Plus, I found the name “fulfilled action” fulfilling.
Smarsh Acquires Digital Reasoning
November 26, 2020
On its own website, communications technology firm Smarsh crows, “Smarsh Acquires Digital Reasoning, Combining Global Leadership in Artificial Intelligence and Machine Learning with Market Leading Electronic Communications Archiving and Supervision.” It is worth noting that Digital Reasoning was founded by a college philosophy senior, Tim Estes, who saw the future in machine learning back in 2000. First it was a search system, then an intelligence system, and now part of an archiving system. The company has been recognized among Fast Company’s Most Innovative Companies for AI and recently received the Frost & Sullivan Product Leadership Award in the AI Risk Surveillance Market. Smarsh was smart to snap it up. The press release tells us:
“The transaction brings together the leadership of Smarsh in digital communications content capture, archiving, supervision and e-discovery, with Digital Reasoning’s leadership in advanced AI/ML powered analytics. The combined company will enable customers to spot risks before they happen, maximize the scalability of supervision teams, and uncover strategic insights from large volumes of data in real-time. Smarsh manages over 3 billion messages daily across email, social media, mobile/text messaging, instant messaging and collaboration, web, and voice channels. The company has unparalleled expertise in serving global financial institutions and US-based wealth management firms across both the broker-dealer and registered investment adviser (RIA) segments.”
Dubbing the combined capabilities “Communications Intelligence,” Smarsh’s CEO Brian Cramer promises Digital Reasoning’s AI and machine learning contributions will help clients better manage risk and analyze communications for more profitable business intelligence. Estes adds,
“In this new world of remote work, a company’s digital communications infrastructure is now the most essential one for it to function and thrive. Smarsh and Digital Reasoning provide the only validated and complete solution for companies to understand what is being said in any digital channel and in any language. This enables them to quickly identify things like fraud, racism, discrimination, sexual harassment, and other misconduct that can create substantial compliance risk.”
See the write-up for its list of the upgraded platform’s capabilities. Smarsh was founded in 2001 by financial services professional Stephen Marsh (or S. Marsh). The company has made Gartner’s list of Leaders in Enterprise Information Archiving for six years running, among other accolades. Smarsh is based in Portland, Oregon, and maintains offices in several major cities worldwide.
Our take? Search plus very dense visualization could not push some government applications across the warfighting finish line. Smarsh on!
Cynthia Murrell, November 26, 2020
Amazon Policeware: Despite Low Profile It Exists
November 25, 2020
Navigate to the trustworthy Berkshire Hathaway Company Businesswire. Read “IPR Center, Amazon Launch ‘Operation Fulfilled Action’ to Stop Counterfeits.” Note that IPR means U.S. government’s National Intellectual Property Rights Coordination Center. Here’s a passage I found interesting:
“Amazon conducts investigations and sidelines inventory if we suspect a product may be counterfeit, ensuring our customers are protected,” said Dharmesh Mehta, vice president, Customer Trust and Partner Support, Amazon. “But we also know that counterfeiters don’t just attempt to offer their wares in one store, they attempt to offer them in multiple places. Now, by combining intelligence from Amazon, the IPR Center, and other agencies, we’re able to stop counterfeits at the border, regardless of where bad actors were intending to offer them. We appreciate the partnership from the IPR Center and other agencies to protect American consumers and prosecute bad actors.”
Investigations? Yep. Read on.
In an effort to protect consumers, this joint operation will analyze data and conduct targeted inspections aimed at preventing counterfeit products from entering the U.S. supply chain. The IPR Center and Amazon will leverage evidence obtained during the operation to expand on-going investigations, with the goal of holding bad actors accountable to the fullest extent of the law. This operation will be led by Amazon’s Counterfeit Crimes Unit, which was created earlier this year to support law enforcement investigations and to initiate civil litigation against counterfeiters.
To learn more about Amazon policeware and intelware, write benkent2020 at yahoo dot com. The DarkCyber research team offers a one hour, for fee Zoom lecture about this interesting and now quite public Amazon capability.
