Digital Content: Confused Yet? I Am

January 19, 2021

I read “CMS Vs. DMS: Understanding the Key Differences.” The write up did not unlock my understanding. From my vantage point, there is a trade association called ARMA. You can get information about this organization from its Web site. As I recall, there are individuals who receive certification to deal with certain types of “records”; for example, nuclear power plant information. Other groups get involved with the nuclear industry, and there are hoops through which one can jump to figure out how to keep track of engineering change orders, the entities touching specialized components, and figure out who has been trained on what.

I am not exactly sure how other entities got involved in some of these often complicated tracking and managing functions. An organization called the Association for Intelligent Information Management used to be called something else. Maybe “imaging” when that seemed to be a great way to get members and run conferences.

What’s this abbreviated history have to do with the CMS versus DMS thing?

Yep, that’s a very good question. For the life of me, it seems as if document management evolved from the records management effort. But the document management experts quickly figured out that lawyers and pharmaceutical companies had to keep track of their information and had some specialized needs which ARMA either couldn’t or didn’t want to upset its apple cart.

Then the Web happened and the content produced for Web pages was even crazier and more disorganized, volatile, and multi-media enhanced than anything the vendors of software and services for nuclear, pharma, and legal eagle sectors possessed.

Enter content management systems. Wow. These were often tricky beasts, whether it was the wonderful Broadvision or the more Volkswagenish Ektron, a new business was born. The customers for CMS were not nuclear types or the chemical structure folks inventing drugs to help people at very reasonable cost absolutely everywhere.

Now let’s get the straight scoop from the CMS versus the DMS write up. Ready? Here we go:

The differences between document and content management systems are nuanced and depend on the scale to which you are using them…

I interpret this to mean that there is no difference. Your mileage may vary.

And how about this:

Where a DMS excels is at the preservation and organization of company documents (records), a CMS is often focused at content presented at websites, which is not specifically locked in individual documents, according to Elmendorp [another expert]

But what about systems focused on company records. Maybe the type of records the ARMA professionals are trained to manipulate, archive, and retrieve?

But do these systems work? Ho, ho, ho.

But here’s the key to the “key” in the title:

Where BPM, EFSS and CCM Fit In

What? What are these acronyms? But even more stunning is the inclusion of “multi-repository search tools known as Enterprise Search.”

Whoa, Nellie! Enterprise search is a solution to the management of content within an organization. News flash! Enterprise search is a utility often embedded in crazy software wrappers to allow someone to have a shot at locating the information needed to answer a business question or an eDiscovery mandate. Chemical structures, linked engineering change orders? Ho, ho, ho.

Who can figure out the differences, whether “key” or not?

Gartner. A diffused group of experts who have to sell information about the vendors to the potential licensees of these systems.

Confusion is the fertilizer for growing consulting revenues. What’s the “key”? Hire consultants. There you go. Insight.

Stephen E Arnold, January 19, 2021

2021: Virtual Conferences and Even Virtual Products

January 19, 2021

I want to keep this note short. Navigate to “The Best Tech of CES 2021 Isn’t Real.” The write up states:

the “beauty” of shows like CES is the ability write about our hands-on experiences with products. But since we couldn’t roam the halls of CES in person this year, it was the perfect time for brands to announce gadgets that weren’t ready for store shelves.

The source did not mention that fabulous fakes were the grace note for that memorable year 2020; for example:

  • Fake news
  • Fake queen of England outputs, and
  • Fake cyber security with a lot of sunshine going you know where.

CES: Virtual conference, virtual products, and fake products. Yeah!

Stephen E Arnold, January 19, 2021

Google: Big Is Good. Huge Is Better.

January 15, 2021

I spotted an interesting datum factoid. The title of the article gives away the “reveal” as thumbtypers are prone to say. “Google Trained a Trillion-Parameter AI Language Model” does not reference the controversial “draft research paper” by a former Google smart software person named Timnit Gebru. The point at issue is that smart software can be trained using available content. Bingo, the smart software reflects the biases in the source content.

Pumping up numbers is interesting and begs the question, “Why is Google shifting into used car sales person mode?” The company has never been adept at communicating or marketing in a clear, coherent manner. How many blog posts about Google’s overlapping services have I seen in the last 20 years? The answer is, “A heck of a lot.”

