DuckDuckGo Makes Search Enhancements by Leveraging Yahoo Partnership
December 13, 2016
The article on Duck.co titled New Features from a Stronger Yahoo Partnership relates the continuation of the relationship between DuckDuckGo and Yahoo. DuckDuckGo has gained fame for its unique privacy policy of not tracking its users, which of course flies in the face of the Google Goliath, which is built on learning about its users by monitoring their habits and improving the search engine using that data. Instead, DuckDuckGo insists on forgetting its users and letting them search without fear of it being recorded somewhere. The article conveys some of the ways that Yahoo is mingled with the David of search engines,
In addition to the existing technology we’ve been using, DuckDuckGo now has access to features you’ve been requesting for years: Date filters let you filter results from the last day, week and month. Site links help you quickly get to subsections of sites. Of course our privacy policy remains the same: we don’t track you. In addition, we’re happy to announce that Yahoo has published a privacy statement to the same effect.
Paranoid internet users and people with weird secretive fetishes alike, rejoice! DuckDuckGo will soon be vastly improved. The article does not state an exact date for this new functionality to be revealed, but it is coming soon.
Chelsea Kerwin, December 13, 2016
How Big a Hurdle Is Encryption Really?
December 12, 2016
At first blush, the recent Wiretap Report 2015 from United States Courts would seem to contradict law enforcement’s constant refrain that encryption is making their jobs difficult. Motherboard declares, “Feds and Cops Encountered Encryption in Only 13 Wiretaps in 2015.” This small number is down from 2014. Isn’t this evidence that law enforcement agencies are exaggerating their troubles? The picture is not quite so simple. Reporter Lorenzo Franceschi-Bicchierai writes:
Both FBI director James Comey, as well as Deputy Attorney General Sally Yates, argued last year that the Wiretap Report is not a good indicator. Yates said that the Wiretap Report only reflects number of interception requests ‘that are sought’ and not those where an investigator doesn’t even bother asking for a wiretap ‘because the provider has asserted that an intercept solution does not exist.
Obtaining a wiretap order in criminal investigations is extremely resource-intensive as it requires a huge investment in agent and attorney time,’ Yates wrote, answering questions from the chairman of the Senate’s Judiciary Committee, Sen. Chuck Grassley (R-IA). ‘It is not prudent for agents and prosecutors to devote resources to this task if they know in advance that the targeted communications cannot be intercepted.
That’s why Comey promised the agency is working on improving data collection ‘to better explain’ the problem with encryption when data is in motion. It’s unclear then these new, improved numbers will come out.
Of course, to what degree encryption actually hampers law enforcement is only one piece of a complex issue—whether we should mandate that law enforcement be granted “back doors” to every device they’d like to examine. There are the crucial civil rights concerns, and the very real possibility that where law enforcement can get in, so too can hackers. It is a factor, though, that we must examine objectively. Perhaps when we get that “better” data from the FBI, the picture will be more clear.
Cynthia Murrell, December 12, 2016
GE Now Manufactures Artificial Intelligence
December 9, 2016
GE (General Electric) makes appliances, such as ovens, ranges, microwaves, washers, dryers, and refrigerators. Once you get them out of the appliance market, their expertise appears to end. Fast Company tells us that GE wants to branch out into new markets and the story is in, “GE Wants To Be The Next Artificial Intelligence Powerhouse .”
GE is a multi-billion dollar company and they have the resources to invest in the burgeoning artificial intelligence market. They plan to employ two new acquisitions and bring machine learning to the markets they already dominate. GE first used machine learning in 2015 with Predix Cloud, which recorded industrial machinery sensor patterns. It was, however, more of a custom design for GE than one with a universal application.
GE purchased Bit Stew Systems, a company similar to the Predix Cloud except that collected industrial data, and Wise.io, a company that used astronomy-based technology to streamline customer support systems. Predix already has a string of customers and has seen much growth:
Though young, Predix is growing fast, with 270 partner companies using the platform, according to GE, which expects revenue on software and services to grow over 25% this year, to more than $7 billion. Ruh calls Predix a “significant part” of that extra money. And he’s ready to brag, taking a jab at IBM Watson for being a “general-purpose” machine-learning provider without the deep knowledge of the industries it serves. “We have domain algorithms, on machine learning, that’ll know what a power plant is and all the depth of that, that a general-purpose machine learning will never really understand,” he says.
