Google: Making Search Better. But What Does Better Mean?

July 17, 2017

I read a darned interesting (no, not remarkable, just interesting) article called “The Google Exec in Charge of Designing Search: ‘There’s Always This Internal Debate about How Much Functionality Should We Add‘”. At first, I thought this was an Onion write up, but I was wrong. The article is a serious expression of the “real” Google. Now the “old” and now “unreal” Google is not applicable. That’s why I thought the write up was like the content I present in HonkinNews.

Here are the points I noted:

First, the write up points out that Google’s core business is its search engine. This surprised me because I thought the firm’s core business was selling ads. I know the “search” system is the honey which attracts the bees (95 percent or so in Europe, for example), but the “search” system is not about finding relevant and objective information. Sure, that happens for some queries, but for most queries, the searches are easy to cache and deliver with matching ads. Examples range from the weather to the latest in the dust ups and make ups between pop stars and starlets.

Second, the source of the write up is an “expert” in “design for search.” I am not sure what “design” means. I am old fashioned and prefer the trusty calculations of precision and recall, the stale bread of Boolean queries, and unfiltered content.

image

I prefer to do my own censoring, thank you. I noted this statement:

The whole goal is to try to organize information and deliver it to you. That’s the problem we’re trying to solve. The design has to accommodate multiple people, multiple expectations, and multiple situations. When you’re looking for whatever answer you want, how do we give you the right answer in a way that you’re like ‘oh yeah, that thing?

No, the “whole goal” consists of sub goals designed to deliver the following, based on my research for the three books in my Google Trilogy (alas, no longer in print but I can provide pre publication copies for those who want to buy a set):

  1. Minimize computational demands on the query matching system via caching frequent queries, partitioning indexes to get around the federation of disparate content like Google Scholar, videos indexed in Google Video, and the gusher of stuff emanating from Google Blogs
  2. With clicks on traditional desktops falling and small screen video queries from smart software or humans (imagine!), Google has to find a way to make ads out of everything. Thus, the need to keep revenue ticking upwards while driving costs down becomes a fairly significant sub goal. Some, like myself, say, “Hey, that’s the actual goal.” Others who enjoy watching billions flood into solving death, keeping Glass alive, and building a new puffy office part would disagree. That’s okay. I think I am right.
  3. Maintain the PR and marketing offensive that makes Google the innovation leader in finding information. The methods involve generating mumbo jumbo that disconnects precision and recall from what Google generates: Results that are often off point or some type of content marketing. (I know content marketing works because the Wall Street Journal told me it does. I assume that’s why Google pays some people to write really rah rah articles about Google. As I said in this week’s HonkinNews, “One must be able to tell the difference between a saint who helps people and a billionaire who rides flying car things.)

The write up identifies the experience “things” which Google is incorporating into its search results. Some of these are content objects like tweets. Others are pages which look like mini reports which cobble together “facts” to make it easy for a person to “know” the answer to the question he, she, or a software module had not yet asked. (Predictive results are part of the pervasive search movement in which Google wants to be a player who gets the biggest payday and the most media love.)

I noted this statement which is worthy of one of the New Age types I bumped into when I lived in Berkeley:

When asked if there are any similarities between the design for Search and the design for Google’s new offices in Mountain View and London, Ouilhet pointed to the fact that both are becoming “more open and more flexible.” He said they were also both becoming more “inclusive between people that belong to Google and people that don’t belong to Google.”

Net net: Google has yet to find Act 2 to its Yahoo/Overture/GoTo inspired business model. Setting up more VC operations, incubators, and buying companies in easy to reach places like Bengaluru, Karnataka, and smart software offices in cheery Edmonton, Alberta are not yet delivering on Act 2. If the European Union has anything to say about Google’s search business, we will have to wait for more action from that Google watcher Margrethe Vestager.

Stephen E Arnold, July 17, 2017

PS. For information about the Google Trilogy, write benkent2020 at yahoo dot com and put Google Trilogy in the Subject field.

Booz Allen Hamilton Under Scrutiny

July 5, 2017

Consulting firm Booz Allen Hamilton is facing an inquiry by the U.S Department of Justice for irregularities in billing inappropriately its clientele mostly comprising of government agencies.