I circled this passage in the write up:

Google researchers developed and benchmarked techniques they claim enabled them to train a language model containing more than a trillion parameters. They say their 1.6-trillion-parameter model, which appears to be the largest of its size to date, achieved an up to 4 times speedup over the previously largest Google-developed language model (T5-XXL).

Got that?

Like supremacy, the trillion parameter AI language model” revolutionizes big.

Google? What’s with the marketing push for the really expensive and money losing DeepMind thing? Big numbers too.

Stephen E Arnold, January 15, 2021

Selling Technology in a Tough Market Roasting in Solar Waves

January 13, 2021

I read a post on Hacker’s News. You may be able to locate it at this link: I don’t know if this is a scam or the answer to the question “Where’s the beef?” The message states:

Hash: SHA256

Happy new year!
Welcome to (mirror: 5bpasg2kotxllmzsv6swwydbojnfuvfb7d6363pwe5wrzhjyn2ptvdqd.onion)

We are putting data found during our recent adventure for sale.

[Microsoft Windows (partial) source code and various Microsoft repositories]
price: 600,000 USD
data: msft.tgz.enc (2.6G)

The Solar Leaks’ post then provides information about the cost of the MSFT, Cisco, and FireEye, et al software. Prices begin at $50,000 for some alleged FireEye goodies and soar to $600,000 for the Microsoft crown jewels.

What’s important, however, is the post-SolarWinds’ misstep marketing environment. Sales professionals of products that provide enhanced cyber security, threat alerts, and the assorted jargon enhanced assertions have to close deals.

Just in time is a helpful write up from Entrepreneur Magazine called “8 Psychological Tricks to Increase Conversion Rates for SaaS Startups.” That’s on time and on target.

I am tempted to summarize the ideas with references to Machiavelli, Al Capone, and high school lovers promising to be together forever. But I will not. I will highlight three of the ideas, and you can pony up some cash to read the full entrepreneurial check list yourself.

Suggestion 1:

Offer fewer choices.

Okay, Amazon, Microsoft, and others offering secure cloud environments, are you listening? Fewer choices. The point of offering choices is to create an opportunity to confuse a customer and allow MBAs with spreadsheet fever to cook up pricing options guaranteed to lead to big surprises when the system is up and running. Cross that threshold and beyond the invoice! Outstanding.

Suggestion 2:

Introduce a third product.

You have to read the article to appreciate the wonderfulness of offering a print subscription, a digital subscription, and a com9bo subscription or an option that forces the “brain to focus on the two closest options.” I am confident that this is backed by an MBA-type book called “Thinking Slow and Slower.”

Suggestion 3:

Increase quantities rather than reduce the price.

Ah, yes, buy five packages of cookies and get an extra 20 percent discount. That’s okay, but I don’t have any place to put extra bags of cookies in my one bedroom trailer parked in Sunrise Acres in Bullet County, Kentucky. More, more, more. Yes, bullet proof. No pun intended.

With cyber security delivered via the cloud in the great SaaS approach, the trick to making sales is to shift from professional sales person to a street hustler offering “original” watches as tourists exit the bus from a tour of the Forbidden City.

What about clarity, factual information, and services which work, well, maybe just mostly work.

Good enough.

Stephen E Arnold, January 13, 2021

Rah Rah Rah for Enterprise Search

January 8, 2021

The founder and CEO of enterprise search firm Mindbreeze, Daniel Fallmann, has penned quite an advertisement for enterprise search in “Employ Your AI as a Smart Partner: Intelligent Ways to Leverage Knowledge” posted by Forbes. For Fallmann, the advantage of AI is the ability to serve up the right information at the right time in rapidly changing business environments. He advises us that any knowledge management system worth its salt will have these technologies: AI, machine learning, natural language processing, natural language question answering, and semantic content processing. He emphasizes:

“Making the relevance of information personalized for each individual is what makes successful search results for employees. This is achieved by observing user behavior (assuming their consent, of course) and learning from it. Various factors that are analyzed include the role of the activity, the actions that were taken in the past in connection with certain information, specific search behavior and even the emotions that users associate with information — a topic closely related to customer experience or the experience economy.”

