Bitvore: The AI, Real Time, Custom Report Search Engine
May 16, 2017
Just when I thought information access had slumped quietly through another week, I read in the capitalist tool which you know as Forbes, the content marketing machine, this article:
This AI Search Engine Delivers Tailored Data to Companies in Real Time.
This write up struck me as more interesting than the most recent IBM Watson prime time commercial about smart software for zealous professional basketball fans or Lucidworks’ (really?) acquisition of the interface builder Twigkit. Forbes Magazine’s write up did not point out that the company seems to be channeling Palantir Technologies; for example, Jeff Curie, the president, refers to employees at Bitvorians. Take that, you Hobbits and Palanterians.
A Bitvore 3D data structure.
The AI, real time, custom report search engine is called Bitvore. Here in Harrod’s Creek, we recognized the combination of the computer term “bit” with a syllable from one of our favorite morphemes “vore” as in carnivore or omnivore or the vegan-sensitive herbivore.
Does This Count As Irony?
May 16, 2017
Does this count as irony?
Palantir, who has built its data-analysis business largely on its relationships with government organizations, has a Department of Labor analysis to thank for recent charges of discrimination. No word on whether that Department used Palantir software to “sift through” the reports. Now, Business Insider tells us, “Palantir Will Shell Out $1.7 Million to Settle Claims that It Discriminated Against Asian Engineers.” Writer Julie Bort tells us that, in addition to that payout, Palantir will make job offers to eight unspecified Asians. She also explains:
The issue arose because, as a government contractor, Palantir must report its diversity statistics to the government. The Labor Department sifted through these reports and concluded that even though Palantir received a huge number of qualified Asian applicants for certain roles, it was hiring only small numbers of them. Palantir, being the big data company that it is, did its own sifting and produced a data-filled response that it said refuted the allegations and showed that in some tech titles 25%-38% of its employees were Asians. Apparently, Palantirs protestations weren’t enough on to satisfy government regulators, so the company agreed to settle.
For its part, Palantir insists on their innocence but say they settled in order to put the matter behind them. Bort notes the unusual nature of this case—according to the Equal Employment Opportunity Commission, African-Americans, Latin-Americans, and women are more underrepresented in tech fields than Asians. Is the Department of Labor making it a rule to analyze the hiring patterns of companies required to report diversity statistics? If they are consistent, there should soon be a number of such lawsuits regarding discrimination against other groups. We shall see.
Cynthia Murrell, May 16, 2017
Alphabet Google Ad Placement: Unfair Analysis?
May 15, 2017
Let’s ignore the mobile phone click farm which seems to be undetectable. (I know. If it were undetectable, the article “The Bizarre Click Farm of 10,000 Phones That Give Fake Likes to Our Most Beloved Apps.”) My thought is that if the clicks work for likes, perhaps the method works for grinding through Adwords’ messages too.
Let’s ignore the cyber attack how to write ups posted to YouTube. For more information, navigate to “Cyber Attack Guides Promoted on YouTube.”
What’s interesting to me this fine day is the article “Look What Happens When You Type Donald Trump Office into Google.” The notion of delivering information which answers a question seems to be a challenge for Google. I learned:
Vladimir Putin appears as the first name when typing in Donald Trump office into the search engine. He also appears alongside Melania Trump and Kellyanne Conway, neither of whom can count themselves as being in the president’s office either.
Alphabet Google faces some interesting challenges. My view is that Google search seems to be fraying. The loose threads are not at the edges. The unravelings are evident in a number of basic functions; for example, objectivity, precision, and recall.
Maybe I am incorrect? On the other hand, maybe not?
Stephen E Arnold, May 15, 2017
Palantir Settles Discrimination Case
May 15, 2017
Does this count as irony? Palantir, who has built its data-analysis business largely on its relationships with government organizations, has a Department of Labor analysis to thank for recent charges of discrimination. No word on whether that Department used Palantir software to “sift through” the reports. Now, Business Insider tells us, “Palantir Will Shell Out $1.7 Million to Settle Claims that It Discriminated Against Asian Engineers.” Writer Julie Bort tells us that, in addition to that payout, Palantir will make job offers to eight unspecified Asians. She also explains:
The issue arose because, as a government contractor, Palantir must report its diversity statistics to the government. The Labor Department sifted through these reports and concluded that even though Palantir received a huge number of qualified Asian applicants for certain roles, it was hiring only small numbers of them. Palantir, being the big data company that it is, did its own sifting and produced a data-filled response that it said refuted the allegations and showed that in some tech titles 25%-38% of its employees were Asians. Apparently, Palantirs protestations weren’t enough on to satisfy government regulators, so the company agreed to settle.
