One View of the Amazon Game Plan
May 27, 2018
I read “Invisible Asymptotes.” Job One for me was trying to match the meaning of “asymptote” with the research my DarkCyber team has conducted into one slice of Amazon’s business roll outs in the last three years.
As you know, an “asymptote” is a mathy way of saying “you can’t get from here to there.” According to Wolfram Mathword:
An asymptote is a line or curve that approaches a given curve arbitrarily closely.
Here’s a diagram. No equations, I promise.
This diagram suggests a business angle to the “asymptote” reference: No matter what you do, it requires effort and a commitment to “quality”. The good news is that although one can quantify time, one cannot quantify “quality” or “perfection.” Okay, gerbil, run in that Ferris wheel gizmo in your cage.
The write up points out:
We focus so much on product-market fit, but once companies have achieved some semblance of it, most should spend much more time on the problem of product-market unfit.
I am not exactly sure what “unfit” means. The author provides a hint:
For me, in strategic planning, the question in building my forecast was to flush out what I call the invisible asymptote: a ceiling that our growth curve would bump its head against if we continued down our current path.
Okay, the idea seems to be that if Amazon enters a new market, the “invisible asymptote” is what slows growth or stops it completely. (Is this the Amazon phone’s and the slowing sales of Alexa in the face of competition from the Google Home device?)
The reason Amazon cannot grow ever larger is because of an “invisible asymptote”; that is, a factor which prevents Amazon from becoming a company that Vanderbilt, JP Morgan, and John D. Rockefeller would have wished they had.
The write up does not discuss Amazon’s semi-new entrance into the law enforcement and intelligence market. That’s a push I am exploring in my lecture at the Telestrategies ISS conference in early June.
The focus shifts to a more mundane and increasingly problematic aspect of Amazon’s business: Shipping fees. Fiat, law, and the costs of fuel are just a few of the challenges Amazon faces. I am not sure these are “invisible”, but let’s trudge forward.
Twitter becomes that foundation for social media. I noted this passage:
No company owes it to others to allow people to build direct competitors to their own product.
If Amazon wants to make law enforcement and intelligence services into a major revenue stream, I think the first evidence of this intent will be cutting off the vendors using Amazon’s infrastructure to serve their clients now. (Keep in mind that most of the specialist vendors in the LE and intel space use Amazon as plumbing. To cite one example, Marinus, the anti human trafficking group, follows this approach.
The author brings up Snapchat and other social media companies. I find this example important. Amazon’s facial recognition capabilities hit out radar when my team was assembling “CyberOSINT: Next Generation Information Access”, written in 2014 and published in 2015.
We did not include Amazon in my review of LE and intel tools because I had only references in some Amazon conference videos, a few patent applications which were particularly vague about applications in the Background and Claims sections of the documents, and chatter at meetings I attended.
The American Civil Liberties Union has made a bit of noise about Amazon’s facial recognition system. Recognition is spelled “rekognition”, presumably to make it easy to locate in the wonky world of Bing and Google search. The reason is that Amazon’s facial recognition system can identify individuals and cross tabulate that piece of information with other data available to the Amazon system.
Instant bubblegum card.
The write up “Invisible Asymptote” talks about social content and social rich media without offering any comment about the importance of these types of data to Amazon’s intelligence services or its marketplace.
The conclusion of the 10,000 word essay is more “invisible asymptote”. Is this Amazon’s the secret sauce:
Lastly, though I hesitate to share this, it is possible to avoid invisible asymptotes through sheer genius of product intuition.
Here’s a diagram from the essay which looks quite a bit like the self help diagram I included at the top of this Beyond Search post:
Several observations:
- The write up makes clear that if anyone thinks Amazon’s platform is neutral, think again.
- Strategists at Amazon are not able to “see” and “explain” the nuts and bolts of the “we may be a monopoly but” approach of the Big Dog of the Amazon
- The long, long essay does not stray very far from selling stuff to consumers who love free shipping.
Taken as a group of three perceptions, what does this say about Amazon?
