibbs demonstrated the advantage of thinking about vectors. 

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There are many uses for "stargate" as this disambiguation page on Wikipedia shows. Some are related to Sci Fi which deals with technology in futurist or even "meta" sense which means "beyond" (Wikipedia). 

This week, some of the Techbros of SV were behind an announcement by President Trump.

• TheStargate Project --  joint venture with private money artificial intelligence (AI) technologies. Many know of AI as it has become a familiar topic due to activities of the past couple of years that brought machine learning to the foreground with mixed results. One example was ChatGPT of OpenAI who, recently, teamed up with Oracle and MGX (company). 

Currently, we are not getting into specifics which will come after we do some looking at the past two years. For us, technology as a focus goes back to a post on 2 Jun 2019 in which we were recapping our technology influence since the start of the Thomas Gardner Society work. In other forums, we have followed and commented on progress in areas like machine learning, especially in the context of data science which is an area of focus. 

Computers and their use? We can trace this through the past few decades. Right now, though, we can point to a former program: Strategic Defense Initiative (SDI) The US Department of Defense (USDOD) had been involved in computing from very early times, motivating choices along the way. Even in the 1960s, there was sufficient knowledge on the part of the public about computers for the news to do regular reporting. For example, in the mid-1960s, a film (2001) with an AI computer (HAL) was a huge hit. 

AI got its start in the 1950s. Work in this area has continued since then, even when not publicly known or under some other label. We will look at examples of that. 

But, the SDI was involved with more than computing. Science and engineering of weapons and defense methods were a main theme where the computer was for support. This is from the SDI article. 

• Advanced weapon concepts, including lasers,[4][5] particle-beam weapons, and ground and space-based missile systems were studied, along with sensor, command and control, and computer systems needed to control a system consisting of hundreds of combat centers and satellites spanning the globe. 

We will look at the choices that led to a decline in the enthusiasm for this program. But, there were many artifacts and systems that came out of this work. We will cover those items over time. 

Why did SDI cease? Early on, the computational side of things was seen as more complicated than could be handled by systems of the time. Then, the scientists started to weigh in on the expected physical systems and suggested that they could not be realized within the anticipated timeframe. Yet, there were things that carried on, with some of them available for data collection. 

That is mentioned as AI being taken over by ML (JMS - AI, not solely ML) is not a given with respect to success. The past two years have seen lots of discussion and words written. Many of the faults are obvious. The GenAI approach has not attained general appeal, except for playing around, and has not found any niche as was thought. Though, business has bought into the approach as it allows them to remove people off of the payroll. 

At the same time, there were some noticable degradations, perhaps more than can be documented without further study. But, who has an interest in that? Basic science and engineering were cut out of the process which seemed to have been mainly marketing driven. 

Some might see the Stargate and SDI connections as too tenuous. But, it's not to my old brain who has been involved for 50 years in advanced computing. Then, R&D was still in vogue. That went away. We now have this ca-pital-sino affair which is a chimera (paying only some; pilfering many). The past two decades have more than enough examples to look at in terms off what is important to consider and why that might be so. Psychology and philosophy, in both an applied and theoretic sense, will be brought to bear. And, people? The prime consideration. 

Fortunately, there are positions being taken that will make sure that the pros and cons are kept in mind. Right now, we are neutral as the faults are obvious. Real benefits from adopting AI are tainted by the marketing exuberance that seems eternal. 

 

Maturity? Again. One thing for sure, the world of humans has gone through about 200 years of evolution with technology. On one western line, we can use Kant's Logic and Prolegomena (those condensations point to his more extensive work) to establish a basis that was ignored for various reasons that we can discuss. One huge potential problem will be the results of the fallout that is inevitable just like we see with capital markets where value disappears, overnight sometimes. 

Crypto is there to remind us of how this can be. In the meantime, let's end with a Financial Times article: AI leaders clash over safety and $100bn Stargate project. Name calling and ad hominen was mentioned by Kant as something to avoid. 

Remarks: Modified: 01/25/2025

01/25/2025 -- 

Science and AI

TL;DR -- Wherein we look at an old problem which has new twists due to technology and its new ways. Media and news morph information severely.  

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Now, I did not use AIn't in the title because I must refer to what might be called the real "AI" which would be a tool for all of us, including science. Now, "science" has a lot of meanings. We are being all-inclusive. Many think the "hard" types are the top-dog. That drives the STEM focus. But, there are the social sciences which deal with people issues. There is the medical science. We can have a "holy" science that could be discussed. The range covers the whole of humanity and the lives involved. 

Lately, computer science came along which is still being defined. AIn't, partly, might be attributable to issues there. But, mathematics, itself, needs attention as it swerved to mainly being quantitative in focus. Some of this goes back to computing's growth over the past century and its becoming useful through time so as to be everywhere now, via the cloud. We will discuss, later, the concept of qualitative means required by mathematics. The "pure" aspects of the discipline might be invoked, but we are talking other issues that technology will bring to bear. 

