Wynyard Telstra Deal
November 16, 2015
I know that search vendors are busy doing customer relationship management, governance, indexing, and many other jargon choked activities in an increasingly desperate attempt to grow organic revenues.
I want to highlight this news item, “Telstra First on Board as Wynyard Seals $3.2 Cyber Solution Deal.” The announcement is important for the low, low profile Wynyard outfit. The company combines a range of content processing functions with a solution that delivers high value, actionable outputs.
High value means that the company reduces the costs of certain tasks and services which can be linked directly to outcomes. Value also means that the services are less expensive than a mosaic of individual content functions.
You will have to do some digging to get information about Wynyard, one of the leaders in the cyber OSINT and related disciplines. According to the write up:
According to Richardson [Wynyard CEO] , ACTA [Wynyard service] identifies cyber breaches that have compromised traditional defenses, operating inside the company network by processing big-data network logs using advanced machine learning techniques to analyze data for anomalous patterns that are out of step with usual behavior. Terms of the deal will see Telstra – one of the world’s largest telecom companies – use ACTA across its internal ICT network to assist in preventing high consequence cyber crime.
Wynyard offers other interesting services. Worth paying attention to this outfit in my opinion. Real value is more than made up MBA silliness.
Stephen E Arnold, November 16, 2015
10 Reasons Why Enterprise Search Vendors Face Sales Friction
November 4, 2015
I have been watching the flow of information from companies which are in the enterprise search business. Some of these firms are ones you may recognize; for example, Elastic and LucidWorks. Others may be off your radar; for instance, Attivio, BA Insight, and Coveo. Some are essentially “hidden” outfits; for example, Diffeo.
The question I pondered when I was making my return from yet another remote location, “What is enterprise search disappeared?” (This is not a grammatical error. Disappeared is one of those jargon terms which add spice to certain government professionals’ life or the opposite.)
I jotted down a list of 10 reasons. I am not sure these are particularly humorous, but the list captures my thoughts on a 17 hour airplane flight.
- Enterprise search burned its bridges with over promising and under delivering decades ago. As a result, search is a utility. Enterprise search as an enterprise application lacks credibility.
- It is easier to talk about finding information in an enterprise and embarrassing with customers cannot locate a memo they wrote 24 hours earlier. Indexing remains the weak spot in many enterprise search systems.
- The cost of normalizing information is far greater than even the most unicorn worshiping financial wizards can stomach. Changing the oil in a La Ferrari is a deal compared to the ever escalating costs of content processing.
- Users get darned annoyed with enterprise search systems which are supposed to do everything, including squeeze the Big Data forest down to a bonsai grove on a marketer’s desk. Revolt takes the form of installing a local solution and keeping the alternative off management’s radar.
- Even the simplest solutions like an appliance requires lots of baby sitting. Free and open source solutions reduce the license fee. The other costs remain.
- Smart systems are still generally stupid and humans have to get involved to make sure the automatic processes do not return increasingly off point results.
- Specialists who can make an enterprise search system actually work are tough to find and keep on the job. Hiring a search specialists ensures one thing: Ever increasing costs for engineering support.
- The darned indexing misses the names of key customers, companies, and products. No matter how many times the system is tweaked, the notion of 85 percent accuracy guarantees 15 percent frustration. Toss in videos and images and most enterprise search systems have no way to process these file types without licensing more technology.
- Many enterprise search vendors are coding the system as they are trying to close deals. Instead of a hardened product, the vendor has delivered a demonstration which has to be configured, tuned, optimized, and updated. Translated: We are writing the software as we are billing the customer.
- The security and permissions settings require a full time person. Even then, incorrect permissions can cost a company a government contract or create legal exposure.
What’s the fix? I guarantee you that reading the recommendations of mid tier consulting firms, the analysis of frustrated academics, and failed webmasters who have morphed into search gurus will not help you out.
Check out the profiles of failed vendors at www.xenky.com/vendor-profiles. These are case examples of how search tuna salad became business health hazards.
