Alphabet Google: Accused Again by Ivory Towerians

August 31, 2017

I love the Alphabet Google thing. Big outfits paid me a few nickels and dimes to research the company’s technology and methods between 2002 and 2009. (Yep, the Google Trilogy thing.) After seven years of reading really exciting patent documents and Google technical papers, I shifted gears. Hey, cyber intelligence is for me, I decided. Change of pace. No ad technology in sight.

Now the string “Google” is appearing in my feeds about topics unrelated to online search and content processing, eDiscovery for cyber intelligence, and the musty, somewhat overhyped Dark Web.

The Google is “real” news, covered by a “real” newspaper. The most recent “Be woke about Google” write up is “Scholar Says Google Criticism Cost Him Job: ‘People Are Waking Up to Its Power‘.”

I highlighted these statements from the “real” newspaper’s article:

Every second of every day Google processes over 40,000 search queries – that’s about 3.5bn questions a day or 1.2trn a year. But there’s one question that Google apparently doesn’t want answered: is Google a monopoly?

“Everyday I see people waking up to the power of Google, Facebook and Amazon. We have to do something as a people, we have to do something through our government and address the power of these companies.

Google said it would “not be a fair characterization at all”, to blame Google for the decision. “I can confirm that our funding levels for 2017 have NOT changed as a result of NAF’s June post, nor did Eric Schmidt ever threaten to cut off funding because of it,” a spokeswoman said via email.

“Google is a very sophisticate [sic] team of people. They know how to spend their money and wield their influence in ways that usually get them what they want.

Yep, a he-said, she-said.

Several observations:

  1. Google is a bunch of moving parts. Based on my watching the company from Harrod’s Creek, I find it interesting that a concrete cause and effect relationship exists between a Google “action” and a management tactic. Google, like Microsoft, is more like a bunch of kayaks in a lake, not a speedboat racing to a rendezvous.
  2. The Guardian and some other European “real” news outfits are eager to punch Googzilla in the nose. Yep, there are some sore losers because Quaero (remember that effort to nuke the GOOG) flopped. If you relish European search, give Unbubble, Giburu, or Qwant a try. That will work out really well for in depth research.
  3. Google has not been particularly secretive about what it does. I recall telling a couple of Googlers that Google spat out high value information somewhat promiscuously. Guess what? None of the poobahs cared. I am not sure any of those with whom I shared this insight listened.

Net net: Google has been doing the Google thing since the company had to generate revenue. The company looked around, found inspiration in Yahoo’s GoTo/Overture model, and has been chugging along the same path for a couple of decades.

The idea of getting woke may sell newspapers, but it is old news and insight into how little “real” journalists and scholars think about the behaviors of large scale information systems. Goggle chugs along.

What’s the “real story”? For me, more attention paid to inventions which don’t make sense, ineffectual tactics which attempt to thwart Facebook’s social hegemony and Amazon’s retail juggernaut, and generating sustainable revenue from something other than advertising.

But these are not as nifty as a big, semi-chaotic company’s making life tough for an academic “team.”

Collateral damage, maybe?

Stephen E Arnold, August 31, 2017

Google and Video Search: Still a Challenge

August 31, 2017

I read “How YouTube Perfected the Feed.” The main idea is that Google used smart software to make YouTube videos easier to find. The trick is not keyword search. Google’s YouTube, which the write up calls a “pillar of the Internet,” uses signals to identify what a person want. Then smart software delivers recommendations. The “new” YouTube’s secret sauce is described this way:

McFadden [a Google wizard] revealed the source of YouTube’s suddenly savvy recommendations: Google Brain, the parent company’s artificial intelligence division, which YouTube began using in 2015. Brain wasn’t YouTube’s first attempt at using AI; the company had applied machine-learning techniques to recommendations before, using a Google-built system known as Sibyl. Brain, however, employs a technique known as unsupervised learning: its algorithms can find relationships between different inputs that software engineers never would have guessed. One of the key things it does is it’s able to generalize,” McFadden said. “Whereas before, if I watch this video from a comedian, our recommendations were pretty good at saying, here’s another one just like it. But the Google Brain model figures out other comedians who are similar but not exactly the same — even more adjacent relationships. It’s able to see patterns that are less obvious.”

The point of the exercise is to generate more ad revenue. With competition from Facebook and others, Google is facing another crack in its control of search. Amazon may generate three times the number of product searches as Google. That’s another problem for the GOOG.

