More PR for Cognitive Search
February 20, 2020
With available data growing faster than traditional search technology seems able to handle, ToolBox predicts, “‘Cognitive Search’ May Be the Sector to Watch.” Writer Santiago Perez considers:
“On an individual level, we have all grappled with the frustrating experience of trying to enter just the right keyword or combination of letters and numbers to get to the exact bit of data we need. But as data multiplies continuously in libraries and archives, a new sort of search with the ability to cut through the chaff is coming into its own. It’s called ‘cognitive search.’ As the term suggests, the ‘thinking’ is deeper than that in a traditional keyword search. It’s leveraged by artificial intelligence and machine learning and gathers insights from signals and behavioral data. The insights can come from activities such as employee visits to web pages, their interactions with each other via chat media or the documents they produce and store.”
Perez cites research (PDF) that indicates between 60 percent and 73 percent of information corporations have gathered is currently unused. However, wonder whether the focus is in the right place here—what is the quality of such data? Where does it originate, how was it gathered, and has anyone verified it? For the vast majority, the answer is “of course not.”
Be that as it may, both Amazon and Microsoft are forging ahead with machine-learning based cognitive search solutions to more thoroughly analyze all that (suspect) data. AWS’s Kendra is currently only available in northern Virginia, Oregon, and Ireland, but they do have a preview available for AWS users. Microsoft is positioning its Project Cortex as the “fourth pillar” of Microsoft Office. See the write-up for more details on each of these products.
Cynthia Murrell, February 20, 2020
LucidWorks: Mom, Do My Three Cs Add Up to an A?
February 19, 2020
Search firm Lucidworks has put out a white paper explaining their new 3 C’s of enterprise search, we learn from the write-up, “Understanding Intention: Using Content, Context, and the Crowd to Build Better Search Applications” from InsideBigData. Registration is required to download and read the paper, but they have also put out a PDF called more simply, “Understanding Intention” that gives us their perspective.
In the 3 Cs section of that document, they note that enterprise search pretty much has content wrapped up. With tools like Hadoop, Solr, and NoSQL, we can now access unstructured as well as structured data. Context means, in part, understanding how different pieces of content relate to each other. It also means analyzing which pieces of information will be relevant to each searcher—and this is the exciting part for Lucidworks. The document explains:
“When a search app knows more about you, it can create a relevant search experience that helps you get personal, actionable search results on a consistent basis. Search apps have solved that problem with signal processing. A signal is any bit of information that tells the app more about who you are. Signals can include your job title, business unit, location, device, and search history, as well as past actions within the search app like clickstream, purchasing behavior, direct reports, upcoming meetings or events, and more.”
Interesting. As for the crowd portion, it has to do with matching searchers with content found by similar entities that have searched before. We’re told:
“When a search app uses the crowd, it goes beyond documents and data, past your specific user profile and relationship, and examines how other users are interacting with the data and information. A search app knows the behavioral information of thousands — sometimes millions — of other users. By keeping track of every user, search apps can bubble up what you will find important and relevant and what other users like you will want, too. The tech uses its knowledge of your office, role, and demographic to match to the same in other users and make intelligent judgments about what will help you the most.”
But how good is the tech, really, at identifying what information one truly needs, and how would we know? Do three Cs add up to an A in search? Not yet, Willy.
Cynthia Murrell, February 19, 2020s
A $600 Desktop Quantum Computer That Breaks Encryption. Wow or Woof?
February 17, 2020
DarkCyber spotted a remarkable claim. A fellow named Dan Gleason, created a portable quantum computer. The idea is that this computing system can hack passwords and maybe cyber security protocols.
The Assertion
The information appeared in an article in BetaNews. “The $600 Quantum Computer That Could Spell the End for Conventional Encryption” reports as actual factual:
Using easily available parts costing just $600…, QUBY runs recently open-sourced quantum algorithms capable of executing within a quantum emulator that can perform cryptographic cracking algorithms. Calculations that would have otherwise taken years on conventional computers are now performed in seconds on QUBY.
