Google: Position on Its Ad Moxie
August 12, 2021
I read “US Judicial Panel Moves Texas Lawsuit against Google to New York.” The guts of the story is some legal maneuvering about where allegations about Alphabet Google will be adjudicated. As in real estate, the keys to value is location, location, location. The legal dust up will take place in the Big Apple.
In the article was a quote allegedly made by a Googley-type. My hunch is that this frank, clear, and positive statement vivifies how the mom and pop online ad outfit will position itself. Here’s the quote:
Google welcomed the panel’s decision, saying it would lead to “just and efficient litigation. “We look forward to demonstrating how our advertising business competes fiercely and fairly to the benefit of publishers, advertisers and consumers,” a Google spokeswoman said in an email statement.
I wonder if the Google used this language in its embrace of recently concluded French litigation?
Stephen E Arnold, August 12, 2021
Microsoft: Amazing Quote about Support
August 12, 2021
I read “El Reg talks to Azure Data veep as Microsoft flicks the switch on Azure Arc for SQL Managed Instances: Longevity, PostgreSQL, and the Default Relational Database of Choice.” I like the phrase “default relational database of choice.” Okay, confidence can be a positive.
Most of the interview is not-so-surprising stuff: End-of-life assurances, hits of a catholic approach to the Codd structure, and a general indifference to the Amazon database initiatives. That’s okay. The expert is Rohan Kumar, who is going to speak Redmond, a peculiar dialect of jargon which often reveals little relevant to the ordinary person trying to restore a trashed SQL Server table.
I did spot one tiny comment. Here is this remarkable assertion:
“We will never let any of our customers run into challenges because Microsoft decided, ‘hey, we’re not going to support you’.”
No kidding? For real? I mean none of the code blocking, security challenging stuff?
Stephen E Arnold, August 12, 2021
Europe: Privacy Footnote
August 11, 2021
If you are not familiar with Chatcontrol, there’s a mostly useful list of resources on the Digital Human Rights blog. The article “Messaging and Chat Control” offers some context as well as a foreshadowing of the possible trajectory of this EU initiative.
The Chatcontrol legislation meshes with Apple’s recent statement that it would be more proactive and transparent about its monitoring activity. You can get a sense of this action in “Expanded Protections for Children.”
A schism exists between those who want to move whatever content is of interest freely. On the other side of the gap are those who want to put controls on digital content flow.
Observations I noted on a flight home from Washington, DC Monday, August 10, 2021, included:
- Digital content flows accelerate and facilitate some unpleasant facets of human behavior. Vendors have done little since the dawn of “online” to manage corrosive bits. Is this now a surprise that after 50 years, elected officials are trying to take action.
- The failure to regulate has been a result of generate misunderstanding of the nature of unfettered digital information flows. As I have pointed out, digital content works exactly like glass beads propelled at a rusted fender. Once the rust is gone, keeping the nozzle aimed at the fender blasts the fender away as well. Hence, we have the social fabric in its present and rapidly deteriorating condition.
- One property of digital information is that those with expertise in digital information can innovate. Thus, there will be workarounds. Some of these will be deployed more rapidly than the filtering and control mechanisms can be updated. I point this out because once a control system is imposed, it becomes increasingly difficult and expensive to keep in tip top shape.
Net net: China has been the pace-setter in this approach to digital information. How easy is it to sketch the trajectory of these long-overdue actions? That’s an interesting question to ponder after a half century to stumble into the school room with a mobile phone and a perception that the online equipped person is a wizard.
Stephen E Arnold, August 11, 2021
A Tiny Idea: Is a New Governmental Thought Shaper Emerging?
August 11, 2021
I read “China’s Top Propaganda Agencies Want to Limit the Role of Algorithms in Distributing Online Content.” What an interesting idea. De-algorithm certain Fancy Dan smart software. Make a human or humanoids responsible for what gets distributed online. Laws apparently are not getting throiugh to the smart software used for certain technology publishing functions. The fix, according to the article, is:
China’s top state propaganda organs, which decide what people can read and watch in the country, have jointly urged better “culture and art reviews” in China partly by limiting the role of algorithms in content distribution, a policy move that could translate into higher compliance costs for online content providers such as ByteDance and Tencent Holdings. The policy guidelines from the Central Propaganda Department of the Communist Party, the Ministry of Culture and Tourism and the State Administration of Radio and Television as well as the China Federation of Literary and Art Circles and Chinese Writers Association, the two state-backed bodies for state-approved artists and authors, mark the latest effort by Beijing to align online content with the state’s agenda and to rein in the role of capital and technology in shaping the country’s minds and mainstream views.