As reported by Washington Times in a news piece titled Booz Allen Hamilton Under Federal Investigation over Billing Irregularities, Contractor Says, the reporter says:

Booz Allen was notified of the probe earlier this month and is working to resolve the matter with federal investigators, the company said in a Securities and Exchange Commission filing Thursday afternoon.

This is not the first time that the consulting firm dubbed as world’s most profitable spy organization has come under fire. In October 2016, an employee of the company was apprehended by federal authorities in possession of classified information. This was the second time an employee of the largest intelligence and defense contractor was arrested on charges of spying and selling classified information.

The investigation pertaining to irregularities in billing in ongoing.

Vishal Ingole, July 5, 2017

IBM Bans Remote Work

June 22, 2017

The tech blog SiliconBeat reveals a startling development in tech-related employment in, “IBM: So Much for Working from Home.” Thousands of professionals who have built their lives around their remote-work arrangements are now being required to come into the office. For many, the shift would mean packing up and moving closer to one of the company’s locations. As writer Rex Crum puts it:

That’s right. Find your way to an office cubicle, or hit the bricks. The Wall Street Journal reported that IBM began instituting the new you-can’t-work-from-home policy this week, and that the company is ‘quietly dismantling’ the program that has been in place for decades. The Journal said the retrenchment on its employees working remotely was being done so that IBM could ‘improve collaboration and accelerate the pace of work.’ It also happens to be taking place not long after IBM reported its 20th-straight quarter of declining year-over-year revenue. Legendary all-time investor Warren Buffett also said this month that Berkshire Hathaway has cut its holdings in IBM by one-third from the 81 million shares the company owned earlier this year.

But will herding all their talent into their buildings really solve IBM’s financial woes? Not according to this Forbes article. Crum recalls that Yahoo made the same move in 2013, when Marissa Mayer put a stop to remote work at that company. (How has that been going?) Will more organizations follow?

Cynthia Murrell, June 22, 2017

HPE IDOL Released with Natural Language Processing Capabilities Aimed at Enterprise-Level Tasks

June 16, 2017

The article titled Hewlett Packard Enterprise Enriches HPE IDOL Machine Learning Engine With Natural Language Processing on SDTimes discusses the enhancements to HPE IDOL. The challenges to creating an effective interactive experience based on Big Data for enterprise-class inquiries are related to the sheer complexity of the inquiries. Additional issues arise around context, specificity, and source validation. The article examines the new and improved model,

HPE Natural Language Question Answering deciphers the intent of a question and provides an answer or initates an action drawing from an organization’s own structured and unstructured data assets, in addition to available public data sources to provide actionable, trusted answers and business critical responses… HPE IDOL Natural Language Question Answering is a core feature of the new HPE IDOL 11.2 software release that features four key capabilities for natural language processing for the enterprise.

These capabilities are the IDOL Answer Bank (with pre-set reference questions), Fact Bank (with structured and unstructured data extraction abilities), Passage Extract (for text-based summaries), and Answer Server (for question analysis and integration of the other 3 areas). The goal is natural conversations between people and computers, an “information exchange”. The four capabilities work together to deliver a complex answer with the utmost accuracy and relevance.

Chelsea Kerwin, June 16, 2017

Google and Hate Speech: None of This I Know It When I See It

June 7, 2017

I read “YouTube Clarifies “Hate Speech” Definition and Which Videos Won’t Be Monetized.” I don’t know much about defining abstractions because I live in rural Kentucky. Our governor just recommended prayer patrols to curb violence in Louisville, home of the Derby and lots of murders on weekends.

Google has nailed down the abstraction “hate speech.” According to the write up, Google’s definition is:

[content which] “promotes discrimination or disparages or humiliates an individual or group of people on the basis of the individual’s or group’s race, ethnicity, or ethnic origin, nationality, religion, disability, age, veteran status, sexual orientation, gender identity, or other characteristic associated with systematic discrimination or marginalization.”

And

“inappropriate use of family entertainment characters,” which means content showing kid-friendly characters in “violent, sexual, vile, or otherwise inappropriate behavior,” no matter if the content is satirical or a parody. The final category is somewhat broad: “incendiary and demeaning content” means that anything “gratuitously” demeaning or shameful toward an individual or group is prohibited.”

