HonkinNews for 29 November 2016 Now Available
November 29, 2016
This week’s HonkinNews covers IBM Watson QAM (not a yam and not part of an internal combustion engine). We also report that Palantir Technologies has stereophonic input to the Trump Transition Team. You will also learn about EasyAsk’s amazing guarantee regarding eCommerce revenues. The show includes another dispatch from the front lines of the artificial intelligence wars. Google is on the offensive. Hitachi aims to become the first Japanese company to notch a perfect score in the enterprise search high diving content. If you thought Willie Shakespeare worked alone, we rain on your parade courtesy of text analytics researchers who identify Kit Marlowe’s digital fingerprints on Henry VI. Imagine. Theater types collaborating. We thought Hollywood types invented this approach to content. This program gives the dates for the three videos about Stephen E Arnold’s The Google Trilogy. You can access the video at this link.
Kenny Toth, November 29, 2016
Need Data Integration? Think of Cisco. Well, Okay
November 25, 2016
Data integration is more difficult than some of the text analytics’ wizards state. Software sucks in disparate data and “real time” analytics systems present actionable results to marketers, sales professionals, and chief strategy officers. Well, that’s not exactly accurate.
Industrial strength data integration demands a company which has bought a company which acquired a technology which performs data integration. Cisco offers a system that appears to combine the functions of Kapow with the capabilities of Palantir Technologies’ Gotham and tosses in the self service business information which Microsoft touts.
Cisco acquired Composite Information in 2013. Cisco now offers the Composite system as the Cisco Information Server. Here’s what the block diagram of the federating behemoth looks like. You can get a PDF version at this link.
The system is easy to use. “The graphical development and management environments are easy to learn and intuitive to use,” says the Cisco Teradata information sheet. For some tips about the easy to use system check out the Data Virtualization Cisco Information Server blog. A tutorial, although dated is, at this link. Note that the block diagram between 2011 and the one presented above has not significantly changed. I assume there is not much work required to ingest and make sense of the Twitter stream or other social media content.
The blog has one post and was last updated in 2011. But there is a YouTube video at this link.
The system includes a remarkable range of features; for example:
- Modeling which means import and transform what Cisco calls “introspect”, create a model and figure out how to make it run at an acceptable level of performance, and expose the data to other services. (Does this sound like iPhrase’s and Teratext’s method? It does to me.)
- Search
- Transformation
- Version control and governance
- Data quality control and assurance
- Outputs
- Security
- Administrative controls.
The time required to create this system is, according to Cisco Teradata, is “over 300 man years.”
The licensee can plug the system into an IBM DB2 running on a z/OS8 “handheld”. You will need a large hand by the way. No small hands need apply.
Stephen E Arnold, November 25, 2016
Pitching All Source Analysis: Just Do Dark Data. Really?
November 25, 2016
I read “Shedding Light on Dark Data: How to Get Started.” Okay, Dark Data. Like Big Data, the phrase is the fruit of the nomads at Garner Group. The person embracing this sort of old concept is an outfit OdinText. Spoiler: I thought the write up was going to identify outfits like BAE Systems, Centrifuge Systems, IBM Analyst’s Notebook, Palantir Technologies, and Recorded Future (an In-Q-Tel and Google backed outfit). Was I wrong? Yes.
The write up explains that a company has to tackle a range of information in order to be aware, informed, or insightful. Pick one. Here’s the list of Dark Data types, which the aforementioned companies have been working to capture, analyze, and make sense of for almost 20 years in the case of NetReveal (Detica) and Analyst’s Notebook. The other companies are comparative spring chickens with an average of seven years’ experience in this effort.
- Customer relationship management data
- Data warehouse information
- Enterprise resource planning information
- Log files
- Machine data
- Mainframe data
- Semi structured information
- Social media content
- Unstructured data
- Web content.
