Mondeca: Tweaking Its Market Position
February 22, 2017
One of the Beyond Search goslings noticed a repositioning of the taxonomy capabilities of Mondeca. Instead of pitching indexing, the company has embraced ElasticSearch (based on Lucene) and Solr. The idea is that if an organization is using either of these systems for search and retrieval, Mondeca can provide “augmented” indexing. The idea is that keywords are not enough. Mondeca can index the content using concepts.
Of course, the approach is semantic, permits exploration, and enables content discovery. Mondeca’s Web site describes search as “find” and explains:
Initial results are refined, annotated and easy to explore. Sorted by relevancy, important terms are highlighted: easy to decide which one are relevant. Sophisticated facet based filters. Refining results set: more like this, this one, statistical and semantic methods, more like these: graph based activation ranking. Suggestions to help refine results set: new queries based on inferred or combined tags. Related searches and queries.
This is a similar marketing move to the one that Intrafind, a German search vendor, implemented several years ago. Mondeca continues to offer its taxonomy management system. Human subject matter experts do have a role in the world of indexing. Like other taxonomy systems and services vendors, the hook is that content indexed with concepts is smart. I love it when indexing makes content intelligent.
The buzzword is used by outfits ranging from MarkLogic’s merry band of XML and XQuery professionals to the library-centric outfits like Smartlogic. Isn’t smart logic better than logic?
Stephen E Arnold, February 22, 2017
Debunking Myths About the Dark Web
February 22, 2017
What is known as the Dark Web has a fair amount of myth surrounding it, thanks to a sensationalized name and a few high-profile media stories. Tech Republic shared an article called, Four misleading myths about the Dark Web, attempting to shine light on some of the common fallacies. In summary, the Dark Web is not necessarily anonymous, it’s not very difficult to access, it’s not all nefarious activity, and there is support for businesses and organizations seeking protection from and prevention of cybertheft and security breaches. The article explains,
The biggest mistake businesses large and small can make regarding the Dark Web is to pretend it doesn’t exist. After the FBI took down the Silk Road, dozens of other niche markets took its place. With a slick interface and well organized ecommerce-like storefront, AlphaBay, one of the largest black markets on the Dark Web, makes shopping for stolen credit card data a breeze. Fortunately for companies, there’s no need to track the Dark Web alone. One technology in particular, Matchlight by Terbium Labs, helps business monitor and locate stolen Dark Web data like stolen source code, employee social security numbers, and other proprietary trade documents.
The Dark Web has become almost synonymous with Tor, the seemingly most popular way to access it. Tor has actually been used since the 1990’s by members of the intelligence community; it was developed by the US Naval Research Laboratory. While over the last decade or so, Tor has been surrounded by media coverage about drugs and crime, it will be interesting to see if the coverage shifts — or increases — because of emerging technologies such as Matchlight.
Megan Feil, February 22, 2017
Search Engine Swaps User Faces into Results
February 22, 2017
Oh, the wonders of modern technology. Now, TechCrunch informs us, “This Amazing Search Engine Automatically Face Swaps You Into Your Image Results.” Searching may never be the same. Writer Devin Coldewey introduces us to Dreambit, a search engine that automatically swaps your face into select image-search results. The write-up includes some screenshots, and the results can be a bit surreal.
The system analyzes the picture of your face and determines how to intelligently crop it to leave nothing but your face. It then searches for images matching your search term — curly hair, for example — and looks for ‘doppelganger sets, images where the subject’s face is in a similar position to your own.
A similar process is done on the target images to mask out the faces and intelligently put your own in their place — and voila! You with curly hair, again and again and again. […]
It’s not limited to hairstyles, either: put yourself in a movie, a location, a painting — as long as there’s a similarly positioned face to swap yours with, the software can do it. A few facial features, like beards, make the edges of the face difficult to find, however, so you may not be able to swap with Rasputin or Gandalf.
Behind the nifty technology is the University of Washington’s Ira Kemelmacher-Shlizerman, a researcher in computer vision, facial recognition, and augmented reality. Her work could have more sober applications, too, like automated age-progressions to help with missing-person cases. Though the software is still in beta, it is easy to foresee a wide array of uses ahead. Now, more than ever, don’t believe everything you see.
