Google Cracks Infinity Which Overshadows Quantum Supremacy Maybe?

April 16, 2024

green-dino_thumb_thumb_thumbThis essay is the work of a dumb dinobaby. No smart software required.

The AI wars are in overdrive. Google’s high school rhetoric is in another dimension. Do you remember quantum supremacy? No, that’s okay, but it makes it clear that the Google is the leader in quantum computing. When will that come to the Pixel mobile device? Now Google’s wizards, infused with the juices of a rampant high school science club member (note the words rampant and member, please. They are intentional.)

An article in Analytics India (now my favorite cheerleading reference tool) uses this headline: “Google Demonstrates Method to Scale Language Model to Infinitely Long Inputs.” Imagine a demonstration of infinity using infinite inputs. I thought the smart software outfits were struggling to obtain enough content to train their models. Now Google’s wizards can handle “infinite” inputs. If one demonstrates infinity, how long will that take? Is one possible answer, “An infinite amount of time.”


The write up says:

This modification to the Transformer attention layer supports continual pre-training and fine-tuning, facilitating the natural extension of existing LLMs to process infinitely long contexts.

Even more impressive is the diagram of the “infinite” method. I assure you that it won’t take an infinite amount of time to understand the diagram:


See, infinity may have contributed to Cantor’s mental issues, but the savvy Googlers have sidestepped that problem. Nifty.

But the write up suggests that “infinite” like many Google superlatives has some boundaries; for instance:

The approach scales naturally to handle million-length input sequences and outperforms baselines on long-context language modelling benchmarks and book summarization tasks. The 1B model, fine-tuned on up to 5K sequence length passkey instances, successfully solved the 1M length problem.

Google is trying very hard to match Microsoft’s marketing coup which caused the Google Red Alert. Even high schoolers can be frazzled by flashing lights, urgent management edicts, and the need to be perceived as a leader in something other than online advertising. The science club at Google will keep trying. Next up quantumly infinite. Yeah.

Stephen E Arnold, April 16, 2024

The Only Dataset Search Tool: What Does That Tell Us about Google?

April 11, 2024

green-dino_thumb_thumb_thumbThis essay is the work of a dumb dinobaby. No smart software required.

If you like semi-jazzy, academic write ups, you will revel in “Discovering Datasets on the Web Scale: Challenges and Recommendations for Google Dataset Search.” The write up appears in a publication associated with Jeffrey Epstein’s favorite university. It may be worth noting that MIT and Google have teamed to offer a free course in Artificial Intelligence. That is the next big thing which does hallucinate at times while creating considerable marketing angst among the techno-giants jousting to emerge as the go-to source of the technology.

Back to the write up. Google created a search tool to allow a user to locate datasets accessible via the Internet. There are more than 700 data brokers in the US. These outfits will sell data to most people who can pony up the cash. Examples range from six figure fees for the Twitter stream to a few hundred bucks for boat license holders in states without much water.

The write up says:

Our team at Google developed Dataset Search, which differs from existing dataset search tools because of its scope and openness: potentially any dataset on the web is in scope.


A very large, money oriented creature enjoins a worker to gather data. If someone asks, “Why?”, the monster says, “Make up something.” Thanks MSFT Copilot. How is your security today? Oh, that’s too bad.

The write up does the academic thing of citing articles which talk about data on the Web. There is even a table which organizes the types of data discovery tools. The categorization of general and specific is brilliant. Who would have thought there were two categories of a vertical search engine focused on Web-accessible data. I thought there was just one category; namely, gettable. The idea is that if the data are exposed, take them. Asking permission just costs time and money. The idea is that one can apologize and keep the data.

The article includes a Googley graphic. The French portal, the Italian “special” portal, and the Harvard “dataverse” are identified. Were there other Web accessible collections? My hunch is that Google’s spiders such down as one famous Googler said, “All” the world’s information. I will leave it to your imagination to fill in other sources for the dataset pages. (I want to point out that Google has some interesting technology related to converting data sets into normalized data structures. If you are curious about the patents, just write benkent2020 at yahoo dot com, and one of my researchers will send along a couple of US patent numbers. Impressive system and method.)