Sounds good, almost like a folding mobile phone from Motorola or Samsung, the marketing collateral from an enterprise search vendor like Coveo or LucidWorks, or the breathless assurances of Weaviate. (Dare I say Google or Watson?)
The Team
Greg Morrell, Founder and President, Active Cypher. Formerly president of Amtec Technologies, a management and capital placement limited liability company, and before that a vice president of development at LNR Property Corp. More information about the company appears in an ETS article.
“Dan Gleason is the chief architect and product developer of Active Cyper’s file level security solution. His special skills are in bring elegant solutions to complex problems.” Source: Active Cypher DarkCyber believes that a $600 portable quantum computer is a complex challenge but with many, many problems to solve. Mr. Gleason, according to Active Cypher’s Web site, possesses “special expertise.” This is “in all Microsoft products and programs.” The “all” is interesting.
Caspian Tavallali is the chief operating officer for Active Cypher. He worked in the office of the chairman at the Parman Capital Group. Previously he worked on an MBA at IE Business School in Madrid.
Mike Quinn, Chief Strategy Officer, Active Cypher. Mr. Quinn worked at Citadel Consulting and previously at Microsoft as “Partner” and General Manager of the Enterprise Cyber Security Group. He also worked at Cisco Systems in “services”.
The teams does not appear deeply steeped in the technology of quantum computing in use at Google, IBM, and other firms able to afford the research, demonstrations, and systems.
What’s the business model for the open source infused portable quantum computer? Here’s the answer according to Mr. Gleason:
In response to the threat, Active Cypher has developed advanced dynamic cyphering encryption that is built to be quantum resilient. Gleason explains that, “Our encryption is not based on solving a mathematical problem. It’s based on a very large, random key which is used in creating the obfuscated cyphertext, without any key information within the cyphertext, and is thus impossible to be derived through prime factorization — traditional brute force attempts which use the cyphertext to extract key information from patterns derived from the key material.”
Ah, ha. License the company’s dynamic ciphering encryption!
Additional Information
More detail about the company’s encryption innovations appears in “Maintaining a Zero-Trust Security Model.” That document references quantum in the context of “quantum resilient.” The idea is that the firm’s approach will not be breakable by quantum computer technology directed at decryption or similar functions. There’s no reference to a portable $600 quantum computer. DarkCyber finds this interesting since the white paper was updated in February 2020. (Amazon has a number of patents related to its zero trust systems and methods. Some of these are reviewed in our Amazon Blockchain white paper. You can request a free summary at this link.)
Who is buying into this concept? The write up suggests that Microsoft is curious and attendees at the RSA Conference (if it is held) will be able to check out the device. The algorithms will take more time to analyze unless one has access to Google’s or IBM’s quantum systems.
Observations
A few observations seem to be in order:
- What comprises a quantum computer? Hand crafted hardware from IBM or systems from DWave?
- Are there programming languages for the portable quantum computer?
- How are the “instabilities” associated with quantum demonstrations resolved?
- How was Mr. Gleason able to create a “$600” quantum computer when the cost of Google’s DWave gizmos such down money in seven figure gulps.
Net Net
If true the $600 quantum computer is “real,” Mr. Gleason will be the Marc Zukerberg – Sergey Brin – Steve Jobs of quantum computing. If not true, Mr. Gleason will be well positioned to work as a social media PR expert.
For now, DarkCyber will sit on the quantum fence. Why? The DWave quantum computer costs about $15 million. DarkCyber is not sure if this includes the cost of staff, refrigeration equipment, and maintenance.
But $600. Almost sci-fi made real in the actual factual world.