For me, I think companies using Amazon’s plumbing will want to do a bit of strategizing using “What if” questions to spark discussion.
For companies behind or beneath the curve, there will be a ceiling, and it will not be easy to break through.
Amazon, on the other hand, may have break through and then replace the old ceiling with a nifty new one made of sterner stuff.
For information about our lectures about Amazon’s Next Big Thing: Intelligence Services, write me at benkent2020@yahoo.com. Put Amazon Streaming Marketplace in the subject line, please.
We now offer for fee webinars and on site consulting sessions. On June 5, 2015, coincident with my two lectures in Prague before an audience of LE and intel professionals, I will release a nine minute DarkCyber video exploring some of the inventions Amazon disclosed in an April document not widely reported in the media. Watch this blog for a link.
Stephen E Arnold, May 27, 2018
Plan a Hike or an Attack: Piece of Cake Now
May 26, 2018
Forget the utility of the procedure for outdoor hikers described in “Plot a Hike on Google Earth.” My first thought was, “What a Mother’s Little Helper” for those involved in military orienteering. I particularly liked the use of Strava, an application with data of some value to those eager to locate certain types of behavior patterns inadvertently created by joggers. I also liked the bouncing between a desktop / laptop computer and mobile devices. No problem for personnel operating from a semi fixed base station. Finally, the “fly around” functionality is helpful. My problem with these capabilities is that they are available to anyone. My personal view is that certain types of technology applications can be put to what I would describe as questionable uses. Why go through the hassle of joining the military or law enforcement, cope with the rigors of FLETC and other training program, and sharpen one’s skills in the field. Take a short cut and put the capabilities in whatever context one wants. Sorry. Too much information.
Stephen E Arnold, May 26, 2018
Google: Excellence Evolves to Good Enough
May 25, 2018
I read “YouTube’s Infamous Algorithm Is Now Breaking the Subscription Feed.” I assume the write up is accurate. I believe everything I read on the Internet.
The main point of the write up seems to me to be that good enough is the high water mark.
I noted this passage, allegedly output by a real, thinking Googler:
Just to clarify. We are currently experimenting with how to show content in the subs feed. We find that some viewers are able to more easily find the videos they want to watch when we order the subs feed in a personalized order vs always showing most recent video first.
I also found this statement interesting:
With chronological view thrown out, it’s going to become even more difficult to find new videos you haven’t seen — especially if you follow someone who uploads at a regular time each day.
I would like to mention that Google, along wit In-Q-Tel, invested in Recorded Future. That company has some pretty solid date and time stamping capabilities. Furthermore, my hunch is that the founders of the company know the importance of time metadata to some of the Recorded Future customers.
What would happen if Google integrated some of Recorded Future’s time capabilities into YouTube and into good old Google search results.
From my point of view, good enough means “sells ads.” But I am usually incorrect, and I expect to learn just how off base I am when I explain how one eCommerce giant is about to modify the landscape for industrial strength content analysis. Oh, that company’s technology does the date and time metadata pretty well.
More on this mythical “revolution” on June 5th and June 6th. In the meantime, try and find live feeds of the Hawaii volcano event using YouTube search. Helpful, no?
Stephen E Arnold, May 25, 2018
Attivio Continues to Move Its Technology Forward
May 25, 2018
Conceived by former Fast Search & Transfer executives, Attivio has moved from a system able to analyze baseball statistics to enterprise search to business intelligence and probably several other market spaces. Enterprise search vendors do that these days.
Now the newest version of Attivio is here, we learn from the company’s blog post, “Attivio Product News: Version 5.5.1 Available Today!” The write-up describes improvements in several areas. With the updated software development kit (SDK), one can test code before deploying it to the platform. As for security, we’re told Attivio has migrated to a stronger algorithm and upgraded libraries to their latest versions. Text extraction has also been improved and now works with over 600 formats. Furthermore, access to recent modules is also included; the post promises:
“Finally, we’ve made the latest modules part of the install. This includes the WebCrawler module, which enables you to ingest web pages, as well as newly released Search Analytics and Search UI Toolkit. As we’ve written about previously, Search Analytics gives you insight into the performance of your search platform in real time. And SUIT, Attivio’s Search UI Toolkit, is a framework for quickly building search applications from the simplest to the most complex. It’s an open source application that can be downloaded from GitHub, and enhanced by the community. It not only works with the Attivio platform, but also with Elasticsearch and Solr.”