Now the talk about smart software is thrilling to many. For me, I highlighted this statement in the article as quite suggestive about the method:

YouTube’s emphasis on videos related to ones you might like means that its feed consistently seems broader in scope — more curious — than its peers. The further afield YouTube looks for content, the more it feels like an escape from other feeds.

The smart software is not about search. Google is processing signals and looking for similarities. I don’t want to be a grouser, but these themes have peppered Google patent documents and technical papers for many years. In my Google: The Digital Gutenberg I reviewed some of the wonkier video ideas. (By the way, the “Gutenberg” metaphor refers to the automatically generated content which Google outputs in response to user actions. Facebook may be more prolific today, but when I was working on Google: The Digital Gutenberg, Google had the distinction of being the world’s largest digital artifact producer.

Several observations:

First, finding videos remains a difficult information retrieval task. I recall the promising approach of Exalead, before Dassault bought the company and used the technology to reduce its dependence on Autonomy and deploy a way to find nuts and bolts. Exalead converted text to speech, generated some semi-useful metadata, and allowed me to search for a word or phrase. The system would then display links to videos which contained the string. The problem with video search is that it is visual and, to my knowledge, no one has figured out how to have software convert an image to a searchable  string. Years ago, I saw a demo from an Israeli company whose software could “watch” a soccer match and flag the goals sometimes. Google’s video search is useful when one looks for words in video titles, video descriptions, video channel names, or the entity producing or starring in the video.

Second, recommendations work reasonably well for digital Walmart-type shoppers. However, many recommendations are off the wall. I bought a bottle of itch reliever spray for my dog. The product was designed for saddle horses. Now Amazon happily shows me boots, bits, and bridles. Other recommendation systems will work the same way. The reason? Signals are given incorrect “weights” and the clustering methods drift away because many smart software methods are “greedy.” (I have a for fee lecture on this subject which is pretty darned interesting and important. Curious? Write benkent2020 at yahoo dot com for info.)

Third, Google’s smart software for video continues to struggle with uploads that are on some pretty dicey topics. I routinely get links to YouTube videos which require me to be over 18. You can check out Google’s filtering for certain content by running queries on both and for “nasheed.” Yep, interesting “promotional” videos are in evidence.

Net net: Talk about smart software creates the impression that great progress in video content access is being made. I agree. There is progress; however, finding videos remains a work in progress.

I suppose Amazon will sell me a horse when it runs out of farm fresh Echoes. Google is recommending videos to me which don’t match what I usually look for. I was curious about non Newtonian fluids. Guess what Google suggested I view? A Chinese table tennis match and my own video.

There you go.

Stephen E Arnold, August 31, 2017

Natural Language Queries Added to Google Analytics

August 31, 2017

Data analysts are valuable members of any company and do a lot of good, but in many instances, average employees – not versed in analyst-ese – need to find valuable data. Rather than bother the analysts with mundane questions, Google has upgraded their analytics to include natural language queries, much like their search function.

Reporting on this upcoming change, ZDnet explains what this will mean for businesses:

Once the feature is available, users will have the ability to type or speak out a query and immediately receive a breakout of analyzed data that ranges from basic numbers and percentages to more detailed visualizations in charts and graphs. Google says it’s aiming to make data analysis more accessible to workers across a business, while in turn freeing up analysts to focus on more complex research and discovery.

While in theory, this seems like a great idea, it may still cause issues with those not asking questions related to the data, analytic method or appropriate prior knowledge. Unfortunately, data analysts are still the best resource when trying to glean information from analytics reports.

Catherine Lamsfuss, August 31, 2017

Support for Open Source AI from Financial Firms

August 31, 2017

Financial tech reporter Ian Allison at the International Business Times finds it interesting that financial services firms are joining tech companies like Google and Microsoft in supporting open source AI solutions. In his piece, “Finance and Artificial Intelligence Are Going ‘Fintech’ and Open Source,” Allison points to one corporate software engineer as instrumental to the trend:

QR Capital Management was probably patient zero when it came to opening up their code around data storage – and this move, shepherded by software engineer Wes McKinney, kickstarted the popular Pandas libraries project. Now he has returned to open source work at Two Sigma. We have also seen open source data storage offerings coming out of Man AHL in the form of Arctic. Taking part in a panel on open source infrastructure, McKinney said investment in an open source project yields dividends later: data storage underlies other verticals, and when other people use the software and build libraries on top of it, that makes in-house systems more compatible.