Stephen E Arnold, November 4, 2015
Xendo, Can Do
October 23, 2015
While it would be lovely to access and find all important documents, emails, and Web sites within a couple clicks, users usually have to access several programs or individual files to locate their information. Stark Industries wanted users to have the power of Google search engine without compromising their personal security. Xendo is a private, personal search engine that connects with various services, including email servers, social media account, clouds, newsfeeds, and more.
Once all the desired user accounts are connected to Xendo, the search engine indexes all the files within the services. The index is encrypted, so it securely processes them. After the indexing is finished, Xendo will search through all the files and return search results displaying the content and service types related to inputted keywords. Xendo promises that:
“After your initial index is built, Xendo automatically keeps it up-to-date by adding, removing and updating content as it changes. Xendo automatically updates your index to reflect role and permission changes in each of your connected services. Xendo is hosted in some of the most secure data-centers in the world and uses multiple layers of security to ensure your data is secured in transit and at rest, like it’s in a bank vault.”
Basic Xendo search is free for individual users with payments required for upgrades. The basic search offers deep search, unlimited access, and unlimited content, while the other plans offer more search options based on subscription. Xendo can be deployed for enterprise systems, but it requires a personalized quote.
Whitney Grace, October 23, 2015
Sponsored by ArnoldIT.com, publisher of the CyberOSINT monograph
Microsoft: Yandex Looking Better than Bing
October 13, 2015
I read “Russia’s Yandex Teams Up with Microsoft for Windows 10.” Microsoft has its work cut out in the search and retrieval sector. The Fast Search & Transfer deal for $1.2 billion, the Powerset technology, the infusion of wizards from Australia, and the wild and crazy promotion for Bing—much activity, questionable payoff.
According to the write up:
Russia’s biggest search engine Yandex said on Tuesday Microsoft would offer it as the default homepage and search tool for Internet browsers across its Windows 10 platform in Russia and several other countries.
I understand the Yandex does a better, no, make that, a much better job indexing content than Bing. In my lectures for professionals engaged in law enforcement and intelligence activities, I show comparisons of output from Bing next to outputs from Yandex. Less Dancing with the Stars and more substance is one way I point up the difference between consumery Bing and Yandex.
According to the write up Microsoft and Yandex have a “strategic cooperation agreement.”
Several observations:
- Microsoft has talked about search for many years. Its products and services are okay. Outfits like Yandex offer results that are more useful for the types of queries I run. Yandex has been around since 2008. Microsoft leaps into action.
- Microsoft’s Bing search has evolved along a trajectory I did not foresee. The colors, the pop culture feel, the intrusiveness of Cortana, and the exclusion of content from Microsoft research baffle me.
- I use Google to locate information about Microsoft’s products and services. That, to me, points to some fundamental problems with Bing.
Net net: Microsoft and search remain and unhappy couple. One question: Will the Microsoft food service people add solyanka to the menu?
Stephen E Arnold, October 13, 2015
Another Categorical Affirmative: Nobody Wants to Invest in Search
October 8, 2015
Gentle readers, I read “Autonomy Poisoned the Well for Businesses Seeking VC Cash.” Keep in mind that I am capturing information which appeared in a UK publication. I find this type of essay interesting and entertaining. Will you? Beats me. One thing is certain. This topic will not be fodder for the LinkedIn discussion groups, the marketers hawking search and retrieval at conferences to several dozen fellow travelers, or in consultant reports promoting the almost unknown laborers in the information access vineyards.
Why not?
The problem with search reaches back a few years, but I will add a bit of historical commentary after I highlight what strikes me as the main point of the write up:
Nobody wants to invest in enterprise search, says startup head. Patrick White, Synata
Many enterprise search systems are a bit like the USS United States, once the slickest ocean liner in the world. The ship looks like a ship, but the effort involved in making it seaworthy is going to be project with a hefty price tag. Implementing enterprise search solutions are similar to this type of ocean-going effort.
There you go. “Nobody.” A categorical in the “category” of logic like “All men are mortal.” Remarkable because outfits like Attivio, Coveo, and Digital Reasoning, among others have received hefty injections of venture capital in recent memory.
The write up makes this interesting point:
“I think Autonomy really messed up [the space]”, and when investors hear ‘enterprise search for the cloud’ it “scares the crap out of them”, he added. “Autonomy has poisoned the well for search companies.” However, White added that Autonomy was just the most high profile example of cases that have scared off investors. “It is unfair just to blame Autonomy. Most VCs have at least one enterprise search in their portfolio. So VCs tend to be skittish about it,” he [added.
