Bing and Google: The News Battle
September 15, 2017
I read “Bing Battles Google News with Its Own Make-Over.” I noted the alliteration: Bing battle. I immediately thought, “Google Gropes.” Both of these companies are trying to reinvent the newspaper using zeros and ones, not dead trees. Let’s look at some of the points I highlighted:
I noted this statement everyone’s most lovable online ad vendor:
Google redesigned their desktop Google News website. Their [sic] new UI has a clean and uncluttered look.
Microsoft responded. I circled this statement:
Microsoft recently updated their Bing News experience that will help users in finding the most up to date and well-rounded information.
Note that the pivot of both sentences is a subjective assertion: “Clean and uncluttered” for the GOOG, and “most up to date and well rounded.”
Some facts would be useful. I am not sure what “clean” or “uncluttered” means. My recollection is that Einstein’s desk like most “dead tree” newspapers are organized in an eclectic manner. Facts supporting these assertions might be difficult to conjure.
The “most up to date” statement should be easy to back up. What’s the latency of the system? The superlative “most” means that Bing is the top dog in news. Hmmm. I don’t buy this.
My point is that the write up provides a useful idea: Neither Bing nor Google has figured out how to present “news” to each system’s online users. The implicit idea is that “dead tree” methods are of little use. Inspiration comes from each system’s response to what the other system does.
Cold War methods applied to online “news”? That’s what the write signals me.
Let’s step back.
Online users have different reasons for wanting news. Some folks chase sports, which as I recall was the most read section of the “dead tree” newspaper company at which I once worked. Other people have quite different reasons for scanning the news; for example, there are some who read the obituaries, others seek cartoons, and others want the latest on the real housewives.
Bing and Google have to figure out how to meet these diverse needs because the “dead tree” crowd has fallen in the forest.
The write up tells me one thing: Neither Google nor Microsoft has any idea about reinventing what “dead tree” newspapers used to do.
Now what? Shape the news to fit what each company’s filters “decide” is “real news”?
Stephen E Arnold, September 15, 2017
Annoyed Xooglers and Lawyers: A Volatile Mixture
September 15, 2017
Straightaway you will want to read the “real” news story from a “real” newspaper. The write up is “Former Employees Sue Google Alleging Bias against Women in Pay and Promotion.” (The story is online as 5 15 pm Eastern US time on September 14, 2017. Any other time? Who knows? The Guardian, another “real news” outfit jumped on the story as well at this link.)
The main point is in my opinion to help more criticism on the Alphabet Google thing.
I highlighted this passage:
Three female former employees of Alphabet Inc’s Google filed a lawsuit on Thursday accusing the tech company of discriminating against women in pay and promotions. The proposed class action lawsuit, filed in California state court in San Francisco, comes as Google is facing an investigation by the U.S. Department of Labor into sex bias in pay practices.
Since I am not a woman, I have zero knowledge about what did or did not happen when the GOOG decided what to pay each person. The write up suggests that Google is a throwback because “its treatment of female employees has not entered the 21st century.”
I think the GOOG is an innovative and progressive outfit. The company creates new products and services using multiple tactics. It is socially progressive because, like Walmart, it allows employees to park their campers in the Google parking lots.
The paragraph which raised my eyebrows was this one:
The department [of labor] last month appealed an administrative judge’s July decision that rejected its request for contact information for more than 20,000 Google employees.
My recollection is that Google is on record with a factual statement revealing that collecting certain employee compensation data is a job that is too difficult.
Why can’t regulators and lawyers trust Alphabet Google the way we do in Harrod’s Creek.
Gathering information about a closed domain of employees is tough. Accept the Google fact. And Google is progressive. Some employees are allowed to live in their trucks, emulating a parking policy of Walmart’s.
Stephen E Arnold, September 15, 2017
My Feed Personalization a Step Too Far
September 15, 2017
In an effort to be even more user-friendly and to further encourage a narcissistic society, Google now allows individuals to ‘follow’ or ‘unfollow’ topics, delivered daily to devices, as they deem them interesting or uninteresting. SEJ explains the new feature which is considered an enhancement of their ‘my feed’ which is intended to personalize news.
As explained in the article,
Further advancements to Google’s personalized feed include improved machine learning algorithms, which are said to be more capable at anticipating what an individual may find interest. In addition to highlighting stories around manually and algorithmically selected topics of interest, the feed will also display stories trending in your area and around the world.
That seems like a great way to keep people current on topics ranging geographically, politically and culturally, but with the addition of ‘follow’ or ‘unfollow’, once again, individuals can reduce their world to a series of pop-star updates and YouTube hits. Isn’t it an oxymoron to both suggest topics and stories in an effort to keep an individual informed of the world around them, and yet allow them to stop the suggestions are they appear boring or lack familiarity? Now, Google, you can do better.
Catherine Lamsfuss, September 15, 2017
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
Markov: Maths for the Newspaper Reader
September 14, 2017
Remarkable. I read a pretty good write up called “That’s Maths: Andrey Markov’s Brilliant Ideas Are Still Bearing Fruit.” I noted the source of the article: The Irish Times. A “real” newspaper. Plus it’s Irish. Quick name a great Irish mathematician? I like Sir William Rowan Hamilton, who my slightly addled mathy relative Vladimir Igorevich Arnold and his boss/mentor/leader of semi clothed hikes in the winter Andrey Kolmogorov thought was an okay guy.