The section “Making Sense of Heterogeneous Datasets” is peculiar. First, the Googlers discovered the basic fact of data from different sources — The data structures vary. Think in terms  of grapes and deer droppings. Second, the data cannot be “trusted.” There is no fix to this issue for the team writing the paper. Third, the authors appear to be unaware of the patents I mentioned, particularly the useful example about gathering and normalizing data about digital cameras. The method applies to other types of processed data as well.

I want to jump to the “beyond metadata” idea. This is the mental equivalent of “popping” up a perceptual level. Metadata are quite important and useful. (Isn’t it odd that Google strips high value metadata from its search results; for example, time and data?) The authors of the paper work hard to explain that the Google approach to data set search adds value by grouping, sorting, and tagging with information not in any one data set. This is common sense, but the Googley spin on this is to build “trust.” Remember: This is an alleged monopolist engaged in online advertising and co-opting certain Web services.

Several observations:

  1. This is another of Google’s high-class PR moves. Hooking up with MIT and delivering razz-ma-tazz about identifying spiderable content collections in the name of greater good is part of the 2024 Code Red playbook it seems. From humble brag about smart software to crazy assertions like quantum supremacy, today’s Google is a remarkable entity
  2. The work on this “project” is divorced from time. I checked my file of Google-related information, and I found no information about the start date of a vertical search engine project focused on spidering and indexing data sets. My hunch is that it has been in the works for a while, although I can pinpoint 2006 as a year in which Google’s technology wizards began to talk about building master data sets. Why no time specifics?
  3. I found the absence of AI talk notable. Perhaps Google does not think a reader will ask, “What’s with the use of these data? I can’t use this tool, so why spend the time, effort, and money to index information from a country like France which is not one of Google’s biggest fans. (Paris was, however, the roll out choice for the answer to Microsoft and ChatGPT’s smart software announcement. Plus that presentation featured incorrect information as I recall.)

Net net: I think this write up with its quasi-academic blessing is a bit of advance information to use in the coming wave of litigation about Google’s use of content to train its AI systems. This is just a hunch, but there are too many weirdnesses in the academic write up to write off as intern work or careless research writing which is more difficult in the wake of the stochastic monkey dust up.

Stephen E Arnold, April 11, 2024

Has Google Aligned Its AI Messaging for the AI Circus?

April 10, 2024

green-dino_thumb_thumb_thumbThis essay is the work of a dumb dinobaby. No smart software required.

I followed the announcements at the Google shindig Cloud Next. My goodness, Google’s Code Red has produced quite a new announcements. However, I want to ask a simple question, “Has Google organized its AI acts under one tent?” You can wallow in the Google AI news because TechMeme on April 10, 2024, has a carnival midway of information.

I want to focus on one facet: The enterprise transformation underway. Google wants to cope with Microsoft’s pushing AI into the enterprise, into the Manhattan chatbot, and into the government.  One example of what Google envisions is what Google calls “genAI agents.” Explaining scripts with smarts requires a diagram. Here’s one, courtesy of Constellation Research:


Look at the diagram. The “customer”, which is the organization, is at the center of a Googley world: plumbing, models, and a “platform.” Surrounding this core with the customer at the center are scripts with smarts. These will do customer functions. This customer, of course, is the customer of the real customer, the organization. The genAI agents will do employee functions, creative functions, data functions, code functions, and security functions. The only missing function is the “paying Google function,” but that is baked into the genAI approach.

If one accepts the myriad announcements as the “as is” world of Google AI, the Cloud Next conference will have done its job. If you did not get the memo, you may see the Googley diagram as the work of enthusiastic marketers. The quantumly supreme lingo as more evidence that Code Red has been one output of the Code Red initiative.