And

“controversial issues or sensitive events,” which YouTube defines as “video content that features or focuses on sensitive topics or events including, but not limited to, war, political conflicts, terrorism or extremism, death and tragedies, sexual abuse, even if graphic imagery is not shown… For example, videos about recent tragedies, even if presented for news or documentary purposes, may not be eligible for advertising given the subject matter.”

This is good to know for three reasons:

  1. Google can define abstractions. No disambiguation subroutines are required.
  2. Google could run ads against this type of content and make money, but Google will not do that. (Did Google run ads against these types of content in the past? Nah, “do not evil” shuts the door on that question.)
  3. Facebook can process Google’s definitions and craft even more functional guidelines. (Me too is the basic process for innovation or becoming a publisher with editorial guidelines.)

Next up for Google to define are “love,” “truth,” justice,” and “salary data.”

Stephen E Arnold, June 7, 2017

Wall Street Can Learn from Google

May 30, 2017

Ruth Porat, CFO, Alphabet tells Economic Club of New York that Wall Street should have an open culture like Google which has helped the company to keep profit levels high and investors happy.

CNBC in its news piece titled Ruth Porat Suggests Financial Crisis Could’ve Been Avoided If Wall Street Acted More Like Google said:

Ruth Porat, the former veteran Morgan Stanley executive who’s now chief financial officer of Alphabet, suggested Monday that the financial crisis could have been prevented — or at least made less severe — if Wall Street had operated with the same transparency as Google’s parent company.

Google has no employee stock option at present. According to Porat, this eliminates the possibility of employees rigging the financial numbers or engaging in financial engineering. For Google, its greatest threat is the pace of innovation.

The company has a weekly meet TGIF wherein executives are asked tough questions by employees on any aspect of the company. Porat feels it is this tool that has helped Alphabet maintain transparency and Wall Street has something to learn from it.

Vishal Ingole, May 30, 2017

How to Use a Quantum Computer

April 20, 2017

It is a dream come true that quantum computers are finally here!  But how are we going to use them?  PC World discusses the possibilities in, “Quantum Computers Are Here—But What Are They Good For?”  D-Wave and IBM both developed quantum computers and are trying to make a profit from them by commercializing their uses.  Both companies agree, however, that quantum computers are not meant for everyday computer applications.

What should they be used for?

Instead, quantum systems will do things not possible on today’s computers, like discovering new drugs and building molecular structures. Today’s computers are good at finding answers by analyzing information within existing data sets, but quantum computers can get a wider range of answers by calculating and assuming new data sets.  Quantum computers can be significantly faster and could eventually replace today’s PCs and servers. Quantum computing is one way to advance computing as today’s systems reach their physical and structural limits.

What is astounding about quantum computers are their storage capabilities.  IBM has a 5-qubit system and D-Wave’s 2000Q has 2,000 qubit.   IBM’s system is more advanced in technology, but D-Wave’s computer is more practical.  NASA has deployed the D-Wave 2000Q for robotic space missions; Google will use it for search, image labeling, and voice recognition; and Volkswagen installed it to study China’s traffic patterns.

D-Wave also has plans to deploy its quantum system to the cloud.  IBM’s 5-qubit computer, on the other hand, is being used for more scientific applications such as material sciences and quantum dynamics.  Researchers can upload sample applications to IBM’s Quantum Experience to test them out.  IBM recently launched the Q program to build a 50-qubit machine.  IBM also wants to push their quantum capabilities in the financial and economic sector.

Quantum computers will be a standard tool in the future, just as the desktop PC was in the 1990s.  By then, quantum computers will respond more to vocal commands than keyboard inputs.

Whitney Grace, April 20, 2017

Yahoo Pay Inequity

April 19, 2017

Former Yahoo CEO Marissa Mayer made a considerable salary, especially considering she came to power during an economic downturn.  Her replacement Thomas McInerney, however, will be making double her salary.  Fortune reports on the income differences in: “Yahoo’s New Male CEO Will Make Double Marissa Mayer’s Salary.”  Pay inequity remains a big topic in today’s job market and this rises to the top as another example of a professional male receiving more money than a woman who held the same position.

