Weekly Watson: On the Road to Italy
April 9, 2016
Don’t art history majors flock to Italy? IBM Watson is not going to marvel at David or the Vatican’s collection of Roman statues.
I read “IBM Watson Takes Analytics Prowess Overseas: Supercomputer to Work on Big Data and Genomics in Italy.”
I learned:
Watson, IBM’s supercomputing brainchild, will soon have its own pied-à-terre across the pond. Big Blue announced Thursday it would launch its first Watson Health European Center of Excellence in Milan near the Human Technopole Italy 2040 research campus.
No revenue yet. The write up revealed:
IBM data scientists, engineers and programmers will collaborate with organizations across Europe to create a new class of cloud-based connected solutions to help speed research of new treatments, personalized medicine, and discoveries to boost public health management while advancing sustainable health systems.
How long will it take for Watson to cure IBM’s revenue respiratory problem? Will the Italian climate, food, and get ‘er done attitude do the job? We can, as always, ask Watson.
Stephen E Arnold, April 9, 2016
Business Analytics: April Fool or Not
April 8, 2016
I read “Business Analytics Is a Big Sham and Over Rated.” My hunch is that the write up is a bit of April fool baloney. But, maybe not?
Many vendors are changing their marketing collateral to proclaim one very special outfit can make sense out of oodles of data and textual information.
The write up makes some interesting statements; for example:
Analysts waste every one’s time. Perhaps the statement should be “often are too busy to deal with requests for their services.”
But the write up is an April Fool joke. The problem is that large organizations and government entities want a silver bullet. Who has witnessed the implosion of a massive enterprise software project?
In my experience, business analytics are becoming a must have function. The problem is that the hoo haa tossed around by vendors and pundits seems reasonably accurate.
Humor and reality are one.
Stephen E Arnold, April 8, 2016
Machine Learning: 10 Numerical Recipes
April 8, 2016
The chatter about smart is loud. I cannot hear the mixes on my Creamfields 2014 CD. Mozart, you are a goner.
If you want to cook up some smart algorithms to pick music or drive your autonomous vehicle without crashing into a passenger carrying bus, navigate to “Top 10 Machine Learning Algorithms.”
The write up points out that just like pop music, there is a top 10 list. More important in my opinion is the concomitant observation that smart software may be based on a limited number of procedures. Hey, this stuff is taught in many universities. Go with what you know maybe?
What are the top 10? The write up asserts:
- Linear regression
- Logistic regression
- Linear discriminant analysis
- Classification and regression trees
- Naive Bayes
- K nearest neighbors
- Learning vector quantization
- Support vector machines
- Bagged decision trees and random forest
- Boosting and AdaBoost.
The article tosses in a bonus too: Gradient descent.
What is interesting is that there is considerable overlap with the list I developed for my lecture on manipulating content processing using shaped or weaponized text strings. How’s that, Ms. Null?
The point is that when systems use the same basic methods, are those systems sufficiently different? If so, in what ways? How are systems using standard procedures configured? What if those configurations or “settings” are incorrect?
Exciting.
Stephen E Arnold, April 8, 2016
Microsoft Does Cognitive Too
April 8, 2016
I read “Microsoft Launches Cognitive Services Based on Project Oxford and Bing.” I immediately thought of MIcrosoft’s smart chatbot adventure. Do I doubt the efficacy of Microsoft’s smart systems? No, I just think that the same approach manifested in Tay probably exists in the suite of APIs announced on March 30, 2016.
I learned:
The brand name Cognitive Services is a nod to IBM’s Watson, which for the past few years has been marketed as a “cognitive computing” product — that is, one that’s based on the way the human brain works.
That is working out very well for IBM. There is a recipe book and many projects. Revenues? Well, sure. Some.
Microsoft offers a search API. That, one hopes, will actually work reasonably well. Microsoft’s track record in the information access department has been interesting.
According to this Microsoft page, there are give search APIs which are available for preview. Use is like a taxi ride, and that type of metered pricing is often unsettling.
The five APIs are:
- Bing Autosuggest
- Bing Image Search
- Bing News Search
- Bing Video Search
- Bing Web Search.
I assume one can mix in academic knowledge, entity linking, and knowledge exploration. In addition, it appears thate is a language understanding intelligent service called Luis. I noted linguistic analysis as an API as well. And for good measure, one can tap text analytics.
For a developer, these Lego blocks offer an opportunity to code up a solution.
On the other hand, there are goodies from outfits from Baidu to Facebook, from Google to X.ai from which to choose.
Just as IBM is saddled with the Jeopardy and recipe book, Microsoft is going to have to live with Tay’s capabilities.
What happens if Tay works into a routine search query? That will be intriguing. Perhaps Tay and Watson can get together and do smart thing?