I think the company or non profit which tries to suck in these data types and process them may run into some cost and legal issues. Analyzing tweets and Facebook posts can be useful, but there are costs and license fees required. Frankly not even law enforcement and intelligence entities are able to do a Cracker Jack job with these content streams due to their volume, cryptic nature, and pesky quirks related to metadata tagging. But let’s move on. To this statement:
Phone transcripts, chat logs and email are often dark data that text analytics can help illuminate. Would it be helpful to understand how personnel deal with incoming customer questions? Which of your products are discussed with which of your other products or competitors’ products more often? What problems or opportunities are mentioned in conjunction with them? Are there any patterns over time?
Yep, that will work really well in many legal environments. Phone transcripts are particularly exciting.
How does one think about Dark Data? Easy. Here’s a visualization from the OdinText folks:
Notice that there are data types in this diagram NOT included in the listing above. I can’t figure out if this is just carelessness or an insight which escapes me.
How does one deal with Dark Data? OdinText, of course. Yep, of course. Easy.
Stephen E Arnold, November 25, 2016
Wake Up, DCGS: Peter Thiel Alert
November 11, 2016
I read a LinkedIn special write up titled “Peter Thiel to Join Trump Transition Team.” The main point of the write up was that Silicon Valley icon and founder of Palantir Technologies has allegedly just hopped on the Trump Transition Express. I learned:
Peter Thiel has agreed to join Donald Trump’s presidential transition team, according to multiple sources close to the situation.
I love those “multiple sources.” Verification is great especially when anonymized.
It strikes me that if the news is on the money, there are some interesting consequences of this decision. Let me pop several out of the microwave which is heating my Bob Evans sausage, egg, and cheese every day classic breakfast.
I start my day the health way: A Bob Evans microwave meal and news about the impact of a new technology voice in the new administration of the new president. Yummy.
First, based on my limited experience in the Washington presidential transition Beltway hoedowns, there may be an opportunity or two to chat up those involved in managing certain large defense and intelligence related projects. Now the conversations are informal, premature, fuzzy, and for sure non binding, but there just might be a few words exchanged about reducing billions in government waste with regard to certain high profile, contentious, over budget, and fractionalized projects. Maybe the Distributed Common Ground System will come up? Maybe providing Gotham to the entire transition team? Who knows? But a taste of Gotham’s manna may be just what the hard working commuters on the Transition Express need to perk up and open their eyes to what technology really can do.
Second, the hinges on the Alphabet Google special door to President Obama’s outfit may be wearing out. Palantir, which Mr. Thiel founded, has Google-type bright lads and lasses who can out Google the Google when it comes to heavy duty information analysis. War fighting “trumps” selling ads for Garcinia- Cambogia.
Some of Mr. Thiel’s inputs may rely on Palantir Gotham for data relevant to a decision taken by Transition Express fellow travelers. If Palantir’s approach shows answers, the Google results list looks — how can I phrase it? — dowdy, lame, old fashioned. Imagine the efficiency of the the new president’s advisors generating knock out visualizations for budgets, action items, and timelines with Gotham. Exciting, no? Yes?
Third, the established outfits like the Beltway outfits which have methods of communicating and influencing now have to rethink getting on the radar of the transition team. Those juicy, rock solid indefinite cost, open ended pipelines of money may have to make some navigational adjustments in real time. But what if Mr. Thiel just is involved in calculating the azimuth? How does a Beltway Top 100 firm make up for lost US government “to be” revenue? My answer, “With alacrity tinged with freneticism.”
If Mr. Thiel is on the transition team, there will be some capture teams worrying about [a] their bonus, [b] their new business plan, and [c] their résumés. The latter will be just super for LinkedIn’s secret job search service too. Who knows? Maybe some of these folks will post anonymous LinkedIn rumors which we enjoy here in Harrod’s Creek.
Stephen E Arnold, November 11, 2016
HonkinNews for November 8, 2016 Now Available
November 8, 2016
This week HonkinNews comments about Microsoft’s mobile phone adventure. You will learn about geo spatial analytics’ companies that may have an impact in certain secret applications. Palantir makes news again. There is more. You can view the seven minute video at this link https://youtu.be/UWCk4n_AC0Y.
