The Retro-Future Presented by Cloud Computing

Larry Page once said the perfect search engine understands what you mean and gives back exactly what you want. The first part of that statement is increasingly defined by voice SEO. The second half of that statement is determined by still learning artificial intelligences, driven by both improving AI technology and data mining.

The original computing model per Golden Age science fiction was one city sized computer running the world. Every computer in the world was really a terminal connected to the world’s true computing hub. The internet that arose in the 1980s relied on connections between millions of smaller computers and many servers. It was distributed and democratic. Cloud computing brings efficiencies of scale, and it is delivering centralization.

While there are still home brew servers hosting Minecraft and personal websites, even many individuals pay for a small partition on a cloud server or blog and store data for free on a cloud server. While we are not yet back to the retro-futuristic vision of one massive city sized computer, we are approaching it when there fewer massive data centers handling most of the load. Personal computers and hosting won’t go away, but there is a point where Pareto’s law applies, rendering the small players nearly irrelevant. And we are at that point where most web searches, data storage and computing is controlled only a few major players.

Artificial intelligence requires significant investment by top talent and hardware, software and networking resources few can match. For that reason, we’ll use the names of big players in AI as the few major firms that count. They are Amazon (Alexa), Microsoft (Cortana), Apple (Siri) and Google (Assistant). These companies are likely to remain in the lead, too, because they already have ways to monetize the voice search queries and, in most cases, the information appliances they sell. Whether it is making money off apps, advertising, content sales like Google books or product sales, their ability to make money delivering products and services ensures they’ll remain dominant. The sheer amount of data they collect on consumers allows them to sell better, too, to the market.

Whether or not we need to review the biases in content delivery and censorship of these few large players becoming similar to public utilities is a whole other debate. The fact remains that they are so large now that they nearly crowd out anyone else. The second tier competitors are either catering to niches these main companies choose to ignore or don’t fully serve.

Some social media sites are trying to reach that same level. Facebook and WeChat’s growth of apps that work entirely within their websites and procurement of unique content, giving rise to an information ecosystem that keeps people there for almost all their needs is an attempt to rival Google or Apple. However, without the ability to use information appliances and the solid income stream from a portion of almost everything sold to consumers, they may not have the resources to grow and reach the top tier.

The massive data collection by the biggest players, their Big Data analysis tools and top talent provide the information that leads to AIs learning. Their AIs learn how to understand voice search faster, recognize shifts in conversational context more readily, collate data more effectively to make the ideal product suggestions and predict individual’s preferences more accurately.  The greater convenience these more intelligent AIs give consumers and improved performance is why it is logical to predict the big players will remain in their dominant positions, and why consolidations will be among those few big players or their acquisitions of companies in the second tier.

And with every merger and purchase, we move closer to the one super-computer that watches all, knows all and tells us what it thinks we’d like to do or should do. That’s Page’s vision. The only difference between the future and the retro-future is the fact that the AI is in a cloud distributed across dozens of data centers each the size of a small city instead of one large city.