Progressive Gauge

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VP Vance runs AI scrimmage – takes on EU bureaucrats

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JD Vance last month dressed down the Euros at Grand Palis AI Summit. Here, an old tech hand reckons with memories of AI policy efforts. Sees surprising devolution.

By Jack Vaughan

Booted footsteps in the hall at night. Coming closer as in an old radio drama — but real. The steps still resound in corners of Europe.  Where some memories of oppression are hard-wired.

The bootsteps might be KGB, Gestapo or Stasi. These were secret police, compiling dossiers and worse.  The US has had its secret agencies tracking its citizens. [Read more…] about VP Vance runs AI scrimmage – takes on EU bureaucrats

Get a grep

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Details vary in different telling, but all agree that Unix operating system co-creator Ken Thompson developed grep while at Bell Labs. His impetus came from a request by a manager for a program that could search files for patterns.

 

Thompson had written and had been using a program, called ‘s’ (for ‘search’), which he debugged and enhanced overnight, the story goes. They nursed it and rehearsed it and grep sprung forth. “g” stands for “global,” “re” stands for “regular expression, “p” stands for “print.” To get something to display on screen in those days you used “print.” Thompson coming up with a software tool, and sharing it throughout the office, and perhaps beyond; to me that captured a moment in time.

 

I picked up on this based on an assigned mini-series for Data Center Knowledge. Also in this mini-series was a look at the roots of the kill command and the birth of SSH security. [links below].  I knew bits of the early Unix history but had to dig for this one.

[Read more…] about Get a grep

Noting the passing in May of Neil Raden

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Noting the passing in May of Neil Raden, who was one of the most unforgettable characters I ever met in my computer trade press days. His death came after a long illness, progress of which he shared with the tech communities in which he’d long been a notable voice.

Neil led an independent consulting and analysis practice as the head of Hire Brains in Santa Fe, New Mexico. He was his own kind of 60s guy, in my experience. That is, he was goateed, a bit skeptical, but truly enthusiastic about technological advances that influenced his era.

Like many others, he came out of fields that weren’t essentially technological, but which were channels to building out new computerized methods, working from first principles. This led him on a winding journey as the mainframe gave way to the PC and the cloud, with problems to solve every step of the way. In his case, the seed soil was advanced mathematical studies and actuarial experience. He forged a home-grown view on technology, with special emphasis on databases, data warehouses and common-sense problem solving.

I got to know Neil on the data warehouse beat, which I covered for Software Magazine, Application Development Trends and SearchDataManagement.com.

When a reporter asked him a question he’d break it down carefully, and look at it from different perspectives…most of which had yet to occur to you. Each question invited yet another strategy for writing your story — that or ten other ones. With Neil, it wasn’t hard to jump from IoT to tensor matrices to federated learning to differential privacy and to data lake houses (tho, the latter was not his favorite!).

With some disappointment, you’d bring the conversation back to the original topic – you got a deadline, right?  But, for my money, any conversation with Neil was a master class in technology assessment.  And if I wanted to talk about Telstar or the Perceptron, he was down with all that too. Following Neil’s train of thought could be like riding the notes of jazz player’s solo.

In the late teens, I’d see him at Oracle Open World in San Franciso, and he’d talk about topological algebra – like chaos theory, a lodestone interest of his. A couple of years later, he’s speaking with me for a story on data and IoT, and topological algebra magically comes up again! I still can’t figure it  out. But I try.

On his health, I have no way of knowing if Neil saw what was coming back then, but I do know he was into being here and now. Recalling how Neil closed an interview, after some flights of technology fancy. He’d just shown me a picture of nature in his adopted home of New Mexico.

He said: “I’ll tell you something really funny, Jack. I’m looking out my window right now.I look out the window and it is beautiful. The land rises up. And on the other side of that is the Rio Grande, and on the other side of the Rio Grande is … ” My recording stopped there.

Well, Neil Raden is sure on the other side of the Rio Grande now. I have to say thanks, I appreciated you sharing your time!

 

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Neil Raden: From a Reporter’s Notebook –

On edge computing and edge AI

One thing I’m concerned about is that the edge is far too important to be controlled by a couple of mega vendors. Once that becomes proprietary it’ll be a disaster.

Why he studied math

I studied math. I studied math because I didn’t want to write papers, and look what I do now!

Question to ask of a new technology paradigm, for example, event processing

The question is ‘can an organization really change the way it operates?’ The technology may not be the hardest part.