For its part, Palantir insists on their innocence but say they settled in order to put the matter behind them. Bort notes the unusual nature of this case—according to the Equal Employment Opportunity Commission, African-Americans, Latin-Americans, and women are more underrepresented in tech fields than Asians. Is the Department of Labor making it a rule to analyze the hiring patterns of companies required to report diversity statistics? If they are consistent, there should soon be a number of such lawsuits regarding discrimination against other groups. We shall see.
Cynthia Murrell, May 15, 2017
USAFacts Centralizes Access to Data on Government Spending
May 12, 2017
Former Microsoft CEO Steve Ballmer’s recent project was inspired by his wife, Connie, who wished him to practice more philanthropy. Wouldn’t it help to know what our government is already doing with its (our) money, he wondered? Out of this question has sprung USAFacts, a website that serves up “federal, state, and local data from over 70 government sources.” I appreciate the presentation, which ties data to four specific directives embedded in the Preamble to our Constitution. For example, the heading Establish Justice and Ensure Domestic Tranquility leads to stats on Crime and Disaster, Safeguarding Consumers and Employees, and Child Safety and Social Services. Tying such information to our founding document will prompt many to consider these data points in a more thoughtful way.
The site’s About page describes its team’s approach and methodology. The effort has not been easy; we’re told:
With his business background, Steve searched for solid, reliable, impartial numbers to tell the story… but eventually realized he wasn’t going to find them. He put together a small team of people – economists, writers, researchers – and got to work.
We soon discovered that dealing with something as big and complex as government – with its more than 90,000 jurisdictions and 23 million employees – required an organizing framework. What better place to look than the Constitution, and, more specifically, the preamble to the Constitution? … While we don’t make judgments about policy, we all agree on the broad purposes of government as laid out in the preamble to the Constitution.
Still, in beta, USA Facts is partnering with academic institutions like the Stanford Institute for Economic Policy Research, the Penn Wharton Budget Model, and Lynchburg College. They are working to document their process and controls, and plan to have their methods reviewed by a “prominent” accounting firm for accuracy. We look forward to watching this project grow.
Cynthia Murrell, May 12, 2017
Russia Compels Google to Relinquish Default Search-Engine Status on Android
May 11, 2017
Russia has successfully pushed Google into playing fair (on one matter, anyway), we learn from “Google Agrees to Open Android to Other Search Engines in Russia” at the Verge. Writer Jacob Kastrenakes reveals:
In addition to paying a $7.8 million fine, Google has agreed to stop preventing phone manufacturers from changing the default search engine to anything but Google. Google won’t be allowed to require any app exclusivity on new phones, nor will it be allowed to prevent other companies’ apps from coming preinstalled.
While Android is an open platform, core parts of the operating system aren’t, including Google’s app store. That’s allowed Google to set strict conditions for any phone manufacturer that wants to build a phone with access to the Play Store’s millions of apps. Russia’s Federal Antimonopoly Service said this counted as an abuse of Google’s dominant market position, and for the past two years, it’s been investigating and suing over the company’s restrictive terms.
Naturally, Russian search giant Yandex stands to gain from the concession. We can expect that company to negotiate with Android-phone manufacturers to have their search engine preinstalled within Russia. In fact, Yandex’s founder and CEO issued a statement celebrating the settlement, noting that “competition breeds innovation.” Indeed.
Russian Android users will soon be empowered to reject Google Search, too. The company promises a to implement a widget for Chrome that will enable users to set a non-Google search engine as their default. The caveat— prospective engines must sign a commercial agreement with Google. After all, that global near-monopoly will not relinquish any more control than it must.
Cynthia Murrell, May 11, 2017
IBM Watson: A Joke?
May 10, 2017
I wanted to ask IBM Watson is it thought the article “IBM’s Watson Is a Joke, Says Social Capital CEO Palihapitiya.” No opportunity. Bummer.
I learned from the real journalism outfit CNBC, which has been known to sell advertising, that:
“Watson is a joke, just to be completely honest,” he said in an interview with “Closing Bell” on the sidelines of the Sohn Investment Conference in New York.
The Social Capital top dog added:
“I think what IBM is excellent at is using their sales and marketing infrastructure to convince people who have asymmetrically less knowledge to pay for something,” Palihapitiya added. “I put them and Oracle in somewhat of the same bucket.”
I like that “asymmetrically less knowledge.” It suggests that the PR firms, the paid consultants who flog the word “cognitive,” and the torrent of odd ball conference talks are smoke and mirrors.
Should one put one’s money into IBM? My reading of the article suggests that the CNBC expert believes that Jeff Bezos and Elon Musk are where the action is. What? No Alphabet Google thing?