Stephen E Arnold, November 25, 2020
Google: Poetry Creation Made Eneasy
November 25, 2020
I spotted “Google’s Verse by Verse AI Can Help You Write in the Style of Famous Poets.” The subtitle illustrates why this Google innovation is probably going to find some Silicon Valley Shakespeares:
Quoth the Bugdroid, “Nevermore.”
The write up guides the reader to this url. Then the page displays:
Okay, let’s write a poem with the Google smart software. I am skeptical because Google set out to solve death. So far, no luck with that project. For poetic style, I quite like the approach of William Abernathy, who wrote a remarkable tribute to Queen Elizabeth called Elisaeis, Apotheosis poeticaas in Latin when he was trying to avoid arrest for religious heresy. (For more info on William Abernathy, navigate to your local university library and chase down Vol. 76, No. 5, Texts and Studies, 1979. “The Elisæis” of William Alabaster (Winter, 1979). Oh, the poem is a tribute to Elizabeth the First. Did I mention the poem was an epic, thousands upon thousands of lines. In Latin too. Hot stuff.)
Well, bummer. Mr. Alabaster is not listed as a stylistic choice on the Google write a poem Web site. I thought AI was smart. Well, let us sally forth with the clever and sometimes interesting Edwin Arlington Robinson who wrote:
Mininver loved the Medici,
Albeit he had never seen one;
He would have sinned incessantly
Could he have been one.
Yep, sin. But I had to pick other poets with which the smart Google AI is familiar. Trepedatiously I selected the fave of elderly literature teachers: Henry Wadsworth Longfellow. Plus in a nod to the Rona and rising infection rates, I plunked my mouse cursor on the liquor-loving and raven loving Edgar Allen Poe. Yep, I noted the “nevermore” in the article’s subtitle. Then I clicked “Next.”
I specified a quatrain in iambic pentameter with the rhyming scheme AB AB.
Google’s smart software wanted a chunk of poesy as a “seed” for the smart software. I provided:
Whoa, teenaged mind, cause no sorrow or pain
I want to point out that this is the first line of a poem my junior class English teacher Edwardine Sperling required us to write. (She loved cardinals, the bird, not the baseball team.) My poetic flight of fancy at age 15 on this line motivated Ms. Sperling to try and get me expelled me from high school. No sense of humor had she. (The compromise proposed by the assistant principal was that Ms Sperling could ban me from the National Honor Society as a result of my inappropriate writing, and I had to sit outside the class in the hallway for the remainder of the semester.)
And what was my “Spirit of Nature” poem about? Nothing much. Just sitting in the woods on a sunny day in early autumn. Then the Spirit of Nature emerged from a pile of leaves. I explained that my Spirit of Nature was the October 1959 Playmate of the Month from Playboy magazine. I elaborated via metaphors (terrible metaphors I must confess) how the Spirit of Nature or Miss October helped move away from “sorrow or pain.” I will leave the details to your imagination. My poem was a hoot. But I got the boot.
Back to the Google smart poetry writer, a system which I hypothesized would have zero imagination and would have been an A student in dear Ms. Sperling’s literature class.
I clicked the Next button again. Magic. Google’s fine system spit out after some prompting after I provided the first line in red. Google goodness is in blue:
Whoa, teenaged mind, cause no sorrow or pain
Enlife a phantom of an idle love;
Yet in a fancy I could now attain
Look on the beauty of that world above!
Great stuff those words in blue crafted sharp and true by Lord Google.
Ms Sperling would have relished the “enlife” word. The prefix “en” leads to many coinages; for example, enbaloney, enstupid, and enmarketing. Maybe enAI? Sure. But no Playboy bunnies. No filthy innuendo. No double entendre. The meaning thing eludes me, but, hey, Google couldn’t solve death either. The GOOG is not doing too well in poesie either I opine. Any questions about Google’s query ad matching semantic system? Good.
Stephen E Arnold, November 24, 2020
Smart Software: Does ML Have Fragile Hips and Painted Lips?