See this link for more about the panda’s library. In the same panel Allison cites above, participants were asked how best to sustain the open source community. McKinney gave this advice:

I feel a compulsion not to let open source projects die. But without sponsorship it can become hard to sustain. So when commercials ask me how they can help, I say sponsor an individual – to triage issues, do patches; that goes a long way.

So, what industry will be next to throw its weight behind open source projects?

Cynthia Murrell, August 31, 2017


Alphabet Google: Allegedly Vindictive? Never, Not Possible

August 30, 2017

I read “Google-Funded Think Tank Fired Scholar over Criticism of Tech Firm.” Europeans get a jolt from criticizing the Alphabet Google. The behavior strikes me as unusual for a company which is sending millions to help Houstonians who find themselves in a Katrina-type crisis.

The write up asserts:

An influential Washington think tank that has received more than $21m in funding from Google and its chairman Eric Schmidt dropped a team of scholars after its leader wrote an article praising the European Union’s decision to fine the tech giant.

The insinuation seems to be that the GOOG is vindictive. If so, those Houstonians may want to make sure they don’t have to buy an Android phone or commit to Google’s online advertising to work off the Google largess.


As I understand the issue, one expert pointed out that Google’s “power” was an issue.

With a flick of Googzilla’s tail, according to the write up, the expert and his merry band on poobahs were slashed. The write up points out that when the Google contacted the outfit it funds, the leaders were eager to do the online ad vendor’s bidding.

This means that the agents of Google, not Alphabet Google itself, used its power whip like Lash La Rue.

From my vantage point in Harrod’s Creek, I am not sure if this report of a vindictive Google is real or fake. I am leaning toward fake. Europeans eager to fine Google for alleged misdeeds are believing every word.

Google vindictive. Never. Not possible in my experience.

Stephen E Arnold, August 30, 2017

Google to Further Predict Relevant News to Subscribers

August 30, 2017

It’s no surprise that these days most people rely on something other than themselves to find relevant news stories, be it social media, a news feed or even Google. For many, it’s easier to let others determine what is truly important. Google, a leader in pointing out useful information and news, has stepped up their steering game and announce the update to their app which will further think for each user.

According to a recent liliputing article,

…the feed still shows things like news, videos, and sports scores. But Google isn’t just choosing content based on the way you interact with Google search, apps, and services anymore. The company will also surface items that are trending locally and around the globe, helping you stay up to date on things that you might otherwise have missed. The company says it uses machine learning algorithms to predict which things you’ll be most interested in seeing.

For those uncomfortable with only seeing news stories Google’s algorithms deem worthy of your consideration there are steps you can take to delete your preferences and habits. Perhaps Google’s intentions are altruistic and the app will be Big Brother approved really helpful to the masses. We sure hope so!

Catherine Lamsfuss, August 30, 2017

Learn About Machine Learning

August 30, 2017

For an in-depth look at the technology behind Google Translate, turn to Stats and Bots’ write-up, “Machine Learning Translation and the Google Translate Algorithm.” Part of a series that aims to educate users about the technology behind machine learning (ML), the illustrated article delves into the details behind Google’s deep learning translation tools. Writer  Daniil Korbut explains the factors that make it problematic to “teach” human language to an AI, then describes Long Short-Term Memory (LSTM) networks, bidirectional RNNs, sequence-to-sequence models, and how Google put those tools together. See the article for those details that are a bit above this writer’s head. There’s just one thing missing—any acknowledgment of the third parties that provide Google with language technology. Oh well.

Another valuable resource on machine learning, found at YCombinator, is Google researcher Jeff Dean’s Lecture for YC AI. The post includes a video that is over an hour long, but it also shares the informative slides from Dean’s presentation. They touch on scientific and medical applications for machine learning, then examine sequence-to-sequence models,  automated machine learning, and “higher performance” ML models. One early slide reproduces a Google blog post in which Dean gives a little history (and several relevant links):

Allowing computers to better understand human language is one key area for our research. In late 2014, three Brain team researchers published a paper on Sequence to Sequence Learning with Neural Networks, and demonstrated that the approach could be used for machine translation. In 2015, we showed that this this approach could also be used for generating captions for images, parsing sentences, and solving computational geometry problems. In 2016, this previous research (plus many enhancements) culminated in Brain team members worked closely with members of the Google Translate team to wholly replace the translation algorithms powering Google Translate with a completely end-to-end learned system (research paper). This new system closed the gap between the old system and human quality translations by up to 85% for some language pairs. A few weeks later, we showed how the system could do “zero-shot translation”, learning to translate between languages for which it had never seen example sentence pairs (research paper). This system is now deployed on the production Google Translate service for a growing number of language pairs.