Cynthia Murrell, February 22, 2017
HonkinNews for 21 February Now Available
February 21, 2017
Hang onto your lightweight mobile. HonkinNews lets you watch recall, precision, and relevance being kicked to pieces by a real live SEO expert and famed author. We love that “famed” thing. You will also get a peek at how to visualize innovation. Inside the box and outside the box look tame compared to our view of the real world. We give you a tip for searching for an image in the Metropolitan Museum of Art’s 350,000 digital collection. You may not like the answer. We did not. If you have a mainframe in your home office, you can load Watson and let it index your significant other’s recipes, or you can process a local bank’s overnight cash transactions. Either way, IBM gives you some Watson juice. And you will get a bit of information about Yahoo’s most recent security issue. Yep, yabba dabba hoot.
Kenny Toth, February 21, 2017
IBM Watson: Mixed Signals from the Real World and IBM Marketers
February 21, 2017
I read a write up which might be fake news for all I know. I live in rural Kentucky and the doings of folks in a big city like Houston are mysterious and far away. Out local doctor squeezes in humans after dealing with race horses and dogs.
I read in Forbes, the capitalist tool, this story: “MD Anderson Benches IBM Watson In Setback For Artificial Intelligence In Medicine.”
The main idea is easy to grasp, even for folks like me sitting near the wood stove in Harrod’s Creek. As I understand it, IBM Watson was supposed to be helping the doctors at the número uno cancer treatment center in their quest to eradicate cancer. I assume the idea was to make more time available to physicians and other health care givers because IBM Watson would have had answers about patient treatment. IBM Watson knew the Jeopardy answers, right. Dealing with cancer-related questions seems to me to be easier: More narrow domain, more consistent terminology, smart people, etc etc.
The possibly fake news write up says:
The partnership between IBM and one of the world’s top cancer research institutions is falling apart. The project is on hold, MD Anderson confirms, and has been since late last year. MD Anderson is actively requesting bids from other contractors who might replace IBM in future efforts. And a scathing report from auditors at the University of Texas says the project cost MD Anderson more than $62 million and yet did not meet its goals.
But there is good news, or at least face saving news. I like this statement in the capitalist tool:
The report, however, states: “Results stated herein should not be interpreted as an opinion on the scientific basis or functional capabilities of the system in its current state.”
The door is not locked. Perhaps IBM Watson will once again be allowed to dine in the MD Anderson cafeteria and spark the pixels on the MD Anderson computing devices. Every smart software cloud may have a silver lining. Right?
But the project seems to be on “hold.” If the news is fake, then the project is full steam ahead, but I think the truth is closer to something like this: The users found the system like other smart software. Sort of helpful sometimes. At other times, the smart software was adding work, time, and frustration to an already high pressure, high stakes environment.
The capitalist tool ventures this observation:
The disclosure comes at an uncomfortable moment for IBM. Tomorrow, the company’s chief executive, Ginni Rometty, will make a presentation to a giant health information technology conference detailing the progress Watson has made in health care, and announcing the launch of new products for managing medical images and making sure hospitals deliver value for the money, as well as new partnerships with healthcare systems. The end of the MD Anderson collaboration looks bad.
I have zero idea what giant conference is held “tomorrow.” But I did notice this write up, which may be a coincidence: “IBM Sees Watson As a Primary Care Provider’s Assistant.” This seems similar to what IBM Watson was going to do at the MD Anderson cancer center. The write up asserts:
IBM is prepping Watson to work alongside primary care physicians and streamline processes. The company also added features to its Watson-based health cloud services.
The IBM Watson system has been enhanced too. The write up reports:
That Watson-primary care provider connection is being rolled out in Central New York in a six-county region and more than 2,000 providers. Meanwhile, Atrius Health, based in Massachusetts, will embed IBM’s cognitive computing tools inside its electronic medical records workflow for primary care providers.
This sounds good. Perhaps this is the “real” IBM Watson news. Rapid adoption and new capabilities make IBM Watson a must have in the smart health care providers arsenal of disease fighting weapons.
But there is that MD Anderson situation.
What do I make of these apparently contradictory write ups, which I assume are fake news, of course?