I want to call attention, however, to the information in the allegedly accurate “Google DeepMind’s CEO Reportedly Thinks It’ll Be Tough to Catch Up with OpenAI’s Sora.” The write up states:

Google DeepMind CEO may think OpenAI’s text-to-video generator, Sora, has an edge. Demis Hassabis told a colleague it’d be hard for Google to draw level with Sora … The Information reported.  His comments come as Big Tech firms compete in an AI race to build rival products.

Am I to believe the genAI system can deliver what enterprises, government organizations, and non governmental entities want: Ways to cut costs and operate in a smarter way?

If I tell myself, “Believe Google’s Cloud Next statements?” Amazon, IBM, Microsoft, OpenAI, and others should fold their tents, put their animals back on the train, and head to another city in Kansas.

If I tell myself, “Google is not delivering and one cannot believe the company which sells ads and outputs weird images of ethnically interesting historical characters,” then the advertising company is a bit disjointed.

Several observations:

  1. The YouTube content processing issues are an indication that Google is making interesting decisions which may have significant legal consequences related to copyright
  2. The senior managers who are in direct opposition about their enthusiasm for Google’s AI capabilities need to get in the same book and preferably read from the same page
  3. The assertions appear to be marketing which is less effective than Microsoft’s at this time.

Net net: The circus has some tired acts. The Sundar and Prabhakar Show seemed a bit tired. The acts were better than those features on the Gong Show but not as scintillating as performances on the Masked Singer. But what about search? Oh, it’s great. And that circus train. Is it powered by steam?

Stephen E Arnold, April 9, 2024





Google AI Has a New Competitive Angle: AI Is a Bit of Problem for Everyone Except Us, Of Course

April 2, 2024

green-dino_thumb_thumb_thumbThis essay is the work of a dumb dinobaby. No smart software required.

Google has not recovered from the MSFT Davos PR coup. The online advertising company with a wonderful approach to management promptly did a road show in Paris which displayed incorrect data. Next the company declared a Code Red emergency (whatever that means in an ad outfit). Then the Googley folk reorganized by laterally arabesque-ing Dr. Jeff Dean somewhere and putting smart software in the hands of the DeepMind survivors. Okay, now we are into Phase 2 of the quantumly supreme company’s push into smart software.


An unknown person in Hyde Park at Speaker’s Corner is explaining to the enthralled passers by that “AI is like cryptocurrency.” Is there a face in the crowd that looks like the powerhouse behind FTX? Good enough, MSFT Copilot.

A good example of this PR tactic appears in “Google DeepMind Co-Founder Voices Concerns Over AI Hype: ‘We’re Talking About All Sorts Of Things That Are Just Not Real’.” Some additional color similar to that of sour grapes appears in “Google’s DeepMind CEO Says the Massive Funds Flowing into AI Bring with It Loads of Hype and a Fair Share of Grifting.”

The main idea in these write ups is that the Top Dog at DeepMind and possible candidate to take over the online ad outfit is not talking about ruing the life of a Go player or folding proteins. Nope. The new message, as I understand it, AI is just not that great. Here’s an example of the new PR push:

The fervor amongst investors for AI, Hassabis told the Financial Times, reminded him of “other hyped-up areas” like crypto. “Some of that has now spilled over into AI, which I think is a bit unfortunate,” Hassabis told the outlet. “And it clouds the science and the research, which is phenomenal.”

Yes, crypto. Digital currency is associated with stellar professionals like Sam Bankman-Fried and those engaged in illegal activities. (I will be talking about some of those illegal activities at the US National Cyber Crime Conference in a few weeks.)

So what’s the PR angle? Here’s my take on the message from the CEO in waiting:

  1. The message allows Google and its numerous supporters to say, “We think AI is like crypto but maybe worse.”
  2. Google can suggest, “Our AI is not so good, but that’s because we are working overtime to avoid the crypto-curse which is inherent in outfits engaged in shoving AI down your throat.”
  3. Googlers gardons la tête froide unlike the possibly criminal outfits cheerleading for the wonders of artificial intelligence.

