Encryption and Rap Lyrics
March 6, 2016
I read “Gang Used Rap Lyrics to Discuss Guns.” According to the write up:
Members of a gang, accused of smuggling automatic weapons into the UK by boat, used lyrics from a song by rapper the Notorious B.I.G. to discuss their arrival, a court has heard.
The write up added:
The Gimme the Loot lyrics were included in a message from Mr Defraine which read: “I’m ready to got this paper g you with me… my pockets looking kinda tight and I’m stressed yo munky let me get the vest”.
Argot can be a challenge for search and content processing. Were those $5,000 teddy bears on eBay really teddy bears?
Nope. Kinda munky maybe?
Stephen E Arnold, March 6, 2016
Palantir Gets a Rah Rah from Bloomberg
March 5, 2016
I posted the unicorn flier in “Palantir: A Dying Unicorn or a Mad, Mad Sign?” I read “Palantir Staff Shouldn’t Believe the Unicorn Flyers.” I assume that the alleged fliers did exist in the Shire and were not figments of a Tolkienesque imagination. (I wonder of JRR’s classes were anchored in reality.)
The write up states:
For now, Palantir people can rest easy in the Shire, a.k.a. downtown Palo Alto, Calif. The company, which was named after the “seeing stones” from the Lord of the Rings, is not at risk of an evil wizard with preferred shares coming to vaporize workers’ share value.
The write up contains a hefty dose of jargon; for example:
During the fourth quarter of 2015, 42 percent of deals had such provisions, compared with 15 percent in the previous two quarters. Investors were also given the right to block an initial public offering that didn’t meet their valuation threshold in 33 percent of deals in the fourth quarter, compared with 20 percent in the second quarter, the study said. Palantir had neither provision.
Okay.
The only hitch in the git along is that Morgan Stanley has cut the value of its stake in Palantir.
Worth watching even if one is not an employee hoping that the value of this particular unicorn is going to morph into a Pegasus.
Stephen E Arnold, March 5, 2016
Quid Cheerleading: The Future of Search
March 4, 2016
I read “The Future of {Re}search.” (I love the curly braces.) The write up identifies the four big things in information access. Keep in mind that the write up is a rah rah for Quid, which is okay.
Here are the main points:
- Semantic search is the next big thing
- Visualization matters
- Humans are part of the search process
- Bots are the “Future of Search.” (The capitalization is from the source document.)
Quid is an interesting company. I thought that the firm was focused on analytics and nifty visualizations. Their catchphrase is “intelligence amplified,” which strikes me as similar to Palantir’s “augmented intelligence.”
If the write up is on the money, Quid is a search vendor in the same way Palantir Technologies is a search vendor.
The point about bots may catch the attention of the ever-alert Connotate folks. I think bots has been an important part of that firm’s services for many years.
So, “the next big thing”? Well, sort of.
Stephen E Arnold, March 4, 2016
The FBI Uses Its Hacking Powers for Good
March 4, 2016
In a victory for basic human decency, Engadget informs us, the “FBI Hacked the Dark Web to Bust 1,500 Pedophiles.” Citing an article at Vice Motherboard, writer Jessica Conditt describes how the feds identified their suspects through a site called (brace yourself) “Playpen,” which was launched in August 2014. We learn:
Motherboard broke down the FBI’s hacking process as follows: The bureau seized the server running Playpen in February 2015, but didn’t shut it down immediately. Instead, the FBI took “unprecedented” measures and ran the site via its own servers from February 20th to March 4th, at the same time deploying a hacking tool known internally as a network investigative technique. The NIT identified at least 1,300 IP addresses belonging to visitors of the site.
“Basically, if you visited the homepage and started to sign up for a membership, or started to log in, the warrant authorized deployment of the NIT,” a public defender for one of the accused told Motherboard. He said he expected at least 1,500 court cases to stem from this one investigation, and called the operation an “extraordinary expansion of government surveillance and its use of illegal search methods on a massive scale,” Motherboard reported.
Check out this article at Wired to learn more about the “network investigative technique” (NIT). This is more evidence that, if motivated, the FBI is perfectly capable of leveraging the Dark Web to its advantage. Good to know.
