The Google Imperative 2018: Do Not Survive. Thrive
January 1, 2018
At a New Year’s celebration, a well-meaning person buttonholed me and asked, “What’s going to happen to Google in 2018?” The person does not search like a high-powered information professional nor like an analyst laboring in the bowels of Shin Bet. I think the fellow wanted a stock tip presented as a query about the GOOG.
I don’t do stock tips.
I shared with the person my opinion that Google is not one company. How many firms have multiple overlapping applications to perform the same function? Want to search for online videos from antsy teens? Use either GoogleVideo.com or YouTube.com? Need to chat online? You have Google Duo and Google Groups and — what? — eight, nine, or more? Need high-speed communications in Puerto Rico? Pick either the Loon balloon or the laser method if you can.
I mentioned to the person who was guzzling bubbly while I sipped my lukewarm bottle of orange flavored Ice Water: “I think Google wants to build bridges, not walls.” I was thinking about the opinions and real news in “Google Looks to Mend Fences after Rocky 2017.” The article suggests or hypothesizes that
the GOOG In 2017, though, the company consistently found itself in damage control mode as it dealt with one controversy after another.
That’s a good thing I suggested.
I mentioned that Google seems to be struggling in relationship with Amazon, the Bezos behemoth which appears to have diversified its revenues, managed to change some business school professors’ thinking about supply chains, and created a gadget business which tells off color jokes much to the delight of 11 year old boys.
Speaking of children, I had in mind this article from Forbes: “Google And Amazon’s Childish Little Fight Is Spilling Into Your Home.” The operative idea is encapsulated in the word “childish.”
What happens when the high school science club gets into a down and out with the high school math club? Well, let me tell you that seating arrangements in the cafeteria change. Friendships are strained. Snide remarks can be heard in hallways.
Net net: Google is operating with a bicameral mind. On one hand, the company wants to do something “big.” On the other, it is scrambling to become pals with China. Recall that Google suggested to China’s leadership that the country should “change.” Now that was about as successful as a Loon balloon in a Category 3 storm I believe. Google’s million dollar lobbying machine is sputtering. Google is embroiled in an expensive battle with the European Union
Three observations:
- The spat with Amazon is an issue, and I am not sure that either company can be completely happy with the other. Let’s hope I am wrong because a teacher whom I know relies on YouTube and Amazon video for entertainment. What’s the adage, “When elephants fight, the grass gets trampled.”
- The problems with governments are going be difficult to wind down. The writing of checks and the promises of being a better corporate citizen have to be sold, then demonstrated. The problem is complicated because some countries see Google like an automated teller machine which spits out money when the lawyers enter the pass code “fines.”
- The diversification of revenue is likely to be a challenge. Google has been trying to come up with additional, high margin, sustainable revenue streams for more than 15 years. Plug those non online ad revenues in Excel. Use the “prediction” function, and what do you get? The result is a curve which does not match what Google has to do to achieve growth nirvana. Reality, unfortunately, is not the same as spreadsheet fever, public relations, and apologizing.
At the party, the person said, “So do I buy or sell Google shares?”
I smiled and said, “Ask Alexa.”
Stephen E Arnold, January 1, 2018
Apples Orchard of AI Talent
January 1, 2018
Here’s an analysis that will be of interest to competitive artificial intelligence professionals. Fast Company reports on its own research in the piece, “Where Apple Recruits Its AI Talent, According to LinkedIn.” Writer Jared Newman begins:
Apple appears to have doubled its headcount in artificial intelligence and related fields since 2014–and more than tripled its number of PhD holders in the sector–as tech companies race to build a generation of smarter products. That’s one conclusion from an analysis of more than 600 Apple employees who specialize in machine learning, computer vision, natural language processing, and other disciplines related to AI. To help us understand where Apple is getting its AI talent, Fast Company created a database from publicly available LinkedIn profiles, searching for employees who either defined their jobs as “scientist” or “researcher” or listed AI-related skills in their resumes. This analysis certainly does have some limitations: It won’t account for employees who have defined their jobs in vague terms on their profiles, self-reported inaccurately or incompletely, or have avoided sharing their employment information on LinkedIn entirely. Apple has reportedly discouraged employees from announcing their AI jobs on LinkedIn in the past, so blind spots in our study are inevitable. Still, this analysis provides a broad snapshot of Apple’s response to a growing AI arms race in the tech industry.
The article goes on to share several graphs representing Apple AI hiring trends, like the proportion of Ph.D. to non-Ph.D., hires by year; or the percentages of employees obtained from acquisitions, universities or government organizations, and other businesses. We can also see from which businesses and universities Apple have hired most, and which acquisitions brought the company the most AI talent. See the article for all the details.
Cynthia Murrell, January 1, 2018
AI Has Become Better at Predicting Your Actions Than You Are
January 1, 2018
It’s official, AI has become smarter than us. Well, maybe. It certainly is more sophisticated about human patterns than we ourselves are. We learned just how advanced in a recent Phys.org article, “Can Math Predict What You’ll Do Next?”
According to the piece:
When making predictions, scientists have historically been limited by a lack of complete data, relying instead on small samples to infer characteristics of a wider population.
But in recent years, computational power and methods of collecting data have advanced to the point of creating a new field: big data. Thanks to the huge availability of collected data, scientists can examine empirical relationships between a wide variety of variables to decipher the signal from the noise.
For example, Amazon uses predictive analytics to guess which books we may like based on our prior browsing or purchase history. Similarly, automated online advertisement campaigns tell us which vehicles we may be interested in based on vehicles sought out the day before.
Not convinced? Consider this story about how Carnegie Mellon’s AI recently won a Texas Hold ‘em Tournament. Poker, of course, is based on subtle human cues, bluffing, and psychology. So, if an AI system is on target there, imagine what it would do if the attention was focused on us?
Patrick Roland, January 1, 2018
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