Since Yahoo has sold its technology and advertising business to Verizon, it only consists of Alibaba stock, Yahoo Japan, and other miscellaneous investments.  One can assume that McInerney will have a much easier job than Mayer did.  McInerney is the former IAC CEO and his base salary will be $2 million, over Mayer’s $1 million.  He will also be getting more income from Yahoo:

What’s more, Yahoo actually expects to pay McInerney $4 million in his first year working at the company, assuming he earns his target bonus, which is equal to his base salary, according to the new disclosures. That’s 25% more than the $3 million the company is paying Mayer for a salary and cash bonus this year. On top of that, McInerney will also be eligible for grants of long-term incentive rewards of up to $24 million, depending on achievement of performance goals. If he were to receive the maximum amount, it would also be twice as much as Mayer’s long-term incentive grant in 2015, the last full year before the Verizon deal was announced.

McInerney will be paid to run the Yahoo equivalent of a mutual fund.  Yahoo will also not be buying new stock, instead, they will focus on managing their Alibaba stock and Yahoo Japan.  Those two investments basically run themselves.

If you ask me, it sounds like once again a woman cleans up a mess, makes it manageable, and a man comes in to take the credit and more pay.

Whitney Grace, April 19, 2017

Intelligence Industry Becoming Privatized and Concentrated

March 10, 2017

Monopolies aren’t just for telecoms and zipper manufacturers. The Nation reveals a much scarier example in its article, “5 Corporations Now Dominate Our Privatized Intelligence Industry.” Reporter Tim Shorrock outlines the latest merger that brings us to this point, one between Pentagon &  NSA contractor Leidos Holdings and a division of Lockheed Martin called Information Systems and Global Solutions. Shorrock writes:

The sheer size of the new entity makes Leidos one of the most powerful companies in the intelligence-contracting industry, which is worth about $50 billion today. According to a comprehensive study I’ve just completed on public and private employment in intelligence, Leidos is now the largest of five corporations that together employ nearly 80 percent of the private-sector employees contracted to work for US spy and surveillance agencies.

Yes, that’s 80 percent. For the first time since spy agencies began outsourcing their core analytic and operational work in the late 1990s, the bulk of the contracted work goes to a handful of companies: Leidos, Booz Allen Hamilton, CSRA, SAIC, and CACI International. This concentration of ‘pure plays’—a Wall Street term for companies that makes one product for a single market—marks a fundamental shift in an industry that was once a highly diverse mix of large military contractors, small and medium technology companies, and tiny ‘Beltway Bandits’ surrounding Washington, D.C.

I should mention that our beloved leader, Stephen E Arnold, used to work as a gopher for one of these five companies, Booz Allen Hamilton. Shorrock details the reasons such concentrated power is a problem in the intelligence industry, and shares the profile he has made on each company. He also elaborates on the methods he used to analyze the shadowy workforce they employ. (You’ll be unsurprised to learn it can be difficult to gather data on intelligence workers.) See the article for those details, and for Shorrock’s discussion of negligence by the media and by Congress on this matter. We can agree that most folks don’t seem to be aware of this trend, or of its potential repercussions.

Cynthia Murrell, March 10, 2016

 

 

Hewlett Packard Enterprise: Emulating IBM?

March 3, 2017

I read “HPE Misses Q1 Revenue Estimates.” The interesting point to me is that HPE seems to be following in IBM footsteps: Declining revenues, interesting explanations. Stakeholders cannot spend explanations in my experience. The write up references the HPE top dog who allegedly said:

I believe HOPE remains on the right track.

HOPE is a product. Believe it or not? The write up points out that HOPE’s revenue was eroding across the companies lines of business. What’s the fix? The right leadership team.

Rah, rah.

Perhaps HPE will prevail in its legal machinations related to the company’s purchase of Autonomy? Perhaps the “right leadership team” will understand that emulating IBM’s chatter about the future may not be enough to deal with the present market climate.

Oh, one more question: Will the “right leadership team” understand the phrase caveat emptor? HPE continues to try to find ways to shift the burden of Hewlett Packard’s own decisions to others.

Could some stakeholders rightly ask, “How about shifting to revenue growth?”

Stephen E Arnold, March 3, 2017

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