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
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