Markov liked literature. Well, more precisely, he liked to count letter frequencies and occurrence in Russian novels like everyone’s fave Eugene Onegin. His observations fed his insight that a Markov Process or Markov Chain was a useful way to analyze probabilities in certain types of data. Applications range from making IBM Watson great again to helping outfits like Sixgill generate useful outputs. (Not familiar with Sixgill? I cover the company in my forthcoming lecture at the TechnoSecurity & Digital Forensics Conference next week.)
I noted this passage which I thought was sort of accurate or at least close enough for readers of “real” newspapers:
For a Markov process, only the current state determines the next state; the history of the system has no impact. For that reason we describe a Markov process as memoryless. What happens next is determined completely by the current state and the transition probabilities. In a Markov process we can predict future changes once we know the current state.
The write up does not point out that the Markov Process becomes even more useful when applied to Bayesian methods enriched with some LaPlacian procedures. Now stir in the nuclear industry’s number one with a bullet Monte Carlo method and stir the ingredients. In my experience and that of my dear but departed relative, one can do a better job at predicting what’s next than a bookie at the Churchill Downs Racetrack. MBAs on Wall Street have other methods for predicting the future; namely, chatter at the NYAC or some interactions with folks in the know about an important financial jet blast before ignition.
A happy quack to the Irish Times for running a useful write up. My great uncle would emit a grunt, which is as close as he came to saying, “Good job.”
Stephen E Arnold, September 14, 2017
Instagram Algorithm to Recognize Cruelty and Kindness
September 14, 2017
Instagram is using machine learning to make its platform a kinder place, we learn from the CBS News article, “How Instagram is Filtering Out Hate.” Contributor (and Wired Editor-In-Chief) Nick Thompson interviewed Instagram’s CEO Kevin Systrom, and learned the company is using about 20 humans to teach its algorithm to distinguish naughty from nice. The article relates:
Systrom has made it his mission to make kindness itself the theme of Instagram through two new phases: first, eliminating toxic comments, a feature that launched this summer; and second, elevating nice comments, which will roll out later this year. ‘Our unique situation in the world is that we have this giant community that wants to express themselves,’ Systrom said. ‘Can we have an environment where they feel comfortable to do that?’ Thompson told ‘CBS This Morning’ that the process of ‘machine learning’ involves teaching the program how to decide what comments are mean or ‘toxic’ by feeding in thousands of comments and then rating them.
It is smarter censorship if you will. Systrom seems comfortable embracing a little censorship in favor of kindness, and we sympathize; “trolls” are a real problem, after all. Still, the technology could, theoretically, be used to delete or elevate certain ideological or political content. To censor or not to censor is a fine and important line, and those who manage social media sites will be the ones who must walk it. No pressure.
Cynthia Murrell, September 14, 2017
Let the Tweets Lead Your Marketing, Come What May
September 14, 2017
It seems that sales and marketing departments just can’t keep up with consumer patterns and behaviors. The latest example of this is explained in a DMA article outlining how to utilize social media to reach target leads. As people rely more on their own search and online acumen and less on professionals (IRL), marketing has to adjust.
Aseem Badshah, Founder, and CEO of Socedo, explain the problem and a possible solution:
Traditionally, B2B marketers created content based on the products they want to promote. Now that so much of the B2B decision making process occurs online, content has to be more customer-centric. The current set of website analytics tools provide some insights, but only on the audience who have already reached your website. Intent data from social media can help you make your content more relevant. By analyzing social media signals and looking at which signals are picking up in volume over time, you can gain new insights into your audience that helps you create more relevant content.
While everything Badshah says may be true, one has to ask themselves, is following the masses always a good thing? If a business wants to maintain their integrity to their field would it be in their best interest to follow the lead of their target demographic’s hashtags or work harder at marketing their product/service despite the apparent twitter-provided disinterest?
Catherine Lamsfuss, September 14, 2017
When Business Models Fail, Hit the Startup Casino
September 13, 2017
I read “Searching for the Next Facebook or Google: Bloomberg Helps Launch Tech Incubator.” On the surface, the write up is not too newsy. Bloomberg (the terminal folks that Thomson Reuters has not been able to kill off with hundreds of millions in cash pumped into its “innovation” efforts) is getting into the startup casino. The idea is that Bloomberg (the former mayor) is bringing incubators to New York City. The hook for the story is that Cornell University is the big fish which has been landed on Roosevelt Island, the one with the tram thing. With Bloomberg beaching Cornell and Technion (the MIT of Israel) ensnared, I have some questions floating in my rural Kentucky mind:
- When an innovation occurs, who will get access to that technology? The universities, the professors, the students, or Bloomberg?
- What will Thomson Reuters do to counter this play by the inventor of the famed and incredibly cluttered terminal for MBA clutching Red Bulls and mocha lattes?