Stephen E Arnold, February 17, 2020
Why Techno-Babble and Crazy Promises Are Necessary
February 3, 2020
Do you believe the assertions about artificial intelligence, natural language processing, and quantum computing? The question is important because, according to the Nieman Lab, “Humans are hardwire to dismiss facts that don’t fit their worldview.” For those who believe in unicorns and fantasize about unicornification, the wilder and crazier the explanations about technology, the more coherent they sound. But try to provide facts, and the human brain is just not that interested if the research is accurate.
The write up asserts:
In theory, resolving factual disputes should be relatively easy: Just present the evidence of a strong expert consensus. This approach succeeds most of the time when the issue is, say, the atomic weight of hydrogen. But things don’t work that way when the scientific consensus presents a picture that threatens someone’s ideological worldview. In practice, it turns out that one’s political, religious, or ethnic identity quite effectively predicts one’s willingness to accept expertise on any given politicized issue.
What do these references to politicization have to do with technology sales and marketing?
DarkCyber believes that when one points out that an error rate of 85 percent means that there are 15 mistakes per 100 items. People think that error rate is okay, acceptable, maybe great. Apply the error rate to identifying potential bad actors, and someone has to figure out how to explain what happened to the 15 actors put in the bad egg bin.
Present this type of “fact” to a group, and most of the people exposed to the fact will ignore it.
But— and here’s the important point — evoke Star Trek, some magical numerical recipe, or just plain old hocus pocus like Google’s endless yammering about search quality, and people believe this stuff.
Years ago, enterprise search pitch men and pitch women discovered that promising to index “all of an organization’s information” and “eliminating time wasted looking for information” was the key to sales. Explaining that enterprise search was more like crafting a specific search system for a particular and quite specific problem was the more rational approach.
Sales were made, but the users were unhappy. The consequences were dire. Companies failed. Investors lost their money. One search executive was convicted of a criminal offense.
Flash forward to today. Predictive analytics, algorithms, and smart software will improve efficiency, reduce costs, unleash innovation, extract value from dark data, and generate new revenue.
Facts are one thing. Marketing hype another. Guess which takes precedence in search, analytics, artificial intelligence, and quantum computing?
If you said facts, you are in the minority if the Neiman Lab write up is correct.
Stephen E Arnold, February 3, 2020
Google Allegedly Ostracized
January 18, 2020
I worked in the San Francisco area once affectionately known as Plastic Fantastic. My recollection is that most of the people with whom I worked and socialized were flexible. There was the occassional throwback who longed for the rigidity of the Midwestern farm life. But overall, chill was the word. The outfit who paid me to do whatever it was they thought I was my skill was an easy going money machine. Most of the high technology outfits were just starting to get a sense of the power and impact afforded those who were comfortable with online technologies, nifty must have gadgets, and a realization that members of the high school science club could call the shots.
Imagine my surprise when I read the allegedly accurate “San Francisco Pride Members Pass Resolution to Ban Google, YouTube from Future Parades.” The write up states:
Members of the LGBTQ+ organization say they passed an amendment to ban Google, YouTube and Alphabet, as well as the Alameda County Sheriff’s Office, from future celebrations after a vote at their monthly membership meeting Wednesday night. In a statement released to SFGATE on Thursday, SF Pride members and former Google engineers Laurence Berland and Tyler Breisacher said they are now urging the board of directors to formally approve the motion at their upcoming meeting on Feb. 5.
Remarkable if true. The Google HR and marketing departments will have to step up their efforts. Recruitment may become more difficult. The PR vibes are doing the Hopf fibration thing. (This is a nice way of saying, “Difficult to understand.”)
Stephen E Arnold, January 18, 2020
Are Catalogs Made from Dead Trees Rising from the Ashes of Retail?