Stephen E Arnold, April 8, 2016
Cybercriminal Talent Recruitment Moves Swiftly on the Dark Web
April 8, 2016
No matter the industry, it’s tough to recruit and keep talent. As the Skills shortage hits hackers published by Infosecurity Magazine reports, cybercriminals are no exception. Research conducted by Digital Shadows shows an application process exists not entirely dissimilar from that of tradition careers. The jobs include malware writers, exploit developers, and botnet operators. The article explains how Dark Web talent is recruited,
“This includes job ads on forums or boards, and weeding out people with no legitimate technical skills. The research found that the recruitment process often requires strong due diligence to ensure that the proper candidates come through the process. Speaking to Infosecurity, Digital
Shadows’ Vice President of Strategy Rick Holland said that in the untrusted environment of the attacker, reputation is as significant as in the online world and if someone does a bad job, then script kiddies and those who have inflated their abilities will be called out.”
One key difference cited is the hiring timeline; the Dark Web moves quickly. As you might imagine, apparently only a short window of opportunity to cash in stolen credit cards. The sense of urgency related to many Dark Web activities suggests speedier cybersecurity solutions are on the scene. As cybercrime-as-a-service expands, criminals’ efforts and attacks will only be swifter.
Megan Feil, April 8, 2016
Sponsored by ArnoldIT.com, publisher of the CyberOSINT monograph
UK Cybersecurity Director Outlines Agencys Failures in Ongoing Cyberwar
April 8, 2016
The article titled GCHQ: Spy Chief Admits UK Agency Losing Cyberwar Despite £860M Funding Boost on International Business Times examines the surprisingly frank confession made by Alex Dewdney, a director at the Government Communications Headquarters (GCHQ). He stated that in spite of the £860M funneled into cybersecurity over the past five years, the UK is unequivocally losing the fight. The article details,
“To fight the growing threat from cybercriminals chancellor George Osborne recently confirmed that, in the next funding round, spending will rocket to more than £3.2bn. To highlight the scale of the problem now faced by GCHQ, Osborne claimed the agency was now actively monitoring “cyber threats from high-end adversaries” against 450 companies across the UK aerospace, defence, energy, water, finance, transport and telecoms sectors.”
The article makes it clear that search and other tools are not getting the job done. But a major part of the problem is resource allocation and petty bureaucratic behavior. The money being poured into cybersecurity is not going towards updating the “legacy” computer systems still in place within GCHQ, although those outdated systems represent major vulnerabilities. Dewdney argues that without basic steps like migrating to an improved, current software, the agency has no hope of successfully mitigating the security risks.
Chelsea Kerwin, April 8, 2016
Sponsored by ArnoldIT.com, publisher of the CyberOSINT monograph
Watson in the Lab: Quoth the Stakeholder Forevermore
April 7, 2016
I read “Lawrence Livermore and IBM Collaborate to Build New Brain-Inspired Supercomputer.” The article reports that one of the US national labs and Big Blue are going to work together to do something with IBM’s neurosynaptic computer chip. I know. I know. IBM is not really into making chips anymore. I think it paid another company lots of money to take the fab business off IBM’s big blue hands.
Never mind, quoth the stakeholder.
The write up reports that the True North “platform”
will process the equivalent of 16 million neurons and 4 billion synapses and consume the energy equivalent of a hearing aid battery – a mere 2.5 watts of power.
I like the reference to nuclear weapons in the article. I used to work at Halliburton Nuclear in my salad days, and there are lots of calculations to perform when doing the nuclear stuff. Calculations are, in my experience, a lot better than doing lab experiments the Marie Curie muddled forward. Big computer capability is a useful capability.
According to the write up:
The [neuromorphic] technology represents a fundamental departure from computer design that has been prevalent for the past 70 years, and could be a powerful complement in the development of next-generation supercomputers able to perform at exascale speeds, 50 times (or two orders of magnitude) faster than today’s most advanced petaflop (quadrillion floating point operations per second) systems. Like the human brain, neurosynaptic systems require significantly less electrical power and volume.
This is not exactly a free ride. The write up points out:
Under terms of the $1 million contract, LLNL will receive a 16-chip TrueNorth system representing a total of 16 million neurons and 4 billion synapses. LLNL also will receive an end-to-end ecosystem to create and program energy-efficient machines that mimic the brain’s abilities for perception, action and cognition. The ecosystem consists of a simulator; a programming language; an integrated programming environment; a library of algorithms as well as applications; firmware; tools for composing neural networks for deep learning; a teaching curriculum; and cloud enablement.
One question: Who is paying whom? Is Livermore ponying up $1 million to get its informed hands on the “platform” or is IBM paying Livermore to take the chip and do a demonstration project.
The ambiguity in the write up is delicious. Another minor point is the cost of the support environment for the new platform. I understand the modest power draw, but perhaps there are other bits and pieces which gobble the Watts.
I recall a visit to Bell Labs.* During that visit, I saw a demo of what was then called holographic memory. The idea was that gizmos allowed data to be written to a holographic structure. The memory device was in a temperature controlled room and sat in a glass protected container. The room was mostly empty. After the demo, I asked one of the Bell wizards about the tidiness of the demo. He laughed and took me to a side door. Behind that door was a room filled with massive amounts of equipment. The point was that the demo looked sleek and lean. The gear required to pull off the demo was huge.