How Fast like is Attivio? A faint imprint of the genetic code is there, but Attivio has, like other search vendors, adopted proprietary and open source technology. The trick is the marketing today. Attivio is chugging along but it faces enterprise search challengers fueled by venture funding. What’s interesting is that money continues to flow into what I would describe as “traditional” enterprise search plays; for example, Coveo. The hurdle, of course, is to convert investors’ money and support into sustainable, growing, profit spinning revenue. And that’s a challenge from my point of view.
See the Attivio post for more details on each of the above improvements. Founded in 2007 (shortly before Fast Search’s implosion and the sale of the Fast property to Microsoft and the legal dust up about Fast Search’s “fast” math). Attivio’s seems to be hiring. That’s encouraging.
Cynthia Murrell, May 25, 2018
Knowhere: News and Smart Software
May 25, 2018
I find the name interesting. Knowhere. The association with “nowhere” seems probable.
The company may have a terrific idea, but will it work? Motherboard reports, “A Startup Media Site Says AI Can Take Bias Out of News.” The site, Knowhere, uses AI technology in its attempt to achieve an impartial balance. Reporter Mack De Geurin writes:
“The site works by searching the internet for popular news stories. The algorithm sorts through newly published articles in near real time to determine what stories are being covered most by news sites. Knowhere then aggregates stories from a continually expanding inventory of more than a thousand different sources with varying political persuasions to create a ‘knowledge graph’ or database of each news story. Of course, all artificial intelligences for the moment have to have some human input: The co-founders weighed each source for trustworthiness, so a publication with a longstanding history of accuracy like the New York Times is weighted differently than a less reputable site like Breitbart. From there, three versions of any article are published: left, impartial, and right. These distinctions are meant to show the reader how word selection and emphasis can produce biased reporting.”
Those three distinctions, left, impartial, and right, are meant to be temporary—the site hopes to eventually share only content that it has rendered impartial. At this point, human judgment is still integral to the process. The company’s Barling states that at least two real, live editors review each story for errors, style, and, crucially, bias. In the end, cofounder Nathaniel Barling emphasizes, each story receives his approval before being posted. He also notes that no story will be published until it has been reported by at least five verified sources.
The article mentions a few previous efforts to leverage AI in the newsroom by assorted news sources, but most of them were aimed at reducing busywork. (A worthy goal, to be sure.) Knowhere, we’re told, is different not only for its focus on unbiased reporting, but also for its use of natural language processing. Some are skeptical, though, that a site which simply restructures the reporting of others is really adding anything of value. For Barling, though, Knowhere is a tool is with which to present the news more clearly, more truthfully. We’ll see.
Cynthia Murrell, May 25, 2018
Search Is a Problem: Still a Clumsy Song and Dance Routine
May 24, 2018
Enterprise search has been around for decades. Hundreds of consultants have asserted patterns, models, methods, and MBA infused strategies to “fix” enterprise search.
Why?
Wherever there is an organization with one or more enterprise search systems, I have found these characteristics:
- Unhappy users
- Unhappy senior manager
- Unhappy bean counters
- Unhappy vendors
- Usually happy consultants if they are paid.
I am biased, old, and hard nosed. After writing the first three editions of the Enterprise Search Report, the New Landscape of Search, adding a word or two to that astounding guru Martin White’s book about Successful Enterprise Search Management, talking with dozens of PhD candidates whose dissertatioins about search and retrieval would change the world, and meeting with vendors large and small for decades—I am amused by the arm waving enterprise search engenders.
Don’t get me wrong. There are very good information access systems. But these vendors license solutions which usually focus on solving a specific problem. Case in point: Blackdot, Terbium Labs, and Verint, and many others.
