IBM Can Train Smart Software ‘Extremely Fast’ an IBM Wizard Asserts

November 30, 2017

Short honk: If you love IBM, you will want to read “AI, Cognitive Realities and Quantum Futures – IBM’s Head of Cognitive Solutions Explains.” The article contains extracts of an IBM wizard’s comments at a Salesforce event. Here’s the passage I noted:

What we find is we always start with POCs, proof of concept. They can be small or large. They’re very quick now, because we can train Watson our new data extremely fast.

If this is true, IBM may have an advantage over many other smart software vendors. Why? Gathering input data, formatting that data into a form the system’s content processing module can handle, and crunching the data to generate the needed indexes takes time and costs a great deal of money. If one needs to get inputs from subject matter experts, the cost of putting engineers in a room with the SMEs can be high.

It would be interesting to know the metrics behind the IBM “extremely fast” comment. My hunch is that head-to-head tests with comparable systems will reveal that none of the systems have made a significant breakthrough in these backend and training processes.

Talk is easy and fast; training smart software not so much.

Stephen E Arnold, November 29, 2017

Business Intelligence: A List of 238 Firms

November 30, 2017

Need a list of “fermium” business intelligence tools. That’s no typo. That is the word on page 2 of Top Business intelligence Solutions. Looking past the misspelling, the write up from Predictive Analytics Today presents a listing in no particular order of more than 200 business intelligence tools. The text is accompanied by little boxes with scores in them like this:


The list was a lot of work. The names of companies are collected in these major categories:

  1. Free cloud business intelligence solutions
  2. Free open source business intelligence tools
  3. Free proprietary business intelligence tools
  4. Open source commercial business intelligence tools
  5. Top business intelligence companies
  6. Free extract, transform and load software
  7. Top extract, transform and load software
  8. Cloud SaaS on demand business intelligence solutions
  9. Freemium cloud business intelligence solutions
  10. Open source balanced scorecard software
  11. Top balanced scorecard software
  12. Open source and free dashboard software
  13. Top dashboard software
  14. Embedded business software
  15. Open source and free unified modeling language tools
  16. Open source and free business process management tools

What I found interesting about the list was:

  • For fee vendors appear in “free” categories; for example, IBM Watson and Microsoft
  • Many of the vendors have versions of their software for the intelligence and law enforcement community. Most of these versions of the companies with specialized tools are not free
  • None of the specialist firms which I track appear on the list; for example, BAE Systems, a company whose tools rival those of many of the other firms on the list.
  • The vendor Attivio was left out. This surprised me because Attivio pitches itself as a business intelligence solution and it has a tie up with Tibco, a product dependent in part on software created by the founders of Recorded Future, a company which I track because it has robust intelligence capabilities embodied in its products and services.
  • There are curious omissions. One important one is Palantir, whose Gotham product powers a number of commercial business intelligence applications like those from Thomson Reuters’ financial product line.
  • Many vendors appear in multiple categories. This left me confused. For major vendors it would have been helpful to provide the company name “IBM” with a summary of what the company offers as free, freemium, open source, proprietary, etc.

Nevertheless, the listing is interesting for those wanting to track some of the vendors pursuing the business intelligence sector. To learn about companies not on the Predictive Analytics’ list, follow DarkCyber, my weekly video program. Each week, I profile intelligence companies which are often off the radar of some commercial procurement teams. That’s unfortunate because the firms I follow are indeed cutting edge when it comes to real life intelligence analysis. Most of these products, in my experience, cost money either for engineering, training, support, or add ons.

You can find the video by navigating to this link or running a query for Arnold Dark Cyber on or on

Stephen E Arnold, November 30, 2017

Big Data Used to Confirm Bad Science

November 30, 2017

I had thought we had moved beyond harnessing big data and were now focusing on AI and machine learning, but Forbes has some possible new insights in, “Big Data: Insights Or Illusions?”

Big data is a tool that can generate new business insights or it can reinforce a company’s negative aspects.  The article consists of an interview with Christian Madsbjerg of ReD Associates.  It opens with how Madsbjerg and his colleagues studied credit card fraud by living like a fraudster for a while.  They learned some tricks and called their experience contextual analytics.  This leads to an important discussion topic:

Dryburgh: This is really interesting, because it seems to me that big data could be a very two-edged sword. On the one hand you can use it in the way that you’ve described to validate hypotheses that you’ve arrived at by very subjective, qualitative means. I guess the other alternative is that you can use it simply to provide confirmation for what you already think.