November 25, 2020
It looks like machine learning must head back to the drawing board. MIT Technology Review discusses recent findings from Google in, “The Way We Train AI Is Fundamentally Flawed.” This is not about the well-known problem of data shift, where data used to train algorithms is not close enough to real-world examples. This is something else entirely.
The paper, which represents the efforts of 40 researchers across seven Googley teams, brings what one engineer describes as a “wrecking ball” to the field. The paper calls the issue “under specification,” a term from statistics that describes an observed effect with many possible causes. Lead researcher Alex D’Amour, with his background in causal reasoning, found the term applies quite well to the machine-learning problem he set out to investigate. Writer Will Douglas Heaven explains:
“Roughly put, building a machine-learning model involves training it on a large number of examples and then testing it on a bunch of similar examples that it has not yet seen. When the model passes the test, you’re done. What the Google researchers point out is that this bar is too low. The training process can produce many different models that all pass the test but—and this is the crucial part—these models will differ in small, arbitrary ways, depending on things like the random values given to the nodes in a neural network before training starts, the way training data is selected or represented, the number of training runs, and so on. These small, often random, differences are typically overlooked if they don’t affect how a model does on the test. But it turns out they can lead to huge variation in performance in the real world. In other words, the process used to build most machine-learning models today cannot tell which models will work in the real world and which ones won’t.”
The researchers found this problem is all sorts of AI applications. Using homogenous training methods, they created several machine-learning models and performed stress tests designed to discern out performance differences. These models covered the areas of image recognition, natural language processing, and medical AI; see the article for specifics.
The main conclusion is that much more testing is needed before machine learning systems are put into practice—a process that is not always possible due to a lack of real-world data. D’Amour also advises engineers would do well to greatly narrow the requirements for their models. Then there is the suggestion that designers produce many models, test those on real-world tasks, and pick the best performer. Not a simple method, but one that might be worth the time and effort to a large company like Google. Whatever the solutions, it is clear AI is not performing as promised. Not yet at least.
Cynthia Murrell, November 25, 2020
China: Control and Common Sense. Common Sense?
November 25, 2020
I must admit that I saw some darned troubling things when I last visited China and Hong Kong. However, I spotted an allegedly accurate factoid in “China Bans Spending by Teens in New Curbs on Livestreaming.” In one of my lectures about the Dark Web I pointed out livestreaming sites which permitted gambling, purchase of merchandise which is now called by the somewhat jarring term “merch,” and buying “time” with an individual offering “private sessions.” I pointed out examples on Amazon Twitch and on a service called ManyVids, an online outfit operating from Canada. (Yep, dull, maple crazed Canada.)
Here’s the passage of particular significance in my opinion:
Livestreaming platforms now must limit the amount of money a user can give hosts as a tip. Users must register their real names to buy the virtual gifts, in addition to the ban on teens giving such gifts. The administration also asked the platforms to strengthen training for employees who screen content and encouraged the companies to hire more censors, who also will need to register with regulators. The media regulator will create a blacklist of hosts who frequently violate the rules, and ban them from hosting livestreaming programs on any platform. [Emphasis added by Beyond Search]
Okay, spending controls will force buyers (sometimes known as “followers”) to be more creative in the buying time function.
But the killer point is “real names.”
No doubt there are online consumers who will bristle at censorship, registration, and blacklisting. Nevertheless, “real names” might be a useful concept for online services not under the watchful eye of party faithful grandmas in a digital hotong. What a quaint idea for outfits like Facebook, Twitter, YouTube, and other online content outputters to consider.