Recently, I discussed AI in the context of quantum mechanics (QM). I'll explain more as we go along, but the gist of the conversation was the difference between an overview versus being in touch with the specifics. The former is the state that anyone not involved with a discipline can attain without additional effort which was not really possible in the past. Now, with the cloud (and Wikipedia), one can read on any subject. Now, of course, AIn't's rise make things murky. What can you believe now? 

If I say, not much, that is a statement that was true in the past. But, now? That "not much" would have to be change to "very little" (can be believed) perhaps even "nothing". Okay? Things are dire. We all have to be exceedingly careful and observant. 

Wait, Wikipedia itself? Well, every page there has a history. We must use that facility. And, all changes are tracked with respect to time, editor, and difference in content. This is so back to the beginning of the page. Other sites offer similar means for determining status and history. In general, going forward, we need markers and more (truth engineering will be the topic for this discussion). 

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So to the theme of the post. The friend showed me [a print of] an article that had appeared in the latest The Economist. Here is another article that quoted The Economist: A New Way To Predict Ship-Killing Rogue Waves. Within this feed, there is a link to the article (requires payment). The article had been marked at the points where the author of The Economist article raved on about AI and the way that this example solved problems beyond the imagination of humans (my paraphrase). Not as a retort, but in the spirit of debate, I marked [the article] where there were words about "mathematical routines" and the use of other techniques to check results of the AI (neural network) approach. Another approach used was of the evolutionary programming type which we have seen used in production. 

Of course, at the end of The Economist's article, there were the words "could" and "should" which are handwaving. The article did not go as far as some modern one have done where it exults of some accomplishment and its promise. Then, at the end, the article (probably forced by the editor) puts in words about this and that and the other thing (my words and emphasis) all being required as, essentially, the thing does not work as the glowing report might have suggested. 

---

In my usual manner, I went to look at the situation. 

Disclosure: The following recognizes the excellent work in this example. The intent is merely to demonstrate what is always a problem: transforming information into other states, faithfully. News and media face this all of the time; modern times seem to be allowing more laxity with its consequences. 

An irony: Perhaps, AI (in a real sense which we have not seen yet) could help hone messages to be more truthful in the transforms. Let's table that, for now. 

The researcher gave a talk at the National Academy of Sciences about legitimate research. And, as is becoming more imperative, he placed his data and the code on GitHub. Also, thanks to the cloud (it has its good points), we can find records for him on Google Scholar, GitHub (repository for code and more where he put his experimental code), and more. 

But, someone at The Economist reported. Or, they read some abstract. 

We, on the other hand, can look at links with supporting information. 

1. The data issues. One commenter touted that there are 300 years of data from an old science. As in all cases, the new approach is starting from the "state of the art" developed by humans and their methods. 

https://static-curis.ku.dk/portal/files/271761876/s41598_021_89359_1.pdf  

2. This is the paper which was quoted by The Economist and others. It can be found at ARXIV. And, the paper only mentions AI cursorily.   

https://arxiv.org/pdf/2311.12579.pdf  

Abstracts are everywhere, as we find nowadays: NIH; Google Scholar; ... 

https://pubmed.ncbi.nlm.nih.gov/37983488/

https://scholar.google.com/citations?view_op=view_citation&hl=en&user=8jzVkXEAAAAJ&citation_for_view=8jzVkXEAAAAJ:3fE2CSJIrl8C

3. The code for the experiments that are reported in the paper and the related data are available at GitHub. This type of disclosure is becoming an imperative for several reasons which we will discuss. Now, one bit of irony is that GitHub has piloted the "pilot" mode which has been going on for awhile where people use xNN/LLM to work code. We will look at that process in a later post. 

https://github.com/dionhaefner/rogue-wave-discovery

----

Now, this is an example of science using computing and doing experiments related to analyzing data. It is only one example of lots of work being done that is legit. Those efforts need to be brought to attention and recognized. Lots of shuffling up goes on, much under the guise of feeds. 

But, with the AIn't and its activities coming into play, how do we know legit from not? That is one of the themes that will be of importance in the future with regard to technology in general. One might say that this type of work is what the internet was created for. 

Now, using "collegial" for the former times and their ways, even then there was need for "peer" review and other scrutiny. But, the spirit of the times stressed truthful work and efforts at promoting proper communcation. 

Background processes (there are many others beyond AIn't) always were problematic. The lesson from the mobile phones and their apps brought that to bear. 

Remarks: Modified: 12/22/2023

11/30/2023 -- Minor corrections. 

