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 YouTube.com and GoogleVideo.com 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

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

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

Google Drops Instant Search as Mobile Use Rises

August 28, 2017

As more and more Googlers turn to mobile devices to access the search giant the Instant Search feature, first introduced in 2010, becomes irrelevant. Originally, this feature was a time saving (albeit milliseconds) feature giving Google users a much-needed edge in search. But that was for desktops. Now that mobile is king, Google is rethinking their strategies.

According The Verge,

…more than half of Google searches happen on mobile, with the scales continually tipping away from desktop as time goes on. On mobile screens, Instant Search doesn’t make as much sense given we use our fingers and virtual buttons to interact with software, and trying to load a results page on top of the onscreen keyboard isn’t exactly good user experience design.

Internet based services recognizing the trend toward mobile use is nothing new, but Google eliminating one of its hallmark features shows that mobile use for search is much more than simply a trend. Always leading the way, Google is making a statement about the direction of search and we expect others to quickly jump on the bandwagon.

Catherine Lamsfuss, August 28, 2017

Google Home Still Knows More

August 21, 2017

Amazon has infiltrated our lives as our main shopping destination.  Amazon is also trying to become our best friend, information source, and digital assistant via Alexa.  Alexa provides a wealth of services, such as scheduling appointments, filling shopping orders, playing music, answering questions, and more.  While Amazon Alexa has a steady stream of users, Ad Week says, “Google Home Is 6 Times More Likely To Answer Your Questions Than Amazon Alexa.”

The company 360i developed software that would determine which digital assistant was more accurate: Google Home or Amazon Alexa.  Apparently Google Home is six times more likely to answer a question than Amazon Alexa.  360i arrived at this conclusion by using their software to ask both devices 3,000 questions.  Alexa won when it came to questions related to retail information, but Google Home won over all with its search algorithms.

It’s relatively surprising, considering that RBC Capital Markets projects Alexa will drive $10 billion of revenue to Amazon by 2020—not to mention the artificial intelligence-based system currently owns 70 percent of the voice market.

Amazon might be the world’s largest market place, so Alexa would, of course, be the world’s best shopping assistant.  The Internet is much larger than shopping and Google scours the entire Web.  What does Amazon use to power Alexa’s searches?

Whitney Grace, August 21, 2017

Google Amps Ads to New Annoying Levels

August 17, 2017

Today, Google is synonymous with search, as they’ve worked very hard to ensure. But search has changed, and not always for the good. One of Google’s hallmark principles at the beginning of their existence was to provide an unbiased search engine with any additions only being to enhance the user experience. Nowadays, though, it seems like Google looks like every other search engine, littered with Ads and flashing videos.

Not impressed with these changes, Wired recently called the search giant out on their recent addition of automatically-playing movie trailers, saying ‘enough is enough’.

Showing a few ads in the image search system isn’t a bad thing. But it shows just how much Google’s thinking has changed. Google’s not a scrappy startup anymore. It’s the world’s most valuable company, and its investors want results. And without much serious competition, the risk of customers bolting for another search engine is pretty low.

Wired is spot on, of course, but what if customers did start trickling out to other search engines that adhere to Google’s original principles and ideologies?

Catherine Lamsfuss, August 17, 2017

Google and Apple Narrow Search Results

August 11, 2017

Remaining relevant means making money in technology and Google and Apple are not about to be outdone by Amazon despite it appears that may be the case. In an effort to stem the potential loss of revenue both Apple and Google are re-engineering their search capabilities to “buttress the value of traditional search.”

According to GeoMarketing, the two tech giants are approaching the same problem from different angles:

In a sense, the battle between the mobile web and apps is a proxy war between Google and Apple.

For Google,

The (Q&A box) fits right in with the current idea of getting direct, personalized responses to queries as opposed to the traditional method of showing infinite hypertext listings based on general popularity. It follows a path that Google has already taken with its search functions, including the automatic addition of the term “near me” into the search box as well as providing searchable menu listings for restaurants and direct bookings to salons and spas.

Apple is focusing on apps rather than search, but with the same end in mind.

As consumers are demanding local results and more organic answers to their search questions, search giants have to continually find ways to accommodate. As long as it results in more revenue, the infinite chase is worth it, we suppose.

Catherine Lamsfuss, August 11, 2017

After Voice, Visual Search Is next Frontier for Search

August 9, 2017

From text to voice, search business has come a long way. If Pinterest co-founder is to be believed, the future of search is visual.