Stephen E Arnold, November 25, 2020
Elastic: The Add Value to Open Source Outfit Bounces Along
November 25, 2020
Elastic Adds New Features to Enterprise Search, Observability, and Security Solutions
Search and data-management firm Elastic has some new features to crow about. BusinessWire posts “Elastic Announces Innovations Across its Solutions to Optimize Search and Enhance Performance and Monitoring Capabilities.” One new tool is Kibana Lens, a visual data analysis tool with a drag-and-drop interface described as intuitive. There is also a beta launch of the searchable snapshots, an efficient way to manage data storage tiers with searchable snapshots. The press release tells us:
“New expanded Elastic Observability features, including user experience monitoring and synthetics, give developers new tools to test, measure, and optimize end-user website experiences. The launch of a new dedicated User Experience app in Kibana provides Elastic customers with an enhanced view and understanding of how end users experience their websites. In addition, Elastic customers can use the new user experience monitoring feature to review Core Web Vitals, helping website developers interpret digital experience signals. Elastic users can also leverage a dev preview release of synthetic monitoring in Elastic Uptime to simulate complex user flows, measure performance, and optimize new interaction paths without impact to a website’s end users. The combination of these two new observability features gives Elastic customers a deeper view of their customers’ digital experience before and after a site update is deployed.”
See the write-up for its list of specific updates and features to Elastic’s Enterprise Search, Observability, Security, Stack, and Cloud products. Built around open source software, the company prides itself on its user-friendly products that have been adopted by major organizations around the world, from Cisco to Verizon. Elastic began as Elasticsearch Inc. in 2012, simplified its name in 2015, and went public in 2018. The company is based in Mountain View, California, and maintains offices around the world.
Cynthia Murrell, November 25, 2020
Amazon and the Cyber Security Industrial Complex
November 24, 2020
This is probably no big deal. Cyber security, threat intelligence, and wonky proprietary tools from startups populated by retired or RIFed intel officers are a big business. I was asked by a “real news” reporter, “How big?” I dutifully sent links to companies selling market forecasts for global cyber security revenues. How big were these numbers? Acquisition big. The hypothesis I have formulated is that when wild and crazy market size projections fly like hungry sparrows, there is a revenue problem. Specifically there are too many sparrows chasing available bugs and bread crumbs. That’s why Blackberry is in the cyber security business. Why LookingGlass stepped away from Cyveillance. That’s why Dark Web indexes of bad actors’ Crime as a Service offerings are a dime a dozen.
It is, therefore, no surprise that the write up “Trend Micro integrates with AWS Network Firewall” explains that Amazon is continuing to add to its pool of 65,000 plus partners. Many of these outfits like Palantir Technologies are in the cyber intelligence and cyber threat business. Bad actors beware.
The write up reports:
Trend Micro’s built-in IPS intelligence will inspect traffic for malicious intent so that the firewall can stop threats before they get a foothold in a virtual private cloud. Together, AWS and Trend Micro offer a simple, scalable service with reliable protection that does not require any infrastructure management.
What’s the hook? Here’s the statement I circled with an Amazon happy face:
Trend Micro’s threat intelligence will be available free with easy deployment for AWS Network Firewall customers.
What do I make of free cyber security services? No much but I hear the Bezos bulldozer pulling into the cyber intelligence and security services shopping mall. Roll up or roll over time for the cheerful orange machine with a big smile painted on the cab.
Stephen E Arnold, November 24, 2020
Court Case Hunger? Judyrecords Is Available
November 24, 2020
Unable to pay the fee for LexisNexis-type commercial search systems? You are not alone. If you want information from court records, navigate to Judyrecords. Within the last couple of months, the system has added more than 35 million cases. Aren’t these data available for free elsewhere? Sure, if you like going through hoops like verification procedures. Judyrecords lets a user plug in the names of entities and view results. I ran one of my go to queries: “Palantir IBM.” Here are the results:
This may not be important to you, but for those who have to wade through for fee legal search systems, Judyrecords is helpful. But for how long? Yes, that is a good question. For now, however, give it a whirl. Keep in mind that US court systems without online technology or special arrangements for document access prevent the system from being comprehensive. Lawyers enjoy results which must be checked by billable professionals, however.
Stephen E Arnold, November 23, 2020
Microsoft Bing Edge Shopping Reinvented. What?