I am not sure I agree. Before there was Autonomy, there was Fulcrum Technologies. The company’s marketing literature is a fresh today as it was in the 1990s. The company was up, down, bought, and merged. The story of Fulcrum, at least up to 2009 or so is available at this link.
The hot and cold nature of search and content processing may be traced through the adventures of Convera (formerly Excalibur Technologies) and its relationships with Intel and the NBA, Delphes (a Canadian flame out), Entopia (a we can do it all), and, of course, Fast Search & Transfer.
Now Fast Search, like most old school search technology, is very much with us. For a dose of excitement one can have Search Technologies (founded by some Convera wizards) implement Fast Search (now owned by Microsoft).
Where Are the Former Big Six in Enterprise Search Vendors: 2004 and 2015
Autonomy, now owned by HP and mired in litigation over allegations of financial fraud
Convera, after struggles with Intel and NBA engagements, portions of the company were sold off. Essentially out of business. Alums are consultants.
Endeca, owned by Oracle and sold as an eCommerce and business intelligence service. Oracle gives away its own enterprise search system.
Exalead, owned by Dassault Systèmes and now marketed as a product component system. No visibility in the US.
Fast Search, owned by Microsoft and still available as a utility for SharePoint. The technology dates from the late 1990s. Brand is essentially low profiled at this time.
Verity, Autonomy purchased Verity and used its customer list for upsales and used the K2 technology as part of the sprawling IDOL suite.
Fast Search reported revenues which after an investigation and court procedure were found to be a bit enthusiastic. The founder of Fast Search was the subject of the Norwegian authorities’ attention. You can check out the news reports about the prohibition on work and the sentence handed down for the issues the authorities concluded warranted a slap on the wrist and a tap on the head.
The story of enterprise search has been efforts—sometimes Herculean—to sell information access companies. When a company sells like Vivisimo for about one year’s revenues or an estimated $20 million, there is a sense of getting that mythic task accomplished. IBM, like most of the other acquirers of search technology, try valiantly to convert a utility into something with revenue lift. As I watch the evolution of the lucky exits, my overall impression is that the purchasers realize that search is a utility function. Search can generate consulting and engineering fees, but the customers want more.
That realization leads to the wild and crazy hyper marketing for products like Hewlett Packard’s cloud version of Autonomy’s IDOL and DRE technology or IBM’s embrace of open source search and the wisdom of wrapping that core with functions.
Enterprise search, therefore, is alive and well within applications or solutions that are more directly related to something that speaks to senior managers; namely, making sales and reducing costs.
What’s the cost of making sure the controls for an enterprise search system are working and doing the job the licensee wants done?
The problem is the credit card debt load which Googlers explained quite clearly. Technology outfits, particularly information access players, need more money than it is possible for most firms to generate. This contributes to the crazy flips from search to police analysis, from looking up an entry in a data base to an assertion that customer support is enabled, hunting for an article in this blog is now real time, active business intelligence, or indexing by proper noun like White House morphs into natural language understanding of unstructured text.
Investments are flowing to firms which could be easily positioned as old school search and retrieval operations. Consider Lexmark, a former unit of IBM, and an employer of note not far from my pond filled with mine run off in Kentucky. The company, like Hewlett Packard, wants to find a way to replace its traditional business which was not working as planned as a unit of IBM. Lexmark bought Brainware, a company with patents on trigram methods and a good business for processing content related to legal matters. Lexmark is doing its best to make that into a Trump scale back office content processing business. Lexmark then bought a technology dating from the 1980s (ISYS Search Software once officed in Crow’s Nest I believe) and has made search a cornerstone of the Lexmark next generation health care money spinning machine. Oracle has a number of search properties. Most of these are unknown to Oracle DBAs; for example, Artificial Linguistics, TripleHop, InQuira’s shotgun NLP technology, etc. The point is that the “brands” have not had enough magnetism to pull revenues on a stand alone basis.