12/22/2023 -- THE FUTURE OF AI IN SCIENCE AND MEDICINE, talk at Gairdner Foundation, Oct 25, 2023. 

Economics, 2024

TL;DR -- Economics? About time. We looked at the science and medicine awards earlier. We have a category of Nobel as the posts are stacking up. A discussion of ChatGpt brought the additional Nobels to attention. The gist of the work is that GenAI/LLM will have minimal impact which brings up questions, such as, why all of the wasted effort and hype? 

--

We just made a "Nobel" category since there are so  many posts and there will be more. Our last post on the subject was about a family member starting an organization that supports excellence for high school students. The focus is mathematics as it will become more important due to computing's use (misuse) of the phenomenality and to its role as supporting science and technology. Other posts dealt with awards this summer that brought to fore an awareness of machine learning (couched as an misnomer, via "AI"). 

Now, economics? On Ln, we saw discussion of AI what was mature where a remark noted that an expert at MIT suggested that gains from AI will be less than 1%. Wait? Sounds like our sort of argument. Besides, one of John's graduate advisors was from MIT. And, John McCarthy was there. It, with Stanford and Carnegie Mellon, was a noted academic resource back in the '70s and '80s, prior to the downturn that was due to several factors. The term for this was "AI winter" with this concept being brought forth now due to the hype-driven scene that we have seen for two years. 

• ChatGPT (Feb, 2023) -- We had written on AI for a long while, using AIn't for the most part. We are dealing with buckets-of-bits that are "warping our imaginations, clouding our intuition" (as we wrote elsewhere). But, notice that this post is about three months late, since OpenAI released their toy/tool in Nov of 2022. I had not been paying close attention to them. Since that time, there are several other posts. And, we have written elsewhere on the matter. Needless to say, in this interchange, we asked about Thomas Gardner. And, instructed it on what we knew then, or thought that we knew. Irony? At that same time, while I was looking at Wolfram's use (Mathematica) of ChatGPT (and others), some research work was being done via WikiTree (see Currrent Status). With that work, the TGS, Inc. foundations were shaken. We did not fall and are in a repair state. Sherborne, UK records show all of the kids, but Seeth, being born in England. Now, we are keeping to the notion of Thomas going back and forth and explain our reasoning. 

---

For now, here are a few links to material about the award. 

• 
  MIT economists Daron Acemoglu and Simon Johnson share Nobel Prize -- The small reward (1%) does not support the hype or the ungodly amount of money and resources going into GenAI/LLM. Conversations are starting to emerge with more critical viewpoints being expressed.  
• Drawing a line from colonialism to artificial intelligence --  We like this as our whole outlook pertains to carry the tales forward about the history of the U.S., especially with respect to the early days. Then, it was the fifth generation that bore the onus of the Revolution. 

The unconstrained hype is normal for people. Newton (gravity and light guy) lost lots of money in some silly scheme. Bohr (more smart) said that the ca-pital-sino (our neologism) cannot allow winning without insider information. Oh? Yes, long ago, he said that. 

Too, where are the engineers? And, we will invoke KBE (knowledge based engineering) which allows the well-educated brains to qualitatively control the beasts of quantitative modes. GenAI/LLM for too long has adopted the aura of Einstein and his mathematics. Well, physics might win some battles with Ma Nature. It does not rule, yet. Nor will it. 

Computing? Out of mathematics via physics. Less than mature in so many ways. 

--- 

The Nobel's work can be used to analyze our progress over time as we consider those who got awarded and all of their compatriots, of their time. We will engage in that sort of discussion. 

Remarks: Modified: 02/16/2025

02/16/2025 -- 

Research, using the internet and AI

TL;DR -- Time goes by. Things happen. Technology can be a boon or a bane. It's wonderful when it works. With the redo of the focus of AI, we are starting a few new approaches. One deals with sharing data but, at the same time, keeping some control on usage. The sustainable future of computing that has slipped out of our fingers can be recovered. 

--

The past couple of weeks have been busy. The year has been busy with new events. Of old news, these dealt with the 250th which we started to mention a decade ago. Now, it's on the doorstep. Of current news, the AIn't, as we call it, happened three years ago last month (Nov). That whole trek is worthy of attention under our the TGS, Inc. focus on technology. 

Then, there is the future which includes many categories. Some of these are familiar. One of late was research started this year with one of the GenAI/LLM offerings. It was neither ChatGPT nor Gemini which we have used and commented on. We'll get to the specifics. After the spring start, there was some redo in the summer that had to do with common errors associated with the techniques involved. 

So, there was a restart. This post is about that (see below). Also, the White House announced their Genesis Mission which is involved with AI (note, I do not use AIn't, in this case) which is a more full look at the software capability. We will go into that more. But, we were happy to see that DOE is driving the thing. One of the first to announce their participation was the INL which is in Idaho. We were there for a few years a while ago. 