- IBM Watson, like other end user smart software systems, is a disappointment in actual use. Humans have to learn how to use the system and then take time to figure out which of the outputs are the ones that are likely to be useful in a particular patient’s case. Instead of saving time, the smart software adds tasks to already stretched professionals.
- The marketing and sales pressure is great. As a result, the marketers’ explanations may not match up with the engineering realities of a search-based system. When the marketers have left the building, the users learn the reality. After normal bureaucratic jabbering, the users’ dissatisfaction become too much for administrators to deal with. Hasta la vista, Sr. Watson.
- IBM, like other outfits betting on smart software, continue to repeat the cycle of belief, hyperbolic marketing, and learning about the costs and problems the smart system triggers. So why did Fast Search & Transfer’s run to fame fall off a cliff? Why is Hewlett Packard annoyed with Autonomy Software? Why did Entopia fail? Why is Lexmark’s new owners trying to exit the search with smart software business? Answer: Hope does not make an end user facing smart system generate sustainable revenues.
Because this IBM Watson news is fake. Why worry? Smart software will lift IBM to heights not experienced since the mainframe was the go to solution to computing needs. If you have a z series, you can run IBM Watson on it. Now that’s something I wish I could experience. My hunch is that none of the docs at MD Anderson will buy a z series and load up Watson because it is so darned useful. Maybe that is the “real” reality?
How does IBM get this Watson thing under control and generating money and producing happy customers? Let’s ask Watson? On the other hand, I don’t think the outputs will be too helpful.
Stephen E Arnold, February 21, 2017
Google Search Versus Academic Library Search
February 21, 2017
Well, Dartmouth’s library search does a killer job on topics like employee compensation, regression analysis, and the intricacies of duacetylmorphine. Google does a better job with Lady Gaga, where to buy pizza in Toledo, and learning about Google services.
I know this because I read and believed “Google Search engine vs Dartmouth Library Search.” The write up is a clarion call to the way things were. I can hear echoes of free Dialog training, the blandishments of the LexisNexis and Westlaw sales professionals, and the explanations of silver, gold, titanium, platinum, and diamond versions of Ebsco’s databases.
The write up points out:
Dartmouth Library access to thousands of articles, journals, abstracts, papers and theses from Dartmouth College, the other Ivy leagues, the other top universities, even out of the United States. So, to answer to the question, what is the difference between Google and Dartmouth Library, I would say Google is more public and is open to everybody. But, it doesn’t give us all of the actual research papers and publications.
Lousy writing aside, research libraries offer more reliable and slightly less crazed information than one finds in the Google index.
What’s frightening me is that this type of comparison is necessary.
Stephen E Arnold, February 21, 2017
Google Shoots for Star Status in the Cloud Space
February 21, 2017
Competition continues in the realm of cloud technology. Amigo Bulls released an article, Can Google Cloud Really Catch Up With The Cloud Leaders?, that highlights how Google Cloud is behind Amazon Web Services and Microsoft Azure. However, some recent wins for Google are also mentioned. One way Google is gaining steam is through new clients; they signed Spotify and even some of Apple’s iCloud services are moving to Google Cloud. The article summarizes the current state,
Alphabet Inc’s-C (NSDQ:GOOG) Google cloud has for a long time lived in relative obscurity. Google Cloud results do not even feature on the company’s quarterly earnings report the way AWS does for Amazon (NSDQ:AMZN) and Azure for Microsoft (NSDQ:MSFT). This appears somewhat ironic considering that Google owns one of the largest computer and server networks on the planet to handle tasks such as Google Search, YouTube, and Gmail. Further, the Google Cloud Platform is actually cheaper than offerings by the two market leaders.
Enterprise accounts with legacy systems will likely go for Microsoft as a no-brainer given the familiarity factor and connectivity. Considering the enterprise sector will make up a large portion of cloud customers, Amazon is probably Google’s toughest competition. Spotify apparently moved to Google from Amazon because of the quality tools, including machine-learning, and excellence in customer service. We will continue following whether Google Cloud makes it as high in the sky as its peers.