Successes measured in investment dollars is not revenue. Palantir is, in effect, a search and retrieval outfit packaged as a super stealthy smart intelligence system. Recorded Future, funded by Google and In-Q-Tel, is doing a bang up job with specialized content processing. There are, remember, search and retrieval companies.
The money in search appears to be made in these plays:
- The Fast Search model. Short cuts until an investigator puts a stop to the activities.
- Creating a company and then selling it to a larger firm with a firm conviction that it can turn search into a big time money machine
- Buying a search vendor to get its customers and opportunities to sell other enterprise software to those customers
- Creating a super technology play and going after venture funding until a convenient time arrives to cash out
- Pursue a dream for intelligent software and survive on research grants.
This list does not exhaust what is possible. There are me-too plays. There are mobile niche plays. There are apps which are thinly disguised selective dissemination of information services.
The point is that Autonomy is a member of the search and retrieval club. The company’s revenues came from two principal sources:
- Autonomy bought companies like Verity and video indexing and management vendor Virage and then sold other products to these firm’s clients and incorporated some of the acquired technology into products and services which allowed Autonomy to enter a new market. Remember Autonomy and enhanced video ads?
- Autonomy managed well. If one takes the time to speak with former Autonomy sales professionals, the message is that life was demanding. Sales professionals including partners had to produce revenue or some face time with the delightful Dr. Michael Lynch or other senior Autonomy executives was arranged.
That’s it. Upselling and intense management for revenues. Hewlett Packard was surprised at the simplicity of the Autonomy model and apparently uncomfortable with the management policies and procedures that Autonomy had been using in highly visible activities for more than a decade as a publicly traded company.
Perhaps some sources of funding will disagree with my view of Autonomy. That is definitely okay. I am retired. My house is paid for. I have no charming children in a private school or university.
The focus should be on what the method for generating revenue is. The technology is of secondary importance. When IBM uses “good enough” open source search, there is a message there, gentle reader. Why reinvent the wheel?
The trick is to ask the right questions. If one does not ask the right questions, the person doing the querying is likely to draw incorrect conclusions and make mistakes. Where does the responsibility rest? When one makes a bad decision?
The other point of interest should be making sales. Stated in different terms, the key question for a search vendor, regardless of camouflage, what problem are you solving? Then ask, “Will people pay money for this solution?”
If the search vendor cannot or will not answer these questions and provide data to be verified, the questioner runs the risk of taking the USS United States for a cruise as soon as you have refurbed the ship, made it seaworthy, and hired a crew.
The enterprise search sector is guilty of making a utility function appear to be a solution to business uncertainty. Why? To make sales. Caveat emptor.
Stephen E Arnold, October 8, 2015
IBM Defines Information Access the Madison Avenue Way
October 7, 2015
Yesterday (October 6, 2015) I wrote a little dialogue about the positioning of IBM as the cognitive computing company. I had a lively discussion at lunch after the story appeared about my suggesting that IBM was making a grand stand play influenced by Madison Avenue thinking, not nuts and bolts realities of making sales and generating revenue.
Well, let’s let IBM rejiggle the line items in its financial statements. That should allow the critics of the company to see that Watson (which is the new IBM) account for IBM revenues. I am okay with that, but for me, the important numbers are the top line revenue and profit. Hey, call me old fashioned.
In the midst of the Gartner talk about IBM, the CNBC exclusive with IBM’s Big Blue dog (maybe just like the Gartner talk and thus not really “exclusive”?), and the wall paper scale ads in the New York Times and Wall Street Journal, there was something important. I don’t think IBM recognizes what it has done for the drifting, financially challenged, and incredibly fragmented search and content processing market. Even the LinkedIn enterprise search discussion group which bristles when I quote Latin phrases to the members of the group will be revivified.
Indexing and groupoiing are useful functions. When applied with judgment, an earthworm of unrelated words and phrases may communicate more effectively.
To wit, this is IBM’s definition of Watson which is search based on Lucene, home brew code, and IBM acquisitions’ software:
Author extraction—Lots of “extraction” functions
Concept expansion
Concept insights—I am not sure I understand the concept functions
Concept tagging—Another concept function
Dialog—Part of NLP maybe
Entity extraction—Extraction
Face detection with the charming acronym F****d—Were the Mad Ave folks having a bit of fun?