Madsbjerg: Which is what’s happening, and with the ethos that we’ve got a truth machine that you can’t challenge because it’s big data. So you’ll cement and intensify the toxic assumptions you have in the company if you don’t use it to challenge and explore, rather than to confirm things you already know.

This topic is not new.  We are seeing unverified news stories reach airwaves and circulate the Internet for the pure sake of generating views and profit.  Corporate entities do the same when they want to churn more money into their coffers than think of their workers or their actual customers.  It is also like Hollywood executives making superhero movies based on comic heroes when they have no idea about the medium’s integrity.

In other words, do not forget context and the human factor!

Whitney Grace, November 30, 2017

The Thing Holding AI Back Is the Thing It Needs Most, Data

November 30, 2017

Here’s an interesting problem: for artificial intelligence and machine learning to thrive, it needs a massive amount of information. However, they need so much data that it causes hiccups in the system. Google has a really interesting solution to this problem, as we learned in the Reuter’s article, “Google’s Hinton Outlines New AI Advance That Requires Less Data.”

The bundling of neurons working together to determine both whether a feature is present and its characteristics also means the system should require less data to make its predictions.


The leader of Google Brain said, “The hope is that maybe we might require less data to learn good classifiers of objects, because they have this ability of generalizing to unseen perspectives or configurations of images.

Less data for big data? It’s just crazy enough to work. In fact, some of the brightest minds in the business are trying to, as ComputerWorld said, “do less with more.” The piece focuses on Fuzzy LogiX and their attempts to do exactly what Google is hypothetically saying. It will be interesting to see what happens, but we are betting on technology cracking this nut.

Patrick Roland, November 30, 2017


Filtering: Facebook Asserts Filtering Progress

November 29, 2017

i read “Hard Questions: Are We Winning the War on Terrorism Online?” The main point is that Facebook is filtering terrorism related content. Let’s assume that the assertion is correct. Furthermore, let’s assume that private group participants are reporting terror-related content so that information not available to the general Facebook community is devoid of terror related content.

This appears to be a step forward.

My thought is that eliminating the content may squeeze those with filtered messages to seek other avenues of information dissemination. For most people, the work arounds will be unfamiliar.

But options exist, and these options are becoming more widely used and robust. I remind myself that bad actors can be every bit as intelligent, resourceful, and persistent as the professionals working at companies like Facebook.

Within the last four months, the researchers assisting me on the second edition of the Dark Web Notebook have informed me:

  1. Interest in certain old-school methods of online communication has increased; for example, text communication
  2. Encrypted apps are gaining wider use
  3. Peer-to-peer mechanisms show strong uptake by certain groups
  4. Dark Web or i2p communication methods are not perfect but some work despite the technical hassles and latency
  5. Burner phones and sim cards bought with untraceable forms of payment are widely available from retail outlets like Kroger and Walgreens in the US.

Those interested in information which is filtered remind me of underground movements in the 1960s. At the university I attended, the surface looked calm. Then bang, an event would occur. Everyone was surprised and wondered where that “problem” came from. Hiding the problem does not resolve the problem I learned by observing the event.

The surface is one thing. What happens below the surface is another. Squeezing in one place on a balloon filled with water moves the water to another place. When the pressure is too great, the balloon bursts. Water goes in unexpected places.

My view is that less well known methods of communication will attract more attention. I am not sure if this is good news or bad news. I know that filtering alone does not scrub certain content from digital channels.

Net net: Challenges lie ahead. Net neutrality may provide an additional lever, but there will be those who seek to circumvent controls. Most will fail, but some will succeed. Those successes may be difficult to anticipate, monitor, and address.

Facebook filtering is comparatively easy. Reacting to consequences of filtering may be more difficult. It has taken many years to to achieve the modest victory Facebook has announced. That reaction time, in itself, is a reminder that there is something called a Pyrrhic victory.