On the data lakehouse

That one really cracks me up. Okay, so we build a data lake and now we can’t do anything with it. Oh, don’t worry we have a new thing — we’re going to call it a data lake house. And we’re going to give you some analytical functions like a data warehouse on top of it. And, you know, I’m trying not to laugh.

 

There are numerous postings on LinkedIn that readily show how very many Neil touched. You can find that feeling, and a sense of Neil’s dedication, in a recent tribute by diginomica.com Editor John Reed, who made sure to cast a light on Neil’s recent writings on AI Ethics, an area he was especially dedicated to  covering. Raden’s writings for the publication can be found here. Some earlier work is also to be found on Medium.

Neil is survived by his wife, TS (Susie) Wiley, his children Mara, Aja, Jacob, Max, and Zoe, eight grandchildren, a brother, Jonathan Raden, and a sister, Audrey Raden.

 

 

 

PASCAL language originator Nicholas Wirth, 89

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Nicholas Wirth, whose 1970 creation of the PASCAL programming language dramatically influenced the development of modern software engineering techniques, died January 1. He was 89.

A long-time professor of Informatics at the ETH Institute in Zurich, Wirth produced PASCAL primarily as a teaching tool, but its innovative language constructs set the stage for C, C++ and Java software languages that flourished in the late 20th Century, and which still have wide use today. Wirth was the winner of the 1984 ACM Turing Award, among other honors.

Wirth named the language after 15th Century philosopher and mathematician, Blaise Pascal, who is often credited as the inventor of the first digital calculator. The PASCAL language was a bridge of sorts, as it attempted to span language styles for business computing by the then-dominant COBOL language, and scientific computing as seen with the FORTRAN language.

The field of software engineering was still in its early days when Wirth began his pioneering work as a graduate student and then as assistant professor at Stanford University. At the time, the status of early hardware implementations from numerical calculators to general-purpose computers was still somewhat nascent.

It was becoming apparent this time that a language focused solely on numerical processing would encounter obstacles as computing evolved.

It was hoped, Wirth wrote in a paper, that “the undesirable canyon between scientific and commercial programming … could be bridged.” [This and other materials cited in this story appeared in ”Recollections about the Development of PASCAL,” published as part of “History of Programming Languages,” in 1996 by Addison-Wesley.]

Wirth also contributed to development of the ALGOL and MODULA languages, often bringing special focus to development of compilers that translated source software into running machine code. His book, “Algorithms + Data Structures = Programs” is often cited as a keystone text for those interested in the fundamentals of software design.

Education was the primary goal of work on PASCAL, which Wirth undertook after a disappointing experience on a somewhat squabbling committee of experts looking to standardize a new version of ALGOL 60.

In his words, Wirth decided “to pursue my original goal of designing a general-purpose language without the heavy constraints imposed by the necessity of finding a consensus among two dozen experts about each and every little detail.”

The work of Wirth and some co-conspirators built on ALGOL, but also drew implicitly on emerging thinking on structured approaches to software development, such as those outlined by E.W. Dijkstra. Certainly, the early ‘bubble gum and bailing wire’ days of computer software were receding as Wirth began his work.

“Structured programming and stepwise refinement marked the beginnings of a methodology of programming, and became a cornerstone in helping program design become a subject of intellectual respectability,” according to Wirth.

The fact that PASCAL was designed as a teaching tool is important – it was constructed in a way that allowed new programmers to learn sound method, while applying their own enhancements.

“Lacking adequate tools, build your own,” he wrote.

And, while innovation was a goal, pragmatism for Wirth was also a high-order requirement.

Wirth’s work on PASCAL started about the time he headed from Stanford to ETH Zurich, with definition of the language achieved in 1970. It was formally announced in “Communications of the ACM” in 1971. Though never the most popular language in terms of numbers, it was very influential, contributing to a movement that emphasized general applications use, strong typing and human-readable code.

PASCAL gained great currency in the early days of personal computers in the United States. A version that became known as Turbo Pascal was created by Anders Hejlsberg, and was licensed and sold by Borland International beginning in 1983. On the wings of Borland ads in Byte magazine, Turbo PASCAL became ubiquitous among desktop programmer communities.

Work of pioneers like Wirth gain special resonance today as a Generative AI paradigm appears poised to automate larger portions of the programming endeavor. Automated code generation is by no means completely new, and the surprises and ‘gotchas’ of the pioneers’ era will no doubt be revisited as the understanding of effective software development processes continues to evolve. Wirth’s words and work merit attention in this regard, and in regard as well to fuller understanding of software evolution. – J.V.