Feed detection—Aha, image related
Image Link extraction—Aha, keeping track of urls
Image tagging—Aha, image indexing. I wonder is this is recognition or using information in the file or a caption
Keyword extraction
Language detection
Language translation
Message resonance—No clue here in Harrod’s Creek
Natural language classifier—NLP again
Personality insights—Maybe figuring out what the personality of the author of a processed file means?
Question and answer (I think this is natural language processing which incorporates many other functions in this list)—More NLP
Relationship extraction—IBM has technology from its purchase of i2 which performs this function. How does this work on disparate streams of unstructured content? I have some thoughts
Review and rank—Does this mean relevance ranking?
Sentiment analysis—Yes, is a document with the word F****d in it positive or negative
Speech to text—Seems similar to text to speech
Taxonomy—Ah, ha. A system to generate a list of controlled terms. No humans needed? Nah, humans can be billable and it is an IBM function
Text extraction—Another extraction function
Text to speech
Tone analyzer—So what is the tone of a document containing the string F****d?
Tradeoff analytics—Hmm. Now Watson is doing a type of analytics presumably performed on text? What are the thresholds in the numerical recipe? Do the outputs make sense to a normal human?
Visual recognition—Baffller
Watson news—Is this news about Watson or news presented in Watson via a feed-type mechanism. Phrase does not even sound cool to me.
Now that’s a heck of a list. Notice that the word “search” does not appear in the list. I did not spot the word “semantics” either. Perhaps I was asleep at the switch.
When I was in freshman biology class in 1962, Dr. Daphne Swartz, a very traditional cut ‘em up and study ‘em scientist, lectured for 90 minutes about classification. I remember learning about Aristotle and this dividing organizations into two groups: Plants and animal. I know this is rocket science, but bear with me. There was the charmingly named Carolus Linnaeus, a fan of herring I believe, who cooked up the kingdom, genus, species thing. Then there was, much later, the wild and crazy library crowd which spawned Dewey or, as I named him, Mr. Decimal.
Why is this germane?
It seems to me that IBM’s list of Watson functions needs a bit of organization. In fact, some of the items appear to below to other items; for example: language detection and language translation. More egregious is the broad concept of natural language processing. One could, if one were motivated, argue that entity extraction, text extraction, and keyword extraction might look similar to a non-Watsonian intellect. Dr. Swartz would probably have some constructive criticism to offer.
What’s the purpose of this earthworm list?
Beats me. Makes IBM Watson seem more than Lucene with add ons?
Stephen E Arnold, October 7, 2015
Watson Weekly: Chasing Sales via Ads. Forget Thought Leadership
October 6, 2015
I was exploring the topics business intelligence and Big Data. I was intrigued by “Is Thought Leadership a Waste of Money?” My reaction was, “Nope, thought leadership is good.” Who wants to fool around with regular marketing methods.
What’s the write up say?
I highlighted this passage from a person who does not know about the genesis of Strategy & Business and the somewhat addled Booz, Allen executive who wanted a BAH branded Economist to generate revenue:
Once upon a time back in 1994, Joel Kurtzman, the then-editor-in-chief of Strategy & Business, coined the term “thought leader” as a means for identifying people within the business marketplace that merited our attention. Thought leaders were the individuals within their respective industries who offered fresh, creative ideas and commentary on industry problems and trends. Two decades later, much of today’s thought leadership has gone from original to repetitive. It’s not that business leaders, C-level executives, or entrepreneurs don’t have great ideas or valuable insights. The problem is a bit more complex.
But here’s the shocker. Strategy & Business was a reaction by Booz, Allen & Hamilton to publications and marketing campaigns mounted by other blue chip consulting firms.
Advertising, at least for blue chip firms, was somewhat low brow. The notion of pumping drivel into the in boxes of Fortune 1000 executives was also distasteful. Today advertising is the cat’s pajamas.
IBM is proving that nothing beats banging one’s own drum even if no one knows what the band is playing.
I opened my dead tree edition of the New York Times this morning )October 6, 2015), and what did I see? The work of Ogilvy & Mather? Sure looks like it. Big ad buy. Big images. Big assertions.