Will the approach work? In my opinion, yes, it will add a joke to the Sundar and Prabhakar Comedy Act. No, I don’t think it will not alter the scurrying in the world of entrepreneurs, investment firms, and “real” Silicon Valley journalists, poohbahs, and pundits.

Stephen E Arnold, April 2, 2024

Who Is Responsible for Security Problems? Guess, Please

March 28, 2024

green-dino_thumb_thumb_thumbThis essay is the work of a dumb dinobaby. No smart software required.

“In my opinion, Zero-Days Exploited in the Wild Jumped 50% in 2023, Fueled by Spyware Vendors” is a semi-sophisticated chunk of content marketing and an example of information shaping. The source of the “report” is Google. The article appears in what was a Google- and In-Q-Tel-backed company publication. The company is named “Recorded Future” and appears to be owned in whole or in part by a financial concern. In a separate transaction, Google purchased a cyber security outfit called Mandiant which provides services to government and commercial clients. This is an interesting collection of organizations and each group’s staff of technical professionals.


The young players are arguing about whose shoulders will carry the burden of the broken window. The batter points to the fielder. The fielder points to the batter. Watching are the coaches and team mates. Everyone, it seems, is responsible. So who will the automobile owner hold responsible? That’s a job for the lawyer retained by the entity with the deepest pockets and an unfettered communications channel. Nice work MSFT Copilot. Is this scenario one with which you are familiar?

The article contains what seems to me quite shocking information; that is, companies providing specialized services to government agencies like law enforcement and intelligence entities, are compromising the security of mobile phones. What’s interesting is that Google’s Android software is one of the more widely used “enablers” of what is now a ubiquitous computing device.

I noted this passage:

Commercial surveillance vendors (CSVs) were the leading culprit behind browser and mobile device exploitation, with Google attributing 75% of known zero-day exploits targeting Google products as well as Android ecosystem devices in 2023 (13 of 17 vulnerabilities). [Emphasis added. Editor.]

Why do I find the article intriguing?

  1. This “revelatory” write up can be interpreted to mean that spyware vendors have to be put in some type of quarantine, possibly similar to those odd boxes in airports where people who smoke can partake of potentially harmful habit. In the special “room”, these folks can be monitored perhaps?
  2. The number of exploits parallels the massive number of security breaches create by widely-used laptop, desktop, and server software systems. Bad actors have been attacking for many years and now the sophistication and volume of cyber attacks seems to be increasing. Every few days cyber security vendors alert me to a new threat; for example, entering hotel rooms with Unsaflok. It seems that security problems are endemic.
  3. The “fix” or “remedial” steps involve users, government agencies, and industry groups. I interpret the argument as suggesting that companies developing operating systems need help and possibly cannot be responsible for these security problems.

The article can be read as a summary of recent developments in the specialized software sector and its careless handling of its technology. However, I think the article is suggesting that the companies building and enabling mobile computing are just victimized by bad actors, lousy regulations, and sloppy government behaviors.

Maybe? I believe I will tilt toward the content marketing purpose of the write up. The argument “Hey, it’s not us” is not convincing me. I think it will complement other articles that blur responsibility the way faces are blurred in some videos.

Stephen E Arnold, March 28, 2024

Backpressure: A Bit of a Problem in Enterprise Search in 2024

March 27, 2024

green-dino_thumb_thumb_thumbThis essay is the work of a dumb dinobaby. No smart software required.

I have noticed numerous references to search and retrieval in the last few months. Most of these articles and podcasts focus on making an organization’s data accessible. That’s the same old story told since the days of STAIRS III and other dinobaby artifacts. The gist of the flow of search-related articles is that information is locked up or silo-ized. Using a combination of “artificial intelligence,” “open source” software, and powerful computing resources — problem solved.