One writeup of the project noted that 400K scientists and engineers will be involved in making AI what it was and can continue to be, before the sidetrack of machine learning which may have been a necessary event but was poorly managed for several reasons which we'll get to. 

For now, looking forward. A recent post by David T. Gardner explains the new approach which we will look into further. In this post -- The Anomaly of the Miles Defuncto (Knight, Deceased) -- see the "Citation & Legal Status Dataset" which is about the use of Zenodo (https://zenodo.org/records/17670478) to control access to and use of documents that are made available for information only while a project does its work. Expect this type of thing to become more prevalent. 

For now, we will push handling details of David's project to a later time as we get a better notion of the expected changes what will accrue from the recent decisions. However, we will be reading David's material on a regular basis. The plan is for us to support his work; a bit of groundwork is necessary prior to that work in the sense of preparedness. 

The internet started to encourage cooperative work by people at disparate sites and of different organizations. That was a collegial focus. With busyness and profit, people get paranoid about someone stealing their ideas. That is quite rational. 

AIn't? It proved the concept by copying and using data from all over without permission and trampling over copywrite rights. That sort of thing will be worked out for a more mature use of AI and computationally-framed data in the future. 

Remarks: Modified: 12/08/2025

12/05, 06, 07/2025 -- Zenodo reading requires a login. Changed the calling sequence. See records via this: https://zenodo.org/records/17670478. DTG changed the section on Sir Christopher. We will focus on this for a while. He's like Nathaniel Eaton, first head of Harvard. Misunderstood. GGP of Ann and many others.  

New infrastructure

TL;DR -- A look at what we need to do and the various contexts involved including our content which covers several domains and our need for configuration management. The web's evolution will be on the table in terms of choices, both good and bad, by the developers of the mess. Updated graphic and comment about WordPress are later edits. This was a pre-COVID post. 

---

We have all heard this over the past couple of decades. Well, we can finally say that things are at a crux, especially with the emergence of DL's facilities. They were always there; of late, people learned how to exploit.

Create or discover? Well, like the chicken and egg, which is first? I'm of both minds where 'discover' is given respect. So, Poisson's name is on stuff. He created this. Or, was he describing what he saw and we labelled it with his name as if the underlying ability came about with observation?

With the internet, we get to reason on these things, again, albeit with some practical focus as the intent is to use the thing properly, smartly, and to the best of our ability. I've put out a few posts about this. In July, it was Techie stuff. There were things before, say the technology blog. This started at WordPress[dot]com but, recently, moved to be under our 'portal to truth' (lots to discuss there). At that site, we have continued our blogging about decisions.

I have been working alone, for the most part, just following my intuition. 'Minimal' was one goal. Last fall, I mentioned some Google discussions that were right on (in this old guy's mind) and comforting, actually. Though, as an aside, they own this blog space. We're looking to pull it, too, under our portal.

In the meantime, AI is going bonkers. It's obvious, to me, that the black box can be tamed. It'll take us getting back to logic. What the hey? Minsky of MIT went to his grave arguing that the aNN (no matter the variations, thereof) as not the way. Not that I agree with him entirely, but he was not off the mark. Everywhere, we see AI this and AI that. Makes one wonder if some parts of the populace have lost their marbles.

As an aside, our portal thoughts make use of the fact that Thomas Gardner is almost a tabula rasa given that we know only a little but have the huge set of progeny to ponder. That means, in other words, the 'every man' is the theme or meme. We'll get back to that.

This blog has been going for 10 years. We started the WordPress one due to the details being handled with regard to choices. Of course, as we studied, we had to see where the crowd was going (below). And (yes, this is real), every time, we looked at what led to the current state (our's and the world of computing's) and tsk'd (want to know why? paying attention to the messes?). Sheesh. Do we ever get anything right? For anything of benefit, there are a slew of side-effects, costs (what have you) that are negatively imposing. This is without fail.

AI came on the scene, again, the past few years. Gaga time. This time, though, the older minds were saying, wait, let's talk: ACM, IEEE, etc. So, that's something else to discuss.

But, with regard to what the TGS needs, we have to develop. I have run across roll-your-own schemes. Guess what? The monied crowd does this to remove dependencies upon others. I'm stressing it due to issues of truth engineering. In any case, code will be to the fore. What? Yes, too many are being led down paths to perdition, it seems. We have been right so far in that assessment. I don't see glowing examples, yet.

As an aside, with regard to the below, we were doing Microsoft in the (mis-guided?) notion of going with ASPX and its way of the world. We'll mention this again.

But, the tools are there for us to do things better. Metrics, in other words, used wisely can be quite helpful. The benefits that have accrued properly to technology are examples. Lots of them. So, getting back to the theme of the post, here is an example.

