By Simon Bond

The rationale behind many of the most successful investors is to go to sectors and places where nobody is, get set, then sit and wait until others catch up.

Most of the time, this takes a tremendous amount of patience and the lead time is longer than people think. Due to the instant and always on nature of the investment world, this gets harder each day as we are continually bombarded with reasons to be wrong. 

I mention this due to the reasoning behind Google’s big hardware event recently, it wasn’t the hardware at all.

It was all about the Assistant, the artificially intelligent digital helper that caters to your every whim and powers your every interaction.

Artificial intelligence (AI) is an area of computer science that emphasises the creation of intelligent machines that work and react like humans. Some of the activities computers with artificial intelligence are designed for include:

  • Speech recognition
  • Learning
  • Planning
  • Problem solving

On average Google now processes over 40,000 search queries every second, which translates to over 3.5 billion searches per day and 1.2 trillion searches per year worldwide.

Cloud-based AI will become an increasingly ingrained part of our everyday life. But it will come at a price. Cloud computing obeys the law of increasing returns, sometimes called the network effect, which holds that the value of a network increases much faster as it grows bigger. The bigger the network, the more attractive it is to new users, which makes it even bigger, and thus more attractive, and so on.

A cloud that serves AI will obey the same law. The more people who use an AI, the smarter it gets. The smarter it gets, the more people use it. The more people that use it, the smarter it gets again. Once a company enters this virtuous cycle, it tends to grow so big, so fast, that it overwhelms any upstart competitors. As a result, our AI future is likely to be ruled by an oligarchy of two or three large, general-purpose cloud-based commercial intelligences.

Futurist Kevin Kelly, one of the most respected writers on the subject has been discussing the issues surrounding AI for decades and in an article published in Wired Magazine in 2014 he said the following:

“AROUND 2002 I attended a small party for Google—before its IPO, when it only focused on search. I struck up a conversation with Larry Page, Google’s brilliant cofounder, who became the company’s CEO in 2011. “Larry, I still don’t get it. There are so many search companies. Web search, for free? Where does that get you?” My unimaginative blindness is solid evidence that predicting is hard, especially about the future, but in my defense this was before Google had ramped up its ad-auction scheme to generate real income, long before YouTube or any other major acquisitions. I was not the only avid user of its search site who thought it would not last long. But Page’s reply has always stuck with me: “Oh, we’re really making an AI.”

I’ve thought a lot about that conversation over the past few years as Google has bought 14 AI and robotics companies. At first glance, you might think that Google is beefing up its AI portfolio to improve its search capabilities, since search contributes 80 percent of its revenue. But I think that’s backward. Rather than use AI to make its search better, Google is using search to make its AI better. Every time you type a query, click on a search-generated link, or create a link on the web, you are training the Google AI. When you type “Easter Bunny” into the image search bar and then click on the most Easter Bunny-looking image, you are teaching the AI what an Easter bunny looks like. Each of the 12.1 billion queries that Google’s 1.2 billion searchers conduct each day tutor the deep-learning AI over and over again. With another 10 years of steady improvements to its AI algorithms, plus a thousand-fold more data and 100 times more computing resources, Google will have an unrivaled AI. 

My prediction: By 2024, Google’s main product will not be search but Artificial Intelligence”.