January 6, 2020
DarkCyber spotted an interesting write up about dead trees. The article is about printed catalogs. Paper. You remember the stuff, don’t you? “Catalog Retailers See Reason for Optimism after Declines” contains a somewhat surprising statement; to wit:
New companies are mailing catalogs. And even died-in-the-wool online retailers like Amazon and Bonobos are getting into the act. “They’re tapping out on what they’re able to do digitally,” said Tim Curtis, president of CohereOne, a direct marketing agency in California. “They’ve got to find some new way to drive traffic to their websites.”
Does this assertion translate into a certain exhaustion of the possibilities of online advertising. Maybe pop up or Google fatigue is affecting people looking for information.
Consider online information services. I encountered a situation with the Daily Mail, a British newspaper. The site would not display. There were ads loading, questions to answer, and pop ups to dismiss. I solved the problem by navigating to another site. Too much hassle.
A paper catalog can be viewed and maybe used to buy something without the annoyance.
“Driving traffic to a Web site” may be less important than a catalog’s ability to deliver information without digital annoyances, creepy tracking cookies, and ads for products one just purchased.
Stephen E Arnold, January 6, 2020
Why Black Boxes in Smart Software?
January 5, 2020
I read “Why Are We Using Black Box Models in AI When We Don’t Need To? A Lesson From An Explainable AI Competition.” The source is HDSR, which appears to be hooked up to MIT. Didn’t MIT find an alleged human trafficker an ideal source of contributions and worthy of a bit of “black boxing”? (See “Jeffrey Epstein’s money bought a cover-up at the MIT Media Lab.”) The answer seems obvious: Keep prying eyes out. Prevent people from recognizing how mundane flashy stuff actually is.
The write up from HDSR states:
The belief that accuracy must be sacrificed for interpretability is inaccurate. It has allowed companies to market and sell proprietary or complicated black box models for high-stakes decisions when very simple interpretable models exist for the same tasks.
The write up moves with less purpose that Jeffrey Epstein.
I noted this statement as well:
Let us insist that we do not use black box machine learning models for high-stakes decisions unless no interpretable model can be constructed that achieves the same level of accuracy. It is possible that an interpretable model can always be constructed—we just have not been trying. Perhaps if we did, we would never use black boxes for these high-stakes decisions at all.
I love the privileged tone of the passage.
Here’s my take:
Years ago I prepared for a European country’s intelligence service an analysis of the algorithms used in smart software. I thought this was an impossible job. But after making some calls, talking to wizards, and doing a bit of reading about what’s taught in computer science classes, my team and I unearthed several interesting factoids:
- The black box became the marketing hot button in the mid 1990s. The outfit adding oomph to mystery and secrecy was Autonomy. If you are not familiar with the company, think Bayesian maths. Keep the neuro linguistic programming mechanism under wraps differentiated Autonomy from its competition.
- Computer science and advanced mathematics courses around the world incorporated into their courses of study some useful and mostly reliable methods; for example, k means. There were another nine computational touchstones we identified. Did we miss a few? Probably, but my team concluded that most of the fancy math outfits were using a handful of procedures and fiddling with thresholds, training data, and workflows to deliver their solutions. Why reveal to anyone that under the hood most of the fancy stuff for NLP, text analytics, machine learning, and the other buzzwords which seem so 2020 were the same.
- My team also identified that each of the widely used, what we called “good enough” methods, could be manipulated. Change a threshold here, modify training data there, create a feedback loop and rules there—the system output results that appeared quite accurate, even useful. Putting the methods in a black box disguised for decades the simple methods used by Cambridge Analytica to skew outputs and probably elections. Differentiation comes not from the underlying methods; uniqueness is a result of the little bitty tweaks. Otherwise, most systems are just lik the competitions’ systems.
Net net: Will transparent methods prevail? Unlikely. Making something clear reduces its perceived value. Just think how linking Jeffrey Epstein to MIT alters the outputs about good judgment.
Black boxes? Very useful indeed. Secrets? Selective revelation of facts? Millennial marketing? All useful
Stephen E Arnold, January 5, 2020
When Millennials Market, Craziness Ensues
January 3, 2020
How this for logic?