This image comes from the source for a post that is worth reading: How WordPress Changed the Internet - 17 Facts about WordPress. I like it if only it shows that the old guy isn't off the wall. 

Aside: The source? W³Tech and their Web usage surveys where they are looking at content management. Look at the count! Babel building.  

In the 2012 time frame, as we were being kicked off of Microsoft's site, I looked at all three of these. In fact, I prototype'd a TGS site. At the time, I was up to my ears in new information having started to really get into the history and genealogy of the Cape Ann crew. So, there wasn't time to play with configuration when 'content' was the key thing. Notice the comparative growth of these three.

Aside, content and configuration? These differ (the media is not the message).

I looked at WordPress, again, in 2014. Those prototypes had been done under our own server. In the new mode, I went and built under WordPress' site (in the beginning, there were no ads; they came later; hence, we're moving). But, in 2012, I fell back to HTML, tables, icons, and mouse handling. It worked. On the 2014 go around, I brought in CSS and some javascript. The latter was, finally, made more central as it builds the page.

Now, what was one problem in 2012? The database. Too much of it (let's discuss). We can go into this, but the TGS site uses Linux and files. Guess what? Recently, after reading some UBerkeley stuff on AI, I went to GitHub, finally. Ah, the choices, related to text or graphics, etc., were all there for daily discussion while people were, at the same time, doing useful stuff within their chosen framework.

Talk diversity. This is one type that we need and can handle. Though, there are always forces pushing for homogeneity. Mathematicians love this.

BTW, on the latest look at WordPress, as I was bringing it into our portal, I looked at the 'biz' aspects of its use. Nickel and dime'ing was my reaction; like the menu that is ala carte. Nice, but, I want to see what's under the cover (or hood or ... - we used to say). Too, I want more than mere parametric influences. BTW, that is one issue with DL and AI, right now.

Yes, again, anyone interested in machine learning in the context of TGS, pipe up, please.

Closing this out, we have lots of things pending. See this blog that will move (https://jmswtlk.github.io/GitHub-ing/) which will cover the deeper technical issues as we go along. So, indeed, we're talking infrastructure in a new sense, actually senses.

Oh yes, ASPX. Recently, I have been helping in a situation where this is the framework. Not as a developer, but rather as a late tester of a new process. Interesting. Some things I liked, others not. How to get the proper balance will always be a key thing? And, whose balance?

Aside, again. The earlier post pointed to a project management scheme that has gotten a lot of attention. It reminds me of the old Apple package that was card-based. That is, one had cards that linked in a manner that was fairly powerful (we're talking 80s, folks). I see it referenced from time to time. Lift the covers, and you'll find old routines still supporting the computing world. Trouble is, though, that it's in the GUI world. Most stuff is. Developers? Many stay away from that. Actually, WikiTree is balanced and a joy to use. GitHub is more textual with add-ons for the GUI'ness.

How ought we to go? Decisions will be made. None will be in concrete.

When looking at Drupal and Joomla, I also looked at Concrete 5. It's still around. The Army picked it. Okay. How does one decide in all of this? Want to know. Computational sustainability. That'll be a future topic.

Aside: Paying attention? Old guy off the wall? Well, no, here is a current discussion of Concrete CMS versus Wordpress. Of course, it is from Concrete CMS's viewpoint. You see, 'new infrastructure' points to changes that will be permanent. Users want more control. Developers want tools. Content creators and managers want ease of applying power. Finally, John can say, about time. Maturity?  

Remarks: Modified: 10/07/2022

10/07/2022 -- Updated graphic on WordPress which had come from a survey. Put in pointers to survey. This week, decided to use WordPress to prototype our configuration. 

Technical review

TL;DR -- Since we are taking a focus on technology as a thing deserving of attention, we will have to be regular in posting information. Expect that more regularly in 2024 as we commemorate the arrival of Thomas and Margaret (or not, depending upon our research)

---

We ought to have these on a regular basis and will starting next year. For this post, we'll look at a New Yorker article, briefly. Then, we'll add in a comment about a recent post. After that, we'll show a graphic with regard to one of our web servers. Then, we'll start a list of the web presence plus gather all of the technical posts together under various categories. 

Ambitious task? Yes, we'll start today and finish this up with a week. At the same time, we will consider how to do these and with what frequency. 

---

AIn't and AI. We'll be more specific next year. 