A modern enterprise search content processing system struggles to keep pace with the changes to already processed content (the deltas) and the flow of new content in a wide range of file types and formats. Thanks, MSFT Copilot. You have learned from your experience with Fast Search & Transfer file indexing it seems.

The 2019 essay “Backpressure Explained — The Resisted Flow of Data Through Software” is pertinent in 2024. The essay, written by Jay Phelps, states:

The purpose of software is to take input data and turn it into some desired output data. That output data might be JSON from an API, it might be HTML for a webpage, or the pixels displayed on your monitor. Backpressure is when the progress of turning that input to output is resisted in some way. In most cases that resistance is computational speed — trouble computing the output as fast as the input comes in — so that’s by far the easiest way to look at it.

Mr. Phelps identifies several types of backpressure. These are:

  1. More info to be processed than a system can handle
  2. Reading and writing file speeds are not up to the demand for reading and writing
  3. Communication “pipes” between and among servers are too small, slow, or unstable
  4. A group of hardware and software components cannot move data where it is needed fast enough.

I have simplified his more elegantly expressed points. Please, consult the original 2019 document for the information I have hip hopped over.

My point is that in the chatter about enterprise search and retrieval, there are a number of situations (use cases to those non-dinobabies) which create some interesting issues. Let me highlight these and then wrap up this short essay.

In an enterprise, the following situations exist and are often ignored or dismissed as irrelevant. When people pooh pooh my observations, it is clear to me that these people have [a] never been subject to a legal discovery process associated with enterprise search fraud and [b] are entitled whiz kids who don’t do too much in the quite dirty, messy, “real” world. (I do like the variety in T shirts and lumberjack shirts, however.)

First, in an enterprise, content changes. These “deltas” are a giant problem. I know that none of the systems I have examined, tested, installed, or advised which have a procedure to identify a change made to a PowerPoint, presented to a client, and converted to an email confirming a deal, price, or technical feature in anything close to real time. In fact, no one may know until the president’s laptop is examined by an investigator who discovers the “forgotten” information. Even more exciting is the opposing legal team’s review of a laptop dump as part of a discovery process “finds” the sequence of messages and connects the dots. Exciting, right. But “deltas” pose another problem. These modified content objects proliferate like gerbils. One can talk about information governance, but it is just that — talk, meaningless jabber.

Second, the content which an employees needs to answer a business question in a timely manner can reside in am employee’s laptop or a mobile phone, a digital notebook, in a Vimeo video or one of those nifty “private” YouTube videos, or behind the locked doors and specialized security systems loved by some pharma company’s research units, a Word document in something other than English, etc. Now the content is changed. The enterprise search fast talkers ignore identifying and indexing these documents with metadata that pinpoints the time of the change and who made it. Is this important? Some contract issues require this level of information access. Who asks for this stuff? How about a COTR for a billion dollar government contract?

Third, I have heard and read that modern enterprise search systems “use”, “apply,” “operate within” industry standard authentication systems. Sure they do within very narrowly defined situations. If the authorization system does not work, then quite problematic things happen. Examples range from an employee’s failure to find the information needed and makes a really bad decision. Alternatively the employee goes on an Easter egg hunt which may or may not work, but if the egg found is good enough, then that’s used. What happens? Bad things can happen? Have you ridden in an old Pinto? Access control is a tough problem, and it costs money to solve. Enterprise search solutions, even the whiz bang cloud centric distributed systems, implement something, which is often not the “right” thing.

Fourth, and I am going to stop here, the problem of end-to-end encrypted messaging systems. If you think employees do not use these, I suggest you do a bit of Eastern egg hunting. What about the content in those systems? You can tell me, “Our company does not use these.” I say, “Fine. I am a dinobaby, and I don’t have time to talk with you because you are so much more informed than I am.”

Why did I romp though this rather unpleasant issue in enterprise search and retrieval? The answer is, “Enterprise search remains a problematic concept.” I believe there is some litigation underway about how the problem of search can morph into a fantasy of a huge business because we have a solution.”