GE is tackling issues in healthcare and energy issues with Predix. GE is proving it can do more than make a device that can heat up a waffle. The company can affect the energy, metal, plastic, and computer system used to heat the waffle. It is exactly like how mason jars created tools that will be used in space.
Whitney Grace, December 9, 2016
Zo Tay! Piz Daint. Microsoft Talks Quantum But Goes Cray
December 8, 2016
There’s a new Microsoft chatbot coming. Microsoft wants to deploy smarter, less racist chatbots I assume. To achieve that goal, Microsoft talks quantum computing and qubits (not Quberts). However, when it comes to crunching data, Microsoft is embracing the ever popular and somewhat iconic Cray outfit.
Navigate to “Microsoft Goes Cray for Deep Learning on Supercomputers.” The write up informed me that:
The deep learning process could be about to change dramatically thanks to work being carried out Cray, Microsoft and the Swiss National Supercomputing Centre. In existing architectures and conventional systems, deep learning requires a slow training process that can take months, something that can lead to significantly higher costs and delays in making scientific discoveries. Cray believes that its work with Microsoft and CSSC could have solved this problem by applying supercomputing architectures to accelerate the training process.
The name of my servers are derived from dogs owned by my friends. Yes, there was an Oreo and a Biscuit.
But what is the name of the pricey, complex, and semi fast Cray supercomputer?
Give up? Here’s a clue: “A prominent peak in Grisons that overlooks the Fuorn pass.”
Need more time?
Give up?
Okay.
The answer is…
Piz Daint
There you go. Tay, Zo, and Piz Daint. Outstanding.
The write up told me:
According to the supercomputer manufacturer, deep learning problems share algorithmic similarities with applications that are traditionally run on a massively parallel supercomputer. So by optimizing inter-node communication using the Cray XC Aries network and a high performance MPI library, each training job is said to be able to leverage more compute resources and therefore reduce the amount of time required to train them.
I too believe everything computer assemblers tell me. I recall a demonstration online system which boasted fancy Dan machines from Sun Microsystems. The high powered, expensive hardware could support four—yep, four—simultaneous users. Another example is the system designed to search video news which boasted a five minute response time. Flashy hardware. Software seemed to be the problem. And Microsoft rarely distributes software which does not work as advertised. I wish I knew how to get that Word numbering system to work. Oh, well.
Keep in mind that Cray is providing some Microsoft hardware with its machines. Plus, Cray is based in Seattle. Microsoft’s and Cray’s partner in the test is the Swiss National Supercomputing Centre (CSCS). I like Switzerland, and I assume there will be some meetings there. The Swiss also enjoy US holiday shopping. I assume there will be or have been some visits by Swiss wizards to Seattle. I am not sure how many meetings will be scheduled in Chippewa Falls, Wisconsin, however. I thought Cray was owned by Tera Computer. I did a quick check on the financial health of the Cray outfit. I concluded that the tie up will definitely be a plus for the Cray folks. By the way, Cray was founded in 1972.
Stephen E Arnold, December 8, 2016
Cray
The One Percent Have Privately Disappeared
December 8, 2016
People like to think that their lives are not always monitored, especially inside their domiciles. However, if you have installed any type of security camera, especially a baby monitor, the bad news is that they are easily hacked. Malware can also be downloaded onto a computer to spy on you through the built-in camera. Mark Zuckerberg coves his laptop’s camera with a piece of electrical tape. With all the conveniences to spy on the average individual, it is not surprising that the rich one percent are literally buying their privacy by disappearing. FT.com takes a look about, “How The Super-Rich Are Making Their Homes ‘Invisible.’”
The article opens with a description about how an entire high-end California neighborhood exists, but it is digitally “invisible” on Google Street View. Celebrities live in this affluent California neighborhood and the management company does not even give interviews. Privacy is one of the greatest luxuries one can buy in this age and the demand will grow as mobile Internet usages increases. The use of cameras is proportional to Internet usage.
