Proprietary Software Cheats Users

November 16, 2017

Cory Doctorow is an outspoken defender of net neutrality, technology education, and user rights.  He has written and spoken about these subjects and shares his opinion on BoingBoing.  The science-fiction magazine Locus recently published one of his new essays,“Cory Doctorow: Demon-Haunted World.”  Doctorow discusses how software can be programmed to take out the human factor of like and steer things in favor of corporations who want to gobble down dollars.

Cheating is a well-established enterprise that originated long before the digital revolution, but it is getting smarter as technology advances.  While in the past it was cheating was more of a danger from outside forces, it is now nestled within the very things we own.

The software allows companies and literally anyone with the know how to cheat you out of money or precious time.  Rather than cheat en masse, the cheating is coming to your home because it is so much easier to infiltrate the individual now.  Even scarier is when he uses an alchemy metaphor, explaining how alchemists were cut-rate lab technicians who believed spirits, God, and demons influenced their experiments.  The technology used for cheating has a similar demonic presence and that is not even the worst factor.

Doctorow pulls out his trump card when he explains how outdated technology laws from the 20th century still had standing today when it is more than obvious they need to be repealed:

What’s worse, 20th-century law puts its thumb on the scales for these 21st-century demons. The Computer Fraud and Abuse Act (1986) makes it a crime, with jail-time, to violate a company’s terms of service. Logging into a website under a fake ID to see if it behaves differently depending on who it is talking to is thus a potential felony, provided that doing so is banned in the small-print clickthrough agreement when you sign up.

 

Then there’s section 1201 of the Digital Millen­nium Copyright Act (1998), which makes it a felony to bypass the software controls access to a copy­righted work. Since all software is copyrightable, and since every smart gadget contains software, this allows manufacturers to threaten jail-terms for anyone who modifies their tractors to accept third-party carburetors (just add a software-based check to ensure that the part came from John Deere and not a rival), or changes their phone to accept an independent app store, or downloads some code to let them choose generic insulin for their implanted insulin pump.

Follow Doctorow’s advice, read, test, learn, and just combat ignorance.

Whitney Grace, November 16, 2017

Elsevier Makes a Brave Play to Steal Wikipedias Users

October 9, 2017

Is Wikipedia about to be unseated in the world of academic publishing? Elsevier thinks they can give the crowdsourced, yet flawed, info hub a serious run for its money. Money, being the key word, according to a recent TechDirt article, “Elsevier Launching Rival to Wikipedia by Extracting Scientific Definitions Automatically from Author’s Texts.”

According to the piece:

Elsevier is hoping to keep researchers on its platform with the launch of a free layer of content called ScienceDirect Topics, offering an initial 80,000 pages of material relating to the life sciences, biomedical sciences and neuroscience. Each offers a quick definition of a key term or topic, details of related terms and relevant excerpts from Elsevier books.

Seems like it makes sense, right? Elsevier has all this academic information at their fingertips, so why send users elsewhere on the web for other information. This extraction system, frankly, sounds pretty amazing. However, TechDirt has a beef with it.

It’s typical of Elsevier’s unbridled ambition that instead of supporting a digital commons like Wikipedia, it wants to compete with it by creating its own redundant versions of the same information, which are proprietary. Even worse, it is drawing that information from books written by academics who have given Elsevier a license.

It’s a valid argument, whether or not Elsevier is taking advantage of its academic sources by edging into Wikipedia’s territory. However, we have a hunch their lawyers will make sure everything is on the up and up. A bigger question is whether Elsevier will make this a free site or have a paywall. They are in business to make money, so we’d guess paywall. And if that’s the case, they’d better have a spectacular setup to draw customers from Wikipedia.

Patrick Roland, October 9, 2017

Trust the Search Black Box and Only the Black Box

September 21, 2017

This article reads like an infomercial for a kitchen appliance.  It asks the same, old question, “How much time do you waste searching for relevant content?”  Then it leads into a pitch for Microsoft and some other companies.  BA Insights wrote, “The Increasingly Intelligence Search Experience” to be an original article, but frankly it sounds like every spiel to sell a new search algorithm.

After the “hook,” the article runs down the history of Microsoft and faceted search along with refiners and how it was so revolutionary at the time.  Do not get me wrong, this was a revolution move, but it sounds like Microsoft invented the entire tool rather than just using it as a strategy.  There is also a brief mention on faceted navigation, then they throw “intelligence search” at us:

Microsoft’s definition of “intelligence” may still be vague, but it’s clear that the company believes its work in machine-learning, when combined with its cloud platform, can give it a leg up over its competitors. The Microsoft Graph and these new intelligent machine-learning capabilities provide personalized insights based on a user’s personal network, project assignments, meeting schedule, and other search and collaboration activities. These features make it possible not only to search using traditional methods and take action based on those results, but for the tools and systems to proactively provide intelligent, personalized, and timely information before you ask for it – based on your profile, permissions, and activity history.