Sorry. Not yet. Marketing and closing deals are different from solving findability issues in an enterprise.

Stephen E Arnold, March 27, 2024

Research into Baloney Uses Four Letter Words

March 25, 2024

green-dino_thumb_thumb_thumbThis essay is the work of a dumb dinobaby. No smart software required.

I am critical of university studies. However, I spotted one which strikes as the heart of the Silicon Valley approach to life. “Research Shows That People Who BS Are More Likely to Fall for BS” has an interesting subtitle; to wit:

People who frequently mislead others are less able to distinguish fact from fiction, according to University of Waterloo researchers


A very good looking bull spends time reviewing information helpful to him in selling his artificial intelligence system. Unlike the two cows, he does not realize that he is living in a construct of BS. Thanks, MSFT Copilot. How are you doing with those printer woes today? Good enough, I assume.

Consider the headline in the context of promises about technologies which will “change everything.” Examples range from the marvels of artificial intelligence to the crazy assertions about quantum computing. My hunch is that the reason baloney has become one of the most popular mental foods in the datasphere is that people desperately want a silver bullet. Other know that if a silver bullet is described with appropriate language and a bit of sizzle, the thought can be a runway for money.

What’s this mean? We have created a culture in North America that makes “technology” and “glittering generalities” into hyperbole factories.  Why believe me? Let’s look at the “research.”

The write up reports:

People who frequently try to impress or persuade others with misleading exaggerations and distortions are themselves more likely to be fooled by impressive-sounding misinformation… The researchers found that people who frequently engage in “persuasive bullshitting” were actually quite poor at identifying it. Specifically, they had trouble distinguishing intentionally profound or scientifically accurate fact from impressive but meaningless fiction. Importantly, these frequent BSers are also much more likely to fall for fake news headlines.

Let’s think about this assertion. The technology story teller is an influential entity. In the world of AI, for example, some firms which have claimed “quantum supremacy” showcase executives who spin glorious word pictures of smart software reshaping the world. The upsides are magnetic; the downsides dismissed.

What about crypto champions? Telegram, founded by two Russian brothers, are spinning fabulous tales of revenue from advertising in an encrypted messaging system and cheerleading for a more innovative crypto currency. Operating from Dubai, there are true believers. What’s not to like? Maybe these bros have the solution that has long been part of the Harvard winkle confections.

What shocked me about the write up was the use of the word “bullshit.” Here’s an example from the academic article:

“We found that the more frequently someone engages in persuasive bullshitting, the more likely they are to be duped by various types of misleading information regardless of their cognitive ability, engagement in reflective thinking, or metacognitive skills,” Littrell said. “Persuasive BSers seem to mistake superficial profoundness for actual profoundness. So, if something simply sounds profound, truthful, or accurate to them that means it really is. But evasive bullshitters were much better at making this distinction.”

What if the write up is itself BS? What if the journal publishing the article — British Journal of Social Psychology — is BS? On one level, I want to agree that those skilled in the art of baloney manufacturing, distributing, and outputting have a quite specific skill. On the other hand, I admit that I cannot determine at first glance if the information provided is not synthetic, ripped off, shaped, or weaponized. I would assert that most people are not able to identify what is “verifiable”, “an accurate accepted fact”, or “true.”

We live in a post-reality era. When the presidents of outfits like Harvard and Stanford face challenges to their research accuracy, what can I do when confronted with a media release about BS. Upon reflection, I think the generalization that people cannot figure out what’s on point or not is true. When drug store cashiers cannot make change, I think that’s strong anecdotal evidence that other parts of their mental toolkit have broken or missing parts.

But the statement that those who output BS cannot themselves identify BS may be part of a broader educational failure. Lazy people, those who take short cuts, people who know how to do the PT Barnum thing, and sales professionals trying to close a deal reflect a societal issue. In a world of baloney, everything is baloney.

Stephen E Arnold, March 25, 2024

Peak AI? Do You Know What Happened to Catharists? Quiz ChatGPT or Whatever

March 21, 2024

green-dino_thumb_thumb_thumbThis essay is the work of a dumb dinobaby. No smart software required.