People who buy privacy by hiding their homes want to avoid prying eyes, such a paparazzi and protect themselves from burglars. The same type of people who buy privacy are also being discreet about their wealth. They do not flaunt it, unlike previous eras. In the business sector, more and more clients want to remain anonymous so corporations are creating shell businesses to protect their identities.
There is an entire market for home designs that hide the actual building from prying eyes. The ultimate way to disappear, however, is to live off the grid:
For extra stealth, property owners can take their homes off the grid — generating their own electricity and water supply avoids tell-tale pipes and wires heading on to their land. Self-sufficient communities have become increasingly popular for privacy, as well as ecological, reasons; some estimates suggest that 180,000 households are living off the grid in the US alone.
Those people who live off the grid will also survive during a zombie apocalypse, but I digress.
It is understandable that celebrities and others in the public eye require more privacy than the average citizen, but we all deserve the same privacy rights. But it brings up another question: information needs to be found in order to be used. Why should some be able to disappear while others cannot?
Whitney Grace, December 8, 2016
Google Search Results Are Politically Biased
December 7, 2016
Google search results are supposed to be objective and accurate. The key phrase in the last sentence was objective, but studies have proven that algorithms can be just as biased as the humans who design them. One would think that Google, one of the most popular search engines in the world, who have discovered how to program objective algorithms, but according to the International Business Times, “Google Search Results Tend To Have Liberal Bias That Could Influence Public Opinion.”
Did you ever hear Uncle Ben’s advice to Spider-Man, “With great power comes great responsibility.” This advice rings true for big corporations, such as Google, that influence the public opinion. CanIRank.com conducted a study the discovered searches using political terms displayed more pages with a liberal than a conservative view. What does Google have to say about it?
The Alphabet-owned company has denied any bias and told the Wall Street Journal: ‘From the beginning, our approach to search has been to provide the most relevant answers and results to our users, and it would undermine people’s trust in our results, and our company, if we were to change course.’ The company maintains that its search results are based on algorithms using hundreds of factors which reflect the content and information available on the Internet. Google has never made its algorithm for determining search results completely public even though over the years researchers have tried to put their reasoning to it.
This is not the first time Google has been accused of a liberal bias in its search results. The consensus is that the liberal leanings are unintentional and is an actual reflection of the amount of liberal content on the Web.
What is the truth? Only the Google gods know.
Whitney Grace, December 7, 2016
IBM Thinks Big on Data Unification
December 7, 2016
So far, the big data phenomenon has underwhelmed. We have developed several good ways to collect, store, and analyze data. However, those several ways have resulted in separate, individually developed systems that do not play well together. IBM hopes to fix that, we learn from “IBM Announces a Universal Platform for Data Science” at Forbes. They call the project the Data Science Experience. Writer Greg Satell explains:
Consider a typical retail enterprise, which has separate operations for purchasing, point-of-sale, inventory, marketing and other functions. All of these are continually generating and storing data as they interact with the real world in real time. Ideally, these systems would be tightly integrated, so that data generated in one area could influence decisions in another.
The reality, unfortunately, is that things rarely work together so seamlessly. Each of these systems stores information differently, which makes it very difficult to get full value from data. To understand how, for example, a marketing campaign is affecting traffic on the web site and in the stores, you often need to pull it out of separate systems and load it into excel sheets.
That, essentially, has been what’s been holding data science back. We have the tools to analyze mountains of data and derive amazing insights in real time. New advanced cognitive systems, like Watson, can then take that data, learn from it and help guide our actions. But for all that to work, the information has to be accessible.”
The article acknowledges that progress that has been made in this area, citing the open-source Hadoop and its OS, Spark, for their ability to tap into clusters of data around the world and analyze that data as a single set. Incompatible systems, however, still vex many organizations.
The article closes with an interesting observation—that many business people’s mindsets are stuck in the past. Planning far ahead is considered prudent, as is taking ample time to make any big decision. Technology has moved past that, though, and now such caution can render the basis for any decision obsolete as soon as it is made. As Satell puts it, we need “a more Bayesian approach to strategy, where we don’t expect to predict things and be right, but rather allow data streams to help us become less wrong over time.” Can the humans adapt to this way of thinking? It is reassuring to have a plan; I suspect only the most adaptable among us will feel comfortable flying by the seat of our pants.