Kenny Toth, November 8, 2016
Worried about Risk? Now Think about Fear
November 3, 2016
I clicked through a remarkable listicle offered by CSO Magazine from my contract savvy pals at IDG. I don’t know much about risk, but I have encountered fear before. I recall an MBA Wall Street person who did not have enough cash to pay for lunch. I picked up the tab. That fellow had fear in his eyes because his firm had just gone out of business. Paying for a car service, nannies, country clubs, and a big house triggered the person’s fright.
You can be captured and tortured in an off the grid prison. Be afraid. Embrace IDG and be safe. Sort of. Maybe.
Well, CIO Magazine wants to use technology to make you, gentle reader, fearful. In case you are not nervous about your job, the London tabloids reports about a nuclear war, and the exploding mobile phone in your pocket.
Here are the “fears” revealed in “Frightening Technology Trends to Worry About.” Here we go:
- Overlooked internal threats. (Yes, someone in your organization is going to destroy you and your livelihood.)
- Finding and retaining top talent. (Of course, Facebook or Palantir will hire the one person who can actually make your firm’s software and systems work.)
- Multiple generations in the workforce. (Yes, what’s an old person going to do when dealing with those under 25. You are doomed. Doomed, I say.)
- Shifts in compliance. (Yes, the regulatory authorities will find violations and prevent your organization from finding new sources of revenue.)
- Migrating to the cloud. (Yes, the data are in the cloud. When you lose a file, that cherished document may be gone forever. Plus, the IT wizard at your firm now works at Palantir and is not answering your texts.)
- Getting buy in on hyper convergence. (Yes, you are pushing the mantra “everything is digital” and your colleagues wonder if you have lost your mind. Do you see hyper pink elephants?)
- Phishing and email attacks. (Yes, your emails are public. Did you use the company system to organize a Cub Scout bake sale, buy interesting products, or set up an alias and create a bogus Twitter account?)
- Hacktivism. (Yes, you worry about hackers and activism. Both seem bad and both are terrifying to you. Quick click on the link from Google telling you your account has been compromised and you need to change your password. Do it. Do it now.)
- The next zero day attack. (Yes, yes. You click on a video on an interesting Web site and your computing device is compromised. A hacker has your data and control of your mobile phone. And your contacts. My heavens, your contacts. Gone.)
- The advanced persistent threat. (Yes, yes, yes. Persistent threats. No matter what you do, your identify will be stolen and your assets sucked into a bank in Bulgaria. It may be happening now. Now I tell you. Now.)
- Mobile exploits. (Oh, goodness. Your progeny are using your old mobile phones. Predators will seek them out and strike them down with digital weapons. Kidnapping is a distinct possibility. Ransom. The news at 6 pm. Oh, oh, oh.)
- State sponsored attacks. (Not Russia, not China, not a Middle Eastern country. You visited one of these places and enjoyed the people. The people are wonderful. But the countries’ governments will get you. You are toast.)
How do you feel, gentle reader. Terrified. Well, that’s what CSO from IDG has in mind. Now sign up for the consulting services and pay to learn how to be less fearful. Yes, peace of mind is there for the taking. No Zen retreat in Peru. Just IDG, the reassuring real journalistic outfit. Now about those contracts, Dave Schubmehl?
Stephen E Arnold, October 3, 2016
The IBM Watson Hype Machine Shouts Again
October 28, 2016
The IBM Watson semi news keeps on flowing. The PR firms working with IBM and the Watson team may bring back the go go days of Madison Avenue. Note, please. I wrote “may.” IBM’s approach, in my opinion, is based on the Jack Benny LSMFT formula. Say the same thing again and again and pretty soon folks will use the product. The problem is that IBM has not yet found its Jack Benny. Bob Dylan, the elusive Nobel laureate, is not exactly the magnetic figure that Mr. Benny was.