Several observations:
- Describing something in marketing science fiction is fun and can be lucrative. The reality is that Lucene, home brew code, and acquired technology do not add up to a breakthrough in smart software. Sorry, cheerleaders.
- Reporting five years of declining revenue puts hyperbole in context. IBM is simply trying to hard to push Watson into everything from recipes to healthcare. The financial reports tell me that the bet is not working.
- Creating wild and crazy Super Bowl ads which suggest a maximum refund tips toward carnival marketing. Floating white cubes are just as incomprehensible to me as PT Barnum’s Feejee mermaid.
Perhaps IBM can roll out a TV spot with Mr. Barnum’s Chang and Eng as a spokes-people.
Stephen E Arnold, May 9, 2017
Swiftype Launches SaaS Enterprise Search Platform
May 10, 2017
While AI is a hot commodity, enterprise search has been more of a disappointment. That is why we are surprised by one company’s confidence in the search market—KMWorld shares, “Swiftype Launches AI-Powered Content Discovery Engine for Enterprise Users.” This integration of AI into enterprise search is the firm’s first (formal) venture into cloud services. Writer Joyce Wells tells us:
With a single search, the company says, a user can locate information across accounts in Salesforce, files on Dropbox, documents in Google G Suite or Office 365, information from internal databases, and conversation threads on Gmail. Swiftype also integrates directly into apps such as Salesforce and Confluence to allow users to search and find content across all of these services without disturbing their existing workflows.
According to the vendor, the platform provides Swiftype AI-powered search applications built natively for mobile, desktop, and web browsers, as well as additional workflow integrations that allow users to search all their data from the applications they already use. There is also a Connector Framework to help quickly connect cloud-based platforms.
So far, Swiftype has integrated the platforms of Google, Microsoft, Salesforce, Atlassian, and Zendesk into their product. We also learn the company’s AI platform, dubbed Enterprise Knowledge Graph, will take into account calendar events, email content, and user behavior as crafts analyses. Launched in 2012, the Swiftype is based in San Francisco.
Cynthia Murrell, May 10, 2017
Machine Learning Going Through a Phase
May 10, 2017
People think that machine learning is like an algorithm magic wand. It works by some writing the algorithmic code, popping in the data, and the computer learns how to do a task. It is not that easy. The Bitext blog reveals that machine learning needs assistance in the post, “How Phrase Structure Can Help Machine Learning For Text Analysis.”
Machine learning techniques used for text analysis are not that accurate. The post explains that instead of learning the meaning of words in a sentence according to its structure, all the words are tossed into a bag and translated individually. The context and meaning are lost. A real world example is Chinese and Japanese because they use kanji (pictorial symbols representing words). Chinese and Japanese are two languages, where a kanji’s meaning changes based on the context. The result is that both languages have a lot of puns and are a nightmare for text analytics.
As you can imagine there are problems in Germanic and Latin-based languages too:
Ignoring the structure of a sentence can lead to various types of analysis problems. The most common one is incorrectly assigning similarity to two unrelated phrases such as “Social Security in the Media” and “Security in Social Media” just because they use the same words (although with a different structure).
Besides, this approach has stronger effects for certain types of “special” words like “not” or “if”. In a sentence like “I would recommend this phone if the screen was bigger”, we don’t have a recommendation for the phone, but this could be the output of many text analysis tools, given that we have the words “recommendation” and “phone”, and given that the connection between “if” and “recommend” is not detected.
If you rely solely on the “bag of words” approach for text analysis the problems only get worse. That is why it phrase structure is very important for text and sentiment analysis. Bitext incorporates phrase structure and other techniques in their analytics platform used by a large search engine company and another tech company that likes fruit.
Whitney Grace, May 10, 2017
AI Not to Replace Lawyers, Not Yet
May 9, 2017
Robot or AI lawyers may be effective in locating relevant cases for references, but they are far away from replacing lawyers, who still need to go to the court and represent a client.
ReadWrite in a recently published analytical article titled Look at All the Amazing Things AI Can (and Can’t yet) Do for Lawyers says:
Even if AI can scan documents and predict which ones will be relevant to a legal case, other tasks such as actually advising a client or appearing in court cannot currently be performed by computers.
The author further explains that what the present generation of AI tools or robots does. They merely find relevant cases based on indexing and keywords, which was a time-consuming and cumbersome process. Thus, what robots do is eliminate the tedious work that was performed by interns or lower level employees. Lawyers still need to collect evidence, prepare the case and argue in the court to win a case. The robots are coming, but only for doing lower level jobs and not to snatch them.
Vishol Ingole, May 9, 2017
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