From the point of view of flailing content management experts, “enterprise search” means finding information in a usually flawed, Rube Goldberg construct called a CMS or content management system.
Against this wallpaper with my scrawled biases, I read “Diagnosing Enterprise Search Failures.” The pivot point for the story is another report that almost two thirds of enterprise search users are not satisfied with the retrieval system.
Like a reprise of a vaudeville act from the 1920s at a rap concert, the music and the footwork are stale, out of touch, and worn.
Enterprise search had its decade in the sun. The period between 1995 and 2005 was the golden age of search. Then the sun imploded. Over-promising and under-delivering made it clear to those licensing enterprise search systems that finding information was not a solution to digital information woes.
In fact, an enterprise search system exacerbated the problems employees encountered when trying to locate specific information. Fast Search & Transfer, Convera, Delphes, Entopia (remember that outfit), and other aggressively marketed companies found out that companies would license technology and then balk at the on going costs.
One by one the big names in enterprise search went out of business or found themselves owned by larger firms with a belief that their managers could make search a winner.
How did that work out? Chase down someone at Lexmark and ask about their experience with ISYS Search Software. Repeat the process at Dassault Systèmes? Do the same thing for products ranging from Artificial Linguistics to Vivisimo.
The result is that the universe of companies offering search solutions has changed since 2008. The legal dust up between HP and Autonomy continues. Search did not make HP happy.
Surveys are fine, but the data reveal nothing new. Enterprise search is not a solution to information problems in an enterprise. Companies are embracing free or low cost solutions based on open source technology. Specialist systems which address specific information access problems are thriving. One may not think of Diffeo and Palantir Technologies as enterprise search systems, but they are information access solutions and not designed to solve a panoply of retrieval and information management issues.
The reason enterprise search fails to please users boils down to the disconnect between what the user wants and what an enterprise wide system can deliver. The vendors promise more than technology can provide.
Checklists, MBA rah rah, and misplaced confidence in technology will not solve these specific challenges:
- The cost of maintaining, upgrading, and tuning an enterprise search system to the needs of specific users is significant
- Users have a keen desire to rely on the software to do the thinking for them. When a system requires the user to think or formulate a query or perform downstream analysis, the search system becomes a problem
- Procurement teams often lack the discipline and clout to lay out tight requirements and select a vendor to do that job. The pattern is to create a wish list, sign a deal, and leave the baggage of failure behind.
- The systems provided do not match what the marketers demo, suggest, or assert the software will actually do in an affordable, reliable, understandable manner.
As a former rental at a reasonably competent management consulting firm, a method for figuring out how to solve a problem has one objective: Sell billable work. I understand that.
Do not confuse a consultant’s report with solving the problem of enterprise search. If enterprise search worked, there would be little appetite for methodologies to figure out failure.
Why such hostility to enterprise search? I think clueless large and medium sized companies want to buy a silver bullet. Even better, the bullet must kill the content vampire with a single, low cost, easy to use, accurate shot.
That’s not going to happen… ever.
The problem is that individuals looking for information need tools to solve quite specific business tasks. In enterprise search, there are numerous points of failure; for example:
- Management support is weak
- Organizational infighting triggers departments to get their own search solution
- The technology does not work
- Results do not meet user needs
- Funding is insufficient
- Technical staff find that fixes are not easy or possible
- Content known to be in the system cannot be found
- Vendors change direction from search to customer support and leave search customers dangling
- The people involved are focused on their careers, lunch, or finding a new job, not the nitty gritty of designing a solution for a specific group of workers with an information need.
And there are other issues related to over-promising and under-delivering. I wrote about this years ago and talked about falling off the cliff of high expectations. Enterprise search users inevitably crash into the reality of the system. Thus, the significant percentage of dissatisfaction with enterprise search.
I know of no enterprise search system which delivers on these points. Furthermore, as venture funding flows into Coveo and LucidWorks, as IBM falls farther and farther behind its revenue goals for Watson search (OmniFind, Vivisimo, et al), and as Microsoft buys more and more search start ups in the hopes of finding a silver bullet to its search mess—It is clear that stakeholders, customers, and users are going to become increasingly annoyed at the problem of enterprise search.