These surveys of Google’s machine translation tools offer a lot of detailed information for those interested in the topic. Just remember that Google is not (yet?) the only game in town.

Cynthia Murrell, August 30, 2017


Mobile Search: Has the Desktop Boat Anchor Search Been Cut Loose??

August 29, 2017

We noted “57% of Search Traffic Is Now Mobile, According to Recent Study.” Who knows if the research is statistically valid, if the math is correct, or the questions ones that an academic would okay?

Nevertheless, if we assume the information is mostly on point, the good old days of big screens, mindless Web surfing just to see what’s online, and mostly uncensored information are gone.

We learned:

A webpage of a particular website most likely to show up first in search results will be different 35% of the time, BrightEdge found. ”If brands do not track and optimize for both device channels, they are likely to misunderstand the opportunities and threats affecting them.  It is recommended that marketers assess the proportion of their traffic coming from mobile and desktop and adjust their strategy accordingly.

If I understand this passage correctly, one gets to create, support, and tune two Web sites: One for the boat anchor crowd and one for the zippy mobile users. Want the full report? Click here.

Stephen E Arnold, August 29, 2017

Google Announces a Mobile-Friendly Change in the Works

August 29, 2017

As more consumers use their Smart Phones and similar devices for everyday internet activity, Google is changing – once again – how search is done. To accommodate mobile users the tech giant just announced that it will begin transitioning to a mobile first index. What does this mean for the average website holder?

According to the guys at Business2Community, it could mean a lot of change is needed to remain competitive. They give several tidbits of advice to website owners but one of the most indicative of how our virtual world is changing is this:

…the consensus is now to have a single website that can work across all devices. Search results aside, a mobile responsive site is one of the best things you can build for your small business, as it is a more accessible and user-friendly way for your potential customers to access your business on a mobile device. With increasing numbers of searches conducted on mobile, by not having a mobile or mobile responsive site, you’re missing out on a large amount of possible conversions…

Of course, Google swears its crawlers will still recognize desktop versions of websites if no mobile is available, but we must ask ourselves, how long until that changes as well?

Catherine Lamsfuss, August 29, 2017

Accenture Makes Two Key Acquisitions

August 29, 2017

Whither search innovation? It seems the future of search is now about making what’s available work as best it can. We observe yet another effort to purchase existing search technology and plug it into an existing framework; DMN reports, “Accenture Acquires Brand Learning and Search Technologies.” Brand Learning is a marketing and sales consultancy, and Search Technologies is a technology services firm. Will Accenture, a professional-services firm, work to improve the search and analysis functionalities within their newly acquired tools? DMN’s Managing Editor Elyse Dupre reports:

A press release states that Brand Learning’s advisory team will join the management consulting and industry specialists within Accenture’s Customer and Channels practice. The partnership, according to the press release, will enhance Accenture’s offerings in terms of marketing and sales strategy, organizational design, industry-specific consulting, and HR and leadership.

It is unclear whether the “advisory team” includes any of the talent behind Brand Learning’s software. As for the Search Technologies folks, the article gives us more reason to hope for further innovation. Citing another press release, Dupre notes that company’s API-level data connectors will greatly boost Accenture’s ability to access unstructured data, and continues:

Search Technologies will join the data scientists and engineers within Accenture Analytics. According to the press release, this team will focus on creating solutions that make unstructured content (e.g. social media, video, voice, and audio) easily searchable, which will support data discovery, analytics, and reporting. Accenture’s Global Delivery Network will also add a delivery center in Costa Rica, the release states, which will serve as the home-base for the more than 70 Search Technologies big data engineers who reside there. This team focuses on customer and content analytics, the release explains, and will work with Accenture Interactive’s digital content production and marketing services professionals.


Furthermore, Kamran Khan, president and CEO of Search Technologies, will now lead a new content analytics team that will reside within Accenture Analytics.

Let us hope those 70 engineers are given the freedom and incentive to get creative. Stay tuned.

Cynthia Murrell, August 29, 2017

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