Cognitive computing via Watson. Yikes, where is the smarter planet? I did some poking around and came across “Tangled Up in Big Blue: IBM Replaces Smarter Planet With … Bob Dylan.”
IBM began to realize that the message of Smarter Planet — basically that computing is and will be integral to everything, as manifested in innovations such as smart power grids and connected cars — is no longer a differentiator for the business, explained Mr. Iwata. The emerging pattern, as harnessed and fostered by its Watson technology, is that these super computing capabilities can be built into anything digital because they live in the cloud.
IBM’s senior vice president of marketing Jon Iwata allegedly said:
“This will resonate strongly with not only our current clients but…companies and decision makers and software developers who aren’t currently IBM clients.”
The result in the dead tree newspapers I saw presented page upon page of IBM Watson marketing. Here are some of the pages from this morning’s print campaign in the New York Times and the Wall Street Journal:
The massive ad campaign reveals that Watson consists of 100 million lines of code. No comment about bugs counts, however.
Obviously, this snapshot is too small to read. Put down your smartphone and buy the dead tree newspapers. Here are the themes I noted:
- Buzzwords
- Components that you, gentle reader, can assemble like Potassium ferrocyanide in chem lab when the teacher is inattentive
- Images of youthful, diverse people who are obviously into Watson
- Copy, lots of copy.
The information recycles that which is available on the IBM Watson Web site. The difference is that the multi page ads are the equivalent of a Bunker Buster dropped into the somewhat indifferent world of search and content processing. How will the likes of minnows like Coveo, dtSearch, Elasticsearch (now Elastic), Recommind, Sinequa, legions of business analytics firms, the specialists pitching everything from indexing (Smartlogic) to semantics (SenseBot), and all manner of information access vendors scattered across a somewhat Martian like landscape. Sure, there may be water, but can one survive on the stuff?
IBM is skipping the thought leader thing and going right to big buck advertising. I can imagine this scenario taking place in Joe Coffee’s. The IBM marketing team is meeting with the ad agency’s equivalent of Bindy Irwin. The scene is a hip coffee shop near the Watson office in Manhattan.
IBM Watson Wizard (IWW): We need something big to get this Watson bandwagon rolling?
Mad Ave Ad Exec (MAAE): Yes, big. We need to do big.
IWW: Let’s brainstorm here? Do you want another cappuccino with the neat latte art?
MAAE: Sure, sure. But make mine a macchiato.
[IBM Watson executive returns with more cappuccino and one artisan cafe macchiato.]
IWW: Who wants the macchiato? What have you got for me?
MAAE: Okay, we have been talking while you were standing on line? By the way, do you want one of us to pay for the coffee?
IWW: Nah, we’ve got more than a billion to burn. Let’s get to it.
MAAE: Here’s the idea. Imagine putting the Watson cognitive computing message in front of every, and I mean every, New York Times and Wall Street Journal reader. We warm up with some Monday Night Football buys and then, bang, we hit the buyers with the message, “Cognitive computing.”
IWW: Well, print? What about viral videos? What about social media?
MAAE: We will do that. We can pay some mid tier consulting types to send out Watson tweets?
IWW: But that did not get any traction?
MAAE: Tweets are good. We need to provide a big bang to make the tweet thing happen.
IWW: What’s the message?
MAAE: We were thinking think. But 21st century style. We want to go with outthink thing.
IWW: Out think. I like it.
MAAE: Now picture this. You know how everyone learned about chemical symbols in high school?
IWW: Yes, but I got a D.
MAAE: No problem. Here’s the picture. [Ad person grabs napkin and sketches a hexagon with a happy face.
We show the components of the Watson system as little chemical symbols with codes in them.
IWW: Symbols? Codes? It looks like a happy face with an F in it.
MAAE: Grab your mental iPhone. Snap this happy icon with the Fd. You see “face detection.” Fd. Crystal clear. Non verbal. Immediate.
IWW: I don’t understand.
MAAE: Work with me on this. We make a list of the APIs and the buzzwords and put them into a graphic. We call the page “IBM Watson is the platform for cognitive business.”
IWW: Oh, like the structures computational chemists use to visualize complex constructs?