Why did Google bow out of enterprise search? Why has Elastic emerged as the go-to solution for many enterprise search applications? Why are companies like Funnelback, Sophia, Exorbyte, and dozens of others scrambling?
Enterprise search looked like a solution to some important problems. Today not so much. Open source search software is fine. However, how many of the open source vendors are going to be able to generate a return for their investors with what amounts to free software.
Enterprise search is the wrong label for today’s solutions. Even proprietary systems in hock for $100 million have longer odds than a nag entered in the Kentucky Derby.
Therefore, thrashing.
Stephen E Arnold, May 24, 2018
Chatbots: Yak, Yak, Yak
May 24, 2018
We want to keep an open mind about smart software and the go-to application designed to terminate the folks with thrilling phone and email customer support jobs.
Just the name, “chatbot” is likely to elicit eyerolls from readers. While we have frequently been told these online oddities will be stepping up into the big leagues of usability, they don’t seem to have really found their niche. That’s what made it all the more surprising when their creators began demanding a little respect in a recent Qrius piece, “Chatbots Deserve More Than Being a Joke, Here’s Why.”
“In the most successful (and useful) applications we were able to schedule meetings and order pizza. …
“[But] We remember the failures. And when Microsoft’s Tay turned into a racist within 24 hours of release, we all laughed. If one of the biggest technology companies in existence couldn’t prevent a chatbot from becoming an anti-semite, what hope was there for the technology writ large?”
The reason we remember the failures and not the successes is because the benefits of one are outweighed by the regret of the other. However, more and more businesses are aiming to change this. Forbes recently reported on how AI was helping make chatbots more useful (go figure!). It’s a compelling point and maybe one that is finally on the verge of becoming relevant. Relevant is not the same as annoying and sometimes very, very dumb.
Patrick Roland, May 25, 2018
CNBC: Poking at the Google
May 24, 2018
CNBC has become one of the more interesting outlets of “real” news. (Just joking.) I did spot a headline which lured me to click. Here is the gem:
Larry Page’s Silence Speaks Volumes as Alphabet Faces One Ethical Crisis after Another
Now I am old fashioned and like to have terms defined. CNBC does not fool around with that waste of time. But here’s a working definition of “ethics” which provides me with some context:
moral principles that govern a person’s behavior
A more beefy definition can be absorbed from Spinoza’s Ethics available at this link.
The CNBC write up asserts:
Page should take more time to communicate with stakeholders beyond the confines of the company’s walls.
CNBC notes that Mr. Page and presumably his fellow traveler Sergey Brin, have organized the Google so that neither has to “talk” unless they want to. Outputs from the Google Alphabet construct come from deputies.
I also noted this statement:
Page is the chief executive of a $740 billion conglomerate whose main division, Google, has a mission statement to “organize the world’s information and make it universally accessible and useful.” That’s precisely what people are concerned about — the responsibility that comes with collecting, storing and analyzing massive amounts of information. How should that information be used? Who gets to decide? Facebook and Mark Zuckerberg have so far borne the brunt of the rising public concern over these questions, thanks to the Cambridge Analytica data leak and that firm’s connections to President Trump. But insiders tell us that a lot of people at Google — which collects just as much or more information than Facebook — are scared of being dragged through the mud next.
Great stuff with a socko closer: “Is he worried?”
Probably not.
Stephen E Arnold, May 25, 2018
IBM and Distancing: New Collar Jobs in France
May 23, 2018
I have zero idea if the information in the article “Exclusive: IBM bringing 1,800 AI jobs to France.” The story caught my attention because I had read “Macron Vowed to Make France a ‘Start-Up Nation.’ Is It Getting There?” You can find the story online at this link, although I read a version of the story in my dead tree edition of the real “news” paper at breakfast this morning (May 23, 2018).
Perhaps IBM recognizes that the “culture” of France makes it difficult for startups to get funding without the French management flair. Consequently a bold and surgical move to use IBM management expertise could make blockchain, AI, and Watson sing Johnny Hallyday’s Johnny, reviens ! Les Rocks les plus terribles and shoot to the top of YouTube views.