Oh!  Microsoft is so smart that they have come up with something brand new that companies which specialize in search have never thought of before.  Come on, how many times have we seen and read claims like this before?  Microsoft is doing revolutionary things, but not so much in the field of search technology.  They have contributed to its improvement over the years, but if this was such a revolutionary piece of black box software why has not anyone else picked it up?

Little black box software has their uses, but mostly for enterprise and closed systems-not the bigger Web.

Whitney Grace, September 21, 2015

Natural Language Processing for Facebook Messenger

September 15, 2017

In its continuing effort to evolve from a basic networking site to a platform for services, Facebook is making Messenger smarter. Silicon reports, “Facebook Bakes Natural Language Processing Messenger Platform 2.1.” The inclusion allows developers to create more functionality for organizations that wish to conduct chatbot-based business through Facebook Messenger itself, without having to utilize another site or app. Reporter Roland Moore-Colyer quotes Facebook’s Vivien Tong as he writes:

‘This first version can detect the following entities [within users’ messages]: hello, bye, thanks, date & time, location, amount of money, phone number, email and a URL. This is the first step in bringing NLP capabilities to all developers, enabling brands to scale their experiences on Messenger.’

The natural language processing capabilities come courtesy of Wit.aim a company Facebook acquired backing in 2015; its services have been available to developers for some time, but were not made native to the Messenger Platform until its latest iteration. Alongside in-built natural language processing, the overhauled Messenger Platform contains software development kits for developers to easily integrate payment services into Messenger and make it easier for to switch customer conversations from automated chatbots to human customer services.

Ah, yes, payment services are crucial, and being able to reach a real person is a sanity-saver (and a client-keeper.) Moore-Colyer notes this development is one in a series of advances for Messenger, and that Facebook’s embrace of smart tech extends to fighting terrorism within its platform.

Cynthia Murrell, September 15, 2017

A Brilliant List of Open Source Localization Tools

August 24, 2017

Open source projects over technology developers the ability to access technology usually locked behind pay walls.  One trouble with open source technology is language translation and the ability for developers to localize their projects.  Language continues to remain a barrier in our technology driven world, but there are tools to overcome it.  OpenSource.com curated a list of, “18 Open Source Translation Tools To Localize Your Project.”

The curator understands the pains of proprietary software:

The proprietary versions of these tools can be quite expensive. A single license for SDL Trados Studio (the leading CAT tool) can cost thousands of euros, and even then it is only useful for one individual and the customizations are limited (and psst, they cost more, too). Open source projects looking to localize into many languages and streamline their localization processes will want to look at open source tools to save money and get the flexibility they need with customization.

The list includes tools for machine translation, which is a hot commodity.  Software that can generate a digestible and accurate translation from one language to another is a must have for many localization projects.  The list recommends checking out Apertium and Moses.  Computer-assisted translation tools are a must have for all translations and language students, because they can save hours of looking up information in dead tree lexicons.  They also work in real time, saving more countless hours, so you should check out OmegaT, Subtitles Translator, and Anaphraseus.  If you are working with multiple translators on your project you will need to utilize a translation management system to organize everyone-think SharePoint.  Jabylon, Zanata, GlobalSight, and Pootle are some good TMS software to check out.  Also included are localization automation tools that can ease your work burden, such as Okapi Framework and Mojito.

Whitney Grace, August 24, 2017

Time to Ditch PowerPoint?

August 23, 2017

For decades, Microsoft PowerPoint has been used for making presentations. That is all set to change as a recent study indicates that PowerPoint presentations are ineffective.

According to an article published by Quartz and titled The Scientific Reason No One Wants to See Your PowerPoint Presentation, the publisher says:

Because the human brain process information both visually (using shapes and colors) and spatially (using location and distance, the researchers said, ZUI helps audiences by locating the information in a place, allowing them to mentally retrieve it later.

The problem with the study is that it appears to be too promotional. For instance, the article says tools like Prezi are better for making presentations because it offers a lot of animated options. Why not then use Gifographics or stock videos then?

The effectiveness of a presentation mostly depends on the person presenting it. Many speakers completely do away with any type of tools so that their audience can concentrate on what the speaker says. Moreover, the presentation can be made effective if the slides are designed professionally. Don’t be surprised if, in the near future, all presentations are made using VR headsets for that truly immersive experience.