For a recent example of the IBM Watson buzz-o-rama, navigate to “IBM Watson: Not So Elementary.” I know the story is important. Here’s the splash page for the write up:
I will definitely be able to spot this wizard if I bump into him in Harrod’s Creek, Kentucky. I wonder what the Watson expert is looking at or for. Could it be competitors like Facebook or outfits in the same game in China and Russia?
The write up begins with an old chestnut: IBM’s victory on Jeopardy. No more games. I learned:
IBM’s cognitive computing system is through playing games. It’s now a hired gun for thousands of companies in at least 20 industries.
I like the “hired” because it implies that IBM is raking in the dough from 20 different industry sectors. IBM, it seems, is back in the saddle. That is a nifty idea but for the fact that IBM reported its 18th consecutive quarter of revenue declines. The “what if” question I have is, “If Watson were generating truly big bucks, wouldn’t that quarterly report reflect a tilt toward positive revenue growth?” Bad question obviously. The Fortune real journalist did not bring it up.
The write up is an interview. I did highlight three gems, and I invite—nay, I implore—you to read and memorize every delicious word about IBM Watson. Let’s look at the three comments I circled with my big blue marker.
Augmented Intelligence
at IBM, we tend to say, in many cases, that it’s not artificial as much as it’s augmented. So it’s a system between machine computing and humans interpreting, and we call those machine-human interactions cognitive systems. That’s kind of how it layers up….it’s beginning to learn on its own—that is moving more in the direction of what some consider true artificial intelligence, or even AGI: artificial general intelligence.
Yikes, Sky Net on a mainframe, think I.
Training Watson
there isn’t a single Watson. There’s Watson for oncology. There’s Watson for radiology. There’s Watson for endocrinology…for law…for tax code…for customer service.
I say to myself, “Wow, the costs of making each independent Watson smart must be high. What if I need to ask a question and want to get answers from each individual Watson? How does that work? How long does it take to receive a consolidated answer? What if the customer service Watson gets a question about weather germane to an insurance claim in South Carolina?”
The Competition
The distinctness of the Watson approach has been to create software that you can embed in other people’s applications, and these are especially used by the companies that don’t feel comfortable putting their data into a single learning system—particularly one that’s connected to a search engine—because in effect that commoditizes their intellectual property and their cumulative knowledge. So our approach has been to create AI for private or sensitive data that is best reserved for the entities that own it and isn’t necessarily ever going to be published on the public Internet.
I ponder this question, “Will IBM become the background system for the competition?” My hunch is that Facebook, Google, Microsoft, Amazon, and a handful of outfits in backwaters like Beijing and Moscow will think about non IBM options. Odd that the international competition did not come up in the Fortune interview with the IBM wizard.
End Game
these systems will predict disease progression in time to actually take preventive action, which I think is better for everybody.
“Amazing, Watson will intervene in a person’s life,” blurt my Sky Net sensitive self.
Please, keep in mind that this is an IBM Watson cheer which is about 4,000 words in length. As you work through the original Fortune article, keep in mind:
- The time and cost of tuning a Watson may cost more than a McDonald’s fish sandwich
- The use of “augmented intelligence” is a buzzword embraced by a number of outfits, including Palantir Technologies, a competitor to IBM in the law enforcement and intelligence community. Some of IBM’s tools are ones which the critics of the Distributed Common Ground System suggest are difficult to learn, maintain, and use. User friendly is not the term which comes to mind when I think of IBM. Did you configure a mainframe or try to get a device driver for OS/2 to work? There you go.
- The head of IBM Watson is not an IBM direct hire who rose through the ranks. Watson is being guided by a person from the Weather Channel acquisition.
How does Watson integrate that weather data into queries? How can a smart system schedule surgeries when the snow storm has caused traffic jams. Some folks may use an iPhone or Pixel or use common sense.