MAAE: What’s a computational structure whatever? I know a happy face thing with a hexagon. This gets the message across. Zap. Like an Instagram, right?
IWW: I get it. I get it.
MAAE: You like it, right? Big bang. Big splash. Big message but simple, clear, easy to grasp.
IWW: How many New York Times and Wall Street Journal readers know what API means?
MAAE: We’ve grab the upside. Wait for it. We will hook the Watson cognitive thing with a superstar. We are thinking Bob Dylan.
IWW: Bob Dylan. I remember him. Butwasn’t there some talk about drugs, political activism, maybe something with Croatia in France?
MAAE: Ancient history and myth. He’s an icon. Picture this. Bob Dylan becomes the image of cognitive computing. Can’t miss. Cannot miss. Winner. We become the messaging for API. Watson APIs will be huge. The chatter about text extraction, image tagging, and concept expansion. Deafening.
IWW: Wow, that sounds almost as powerful as the Jeopardy game show promotion. I really liked that game show thing. Watson won too.
MAAE: Right. That’s the value of post production. Now. One final point. Jules here came up with a great idea while you were waiting on line. We take the rock solid facts about Watson. Jules thinks this was your idea, and it is a great one. Watson. Only 100 million lines of code, you know, more than in a Volkswagen-type fuel emission system. We sprinkle these facts under a headline like “A cognitive business is a business that thinks.” Stir in Dylan and you can write your own ticket in this cognitive computing thing.
IWW: But what about outthink thing? You said the new hook was outthink.
MAAE: Yes, yes, outthink is the glue. Cognitive API outthink. Huge. I will send a contract over to you later today.
IWW: Do you think we will make any sales?
MAAE: Sales? Sure, sure. Winner. Be sure to turn around that contract. We need to get rolling like a rolling stone. Winner.
What other boosters did Watson receive on October 6, 2015. Well, the IBM Big Blue Boss is on CNBC. Not as perky as Bindy, but pretty excited about granting CNBC an exclusive.
One question: What about revenues? You know three years of declining revenue.
Stephen E Arnold, October 6, 2015
Stephen E Arnold, October 6, 2015
Full Text Search Gets Explained
October 6, 2015
Full text search is a one of the primary functions of most search platform. If a search platform cannot get full text search right, then it is useless and should be tossed in the recycle bin. Full text search is such a basic function these days that most people do not know how to explain what it is. So what is full text?
According to the Xojo article, “Full Text Search With SQLite” provides a thorough definition:
“What is full text searching? It is a fast way to look for specific words in text columns of a database table. Without full text searching, you would typically search a text column using the LIKE command. For example, you might use this command to find all books that have “cat” in the description…But this select actually finds row that has the letters “cat” in it, even if it is in another word, such as “cater”. Also, using LIKE does not make use of any indexing on the table. The table has to be scanned row by row to see if it contains the value, which can be slow for large tables.”
After the definition, the article turns into advertising piece for SQLite and how it improves the quality of full text search. It offers some more basic explanation, which are not understood by someone unless they have a coding background. It is a very brief with some detailed information, but could explain more about what SQLite is and how it improves full text search.
Whitney Grace, October 6, 2015
Sponsored by ArnoldIT.com, publisher of the CyberOSINT monograph
Search Engine Optimization: Get Out Your Checkbook
October 5, 2015
No traffic? Low traffic? No mobile traffic? Can’t find your site on Bing or Google?
If these questions poke your marketing nerve, you may consider hiring an “expert” to help you out. Most of the traffic and “find you in Google” specialists are doing business as SEO experts. Personally I would skip the SEO baloney and just buy traffic love via Google Adwords.
Search engine optimization is a catch all to address expensive Web sites which no one visits. Yikes. Considering that most traffic on the Web flows to five percent of the billion plus Web sites, traffic to a personal or small business Web site is terrible.
What’s the fix?
The SEO crowd wants you to spend money with them, not Adwords. Google’s approach is different. The company wants to sell you traffic. The two ideas are intertwined, but you would not know this by reading “How Much Does Good SEO Cost?”
The write up summarizes a number of ball park costs; for example:
- Hire a full time employee: Maybe $50,000 to $100,000. How’s that fit your budget, gentle reader.