The value of putting a human or humanoids in the target zone is an explicit acknowledgement that “gee, I’m sorry” and “our algorithms are just so advanced my team does not know what those numerical recipes are doing” will not fly or get to the airport.
I am not too interested in the impact of these rules in the Middle Kingdom. What I want to track is how these rules diffuse to nation states which are counting on a big time rail link or money to fund Chinese partners’ projects.
Net net: Chinese government agencies, where monitoring and internal checks and balances are an art form, possibly will make use of interesting algorithms. Commercial enterprises and organizations grousing about China’s rules and regulations will have fewer degrees of freeedom. Maybe no freedom at all. Ideas may not be moving from the US East Coast and the West Coast. Big ideas like clipping algorithmic wings are building in China and heading out. Will the idea catch on?
Stephen E Arnold, August 11, 2021
Algolia and Its View of the History of Search: Everyone Has an Opinion
August 11, 2021
Search is similar to love, patriotism, and ethical behavior. Everyone has a different view of the nuances of meaning with a specific utterance. Agree? Let’s assume you cannot define one of these words in a way that satisfies a professor from a mid tier university teaching a class to 20 college sophomores who signed up for something to do with Western philosophy: Post Existentialism. Imagine your definition. I took such a class, and I truly did not care. I wrote down the craziness the brown clad PhD provided, got my A, and never gave that stuff a thought. And you, gentle reader, are you prepared to figure out what an icon in an ibabyrainbow chat stream “means.” We captured a stream for one of my lectures to law enforcement in which she says, “I love you.” Yeah, right.
Now we come to “Evolution of Search Engines Architecture – Algolia New Search Architecture Part 1.” The write up explains finding information, and its methods through the lens of Algolia, a publicly traded firm. Search, which is not defined, characterizes the level of discourse about findability. The write up explains an early method which permitted a user to query by key words. This worked like a champ as long as the person doing the search knew what words to use like “nuclear effects modeling”.
The big leap was faster computers and clever post-Verity methods of getting distributed index to mostly work. I want to mention that Exalead (which may have had an informing role to play in Algolia’s technical trajectory) was a benchmark system. But, alas, key words are not enough. The Endeca facets were needed. Because humans had to do the facet identification, the race was on to get smart software to do a “good enough” job so old school commercial database methods could be consigned to a small room in the back of a real search engine outfit.
Algolia includes a diagram of the post Alta Vista, post Google world. The next big leap was scaling the post Google world. What’s interesting is that in my experience, most search problems result in processing smaller collections of information containing disparate content types. What’s this mean? When were you able to use a free Web search system or an enterprise search system like Elastic or Yext to retrieve text, audio, video, engineering drawings and their associated parts data, metadata from surveilled employee E2EE messages, and TikTok video résumés or the wildly entertaining puff stuff on LinkedIn? The answer is and probably will be for the foreseeable future, “No.” And what about real time data, the content on a sales person’s laptop with the changed product features and customer specific pricing. Oh, right. Some people forget about that. Remember. I am talking about a “small” content set, not the wild and crazy Internet indexes. Where are those changed files on the Department of Energy Web site? Hmmm.
The fourth part of the “evolution” leaps to keeping cloud centric, third party hosted chugging along. Have you noticed the latency when using the OpenText cloud system? What about the display of thumbnails on YouTube? What about retrieving a document from a content management system before lunch, only to find that the system reports, “Document not found.” Yeah, but. Okay, yeah but nothing.
The final section of the write up struck me as a knee slapper. Algolia addresses the “current challenges of search.” Okay, and what are these from the Algolia point of view: The main points have to do with using a cloud system to keep the system up and running without trashing response time. That’s okay, but without a definition of search, the fixes like separating search and indexing may not be the architectural solution. One example is processing streams of heterogeneous data in real time. This is a big thing in some circles and highly specialized systems are needed to “make sense” of what’s rushing into a system. Now means now, not a latency centric method which has remain largely unchanged for – what? — maybe 50 years.
What is my view of “search”? (If you are a believer that today’s search systems work, stop reading.) Here you go:
- One must define search; for example, chemical structure search, code search, HTML content search, video search, and so on. Without a definition, explanations are without context and chock full of generalizations.