November 24, 2020
I read “Reinventing Online Shopping on Microsoft Edge.” I like the word “reinventing.” It implies that online shopping is not using Amazon.com. Much to Google’s chagrin, the Bezos bulldozer has become the number one destination for those in the lower 48 who are looking for products. Six out of 10 shopping “journeys” begin online, according to Sleeknote. The same outfit reports that nearly half of US online commerce sales end up at Amazon. An outfit called Moz reports:
With 54 percent of product searches now taking place on Amazon, it’s time to take it seriously as the world’s largest search engine for e-commerce. In fact, if we exclude YouTube as part of Google, Amazon is technically the second largest search engine in the world.
So what about shopping on Microsoft Edge?
I ran this query on Microsoft Edge for AMZ 5700 video card. Here’s what I saw on November 22, 2020:
I ran the same query on Firefox. Here’s what I saw:
Both are different. The write up about reinventing shopping asserts that there are true blue, accidental, and incidental shoppers. That’s MBA think in action. The write up continues:
we [Microsoft] came up with a native-to-browser design framework that tailors shopping assistance to prioritize different information depending on the shopper’s stage in their journey. We determine what stage a person is at based on what kind of page they’re on.
Microsoft points out:
As you design your experiences, think about relying on a consistent UI paradigm that is both familiar and always available to the user. In our case, the UI framework leverages the URL bar, or address bar, in Edge as a quick one-touch anchor for shopping assistance. The URL bar is where people expect things relevant to the current webpage to show up — and we are extending the same model to surface optimized shopping insights. [Emphasis added]
I want to point out:
- I see two different user interfaces: One looks like a Google jumble and the other looks like eBay
- I don’t look for shopping information in the url bar. The url bar is where I want to see — wait for it, please — the url
- Neither interface benefits from little pictures. I am searching for a specific thing and I want a link to a relevant page, not a jazzed up “report.”
Amazon’s shopping is certainly not perfect, but I don’t have to figure out why the display looks different in different browsers or what’s is available.
MBA alert: Amazon and Google have much more traffic than Bing when it comes to shopping. You can check your traffic data for verification, not look in the url bar for an experience. This reality check will verify that blue is the sadness of shopping data analysis, the accidental weirdness Microsoft result pages present to a human shopper, and the incidental effort varying graphical interfaces display.
Stephen E Arnold, November 23, 2020
Deep Fakes Are Old
November 24, 2020
Better late than never, we suppose. The New York Post reports, “BBC Apologizes for Using Fake Bank Statements to Land Famous Princess Diana Interview.” Princess Diana being unavailable to receive the apology, the BBC apologized to her brother instead for luring her into the 1995 interview with counterfeit documentation. Writer Marisa Dellatto specifies:
“Network director-general Tim Davie wrote to Diana’s brother, Charles Spencer, to acknowledge the fraudulent actions of reporter Martin Bashir 25 years ago. Last month, the BBC finally admitted that Bashir showed Spencer bank statements doctored by a staff graphic designer. Spencer had alleged that Bashir told his sister ‘fantastical stories to win her trust’ and showed him fake bank records which reportedly helped land Bashir the interview. At the time, the princess was apparently deeply worried she was being spied on and that her staff was leaking information about her. Bashir’s ‘evidence’ allegedly made her confident to do the interview, one year after she and [Prince] Charles split.”
This is the interview in which Princess Di famously remarked that “there were three of us in this marriage, so it was a bit crowded,” and the couple filed for divorce in the weeks that followed. (For those who were not around or old enough to follow the story, her statement was a reference to Prince Charles’ ongoing relationship with Camila Parker Bowles, whom he subsequently married.)
For what it is worth, a BBC spokesperson insists this sort of deception would not pass the organization’s more stringent editorial processes now in place. Apparently, Bashir also intimidated the Princess with fake claims her phones had been tapped by the British Intelligence Service. Though it did issue the apology, the BBC does not plan to press the issue further because Bashir is now in poor health.
Cynthia Murrell, November 24, 2020
-
- Subscribe to Beyond Search
Feature archive
News archive
-