I read “Have We Reached Peak AI?” The question is an interesting one because some alleged monopolies are forming alliances with other alleged monopolies. Plus wonderful managers from an alleged monopoly is joining another alleged monopoly to lead a new “unit” of the alleged monopoly. At the same time, outfits like the usually low profile Thomson Reuters suggested that it had an $8 billion war chest for smart software. My team and I cannot keep up with the announcements about AI in fields ranging from pharma to ransomware from mysterious operators under the control of wizards in China and Russia.


Thanks, MSFT Copilot. You did a good job on the dinobabies.

Let’s look at a couple of statements in the essay which addresses the “peak AI” question.

I noticed that OpenAI is identified as an exemplar of a company that sticks to a script, avoids difficult questions, and gets a velvet glove from otherwise pointy fingernailed journalists. The point is well taken; however, attention does not require substance. The essay states:

OpenAI’s messaging and explanations of what its technology can (or will) do have barely changed in the last few years, returning repeatedly to “eventually” and “in the future” and speaking in the vaguest ways about how businesses make money off of — let alone profit from — integrating generative AI.

What if the goal of the interviews and the repeated assertions about OpenAI specifically and smart software in general is publicity and attention. Cut off the buzz for any technology and it loses its shine. Buzz is the oomph in the AI hot house. Who cares about Microsoft buying into games? Now who cares about Microsoft hooking up with OpenAI, Mistral, and Inception? That’s what the meme life delivers. Games, sigh. AI, let’s go and go big.

Another passage in the essay snagged me:

I believe a large part of the artificial intelligence boom is hot air, pumped through a combination of executive bullshitting and a compliant media that will gladly write stories imagining what AI can do rather than focus on what it’s actually doing.

One of my team members accused me of FOMO when I told Howard to get us a Flipper. (Can one steal a car with a Flipper? The answer is, “Not without quite a bit of work.) The FOMO was spot on. I had a “fear of missing out.” Canada wants to ban the gizmos. Hence, my request, “Get me a Flipper.” Most of the “technology” in the last decade is zipping along on marketing, PR, and YouTube videos. (I just watched a private YouTube video about intelware which incorporates lots of AI. Is the product available? Nope. But… soon. Let the marketing and procurement wheels begin turning.)

Journalists (often real ones) fall prey to FOMO. Just as I wanted a Flipper, the “real” journalists want to write about what’s apparently super duper important. The Internet is flagging. Quantum computing is old hat and won’t run in a mobile phone. The new version of Steve Gibson’s Spinrite is not catching the attention of blue chip investment firms. Even the enterprise search revivifier Glean is not magnetic like AI.

The issue for me is more basic than the “Peak AI” thesis; to wit, What is AI? No one wants to define it because it is a bit like “security.” The truth is that AI is a way to make money in what is a fairly problematic economic setting. A handful of companies are drowning in cash. Others are not sure they can keep the lights on.

The final passage I want to highlight is:

Eventually, one of these companies will lose a copyright lawsuit, causing a brutal reckoning on model use across any industry that’s integrated AI. These models can’t really “forget,” possibly necessitating a costly industry-wide retraining and licensing deals that will centralize power in the larger AI companies that can afford them.

I would suggest that Google has already been ensnared by the French regulators. AI faces an on-going flow of legal hassles. These range from cash-starved publishers to the work-from-home illustrator who does drawings for a Six-Flags-Over-Jesus type of super church. Does anyone really want to get on the wrong side of a super church in (heaven forbid) Texas?

I think the essay raises a valid point: AI is a poster child of hype.

However, as a dinobaby, I know that technology is an important part of the post-industrial set up in the US of A. Too much money will be left on the table unless those savvy to revenue flows and stock upsides ignore the mish-mash of AI. In an unregulated setting, people need and want the next big thing. Okay, it is here. Say “hello” to AI.