- Search works when the content domain is “small” and clearly defined. A one size fits all content is pretty much craziness, regardless of how much money an IPO’ed or SPAC’ed outfit generates.
- The characteristic of the search engines my team and I have tested over the last — what is it now, 40 or 45 years — is that whatever system one uses is “good enough.” The academic calculations mean zero when an employee cannot locate the specific item of information needed to deal with a business issue or a student wants to locate a source for a statement from a source about voter fraud. Good enough is state of the art.
- The technology of search is like a 1962 Corvette. It is nice to look at but terrible to drive.
Net net: Everyone is a search expert now. Yeah, right. Remember: The name of the game is sustainable revenue, not precision and recall, high value results, or the wild and crazy promise that Google made for “universal search”. Ho ho ho.
Stephen E Arnold, August 11, 2021
NSO Group: Origins
August 11, 2021
I read “Israel Tries to Limit Fallout from the Pegasus Spyware Scandal.”
I noted this statement which is has been previously bandied about:
Israel has been trying to limit the damage the Pegasus spyware scandal is threatening to do to France-Israel relations. The Moroccan intelligence service used the software, made by an Israeli company with close ties to Israel’s defense and intelligence establishments, to spy on dozens of French officials, including fourteen current and former cabinet ministers, among them President Emmanuel Macron and former prime minister Edouard Phillipe.
The write up reports:
There were reasons for Macron’s irritation: The NSO Group was established in 2009 by three Israelis — Niv Carmi, Shalev Hulio, and Omri Lavie. Contrary to popular belief, the three were not veterans of the vaunted Unit 8200, the IDF’s signal intelligence branch (although many of the company’s employees are). It is generally accepted by intelligence services around the world that many Israeli high-tech companies share information they glean from their contracts abroad with the Israeli security services, if they think such information is vital to Israel’s security (this is why the Committee on Foreign Investment in the United States, or CFIUS, has been reluctant to allow Israeli cyber companies access to the U.S. market).
Interesting.
Stephen E Arnold, August 11, 2021
DuckDuckGo Produces Privacy Income
August 10, 2021
DuckDuckGo advertises that it protects user privacy and does not have targeted ads in search results. Despite its small size, protecting user privacy makes DuckDuckGo a viable alternative to Google. TechRepublic delves into DuckDuckGo’s profits and how privacy is a big money maker in the article, “How DuckDuckGo Makes Money Selling Selling Search, Not Privacy.” DuckDuckGo has had profitable margins since 2014 and made over $100 million in 2020.
Google, Bing, and other companies interested in selling personal data say that it is a necessary evil in order for search and other services to work. DuckDuckGo says that’s not true and the company’s CEO Gabriel Weinberg said:
“It’s actually a big myth that search engines need to track your personal search history to make money or deliver quality search results. Almost all of the money search engines make (including Google) is based on the keywords you type in, without knowing anything about you, including your search history or the seemingly endless amounts of additional data points they have collected about registered and non-registered users alike. In fact, search advertisers buy search ads by bidding on keywords, not people….This keyword-based advertising is our primary business model.”
Weinberg continued that search engines do not need to track as much personal information as they do to personalize customer experiences or make money. Search engines and other online services could limit the amount of user data they track and still generate a profit.
Google made over $147 billion in 2020, but DuckDuckGo’s $100 million is not a small number either. DuckDuckGo’s market share is greater than Bing’s and, if limited to the US market, its market share is second to Google. DuckDuckGo is a like the Little Engine That Could. It is a hard working marketing operation and it keeps chugging along while batting the privacy beach ball along the Madison Avenue sidewalk.
Whitney Grace, August 10, 2021
COVID Forces Google To Show Its Work And Cites Sources
August 10, 2021
Do you remember in math class when you were told to show you work or when writing an essay you had to cite your sources? Google has decided to do the same thing with its search results says Today Online in the article, “Google Is Starting To Tell You How It Found Search Results.” Google wants to share with users why they are shown particular results. Soon Google will display an option within search results that allows users to see how results were matched to their query. Google wants users to know where their search results come from to better determine relevancy.
Google might not respect users’ privacy, but they do want to offer better transparency in search results. Google wants to explain itself and help its users make better decisions:
“Google has been making changes to give users more context about the results its search engine provides. Earlier this year it introduced panels to tell users about the sources of the information they are seeing. It has also started warning users when a topic is rapidly evolving and search results might not be reliable.”