Cynthia Murrell, March 4, 2016
Sponsored by ArnoldIT.com, publisher of the CyberOSINT monograph
Artificial Intelligence Competition Reveals Need for More Learning
March 3, 2016
The capabilities of robots are growing but, on the whole, have not surpassed a middle school education quite yet. The article Why AI can still hardly pass an eighth grade science test from Motherboard shares insights into the current state of artificial intelligence as revealed in a recent artificial intelligence competition. Chaim Linhart, a researcher from an Israel startup, TaKaDu, received the first place prize of $50,000. However, the winner only scored a 59.3 percent on this series of tasks tougher than the conventionally used Turing Test. The article describes how the winners utilized machine learning models,
“Tafjord explained that all three top teams relied on search-style machine learning models: they essentially found ways to search massive test corpora for the answers. Popular text sources included dumps of Wikipedia, open-source textbooks, and online flashcards intended for studying purposes. These models have anywhere between 50 to 1,000 different “features” to help solve the problem—a simple feature could look at something like how often a question and answer appear together in the text corpus, or how close words from the question and answer appear.”
The second and third place winners scored just around one percent behind Linhart’s robot. This may suggest a competitive market when the time comes. Or, perhaps, as the article suggests, nothing very groundbreaking has been developed quite yet. Will search-based machine learning models continue to be expanded and built upon or will another paradigm be necessary for AI to get grade A?
Megan Feil, March 3, 2016
Sponsored by ArnoldIT.com, publisher of the CyberOSINT monograph
Delve Is No Jarvis
March 3, 2016
A podcast at SearchContentManagement, “Is Microsoft Delve Iron Man’s Edwin Jarvis? No Way,” examines the ways Delve has yet to live up to its hype. Microsoft extolled the product when it was released as part of the Office 365 suite last year. As any developer can tell you, though, it is far easier to market than deliver polished software. Editor Lauren Horwitz explains:
“While it was designed to be a business intelligence (BI), enterprise search and collaboration tool wrapped into one, it has yet to make good on that vision. Delve was intended to be able to search users’ documents, email messages, meetings and more, then serve up relevant content and messages to them based on their content and activities. At one level, Delve has failed because it hasn’t been as comprehensive a search tool as it was billed. At another level, users have significant concerns about their privacy, given the scope of documents and activities Delve is designed to scour. As BI and SharePoint expert Scott Robinson notes in this podcast, Delve was intended to be much like Edwin Jarvis, butler and human search tool for Iron Man’s Tony Stark. But Delve ain’t no Jarvis, Robinson said.”
So, Delve was intended to learn enough about a user to offer them just what they need when they need it, but the tool did not tap deeply enough into the user’s files to effectively anticipate their needs. On top of that, it’s process is so opaque that most users don’t appreciate what it is doing, Robinson indicated. For more on Delve’s underwhelming debut, check out the ten-minute podcast.
Cynthia Murrell, March 3, 2016
Sponsored by ArnoldIT.com, publisher of the CyberOSINT monograph
No Search Just Browse Images on FindA.Photo
March 2, 2016
The search engine FindA.Photo proves itself to be a useful resource for browsing images based on any number of markers. The site offers a general search by terms, or the option of browsing images by color, collection (for example, “wild animals,” or “reflections”) or source. The developer of the site, David Barker, described his goals for the services on Product Hunt,
“I wanted to make a search for all of the CC0 image sites that are available. I know there are already a few search sites out there, but I specifically wanted to create one that was: simple and fast (and I’m working on making it faster), powerful (you can add options to your search for things like predominant colors and image size with just text), and something that could have contributions from anyone (via GitHub pull requests).”
My first click on a swatch of royal blue delivered 651 images of oceans, skies, panoramas of oceans and skies, jellyfish ballooning underwater, seagulls soaring etc. That may be my own fault for choosing such a clichéd color, but you get the idea. I had better (more various) results through the collections search, which includes “action,” “long-exposure,” “technology,” “light rays,” and “landmarks,” the last of which I immediately clicked for a collage of photos of the Eiffel Tower, Louvre, Big Ben, and the Great Wall of China.