Cynthia Murrell, December 7, 2016
Want to Get Published in a Science Journal? Just Dole out Some Cash
December 7, 2016
A Canadian, Tom Spears has managed to publish a heavily plagiarized paper in a science journal by paying some cash. Getting published in a scientific and medical journal helps in advancing the career. ‘
In an article published by SlashDot titled Science Journals Caught Publishing Fake Research For Cash, the author says:
In 2014, journalist Tom Spears intentionally wrote “the world’s worst science research paper…a mess of plagiarism and meaningless garble” — then got it accepted by eight different journals. He did it to expose journals which follow the publish-for-a-fee model, “a fast-growing business that sucks money out of research, undermines genuine scientific knowledge, and provides fake credentials for the desperate.
This is akin to students enlisting services of hackers over Dark Web to manipulate their grades and attendance records. However, in this case, there is no need of Dark Web or Tor browser. Paying some cash is sufficient.
The root of the problem can be traced to OMICS International, an India-based publishing firm that is buying publication companies of these medical journals and publishing whatever is sent to them for cash. In standard practice, the paper needs to be peer-reviewed and also checked for plagiarism before it is published. As written earlier, the separation line between the Dark and Open web seems to be thinning and one day will disappear altogether.
Vishal Ingole, December 7, 2016
Shade Created by Mountainous Stacks of Cash Passing from Google to Washington
December 6, 2016
The article titled Google’s Murky Washington Lobbying Is Making Apple Look Good on Observer points out yet another area of shady activity by Google. In the last five to ten years, Google has led the charge of tech firms into Washington, D.C. Google employees include multiple ex-White House staffers, and vice versa, Google spends tens of millions on lobbying per year (compared to Apple’s measly $5M) and Google donated over a million dollars to various political candidates in 2014 through its PAC. The article presents why this is not ideal:
Google has built significant relationships with the US government – directly through the revolving door of personnel, traditional lobbying, political contributions; and indirectly through trade associations and other advocacy groups. The lack of transparency, especially for a company that specializes in information, is problematic. Google’s very calculated strategy has bought out new critics, including some shareholders. Given the climate Google operates in most people would expect transparency, and instead Google has chosen opacity, which is troubling.
As we know, the American people get very antsy when it comes to the state of our oligarchy. We are keenly aware of the huge amounts of money being passed around, especially when it comes to lobbying. At this point, the only company spending more on lobbying than Google is GE. But what exactly this money buys for Google remains murky, and that should make us all extremely uncomfortable.
Chelsea Kerwin, December 6, 2016
Associative Semantic Search Is a New Technology, Not a Mental Diagnosis
December 6, 2016
“Associative semantic” sounds like a new mental diagnosis for the DSM-V (Diagnostic and Statistical Manuel of Mental Disorders), but it actually is the name of a search technology that sounds like it amplifies the basic semantic search. Aistemos has the run down on the new search technology in the article, “Associative Semantic Search Technology: Omnity And IP.” Omnity is the purveyor of the “associative semantic search” and it makes the standard big data promise:
…the discovery of otherwise hidden, high-value patterns of interconnection within and between fields of knowledge as diverse as science, medicine, engineering, law and finance.
All of the companies centered on big data have this same focus or something similar, so what does Omnity offer that makes it stand out? It proposes to find connections between documents that do not directly correlate or cite one another. Omnity uses the word “accelerate” to explain how it will discover hidden patterns and expand knowledge. The implications mean semantic search would once again be augmented and more accurate.
Any industry that relies on detailed documents would benefit:
Such a facility would presumably enable someone to find references to relevant patents, technologies and prior art on a far wider scale than has hitherto been the case. The legal, strategic and commercial implications of being able to do this, for litigation, negotiation, due diligence, investment and forward planning are sufficiently obvious for us not to need to list them here.
The article suggests those who would most be interested in Omnity are intellectual property businesses. I can imagine academics would not mind getting their hands on the associative semantic search to power their research or law enforcement could use it to fight crime.
Whitney Grace, December 6, 2016
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