Stephen E Arnold, March 21, 2024

Want Clicks: Do Sad, Really, Really Sorrowful

March 13, 2024

green-dino_thumb_thumb_thumbThis essay is the work of a dumb dinobaby. No smart software required.

The US is a hotbed of negative news. It’s what drives the media and perpetuates the culture of fear that (arguably) has plagued the country since colonial times. US citizens and now the rest of the world are so addicted to bad news that a research team got the brilliant idea to study what words people click. Nieman Lab wrote about the study in, “Negative Words In News Headlines Generate More Clicks-But Sad Words Are More Effective Than Angry Or Scary Ones.”


Thanks, MSFT Copilot. One of Redmond’s security professionals I surmise?

Negative words are prevalent in headlines because they sell clicks. The Nature Human Behavior(u)r journal published a study called “Negativity Drives Online News Consumption.” The study analyzed the effect of negative and emotional words on news consumption and the research team discovered that negativity increased clickability. These findings also confirm the well-documented behavior of humans seeking negativity in all information-seeking.

It coincides with humanity’s instinct to be vigilant of any danger and avoid it. While humans instinctually gravitate towards negative headlines, certain negative words are more popular than others. Humans apparently are driven to click on sad-related synonyms, avoid anything resembling joy or fear, and angry words don’t have any effect. It all goes back to survival:

“And if we are to believe “Bad is stronger than good” derives from evolutionary psychology — that it arose as a useful heuristic to detect threats in our environment — why would fear-related words reduce likelihood to click? (The authors hypothesize that fear and anger might be more important in generating sharing behavior — which is public-facing — than clicks, which are private.)

In any event, this study puts some hard numbers to what, in most newsrooms, has been more of an editorial hunch: Readers are more drawn to negativity than to positivity. But thankfully, the effect size is small — and I’d wager that it’d be even smaller for any outlet that decided to lean too far in one direction or the other.”

It could also be a strict diet of danger-filled media too.

Whitney Grace, March 13, 2024

In Tech We Mistrust

March 11, 2024

While tech firms were dumping billions into AI, they may have overlooked one key component: consumer faith. The Hill reports, “Trust in AI Companies Drops to 35 Percent in New Study.” We note that 35% figure is for the US only, while the global drop was a mere 8%. Still, that is the wrong direction for anyone with a stake in the market. So what is happening? Writer Filip Timotija tells us:

So it is not just AI we mistrust, it is tech companies as a whole. That tracks. The study polled 32,000 people across 28 countries. Timotija reminds us regulators in the US and abroad are scrambling to catch up. Will fear of consumer rejection do what neither lagging lawmakers nor common decency can? The write-up notes:

“Westcott argued the findings should be a ‘wake up call’ for AI companies to ‘build back credibility through ethical innovation, genuine community engagement and partnerships that place people and their concerns at the heart of AI developments.’ As for the impacts on the future for the industry as a whole, ‘societal acceptance of the technology is now at a crossroads,’ he said, adding that trust in AI and the companies producing it should be seen ‘not just as a challenge, but an opportunity.’” “Multiple factors contributed to the decline in trust toward the companies polled in the data, according to Justin Westcott, Edelman’s chair of global technology. ‘Key among these are fears related to privacy invasion, the potential for AI to devalue human contributions, and apprehensions about unregulated technological leaps outpacing ethical considerations,’ Westcott said, adding ‘the data points to a perceived lack of transparency and accountability in how AI companies operate and engage with societal impacts.’ Technology as a whole is losing its lead in trust among sectors, Edelman said, highlighting the key findings from the study. ‘Eight years ago, technology was the leading industry in trust in 90 percent of the countries we study,’ researchers wrote, referring to the 28 countries. ‘Now it is most trusted only in half.’”

Yes, an opportunity. All AI companies must do is emphasize ethics, transparency, and societal benefits over profits. Surely big tech firms will get right on that.

Cynthia Murrell, March 11, 2024

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