On the other hand, the play may be a long shot.
What I did find interesting in the write up was this statement:
IBM continues to make moves aimed at distancing itself from peers.
That is fascinating. IBM has faced a bit of pushback as it made some personnel decisions which annoyed some IBMers. One former IBM senior manager just shook his head and grimaced when I mentioned the floundering of the Watson billion dollar bet. I dared not bring up riffing workers over 55. That’s a sore subject for some Big Blue bleeders.
I also liked the “New Collar” buzzword.
To sum up, I assume that IBM will bring the New Collar fashion wave to the stylish world of French technology.
Let’s ask Watson. No, bad idea. Let’s not. I don’t have the time to train Watson to make sense of questions about French finance, technology, wine, cheese, schools, family history, and knowledge of Molière.
Stephen E Arnold, May 23, 2018
Amazon: A New Revenue Stream Begins to Flow
May 23, 2018
Amazon is a bit of an exception when compared to Facebook and Google. In general, Amazon’s business has cruised along without eliciting the criticism which swarms around Facebook.
Yesterday I had an experience which revealed how strongly some companies feel that Amazon is in some way sacrosanct. There is an outfit which Jessica B., one of the investigative journalists who worked for me before I retired, used PRUnderground to put out news releases about my books, speeches, and my various projects. One of the young people who help me drafted a 500 word news release about one of the research findings which I will present at the upcoming Telestrategies ISS conference in Prague. The attendees will be active law enforcement, intelligence, and security professionals. The release was a summary of one of the new services which Amazon has begun to introduce.
The PRUnderground professionals informed me that what the person wrote and submitted for release on June 5 was not permissible. The angle was that PR about another company was not PR. Amazon is probably happy that my news release is not news. (We also encountered another instance of censorship with this story. The LinkedIn system blocked this write up, presumably because the writer who did the story was not treating Microsoft in a proper manner. Interesting.)
I read “Amazon Is Selling Facial Recognition to Law Enforcement for a Fistful of Dollars.” The source is the Washington Post which may be a project favored by Jeff Bezos, the big Amazonian.
Several observations:
I have been reporting about Chinese and Israeli facial recognition systems in my weekly DarkCyber videos. I generally prefer to report about non US companies, but here is the Washington Post reporting about facial recognition sold to government entities. I wonder if the professionals at PRUnderground would have run a news release about the story. I suppose I could ask help@prunderground.com, but I think I will conserve my energy for my research and analysis of what some youngsters call the “actual factual.”
What happens if one combines the story about Rekognition, which has been around since 2015 when I heard about the system with the information which I will present in my “Deanonymizing Digital Currency Transactions”?
My hunch is that some stock market types, a handful of specialist vendors serving the LE and intel communities, and a few people in the US government who have attended my lectures this year might find the two items of significant interest.
On June 5, 2018, I will include some of the information in the DarkCyber released coincident with my speeches in Prague.
In the meantime, Amazon is an interesting company and one that is positioned to disrupt a reasonably large market for investigative tools and services. To give one example, what if the crowd facial recognition feature is cross correlated with purchase history, banking information, and other data housed by Amazon?
Think about that idea. Think about cross correlation in real time of multiple streams of data. I did.
I won’t be doing a PRUnderground release. I will just plug along, content in the knowledge that the Washington Post three years after Rekognition moved from idea to buggy beta tuned into what I think is now old news.
My hunch is that this item will not appear in my LinkedIn feed either. The shaping of fact based information must continue.
Perhaps I will ask Alexa. “Why is Amazon pushing so hard to land a large Department of Defense contract?” and “Why is Amazon dipping its Bezos sized toe into the law enforcement services market?”
I will share my hypothesis with the 200 or 300 LE and intel professionals who attend my two lectures. I will be offering for fee webinars and in person training on this subject later this year. Who knows? I might even write a short analytic white paper.
Publicity on LinkedIn and PRUnderground. Probably unlikely.
Stephen E Arnold, May 23, 2018
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