Looking ahead, Fallmann sees three significant developments in his field: X analytics, multimedia sources included in search results; weak supervision, a process that allows systems to learn independently and improve with use; and explainable AI (XAI), a way for systems to express their logic in a way humans can understand and manage. We’re told:

“Thanks to these new developments in intelligent systems like those used for enterprise search and knowledge management, workers no longer have to manage newly automated processes. Instead, they can combine their experience with artificial intelligence. This can generate a great opportunity to see ROI with reductions in the time it takes to complete tasks and eliminate repetitive tasks. This can help people play to more distinctively human strengths like social interactions, creativity and tact. And best of all, it can help workers spend their time on more impactful activities like strategy, innovation and problem-solving.”

No doubt, Mr. Fallmann would recommend Mindbreeze’s InSpire platform as the ideal solution. With headquarters in Chicago and in Linz, Austria, that company was founded in 2015 and is connected to a Microsoft reseller.

Cynthia Murrell, January 8, 2021

Palantir Titan Positioning

January 7, 2021

I spotted the jargon now used by Palantir for its Titan platform. No, the jargon is not platform. Here’s what the policeware powerhouse states at the Titan Web page:

Titan’s platform upgrade makes Gotham more performant, open, and proactive, so that the world’s institutions can continue turning data into intelligence.

I once heard a Fast Search & Transfer whiz kid use the word “performant.” In 2006, I asked, “What does performant mean?” The answer was, “It means fast.” I asked, “Like the name of your company or fast as in speed?” The reply, “Fast.” That’s the type of answer that may have contributed to some of Fast Search’s challenges.

I also like the Palantirish word “proactive,” which seems forward leaning.

The search and business intelligence vendors have been using the phrase “turning data into intelligence” for years.

To sum up, Palantir is becoming performant in marketing its platform which converts all sorts of information into “intelligence.” Now what is “intelligence”? Answer fast or performantly, please.

Stephen E Arnold, January 7, 2021

Marketing Insight or Marketing Desperation?

January 6, 2021

A couple of weeks ago, I became aware of a shift in techno babble. Here are some examples and their sources:

Fire-and-forget. Shoot a missile and smart software does the rest… when necessary. Source: War News

Hyperedge replacement graph grammars (HRGs). A baffler. Source: Something called NEURIPS

Performative. I think this means go fast or complete a task in a better way. Source: Mashable

Proceleration. The Age of Earthquakes.

Tangential content. The idea is that information does not have to be related; for example, if you write about car polish for a living, including articles about zebras is a good thing. Source: Next Web

Transition from pets to cattle. Moving from the status of a beloved poodle to a single, soon to be eaten bovine. Source: Amazon AWS

Fascinating terminology. Time for digital detox and maybe red tagging. No, I don’t know what these terms means either. I assume that vendors of smart software which can learn without human fiddling knows these terms and many more because of experience intelligence platforms.

Stephen E Arnold, January 6, 2021

Misinformation: Semi-Explained

December 30, 2020

I read “Why We’re Posting about Misinformation More Than Ever.” I am not going to work through the Silicon Valley MBA, jargon fest. The informing idea for the essay may be this statement:

Neither the media nor fact-checkers controlled the online conversation surrounding “misinformation” this year.

I am tempted to ask, “Who appointed media and fact checkers as the arbiters of truth”? But, no, I will not ask this question.

Instead I will focus on the big concept of a single online publication dog paddling with enthusiasm to generate revenue, writing about misinformation.

I want to ask several questions and perhaps an enthusiastic Silicon Valley MBA thumb typer or a graduate of a up market journalism school will answer each. Here we go:

  1. Is Vox is writing about misinformation because Vox is outputting misinformation? The skewed output is similar to a Google results list just powered by humans, not algorithm magic.
  2. Does Vox wants clicks because clicks generate the desirable pile of money?
  3. Does Vox believe that technology is now the fabric of modern life; therefore, politics, specious write ups about what a company should do, and trying really hard to become more than an online information service is the path to influence?

Standing by.

Stephen E Arnold, December 30, 2020

Google and Its Smart Software

December 28, 2020

I spotted “What AlphaGo Can Teach Us About How People Learn.” The subtitle is Google friendly:

David Silver of DeepMind, who helped create the program that defeated a Go champion, thinks rewards are central to how machines—and humans—acquire knowledge.