Google search makes money by selling ads and sponsoring content in search results. Google labels any sponsored results with an “ad” tag. However, one can assume that Google does push more sponsored content into search results than it tells users. Helping users understand content and make informative choices, is a great way to educate users. Google isn’t being altruistic, though. Misinformation about vaccines and COVID-19 has spread like wildfire since the past US presidential administration. Users have demanded that Google, Facebook, and other tech companies be held accountable as they are platforms used to spread misinformation. Google sharing the why behind search queries is a start, but how many people will actually read them?
Whitney Grace, August 10, 2021
Quote to Note: An Open Source Developer Speaks Truth
August 10, 2021
Navigate to “Lessons Learned from 15 Years of SumatraPDF, an Open Source Windows App.” Please, read the article. It is excellent and applicable to commercial software as well.
Here’s the quote I circled and enhanced with an exclamation point:
… changing things takes effort and the path of least resistance is to do nothing.
Keep this statement in mind when Microsoft says it has enhanced the security of its updating method or when Google explains that it has improved its search algorithm.
The author of “Lessons Learned…” quotes Jeff Bezos (the cowboy hat wearing multi billionaire who sent interesting images which were stunning I have heard) as saying:
There will never be a time when users want bloated and slow apps so being small and fast is a permanent advantage.
I would add that moving data rapidly out of an AWS module evokes an Arnold corollary:
Speed costs more, often a lot more.
The essay is a good one, and I recommend that you read it, not just the quotes I reproduced in this positive comment about the content.
Stephen E Arnold, August 10, 2021
Explaining Me-Too, Copycatting, and What Might be Theft
August 10, 2021
Consider TikTok. LinkedIn has found itself behind the video résumé eight ball. The Google, not to be left out of the short video game, is rolling out YouTube Shorts. Despite the hoo-ha output on a podcast with two alpha wizards, the Shorts thing is a lot like TikTok. Instead of China’s watchful eye, the Google just wants to keep advertisers happy, really, really happy. Which is better? Wow, that’s an interesting question when one defines “better.” I don’t know what better means, but you may.
I read “Is Iterated Amplification Really More Powerful Than Imitation?” For me, the write up is a logical differentiation within the adage “If it looks like a duck, swims like a duck, and quacks like a duck, then it probably is a duck.” Yep, that smart software has identified actor A and a match for a known bad actor. Works great. Sort of.
However, the duck analogy is of little utility in the work from home, thumb typing world. Thus, enter the phrase iterated amplification. The euphony is notable, but I am a duck kind of person.
The write up explains in a way which evokes memories of my one and only college course in semantics. Who taught this gem? A PhD from somewhere east of Russia who aspired to make the phoneme –er his life’s work. The –er in which he was planning to leverage into academic fame was its usage in words like hamburger. Okay, I will have a duckburger with pickles and a dash of -mustard. So it is not me-too; it is imitative, iterated amplification. (And the logical end point is similar, if not almost identical systems. A bit like ducks maybe?)
I learned in the essay:
iterated amplification is not necessarily the most efficient way to create a more powerful AI, and a human mimics would have the flexibility to choose other techniques. Current AI researchers don’t usually try to increase AI capabilities by iterated amplifications, but instead by coming up with new algorithms.
“New algorithms?” I thought today’s smart software recycled code chunks from open sources, friendly smart cloud outfits like Amazon, Google, IBM (excited am I), Microsoft, and others.
The innovation might be interpreted as playing with thresholds and fiddling with the knobs and dials on procedures explained in class or by textbook writers like Peter Norvig. Lectures on YouTube can be helpful too. Maybe what works best is a few smart interns who are given the message: Adjust until we get something we can use.
Duck analogy: Google’s DeepMind has been me-too’ed by other outfits. These outfits have mostly forgotten where the method originated. Upon inspection, the method may have been the outcome of a classroom assignment.
That’s why facial recognition systems and other applications of smart software often generate me too, me too outputs; that is, misidentification is more reliable than identification. With recognition ranging from 30 percent confidence to 90 percent confidence, there’s some room for error. Actually, there’s room for darned crazy errors and fascinating secondary consequences.
Just admit that “innovation” is not much different from a duck. And imitation is less costly than doing the original thinking work. Revenue, not bright ideas, are more reliable than cooking up a power from the air scheme.
Stephen E Arnold, August 10, 2021
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