Megan Feil, February 21, 2017
Gender Bias in Voice Recognition Software
February 21, 2017
A recent study seems to confirm what some have suspected: “Research Shows Gender Bias in Google’s Voice Recognition,” reports the Daily Dot. Not that this is anything new. Writer Selena Larson reminds us that voice recognition tech has a history of understanding men better than women, from a medical tracking system to voice-operated cars. She cites a recent study by linguist researcher Rachael Tatman, who found that YouTube’s auto captions performed better on male voices than female ones by about 13 percent—no small discrepancy. (YouTube is owned by Google.)
Though no one is accusing the tech industry of purposely rendering female voices less effective, developers probably could have avoided this problem with some forethought. The article explains:
’Language varies in systematic ways depending on how you’re talking,’ Tatman said in an interview. Differences could be based on gender, dialect, and other geographic and physical attributes that factor into how our voices sound. To train speech recognition software, developers use large datasets, either recorded on their own, or provided by other linguistic researchers. And sometimes, these datasets don’t include diverse speakers.
Tatman recommends a purposeful and organized approach to remedying the situation. Larson continues:
Tatman said the best first step to address issues in voice tech bias would be to build training sets that are stratified. Equal numbers of genders, different races, socioeconomic statuses, and dialects should be included, she said.
Automated technology is developed by humans, so our human biases can seep into the software and tools we are creating to supposedly to make lives easier. But when systems fail to account for human bias, the results can be unfair and potentially harmful to groups underrepresented in the field in which these systems are built.
Indeed, that’s the way bias works most of the time—it is more often the result of neglect than of malice. To avoid it requires realizing there may be a problem in the first place, and working to avoid it from the outset. I wonder what other technologies could benefit from that understanding.
Cynthia Murrell, February 21, 2017
Be Like Cortana, Really Microsoftish
February 20, 2017
We noted “Microsoft Adds More AI Tools to Dev Cognitive Services Suite.” The battle for lock in continues. Facebook, Google, and others in the online oligopolistic club want to initiate members to their group. The best way, it seems, is to shower the developers with freebies. This is a variant of the Xalisco approach to drug distribution in the United States. Free stuff gets folks coming back for me. Well, that’s the theory.
The write up says:
Microsoft has released three artificial intelligence (AI) tools used in its Skype Translator, Bing search and Cortana speech recognition services to developers as part of a bundle of 25 tools in Microsoft Cognitive Services.
Yes, cognitive. That’s the IBM Watson word, isn’t it? The write up adds:
The collection of tools will enable developers to add features such as emotion and sentiment detection, vision and speech recognition, and language understanding to their applications, according to Microsoft, which claims that they will require “zero expertise in machine learning” to use.
How are these tools working? I would ask Tay, but I prefer a less biased type of Microsoft smart software. And Cortana? Isn’t that the intrusive thing in Windows 10. I can type, thank you.
But, hey, free is free. What’s the long term cost? Good question. Perhaps I can ask Bing? On the other hand, I could swing by H&R Block and ask Watson.
Stephen E Arnold, February 20, 2017
Pinterest Offers the Impulse Shopper a Slice of Wonderfulness
February 20, 2017
How about point-and-click impulse buying? Sound good? Pinterest has merged looking at pictures with spending money for stuff.
Navigate to “Pinterest’s New ‘Lens’ IDs Objects and Helps You Buy Them.” I know that I spend hours looking at pictures on Pinterest. When I see wedding snapshots and notice a pair of shoes to die for, I can buy them with a click… almost. My hunch is that some children may find Pinterest buying as easy as Alexa Echo and Dot buying.
I learned:
[Pinterest] announced a new feature called Lens, which will enable people to snap a picture of an item inside the Pinterest app. The app will then suggest objects it thinks are related. Think Shazam but for objects, not music. Surfacing the products will make it easier for people to take action, according to Pinterest. That could include everything from making a purchase to cooking a meal.
One of Pinterest’s wizards (Evan Sharp) allegedly said:
“Sometimes you spot something out in the world that looks interesting, but when you try to search for it online later, words fail you.” The new technology, Sharp said, “is capable of seeing the world the way you do.”
Isn’t the consumerization of no word search a life saver? Now I need a new gown to complement my size 11 triple E high heels. There’s a bourbon tasting in Harrod’s Creek next week, and I have to be a trend setter before we go squirrel hunting.
Stephen E Arnold, February 20, 2017
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