• The Godfather of AI - See the New Yorker, 11/17/2023. This is the main article and dealt with an interview of Hinton. There was a genealogical notion brought up. He is Brit and a descendant of Rev. Boole of the logic and algebra that we all love. After casting about for some direction, he picked neural nets. One early act was popularizing the Boltzmann Machine. As we all know, none of the machines/methods found so far is all-powerful. Subsequent work ended up with the back-prop algorithm. In a sense, this is similar to numeric processing oriented toward resolving a multiple-body issue. Definitely, constraint satisfaction applications need a good look. One interesting tidbit is that the author of this article used Kafka's worlview as the basis for an example. This was written up in an issue of the 1986 Nature periodical. To note, please. On seeing an interaction with ChatGPT, he was astonished so as to talk "level of understanding" and even uttered "alive" in the context. He has seen lower-level reality in that his later work deals with neuromorphic approaches. 
• The Economist as example - See the last post: Science and AI. This was motivated by seeing an article in the 11/25/2023 issue of the paper (not a magazine, they say) in which a reporter hypes some good work dealing with rogue waves. Now, everyone ought to be interested as waves are everywhere and densely sought by thinkers. Yet, in terms of the seas, this is old research with lots of data. Too, people have done an exemplary job in trying to understand the data. So, the researcher used the neural net to look at some pre-processed data where the mathematical elements were emphasized. Okay. Good results. But, a genetic (to be discussed) approach was about as capable. The researcher had a disclosurer at the top of his report. Did not TheEconomist writer not see this? Too, there is discussion about next steps. Our gripe? The use of AI as it encompasses much more than machine learning. Now, the post? Links to the data and the paper and the code itself which is at GitHub. That is how things will be, more or less, as research goes further. 

---

In some cases, we can use the facilities provided by the servers: Google; WordPress; Quora; FB. But, for our server, we use a Linux-based shared server. We think of it as balancing reliance on the cloud. Lots to discuss there. 

Related to: TGSoc.org/papers

What we see are six metrics. The world has gone mad numerically, many ways. So, that, too, will be discussed. But, with respect to the flow of activity, the topic was motivated by OpenAI's little trick last November. They didn't do the world a whole lot of favors; rather, we will see, in less than two years, just how negative the impact might have been. Now, will subsequent activity on their part relieve some of this. 

An adage is apropos: one cannot train out the crap that was trained into a system via machine learning. 

At the "Papers" site, we put out an article in May and then followed in the latter months. 

---

Aside: John retired as a Technical Fellow having worked in advanced computing systems most of his career. As such, he dwelt in the space between applications and the underlying technology, principally with regard to data management (early data science) and computational mathematics (in the space of engineering support). When he says, buckets of bits, it's with experience. Knowledge and intelligence? Those were themes in the advanced crowd all during the evolution of computing as we know it now. Or, actually, as we do not know it. Think black boxes and their mysteries? They were created by us. To quote an author who is aware of our work: demon of our own designs. 

---

Punting down the road, we have this blog. Plus there are two on WordPress. Then, our website is hosted on Web Hosting Hub. We started with Microsoft's Open Office (need to find the specific name) and moved when MS pulled the plug. That choice dropped the support for many small businesses who had tried to leverage that capability for their on-line needs. See this search: Configuration. You see, this is paired with "Content" or absence of it (which is very much the case in lots of web stuff). The timeframe was 2012 which was two years after we started. At our portal (to truth), we detail our research with respect to rolling our own. At the time, we were astonished by the amount of work done by those who have the time with permutations without end being made available. Interesting. 

Permutations? Sure, group theory comes to mind. It'll be in the background as we proceed. One problem with AIn't? There is no AI. We're talking sophisticated mathematics in action. So, let's raise that level to where we can get the general populace on board with the future. After all, leaving these things to wizard's is problematic. Did we not all learn that over the past two decades? 

Remarks: Modified: 11/30/2023

11/30/2023 --

Year to date, 2023

TL;DR -- We have looked at Bard and ChatGPT. The latter had our interest while records at Sherborn were scrutinized. We found out unexpected data about Thomas and Margaret that was sufficient to raise questions about what we know. We had already started the FAQ way back. So, with these two subjects for work, we can deal with technology as we adjust the story to account for the new information. In short, that is not something to moan about; no, it's right in line with how work ought to proceed. 

--

This is a continuation of the last post (Intro to Bard).  Bard is the generative LMM approach being tested by Google. As we have said, technology is our interest which is a broad field. Of late, interest has gone with unbounded enthusiasm toward what we call AIn't; in particular, though, we will look more at ChatGPT which came on the scene in November of 2022. 

This post recaps activity in two areas, but, first, here is a brief summary of posts related to the subject:

• How dumb is AI? -- this 2021 post reported on an article that was in the IEEE Spectrum. The IEEE.org is a technical organization that is over 100 years old and deals with the core of technology (namely, power and its meaningful use). AI and knowledge processing rely upon the work of IEEE folks to provide computational resources. 
• Current challenge -- this 2022 post discussed several topics; one of these was the Harvard Business Review's look at AI. Too, at the time, the ACM.org which consists of folks from academia and from technical management was paying attention. 
• A(rtificial) I(intelligence) researched properly - this 2021 post did a recap on the technology use of the TGS, Inc., since the beginning. This bullet is here as it is a parallel activity to what is discussed below.
• Two searches to support future work as references: AI (the theme of today's news); truth engineering (principles from engineering services related to computational systems and their issues).   