Stephen E Arnold, October 28, 2016
Picking Away at Predictive Programs
October 21, 2016
I read “Predicting Terrorism From Big Data Challenges U.S. Intelligence.” I assume that Bloomberg knows that Thomson Reuters licenses the Palantir Technologies Metropolitan suite to provide certain information to Thomson Reuters’ customers. Nevertheless, I was surprised at some of the information presented in this “real” journalism write up.
The main point is that numerical recipes cannot predict what, when, where, why, and how bad actors will do bad things. Excluding financial fraud, which seems to be a fertile field for wrong doing, the article chases the terrorist angle.
I learned:
- Connect the dots is a popular phrase, but connecting the dots to create a meaningful picture of bad actors’ future actions is tough
- Big data is a “fundamental fuel”
- Intel, PredPol, and Global Intellectual Property Enforcement Center are working in the field of “predictive policing”
- The buzzword “total information awareness” is once again okay to use in public
I highlighted this passage attributed too a big thinker at the Brennan Center for Justice at NYU School of Law:
Computer algorithms also fail to understand the context of data, such as whether someone commenting on social media is joking or serious,
Several observations:
- Not a single peep about Google Deep Mind and Recorded Future, outfits which I consider the leaders in the predictive ball game
- Not a hint that Bloomberg was itself late to the party because Thomson Reuters, not exactly an innovation speed demon, saw value in Palantir’s methods
- Not much about what “predictive technology” does.
In short, the write up delivers a modest payload in my opinion. I predict that more work will be needed to explain the interaction of math, data, and law enforcement. I don’t think a five minute segment with talking heads on Bloomberg TV won’t do it.
Stephen E Arnold, October 21, 2016
Online and without Ooomph: Social Content
October 15, 2016
I am surprised when Scientific American Magazine runs a story somewhat related to online information access. Navigate to read “The Bright Side of Internet Shaming.” The main point is that shaming has “become so common that it might soon begin to lose its impact.” Careful wording, of course. It is Scientific American, and the write up has few facts of the scientific ilk.
I highlighted this passage:
…these days public shaming are increasingly frequent. They’ve become a new kind of grisly entertainment, like a national reality show.
Yep, another opinion from Scientific American.
I then circled in Hawthorne Scarlet A red:
there’s a certain kind of hope in the increasing regularity of shamings. As they become commonplace, maybe they’ll lose their ability to shock. The same kinds of ugly tweets have been repeated so many times, they’re starting to become boilerplate.
I don’t pay much attention to social media unless the data are part of a project. I have a tough time distinguishing misinformation, disinformation, and run of the mill information.
What’s the relationship to search? Locating “shaming” type messages is difficult. Social media search engines don’t work particularly well. The half hearted attempts at indexing are not consistent. No surprise in that because user generated input is often uninformed input, particularly when it comes to indexing.
My thought is that Scientific American reflects shaming. The write up is not scientific. I would have found the article more interesting if:
- Data based on tweet or Facebook post analyses based on negative or “shaming” words
- Facts about the increase or decrease in “shaming” language for some “boilerplate” words
- A Palantir-type link analysis illustrating the centroids for one solid shaming example.
Scientific American has redefined science it seems. Thus, a search for science might return a false drop for the magazine. I will skip the logic of the write up because the argument strikes me as subjective American thought.
Stephen E Arnold, October 15, 2016
HonkinNews for October 4, 2016 Available
October 4, 2016
This week’s HonkinNews is available at this link. The feature story explores Palantir Technologies’ love-less love relationship with the US Army. Palantir’s approach to keeping its government customers happy is innovative. We also comment about Google’s blurring of cow faces in StreetView. Learn why SearchBlox is giving vendors of expensive, proprietary enterprise search systems cramps in their calves. Microsoft continues to pay users to access the Internet via Edge and use Bing to search for information. How much does the US government spend for operations and maintenance of its systems? The figure is surprising, if not shocking. This and more in HonkinNews for October 4, 2016.
Kenny Toth, October 4, 2016
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