Stephen E Arnold, November 29, 2017

Stephen E Arnold, November

Foreign Agent Designation: Excitement for Some Folks and Some Possible Consequences, Mom

November 29, 2017

I read “In Retaliatory Move, Putin Signs Media Foreign Agents’ Law.” The write up explains:

Russian officials have said the change is a retaliatory response to the US government’s request that RT, the Russian TV network, register its American arm as a foreign agent under the Foreign Agents Registration Act (FARA).

Is FARA extensible to the families of those who work for “foreign agents”? What downstream consequences will the designation “foreign agent” have for students, academics “on loan”, and others involved with research or work for the companies so designated?

My thought: Enforcement of rules can be tight or loose, logical or illogical. The families of Russian citizens with relatives working in “foreign agent” companies may be asking similar questions.

Stephen E Arnold, November 26, 2017

Semantic Scholar Expanding with Biomedical Lit

November 29, 2017

Academic publishing is the black hole of the publishing world.  While it is a prestigious honor to have your work published by a scholar press or journal, it will not have a high circulation.  One reason that academic material is blocked behind expensive paywalls and another is that papers are not indexed well.  Tech Crunch has some good news for researchers: “Allen institute For AI’s Semantic Scholar Adds Biomedical Papers To Its AI-Sorted Corpus.”

The Allen Institute for AI started the Semantic Scholar is an effort to index scientific literature with NLP and other AI algorithms.  Semantic Scholar will now include biomedical texts in the index.  There is way too much content available for individuals to read and create indices.  AI helps catalog and create keywords for papers by scanning an entire text, pulling key themes, and adding it to the right topic.

There’s so much literature being published now, and it stretches back so far, that it’s practically impossible for a single researcher or even a team to adequately review it. What if a paper from six years ago happened to note a slight effect of a drug byproduct on norepinephrine production, but it wasn’t a main finding, or was in a journal from a different discipline?

Scientific studies are being called into question, especially when the tests are funded by corporate entities.  It is important to verify truth from false information as we consume more and more each day.  Tools like Semantic Scholar are key to uncovering the truth.  It is too bad it does not receive more attention.

Whitney Grace, November 29, 2017


Instant Messaging Security Is Becoming a Serious Issue

November 29, 2017

It might sound like a problem from twenty years ago, but the security of instant messages is a serious concern. We didn’t even know it was a thing, but once we started digging—yikes. We started this journey with the Make Use Of article, “Signal Desktop Brings Secure Messaging to Your PC.”

According to the story:

Signal, the messaging app which values privacy above all else, now has a standalone desktop app. Signal Desktop, which is available for Windows, MacOS, and Linux, replaces the Signal Chrome app. The app itself isn’t very different, but having a dedicated desktop offering is always welcome.


While most of the big messaging apps are starting to take your privacy seriously, Signal has made this its number one priority. This has made it popular with people for whom privacy is of the utmost importance, such as politicians and journalists. All of whom can now use Signal Desktop.

Sounds like Signal is hitting the desktop market just in time. A recent study found that doctors are sharing sensitive patient information via instant messaging software. Whoa. If anything should be secure, it’s that. Let’s hope they get onboard soon.

Patrick Roland, November 29, 2017

DarkCyber for 28 November 2017 Now Available

November 28, 2017

DarkCyber for November 28, 2017, covers four Dark Web stories. The first is CaaS or Crime as a Service. The report points to an Interpol reports which explains a major shift in methods for online criminals. The second item describes Terbium Labs technology. The Baltimore-based company’s Matchlight system can locate confidential information available on the Dark Web. Next, Stephen E Arnold talks about hosting providers for Dark Web sites. The examples include companies from Ukraine, Moldova, and Holland. The program concludes with a discussion of a Google Blogger service story. The Blogger post provides clear text names and ONION urls for a number of Dark Web sites which may provide access to illegal products or services. With the information on Blogger, library patrons and students can access this information from a standard Web browser.

Kenny Toth, November 28, 2017

Immersive Search: A MSFT Me Too, Me Too?

November 28, 2017

We noted “New Windows Search Interface Borrows Heavily from MacOS.” If true, the approach is little more than MSFT’s putting search results in the center of the display screen. Instead of “me too, me too”, MSFT may call this innovation “immersive search.” A great advance. Why not let me decide where to display search results?

Stephen E Arnold, November 28, 2017

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