- Hire an agency: No cost given. Use your imagination.
- Hire a dedicated SEO firm: No cost given. Use your imagination again.
But the way to go is to set aside money for an expert consultant / practitioner. At each stair step, the customer gets more SEO goodness. Exactly what the payoff is, is not clear to me. But here are the suggested price levels spelled out in the write up:
- Put folks on a monthly retainer. Less than $500 per month. Cheaper than a daily Starbuck’s coffee
- A retainer for $1,000 to $5,000 per month: This is SEO hog heaven for an outfit with 10 clients, the SEO wizard may generate more free cash than your business
- $5,000 to $10,000 per month: “Ambitious goals”. You bet
- $10,000 to $20,000 per month: The owners will retire early if their customers pay their bills.
The canny business owner in search of SEO love can sign a contract. This is interesting. Here are the price points from the article which I assume are based on thorough research in fees charged by a statistically valid sample of SEO firms. (Somehow I question the rigor of the information gathering process.) Let’s look at the benchmarked fees:
- Link profile audits: $2,500 to $7,500
- SEO / Web site audits: $2,500 to $7,500 or higher, gentle reader
- Link building: $250 to $2,000 per link. Wowza
- Per page optimization and implementation: $100 to $250. (Fascinating since some content management systems make per page operations pretty darned exciting for a skilled programmer. For dabblers, think about downtime, gentle reader.)
- Copywriting: $0.75 to $1.00 per word.
If you are on a budget, you can hire a consultant for an hour; for example, a $100 to $300 fee seems to be normal. Keep in mind that there are roughly 2,000 billable hours per year, so this fee range is designed to compensate an expert in SEO at a minimum of $200,000 per year. Ready to abandon your day job, gentle reader?
Now these costs spark several thoughts in this addled goose’s mind.
First, exactly what is the payoff from SEO versus spending the money for Google Adwords?
Second, what specific changes the SEO expert makes results in “more” traffic, likes, or whatever? How is an SEO action tied to a payoff?
Third, what happens to the client’s Web site if the SEO activity gets the site down checked, blackballed, or less traffic?
Dear old Google wants folks to make Web sites so it takes Google as little computing time as possible to index the site, extract data, and do all the Googley things which makes me love the company so darned much.
My experience is that making a change to a site or putting up a new site leads to a bit of Google love. After a couple of indexing cycles, the traffic declines. Desperate site owners embrace SEO. After that doesn’t work, the road leads back to buying traffic via Adwords.
Thus, the Google likes anything that does not work as well as buying traffic.
Perhaps the SEO crowd should just sell Adwords? But that may not be as lucrative or create opportunities for the client to engage in the “Why isn’t your work producing traffic meetings?” I bet those are fun and inevitable too.
Stephen E Arnold, October 5, 2015
Microsoft Bing in Edge is Baidu: Confused?
September 24, 2015
I received an alert about Bing. I usually ignore these. The headline did not reference search. The article is billed as “Windows 10 in China.” I am not sure why I scanned the item, but I noted that the Microsoft blog post contained an interesting factoid about Bing search.
Here’s the passage I noted:
Together [Baidu and Microsoft], we will make it easy for Baidu customers to upgrade to Windows 10 and we will deliver a custom experience for customers in China, providing local browsing and search experiences. Baidu.com will become the default homepage and search for the Microsoft Edge browser in Windows 10.
I wondered if I understood the message. The Windows 10 browser, called Edge, will include a Web and local search function. The search is going to be provided by Baidu for “local browsing and search experiences.”
I find this interesting for two reasons: Is Bing, assisted by a search wizard from Australia, now “funneling” queries to Baidu? and Has Microsoft given up on the job of indexing Chinese language content?
I recall reading “About Microsoft Research Asia,” and learning that one of the goals for Microsoft’s expanding research activities in Asia was:
Search and online advertising takes Web search and online advertising to the next level by applying data-mining, machine-learning and knowledge-discovery techniques to information analysis, organization, retrieval and visualization.
Now the company is relying on a third party for search. Is this a signal that Bing is not up to the search and retrieval job in China?
Stephen E Arnold, September 24, 2015
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