HBO's Mountainhead Will Make You Laugh as the World Burns
Over Succession 's four seasons, series creator Jesse Armstrong made a name for himself as television's go-to chronicler of the uber-rich. The HBO show depicted the inner workings of a powerful, Murdoch-esque media clan and the way its members lived, traveled, celebrated and humiliated one another. It was a tantalizing look at what it might be like to have wealth so profound that it sets you apart from everyone and gives you the power to influence politics worldwide.
Now, after two years off the air, Armstrong returns to HBO on May 31 with a new movie, Mountainhead, which almost feels like it could be a Succession spinoff. (He says he even contemplated having ATN, Succession 's Fox-like news channel, playing in the background.) The cool color palette is the same; so are the zingers. Nicholas Britell is back to compose the score. Instead of media scions, however, Armstrong has turned his attention to the newest generation of powerful elites—tech bros—and raised the absurdity of the scenario.
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The Gartner Hype Cycle is a valuable framework for understanding where an emerging technology stands on its journey into the mainstream. It helps chart public perception, from the 'Peak of Inflated Expectations' through the 'Trough of Disillusionment,' and eventually up the 'Slope of Enlightenment' toward the 'Plateau of Productivity.' In 2015, Gartner removed big data from the Hype Cycle. Analyst Betsy Burton explained that it was no longer considered an 'emerging technology' and 'has become prevalent in our lives.' She's right. In hindsight, it's remarkable how quickly enterprises recognized the value of their data and learned to use it for their business advantage. Big data moved from novelty to necessity at an impressive pace. Yet in some ways, I disagree with Gartner. Adoption has been widespread, but effectiveness is another matter. Do most enterprises truly have the tools and infrastructure to make the most of the data they hold? I don't believe they do. Which is why I also don't believe the true big data revolution has happened yet. But it's coming. Dissecting the Stack A key reason big data is seen as mature, even mundane, is that people often confuse software progress with overall readiness. The reality is more nuanced. Yes, the software is strong. We have robust platforms for managing, querying, and analyzing massive datasets. Many enterprises have assembled entire software stacks that work well. But that software still needs hardware to run on. And here lies the bottleneck. Most data-intensive workloads still rely on traditional central processing units (CPUs)—the same processors used for general IT tasks. This creates challenges. CPUs are expensive, energy hungry, and not particularly well suited to parallel processing. When a query needs to run across terabytes or even petabytes of data, engineers often divide the work into smaller tasks and process them sequentially. This method is inefficient and time-consuming. 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