Having set the framework for the next items, we can look at what happened this year. Then, we will discuss some next steps with Bard.  

• In February of 2023, we were asked about  ChatGPT since there was a lot of discussion by educated folks about its abilities. By that time, the enthused had already run down the road with uses even to the extent of introducing packages using the system. On the other hand, we were more cautious as there had already been issues made known. There was a clever little phrase associated with the issue: hallucination. To us, the underpinnings are mathematics which we can lift to general awareness. So, some of the behavior is due to the way that the conversational aspect is tuned. Then, we have a positive tone that was assumed to be the right one for this type of interface. Know-it-all is what I think. Technically, we are talking a type of 'interpolation' and will be explaining what we see. But, there is another issue. The push to have unsupervised learning which is motivated, somewhat, by omniscience considerations (look at the Singularity arguments as a huge factor in this discourse). But, the input was crap for several reason. So, why would not the system trained on the bad data has issues, too? Somewhat, one could talk "liar" as the resulting paradoxical behavior except that there is no consciousness involved nor the choices related to that ability of humans. Frankly, it's a mess. Crap cannot be trained out after it pollutes the thing. The method dropped the limitations that might have been brought by supervised learning. Lots to discuss. 
• At the same time that we were looking at ChatGPT and being involved in discussions, a researcher stepped through the Sherborne records and found that all of the children of Thomas and Margaret had been baptized in England. There were two things for us to look at. One had to do with Gloucester's 400th. If Thomas and Margaret were there, we needed to write this up. We had expected to use 1624 and were waiting for material that supported that year. The researcher reported his findings on WikiTree. Their response was to split the Thomas Gardner profile into two persons. The father of the children was married to Margaret Fryer. He was written up by Dr. Frank. The other profile has little information except for reporting the data and the two profiles. Research will fill in the pieces. How did we miss this work? Well, the involvement with catching up on ChatGPT took some time and attention. We were only a couple of weeks late to the show and made our remarks about the state of affairs. 

We are working on the issues. Rev. Hubbard wrote (1680) that Thomas Gardner was at Cape Ann early. And, the Rev gave no indication of two people. Dr. Frank (and others) noted that there was talk of two gentlemen. But, Thomas could have come back and forth. 

Now, an interesting twist is that both ChatGPT and Bard have erroneous data. How do we make this known so that there is a change with supporting remarks left behind? We need to look at the whole affair and the technical details. So, we're working on that, too. 

But, what to train it as being correct? There's the rub. We have put remarks in various places with respect to the current work and the coming changes with no timeframe specified yet. That seemed to be the reasonable stance. 

You know, that has been our approach from the beginning (see the FAQ, link above). We are trying to establish the proper basis. All of the current literature cannot be just cast off. We need to look at motivations and at the basis for decisions made in the past. After all, that would pertain to future decisions. So, we'll hold steady as research proceeds. We already have posts with regard to this work. 

Expect, that technology will play a part, too. After all, it will be the future that is impacted with what we do today. Let's do it right, or as right as we can given our situation and resources. 

Remarks: Modified: 08/06/2023

08/05/2023 --  The post on reseraching AI (3rd bullet, 1st list) has risen, of late, to being on the top-watched list. Too, we are working on GB XIII, 1 which will cover our work so far this year. ... With respect to Thomas and Cape Ann, we will adopt "new directions" as the theme. 

08/06/2023 -- Pointed to the Getting Technical post which references work with Bard. Recently, we have give Bing's little thingee a run through. We want to do a little technical bit, on a subject that is newly framed, at each of these and do a comparison. One future theme will address how to get these things to settle down in order for them to help us hone our reason and understanding (ala Kant, for one). Right now? It's a mess, quite frankly. 

 

Some notes on AI/ML

TL;DR -- GenAI/LLM has been on the scene for over three years. Lots has happened which we have participated in and watched. Things are getting interesting on all of the sides to the story. This post stops and posts a few links related to using Spinoza's thoughts to ponder this modern puzzle. 

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AI/ML (known too as GenAI/LLM) has been on the scene now for over three years. In terms of the total picture, the history and data are there for us to study. What's happened in 2026 is a type of acceleration. The split of 'yeah' and 'nay' is still there. But, other dynamics came into play that changed the game this year. 

We're still using "AIn't" to depict this wannabe attempt. I quit using any of these systems in early 2025 when the "agentic" came prominent. Why? We prototyped lots of the ideas of that approach four decades ago (in the "knowledge" era) and did good stuff within the constraints of the time. So, I will get to documenting that from my experience and according to what I observed. What we learned there is apropos. 