Assertion: What you read in blog posts stopped working months ago.
Logic problem: This assertion appears in a blog post “5 Marketing Trends for 2020 by a Grumpy Martech CEO.”
Observation: The statement is contradicted by its appearance in a blog post.
Your view may be more generous than mine. That’s what makes life interesting.
What else does the write up reveal in its logical flourish?
- Don’t do cold calls. Observation: Yeah, but that’s what conventions are based on. Walking up to a person and introducing oneself and engaging in a conversation. If you do this, your are making a big mistake. Alternative: Telepathy maybe?
- Marketing tools do the same thing. Yeah, that’s a bold statement. But isn’t there a difference between relying on a networking event armed with a — horror of horrors — a printed brochure and buying Google AdWords? Same thing? No, gentle reader. No, no, no.
- Words don’t work. Got it. Videos with music. There you go.
- Use a new channel like a — wait for it — a directory. Example: Capterra? What? Isn’t that a hollow shell with a bit of fluff added for impact.
Amazing!
Stephen E Arnold, January 3, 2019
Intellisophic: Protected Content
December 28, 2019
Curious about Intellisophic? If you navigate to www.intellisophic.com, you get this page. If you know that Intellisophic operates from www.intellisophic.com, you get a live Web site that looks like this:
No links, and there is no indication who operates this page.
You persevere and locate a link to the “real” Intellisophic. You spot the About page and click it. What renders?
Yep, protected information.
Even companies providing specialized services to governments with “interesting” investors and solutions, provides a tiny bit of information; for example, check out https://voyagerlabs.co/.
DarkCyber finds it interesting that a company in the information business, does not provide any information about itself.
Stephen E Arnold, December 28, 2019
Emoto Marketing: Is This a Trendlet Aborning
December 26, 2019
I read, quite by accident, a write up mentioned by a young executive at a holiday party. The essay manifests what I call “emoto marketing”. This is shorthand for an emotional, sensitive, I-want-to-help approach to selling consulting services.
You can read this interesting sales pitch at Leowid, which is the author’s shorthand for himself. The essay is “I Coached 101 CEOs, Founders, VCs and Other Executives in 2019: These Are the Biggest Takeaways.” Be aware that there is a pop up enjoining the reader of the essay to “join me for regular adventures into the unknown.”
Now if there is one thing that, in my experience, makes high performers nervous is the unknown. Plus, there’s the risk of failure, which today includes allegations of improper behavior, missteps memorialized in pix from a college party, and plain old human failings like alcohol, synthetic opioids, and friendly Uber drivers.
Straight away, I translate the 101 into one therapy session every three days or a couple of conferences with 50 and a half shattered attendees. Either way, the learnings from these emoto interactions could be indicative of why software able to figure out the emotional payload of an email will thrive in 2020. Doesn’t everyone one a semantically, context aware daemon buzzing in one’s mobile device?
Let’s look at three of the findings; read the essay for the other insights. Be sure to sit down, however. The revelations may knock the wind out of the sails of your 75 foot sailboat.
- People are “bags of emotion.” I sort of knew this after I learned a person unhappy with holiday gifts, pulled out a weapon and began taking pot shots at the gift givers.
- Manage focus, not time. I understand that paying attention and listening are important. I watch LivePD and see how the inattentive find themselves in uncomfortable situations.
- Boundaries create connections. The social graph is important to the emoto marketer.
To sum up, the essay combines pseudo science, self help, and MBA speak with unabashed emotional appeals. If facts won’t work, go for emotion.
DarkCyber will focus, not just listen, in order to discern other examples of this approach to selling services. Imagine an emoto marketing campaign from McKinsey & Co or a government agency.
The author trained as a trauma therapist and lives in Vienna, Austria (a very flexible and emotional city I believe). Oh, the author lives near a forest.
Fascinating.
Stephen E Arnold, December 26, 2019
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