I recall that the scientist said, “The holographic part was easy. Making the system small is the challenge.”
Perhaps the neuromorphic chip has similar support equipment requirements.
I will let you know if I find out who is paying for the collaboration. I just love IBM. Watson, do you know who is paying for the collaboration?
——
* Bell Labs was one of the companies behind my ASIS Eagleton Award in the 1980s.
Stephen E Arnold, April 7, 2016
Google Dismisses Sky Net. Bummer.
April 7, 2016
I was looking forward to running through the hollows of Kentucky in order to avoid killer machines.
After reading “Google’s Schmidt Says Computers Not a Threat to Humans of Jobs,” I have a very different future to ponder. I am confident that Google’s senior managers can predict or perhaps “shape” the future.
I learned from the write up:
You know those movies where the machines take over and the human race gets enslaved by computers? Pure applesauce, says Eric Schmidt, chairman of Google’s parent company, Alphabet.
Hey, good news. And the source is certainly not going to predict something that may not work out. Forget the Orkut thing and the Boston Dynamics’ adventure, please. I suggested that the local day care center lease a couple of Google’s robotic dogs for the little children to love and enjoy.
I also learned:
Fears about computers run amok are the stuff of movies, he argued, and that the technology serves to help people not hurt them — including when it comes to things like income and employment. “I worry about inequality but there’s no evidence the stuff we do creates a permanent underclass,” said Schmidt…
I love it when my search results do not reflect what I put in quotes. Quotes are or were the way to tell the GOOG that I wanted an exact match. Same with using Google Maps to find a restaurant in Washington, DC in front of which I am standing. Google did not “know” about the eatery.
My fears? Unfounded. I believe everything Google presents to me. Don’t you?
Stephen E Arnold, April 7, 2016
Google Hummingbird Revealed by a Person Not Working for Google
April 7, 2016
Another wizard has scrutinized the Google and figured out how to make sure your site becomes number one with a bullet.
To get the wisdom, navigate to “Hummingbird – Mastering the art of Conversational Search.” The problem for the GOOG is that it costs a lot of money to index Web sites no one visits. Advertisers want traffic. That means the GOOG has to find a way to reduce costs and sell either more ads or fewer ads at a higher price.
The write up pays scant attention to the realities of the Google. But you will learn the tips necessary to work traffic magic. Okay, I don’t get too excited about info about Google from folks who are not working at the company or who have worked at the company. Sorry. Looking at the Google and reading tea leaves does not work for me.
But what works, according to the write up, are these sure fire tips. Here we go:
- Bone up on latent semantic indexing. Let’s see. That method has been around for 30, maybe 40 years. Get a move on, gentle reader.
- Make your Web site mobile friendly. Unfortunately mobile Web sites don’t get more traffic than a regular Web site which does not get much traffic. Sorry. The majority of clicks flow to a small percentage of the accessible Web sites.
- Forget the keyword thing. Well, I usually use words to write my articles and Web sites. I worry about focusing on a small number of topics and using the words necessary to get my point across. Keywords, in my opinion, are derivatives of information. Forgetting keywords is easy. I never used them before.
- Make your write ups accurate. Okay, that’s a start. What does one do with “real” news from certain sources. The info is baloney, but everyone pretends it is accurate. What’s up with that? The accuracy angle is part of Google’s scoring methods. Each has to deal with what’s correct in his or her own way. Footnotes and links are helpful. What happens when someone disagrees. Is this “accurate”? Oh, well.
- “Be bold and broad.” In my experience, not much content is bold and broad.
Now you understand Google Hummingbird. Will your mobile Web site generate hundreds of thousands of uniques if you adhere to this road map? Nah. Why not follow Google’s guidelines from the Google itself?
Stephen E Arnold, April 7, 2016
The Missing Twitter Manual Located
April 7, 2016
Once more we turn to the Fuzzy Notepad’s advice and their Pokémon mascot, Evee. This time we visited the fuzz pad for tips on Twitter. The 140-character social media platform has a slew of hidden features that do not have a button on the user interface. Check out “Twitter’s Missing Manual” to read more about these tricks.
It is inconceivable for every feature to have a shortcut on the user interface. Twitter relies on its users to understand basic features, while the experienced user will have picked up tricks that only come with experience or reading tips on the Internet. The problem is:
“The hard part is striking a balance. On one end of the spectrum you have tools like Notepad, where the only easter egg is that pressing F5 inserts the current time. On the other end you have tools like vim, which consist exclusively of easter eggs.
One of Twitter’s problems is that it’s tilted a little too far towards the vim end of the scale. It looks like a dead-simple service, but those humble 140 characters have been crammed full of features over the years, and the ways they interact aren’t always obvious. There are rules, and the rules generally make sense once you know them, but it’s also really easy to overlook them.”
Twitter is a great social media platform, but a headache to use because it never came with an owner’s manual. Fuzzy notepad has lined up hint for every conceivable problem, including the elusive advanced search page.
Whitney Grace, April 7, 2016
Sponsored by ArnoldIT.com, publisher of the CyberOSINT monograph
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