- Who will be able to hire the bright sprouts who flock via tram to Roosevelt Island?
- Has IBM’s MIT play been “trumped” (no pun intended) because Bloomberg can play most of the numbers on the startup casino’s roulette wheel?
- Will Facebook and Google just buy Stanford University and leave the old school companies to the backwaters on the East coast?
- Which big company will fund the High Technology High School in New Jersey? (Strike that. New Jersey?)
Worth watching?
Stephen E Arnold, September 13, 2017
Another Captain Obvious or Fanciful Thinking: Silicon Valley and the US Government in Conflict?
September 13, 2017
I read “There’s Blood In The Water In Silicon Valley.” The main idea is that Sillycon Valley is too big for its Air birds. The US government, riding its white horse and wearing its shining armor, will ride to the rescue of the citizens, nay, the country.
The write up tells me in “real news” tones:
The new corporate leviathans that used to be seen as bright new avatars of American innovation are increasingly portrayed as sinister new centers of unaccountable power, a transformation likely to have major consequences for the industry and for American politics.
There you go. “Leviathans.” “Sinister.” “Unaccountable.” “Power.”
Objective, dispassionate, the real world exposed.
The bad guys are Amazon, Facebook, Google, and any other Sillycon Valley outfits doing what companies do.
From my vantage point in the high-tech center of the mid South, I am not sure I see these outfits as doing anything different from what other big outfits do; for example:
- Big pharma and its pricing tactics
- GM and its auto engineering methods
- Too-big-to-fail banks doing their fancy dancing.
Need I go on.
The business set up in the US is not going to be changed quickly or significantly in my opinion. There are some reasons I hold this view, no matter what “real journalism” outfits asserts. Here are some of my factoids:
- The US government bureaucracy does not move quickly. Certain changes in bureaucratic behavior are slowed because of the revolving door between US government and industry, government workers interest in advancing their careers via lateral arabesques and the quest for grabbing the brass ring of the SES (senior executive service)
- Lobbyists and influencers have an old-fashioned tin-can-and-string communication method between those who pay the lobbyists and those who make the laws and, to some extent, influence how they are interpreted in US government entities
- Political considerations command the attention of those within and outside the US government. There are jobs at stake, and having Amazon shut down one of its nerve centers to move to more favorable climes is a bit of a concern in many circles.
And there are other factors ranging from those who own stock in the evil Sillycon Valley companies to the desire to get one’s kid a job at an outfit like Facebook or Google.
My thought is that outfits like Equifax may warrant more attention than the Sillycon Valley bros. But “real news” outfits set the agenda, right? Maybe. Sillycon Valley is one facet of the “business as usual” methods employed through many standard industrial code sectors.
Here’s a thought? Why not suggest that outfits like Equifax are regulated by a government agency. The Amazons, Facebooks, and Googles have lots of oversight compared to the controls placed on the US credit bureaus.
Why not ride on over to Equifax and sparkle in the sun?
Stephen E Arnold, September 13, 2017
Tech Industry Toxicity Goes Beyond Uber
September 13, 2017
Shiny new things have distracted people from certain behaviors, and Fast Company is calling out the entire technology startup culture in, “Why Silicon Valley Can’t Call Uber an Anomaly.” Writer Austin Carr takes us briefly through Uber’s tribulations, which culminated in the departure of infamous CEO Travis Kalanick. See the article for that useful summary, but Carr’s question was whether Uber’s noxious culture is unusual. He writes:
Silicon Valley, though, is insular and guarded. In my reporting, I encountered few people willing to speak openly, let alone critically, about Uber’s troubles. Those who did (most of them, notably, women) argue that there’s an opportunity for course correction right now. It starts by acknowledging that the Valley isn’t yet the utopian meritocracy it strives to be—and that Uber’s errant system exposed some fundamental bugs in the startup economy.
Carr identifies and discusses three of these bugs. First, that which makes a startup succeed often does not scale up well. For example, a confrontational culture that pits workers against each other might fuel a startup’s launch, but becomes unsustainable in a large, global corporation. The second problem is the myth of the “omniscient founder.” Though most of us realize that generating a brilliant idea does not necessarily go hand-in-hand with the capacity to run a large organization, much of the tech industry still seems taken by the foolish notion of one man at the top skillfully managing each and every aspect of the business. Carr points out that even Steve Jobs and Larry Page saw the wisdom in stepping back, and each tapped someone with more corporate experience to run their companies for a while. Not only is this hero-at-the-top attitude inefficient, it also risks the devaluation of every other employee. Talent does not stay where it is not respected.
Finally, Carr observes, the system of accountability needs an overhaul. It takes a lot of scandals to push investors to hold tech companies accountable for bad behavior, and even then board members hesitate to act. The article concludes:
If there really were healthy checks and balances, boards wouldn’t wait for public outrage to act. But to acknowledge that Uber’s system of accountability failed is to acknowledge that fundamental change—something Silicon Valley normally embraces—is necessary. If the Valley truly prides itself on moving fast and breaking things, it ought to start here.
We are curious to see how the industry will respond to such escalating criticisms.
Cynthia Murrell, September 13, 2017
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