Chelsea Kerwin, March 2, 2016
Sponsored by ArnoldIT.com, publisher of the CyberOSINT monograph
Natural Language Processing App Gains Increased Vector Precision
March 1, 2016
For us, concepts have meaning in relationship to other concepts, but it’s easy for computers to define concepts in terms of usage statistics. The post Sense2vec with spaCy and Gensim from SpaCy’s blog offers a well-written outline explaining how natural language processing works highlighting their new Sense2vec app. This application is an upgraded version of word2vec which works with more context-sensitive word vectors. The article describes how this Sense2vec works more precisely,
“The idea behind sense2vec is super simple. If the problem is that duck as in waterfowl andduck as in crouch are different concepts, the straight-forward solution is to just have two entries, duckN and duckV. We’ve wanted to try this for some time. So when Trask et al (2015) published a nice set of experiments showing that the idea worked well, we were easy to convince.
We follow Trask et al in adding part-of-speech tags and named entity labels to the tokens. Additionally, we merge named entities and base noun phrases into single tokens, so that they receive a single vector.”
Curious about the meta definition of natural language processing from SpaCy, we queried natural language processing using Sense2vec. Its neural network is based on every word on Reddit posted in 2015. While it is a feat for NLP to learn from a dataset on one platform, such as Reddit, what about processing that scours multiple data sources?
Megan Feil, March 1, 2016
Sponsored by ArnoldIT.com, publisher of the CyberOSINT monograph
LinkedIn: Looking for Its Next Gig?
February 29, 2016
I signed up for the free LinkedIn years ago. I don’t do too much LinkedIn surfing. I do delete the email I get from the company. I had one of the goslings post a list of my articles to see what would happen. (Results of the test: Nothing happened.) I find it amusing that marketers and PR “professionals” want to be my LinkedIn contact. I used to write these folks and ask, “Why do you want to be my LinkedIn friend?” (Results of the test: No one writes back.) Now you know why I don’t do much LinkedIn surfing. No, I don’t read the musings of the firm’s “thought leaders.”
I did read “LinkedIn Problems Run Deeper Than Valuation.” The write up informed me of this interesting “assertion”:
The problem stems from each of the company’s revenue streams, which ultimately diminish the business value of using the service. Whether it’s being paid to promote content, focusing on sales and recruitment over other professions, or interruptive advertising, these streams incentivize poor behavior by individual users on the site.
I like that “poor behavior” and the incentive angle. The concrete foundation of LinkedIn, it seems to me, is spam.
The company, according to the write up, has a reason to face each day with a big smile:
The company still has assets that are the envy of any tech company — a vast user base and a wealth of content to exploit.
As Yahoo’s publishing experiment demonstrates, content may not be enough.
I think the larger issue is the fact that social networks often lose their stickiness after a period of time. Google’s social efforts seem to mirror the challenges of MySpace. LinkedIn may find itself trapped by its own job hunting system choked with marketers’ leading thoughts.
Why not drive for Uber, Lyft, or Amazon? Less spam and probably a shorter path to some real cash. By the way, did you ever try to locate something using the company’s search engine? Quite a piece of work is that.
Stephen E Arnold, February 29, 2016
New Tor Communication Software for Journalists and Sources Launches
February 29, 2016
A new one-to-one messaging tool for journalists has launched after two years in development. The article Ricochet uses power of the dark web to help journalists, sources dodge metadata laws from The Age describes this new darknet-based software. The unique feature of this software, Ricochet, in comparison to others used by journalists such as Wickr, is that it does not use a server but rather Tor. Advocates acknowledge the risk of this Dark Web software being used for criminal activity but assert the aim is to provide sources and whistleblowers an anonymous channel to securely release information to journalists without exposure. The article explains,
“Dr Dreyfus said that the benefits of making the software available would outweigh any risks that it could be used for malicious purposes such as cloaking criminal and terrorist operations. “You have to accept that there are tools, which on balance are a much greater good to society even though there’s a tiny possibility they could be used for something less good,” she said. Mr Gray argued that Ricochet was designed for one-to-one communications that would be less appealing to criminal and terrorist organisers that need many-to-many communications to carry out attacks and operations. Regardless, he said, the criminals and terrorists had so many encryption and anonymising technologies available to them that pointing fingers at any one of them was futile.”
Online anonymity is showing increasing demand as evidenced through the recent launch of several new Tor-based softwares like Ricochet, in addition to Wickr and consumer-oriented apps like Snapchat. The Dark Web’s user base appears to be growing and diversifying. Will public perception follow suit?
Megan Feil, February 29, 2016
Sponsored by ArnoldIT.com, publisher of the CyberOSINT monograph
-
- Subscribe to Beyond Search
Feature archive
News archive
-