For instance, the NNN is known as a general function approximator. And, functions are a focus, say from the work related to the functional software approach (Haskell, et al - but, Lisp early, okay?); functions are mappings as we see with category theory; automated processes (basis for the web and SAAS) are from the knowledg era and encapsulated the behavorial/active aspects of objects/classes within the computational sphere; ...

What follows is a list of links related to technical and philosophical themes. These are not disjoint concepts. For each, there is a little comment. 

• DeepAI -- this is their GitHub site which collects some of the offerings behind some of the work that we will be refrencing. GitHub is an on-line system for managing information that is continually be updated and managed, such as code (but some have used its facilities for a collection of technical, topical essays. 
• What Kant and Spinoza can teach us about AI -- Two of Demis Hassabis’s favourite philosophers, Spinoza and Kant, help illuminate the conundrum: can AI turn chaotic data into intelligible, structured reality? ... I have mentioned these two philosophers quite a lot in posts on Linkedin of late. And, my use of AIn't comes directly from agruments by these guys. And so, there are discussions still pending.  
• One view of many on Spinoza by an artist -- interesting take on things; lifting us out of the technical for its own sake.  
• ..., will be splitting this list --- Spinoza (Wikipedia) ; Spinoza (SEP) ; Gutenberg (text) ; Gutenberg (Ethics) ; 
• Mapping Spinoza's Ethics -- offers mean to visualize the "argumentative structure". 
• DeepAI on Spinoza -- they have several philosophers covered which we will get to. 
  
• Chat Spinoza -- when we first saw this, we thought that it was cute; but, we also like how things are interconnected so as to allow analysis. 
• ... 

Uriel de Costa

This post will be a reference for us, too, as we go forward with the 400th, 250th, and the history of the U.S. and technology (say remembering Gibbs, the American, who cntributed to thermodynamics and caught the eye of the illustrious James Clerk Maxwell of Scotland. But, taking things into the 20th Century, we will have to bring up Planck. Why? His early thermodynamics work that quoted Gibbs and also explained the basics from a chemical sense.  

Remarks: Modified: 04/11/2026

04/10/2026 -- Added words and links. 

Ethics and value

TL;DR -- The ACM which is an old computing organization takes on ethics and its absence from the everyday decisions.  

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We have had a few posts on technology. A recent one looked at an ongoing bit of discussion: content versus configuration (which is a type of recurrent thing that is so common). Then, we just relooked at a dilemma related to technology of a particular sort, namely that wild-west thing of the internet. Also, we noted that genealogists 'foot drag' which is fine. Nothing that we're doing here will harm anything other than egos. 

Wait, was that just or was it harm causing? Or, was it necessary? Those types of things get ignored in the day to day, especially in the business world behind the doors. Oh yes, ethics is a subject that we can go on about without end but won't. 

It is important, though. The latest CACM has an article on AI and Ethics. The ACM is an old group involved with computing from the beginning. They even had the opportunity to have an annual prize titled Turing Award. The 2020 winners - Hanrahan and Catmull - worked on 3D graphics (including getting Pixar going). 

The article motivating this post is titled: Operationalizing AI Ethics Principles. Frankly, this is nice to see since many discussion about AI are seemingly unethical in the sense of the potential for AI to do harm (of very many varieties). One possible excuse might deal with complexity's hardness which is true. So, computing and ethics still have a lot of open areas needing discussion. One might say that's human nature. 

Over the past decade, we have tread through the valleys, so to speak, even that one of silicon. Gosh, would the wild west of the internet have even happened if ethics were on the table? Of late, there seems to be an interest, so we'll pay attention. Not to get too deep now, let's close with pointers to ethics and a few topics. 

• Ethics and blogging 
• Ethics and genealogy 
• IEEE Code of Ethics (thrown in as this group's members touch everything technical)
• ACM Code of Ethics (see image)

As said, no end to the subject. We are in a new age, technically enhanced or challenged depending upon one's view. Before the internet, we had TV and before that radio and ... Of late, some seem to have lost their manners. Is such an observation unethical? Is snarkiness a matter of not being ethical? 

Going back to Thomas and Margaret and their time, we have noted that there is little that we know of the couple except for what they wrought via their children. We are actively documenting that. We noted, too, that Thomas did not even bother to join the church until later (about 1636 - we have that year mentioned in one of these posts) which might look, in hindsight, to have been a move to keep his children out of trouble with the local society. We know, those Puritans (was that snarky?). 

One thing that we can know is that the 400 years of history can have some importance to today's world. And, looking about, there is no end to the amount of work that one can do. We will just be as ethical as we can be. 

Remarks: Modified: 12/12/2020

12/12/2020 --