In an interview to BBC Correspondent and published as the video titled Pinterest Co-Founder Says Photos Hold the Future of Search, co-founder Evan Sharp says:

There are billions of ideas on Pinterest and users search an equal number of them on Pinterest. Our primary source of revenue is advertising wherein we help business promote their products and services through Pins

There might be some substance to what Sharp is saying. Google recently revealed Google Lens and Google Deep Dream. While Google Lens helps users to identify and search objects around them, Deep Dream is a creative tool used for creating composite images using various sources. The intent is to encourage users to use visual tools that the company is building.

VR and AR are the buzzwords now and soon marketers will be placing virtual ads within these visual mediums to promote their products. Though Google Goggles failed to take off, it was probably because the product was ahead of its time. How about a second take now?

Vishal Ingole, August 9, 2017

Google as Art Teacher

August 3, 2017

A recent Google improvement focuses on art, we learn from “Google’s Improved Search Seeks to Make Us All Art Experts” at CNet. Now, results of art-related Google searches will be packed with relevant information and, in many cases, high-resolution images. Museums around the world have been working with Google to enable these features. Reporter Zoey Chong cites a blog post from the company as she writes:

The new feature — mildly reminiscent of the travel guide tab that comes up when you search a city or country — is the result of a collaboration between Google’s Arts and Culture team and its search engineers. When you search for an artist like Gustav Klimt, for example, an interactive panel pops up that allows you to see an overview of the artist, his works, as well as where you can find them. Some pieces can also be viewed in high-resolution. Google said this is made possible with the Art Camera, a custom-made robotic camera to digitize artworks. A fleet of these cameras travels around the world and cultural institutions can use them digitally preserve and share artworks online. Google has also implemented similar features on Street View. If you navigate around museums, you can click on a painting to see it in high-resolution or to understand more information, which Google said is provided by the museums.

A short video embedded in the article demonstrates how this looks in Street View. Chong tried the feature out with works at the National Gallery Singapore, and reports that not every piece of artwork she virtually viewed has more information available; that is because the museums get to decide how much they wish to share online. The company reports that, on their platform, over 500 million searches a month are art-related.

Cynthia Murrell, August 3, 2017

Smartlogic: A Buzzword Blizzard

August 2, 2017

I read “Semantic Enhancement Server.” Interesting stuff. The technology struck me as a cross between indexing, good old enterprise search, and assorted technologies. Individuals who are shopping for an automatic indexing systems (either with expensive, time consuming hand coded rules or a more Autonomy-like automatic approach) will want to kick the tires of the Smartlogic system. In addition to the echoes of the SchemaLogic approach, I noted a Thomson submachine gun firing buzzwords; for example:

best bets (I’m feeling lucky?)
dynamic summaries (like Island Software’s approach in the 1990s)
faceted search (hello, Endeca?)
model
navigator (like the Siderean “navigator”?)
real time
related topics (clustering like Vivisimo’s)
semantic (of course)
taxonomy
topic maps
topic pages (a Google report as described in US29970198481)
topic path browser (aka breadcrumbs?)
visualization

What struck me after I compiled this list about a system that “drives exceptional user search experiences” was that Smartlogic is repeating the marketing approach of traditional vendors of enterprise search. The marketing lingo and “one size fits all” triggered thoughts of Convera, Delphes, Entopia, Fast Search & Transfer, and Siderean Software, among others.

I asked myself:

Is it possible for one company’s software to perform such a remarkable array of functions in a way that is easy to implement, affordable, and scalable? There are industrial strength systems which perform many of these functions. Examples range from BAE’s intelligence system to the Palantir Gotham platform.

My hypothesis is that Smartlogic might struggle to process a real time flow of WhatsApp messages, YouTube content, and mobile phone intercept voice calls. Toss in the multi language content which is becoming increasingly important to enterprises, and the notional balloon I am floating says, “Generating buzzwords and associated over inflated expectations is really easy. Delivering high accuracy, affordable, and scalable content processing is a bit more difficult.”

Perhaps Smartlogic has cracked the content processing equivalent of the Voynich manuscript.

image

Will buzzwords crack the Voynich manuscript’s inscrutable text? What if Voynich is a fake? How will modern content processing systems deal with this type of content? Running some content processing tests might provide some insight into systems which possess Watson-esque capabilities.

What happened to those vendors like Convera, Delphes, Entopia, Fast Search & Transfer, and  Siderean Software, among others? (Free profiles of these companies are available at www.xenky.com/vendor-profiles.) Oh, that’s right. The reality of the marketplace did not match the companies’ assertions about technology. Investors and licensees of some of these systems were able to survive the buzzword blizzard. Some became the digital equivalent of Ötzi, 5,300 year old iceman.

Stephen E Arnold, August 2, 2017

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