The Progressive Gauge obituary gets some extra time now, with a few minutes of extra material.

My Take: I came to cover software for embedded systems, electronic design automation and, then, business applications, at a time when structured programming and defined methodologies were in full ascendance.
Methodologies narrowed over many years into a general accepted path to software modeling. But they tended to flower wildly at first. They started with some philosophic underpinnings, but could easily be charged as well as something that worked for someone that they thought could become a product. The downside was each new methodology might suggest that your problem was the methodology you were already using, which was not always the actual case. The joke of a bench developer I shared a cube with for a while was “What’s a methodology?” Answer: “A method that went to college.”

The methodology generally carried the name of the inventor, not a historical figure as with PASCAL.

The complexity of the deepest levels of the new operating system, compiler, design and language approaches was daunting for this writer.

My work in the computer trade press afforded me the opportunity to meet Unix co-creator Dennis Ritchie of Bell Labs (at the time he was rolling out the Plan 9 OS)and Java author James Gosling (then of Sun Microsystems). Met two of the three “UML Amigos,” Grady Booch, then of Rational Software, and Ivar Jacobson, head of Ivar Jacobson International. Interviewing Ivar on one occasion was particularly memorable. He asked that I interview a software avatar he had just created, an animated figure which spoke and represented his thinking on technology issues, rather than speak with him directly.

These assignments surely were ‘a tall order for a short guy!’

I offer these notes here in my role as a generalist. While computer history doesn’t repeat, it rhymes. This history is always worth a re-visit, especially as clearly-new paradigms fly out of coders’ 2024 work cubes. It has been interesting for me to look at the origination of PASCAL, and to learn about Nicholas Wirth, the individual who brought PASCAL into the world.

Pascaline
Pascaline

Links
https://cacm.acm.org/magazines/2021/3/250705-50-years-of-pascal/fulltext
https://www.standardpascaline.org/PascalP.html
https://amturing.acm.org/award_winners/wirth_1025774.cfm
http://PASCAL.hansotten.com/niklaus-wirth/recollections-about-the-development-of-PASCAL/
https://blogs.embarcadero.com/50-years-of-pascal-and-delphi-is-in-power/

Who took my soapbox? A note on media and AI

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As 2023 came to its end, a New York Times suit affirmed a general impression that Generative AI and ChatGPT would find some friction on the way to a well-hyped, lead-pipe cinch and especially glorious future.

For those that have used this software, a recent improvement on existing machine learning interaction, it is not surprising. Microsoft’s/OpenAI’s ChatGPT and its main competitor, Google Bard, are breakthroughs. They provide a different level of access to the world’s knowledge.

Instead of pointing the searcher to brief fair-use citations of Web stories ala Google Search, ChatGPT and Bard provide somewhat thoughtful summaries of issues — ones that might do a junior or middle-level manager quite well when it’s time for yearly performance evaluations.

The new paradigm for Web activity threatens beleaguered publishers. They are not on a roll. The 4th estate is now painted as an unwanted gate keeper of opinion. Publishers that saw an advertising market pulverized by Google Search results now see an AI wunderkind about to drain publishing’s last pennies.

An anticipated slew of AI suits is now spearheaded by the Times, which filed a lawsuit citing OpenAI and Microsoft for copyright breach. Some go tsk, tsk. Wall Street oddsmakers that enjoyed an AI stock bump in 2023 were quickest to dismiss the Times’ chances versus ChatGPT. OpenAI has said it is in discussions with some publishers, and will work to achieve a beneficial arrangement.

Among the financial community, concern spreads that Generative AI’s magical abilities could be dampered. That is summed up by Danny Cevallos, MSNBC legal analyst, who worries about the impossible obligation to mechanize copyright royalties for AI citations across the globe.

The concerns comes despite the multidecade success of Silicon Valley’s Altruistic Surveillance movement. It can find you wherever you are, web users know. Still, Cevallos highlights the difficulty of, for example, finding and paying a copyright owner in a log cabin somewhere in Alaska.

“That would mean the end of future AI,” he said on CNBC’s Power Lunch. “It could be argued that the Times has to lose for progress to survive.”

We can anticipate that glory-bound Generative AI will find some rocks in its pathway in 2024 — but most will be in the form of stubborn, familiar IT implementation challenges. In the meantime, people that make a living in media will have to work to promote their interests, as other commercial interests chip away under the cover of AI progress. – Jack Vaughan

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