Vishal Ingole, August 23, 2017

Software That Detects Sarcasm on Social Media

July 20, 2017

Technion-Israel Institute of Technology Faculty of Industrial Engineering and Management has developed Sarcasm SIGN, a software that can detect sarcasm in social media content. People with learning difficulties will find this tool useful.

According to an article published by Digital Journal titled Software Detects Sarcasm on Social Media:

The primary aim is to interpret sarcastic statements made on social media, be they Facebook comments, tweets or some other form of digital communication.

As we move towards a more digitized world where the majority of our communications are through digital channels, people with learning disabilities are at the receiving end. As machine learning advances so do the natural language capabilities. Tools like these will be immensely helpful for people who are unable to understand the undertones of communication.

The same tool can also be utilized by brands for determining who is talking about them in a negative way. Now ain’t that wonderful Facebook?

Vishal Ingole, July 20, 2017

Elastic Stack Offers Machine Learning Functionality on the Side

June 1, 2017

Elastic, the company behind the Elasticsearch stack, has announced the release of a commercial add-on available via X-Pack. The product will detect unusual changes or anomalies in Elasticsearch’s real-time data results.

Elastic is not overpromising the features of the add-on – a fact that is praised by Infoworld in Elasticsearch Stack Wises Up with Machine Learning:

One possible issue is that non-open-source machine learning applications can look more impressive than they actually are. Elastic is avoiding that (for now) by confining the promise of the new features to specific, well-defined goals. It’s also likely to be even more powerful when a full non-beta version is available at the scale provided by cloud partners like Google.

Elastic, based on Lucene, has emerged as the go-to choice for enterprise search. A free and open source version of the software is available at https://www.elastic.co/downloads/elasticsearch. By keeping its goals realistic, is Elastic poised to not only be in the race for the long haul, but win the search gold medal?

Mary Pattengill, June 1, 2017

SirionLabs Plants New United States Headquarters in California

April 27, 2017

The article on TechCrunch titled SirionLabs Establishes US Foothold to Scale Its NLP Contract Management Software frames the rapid growth and expansion of the enterprise vendor management software provider founded in 2012. SirionLabs was founded by CEO Ajay Agrawal, who recognized the large cost of supplier relationship management built into a contract’s value and decided to start a company focused on automating the process, but only partially. The article explains,

The establishment of a U.S. presence represents a strategic shift in the company’s growth plans…While the startup has had offices in the U.K., Germany, Denmark and Singapore, it has been slow to establish a permanent U.S. team…Sirion, the company’s platform, is currently used by companies like BP and Vestas to manage service providers and augment humans that traditionally manage vendor relationships. The startup expects to use natural language processing to analyze more than $8 billion in total contract value over the next year.

In order to mitigate the risk of the enormous number of potential discrepancies in a given contract, Sirion compels both parties to be accountable by agreeing on the outcome. That addendum hasn’t scared off BP, or Seal Software clients such as Deloitte, HP, Experian, and SalesForce.

Chelsea Kerwin, April 27, 2017

Voice Recognition Software Has Huge Market Reach

March 3, 2017

Voice recognition software still feels like a futuristic technology, despite its prevalence in our everyday lives.  WhaTech explains how far voice recognition technology has imbedded itself into our habits in, “Listening To The Voice Recognition Market.”

The biggest example of speech recognition technology is an automated phone system.  Automated phone systems are used all over the board, especially in banks, retail chains, restaurants, and office phone directories.  People usually despise automated phone systems, because they cannot understand responses and tend to put people on hold for extended periods of time.

Despite how much we hate automated phone systems, they are useful and they have gotten better in understanding human speech and the industry applications are endless:

The Global Voice Recognition Systems Sales Market 2017report by Big Market Research is a comprehensive study of the global voice recognition market. It covers both current and future prospect scenarios, revealing the market’s expected growth rate based on historical data. For products, the report reveals the market’s sales volume, revenue, product price, market share and growth rate, each of which is segmented by artificial intelligence systems and non-artificial intelligence systems. For end-user applications, the report reveals the status for major applications, sales volume, market share and growth rate for each application, with common applications including healthcare, military and aerospace, communications, and automotive.

Key players in the voice recognition software field are Validsoft, Sensory, Biotrust ID, Voicevault, Voicebox Technologies, Lumenvox, M2SYS, Advanced Voice Recognition Systems, and Mmodal.  These companies would benefit from using Bitext’s linguistic-based analytics platform to enhance their technology’s language learning skills.

Whitney Grace, May 3, 2017

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