The write up contains a number of interesting statements. You will want to work through the essay and excavate those which cause your truth meter to vibrate with excitement. I noted this segment:

I don’t want to put a timescale on it [general artificial intelligence], but I would say that everything that a human can achieve, I ultimately think that a machine can. The brain is a computational process, I don’t think there’s any magic going on there.

I noted the “everything.” That’s an encompassing term. In fact, the term “everything” effectively means the old saw from Paradise Lost”

O sun, to tell thee how I hate thy beams, That bring to my remembrance from what state I fell; how glorious once above thy sphere; Till pride and worse ambition threw me down, Warring in heaven against heaven’s matchless King. (IV, 37–41)

I also noted this Venture Beat write up called “DeepMind’s Big Losses and the Questions around Running an AI Lab.” The MBA speak cannot occlude this factoid (which I assume is close enough for horse shoes):

According to its annual report filed with the UK’s Companies House register, DeepMind has more than doubled its revenue, raking in £266 million in 2019, up from £103 million in 2018. But the company’s expenses continue to grow as well, increasing from £568 million in 2018 to £717 in 2019. The overall losses of the company grew from £470 million in 2018 to £477 million in 2019.

Doing “everything” does seem to be expensive. It was expensive for IBM to get Watson on the Jeopardy show. Google has pumped money into DeepMind to nuke a hapless human Go player.

I also noted this write up: “Google Told Scientists to Use a Positive Tone in AI Research, Documents Show.” I noted this passage:

Four staff researchers, including the senior scientist Margaret Mitchell, said they believe Google is starting to interfere with crucial studies of potential technology harms.

Beyond Search believes that these write ups make clear:

  1. Google is in the midst of a public relations offensive. Perhaps it is more of a singularity than Google’s announcements about quantum computing. My hunch is that Timnit Gebru’s experience may be an example of Google-entanglement.
  2. Google is trotting out the big dogs to provide an explainer about “everything.” Wait. Isn’t that a logical impossibility like the Godel thing?
  3. Google is in the midst of another high school science club management moment. The effort is amusing in a high school science club way.

Net net: My take is that Google announced that it would “solve death.” This did not happen. “Everything”, therefore, is another example of the Arnold Law of Online: “Online fosters a perception that one is infallible, infinite, and everlasting.” Would anyone wager some silver on the veracity of my Law?

Stephen E Arnold, December 28, 2020

IBM Watson: More Promises after Previous Promises. Will IBM Deliver This Time?

December 23, 2020

Wow, I had almost forgotten that IBM Watson was going to be a $1 billion business back in 2014. How quickly some forget that Lucene, home brew code, and acquisitions blended with science fiction? In 2017, the former Big Blue executive said in the Harvard Business Review:

“Watson will touch one billion people by the end of this year.”

Touch is not generate $1 billion and more in sustainable revenues. Nope, Watson failed in cancer, did zippo to fight Covid, and did create some memorable full page ads like the weird chemical structure thing in 2015:

ibm chem structure

Yeah, building blocks of cognitive software.

IBM Sets Its NLP Ambitions High With New Capabilities In Watson” explains that IBM is making progress. Note this statement:

While recent announcements by IBM focus around language, explainability, and workplace automation, the update around its language capabilities include reading comprehension, FAQ extraction and improving interactions in Watson Assistant. All these products aim to bring resilience, productivity and value for enterprises.

I like the explainability. Why not explain why the supercomputer Covid drug analysis did not generate a usable output, defaulting to a long list of “maybe these will work drugs” for humans to figure out what would work and what would not. Helpful in a time of crisis.

I don’t want to dwell on the implications that IBM Watson can now understand what humanoids write, particularly in short, cryptic WhatsApp messages about an illegal transaction. Let me quote one dollop of pink confectioner’s sugar paste:

…the company also announced a new intent classification model in IBM Watson Assistant, which is aimed at understanding an end user’s goal or intent behind engaging with the virtual assistant. It will then be used to train the systems accordingly while enabling greater accuracy in virtual assistants.

With a new president, I thought that the old IBM over hyped cognitive PR squibs had been retired for Ms. Rometty to oversee.


IBM is back in the hyperbole game. Let’s ask Watson. On second thought, nah.

Stephen E Arnold, December 23, 2020

Next Page »

  • Archives

  • Recent Posts

  • Meta