Strong technologies capture the imaginations of technology enthusiasts. That is why many important technologies start out as weekend hobbies. Enthusiasts vote with their time, and, unlike most of the business world, have long-term horizons. They build from first principles, making full use of the available resources to design technologies as they ought to exist.
The mainstream technology world notices the excitement and wants to join in, but isn’t willing to go all the way and embrace the strong technology. To them, the strong technology appears to be some combination of strange, toy-like, unserious, expensive, and sometimes even dangerous. So they embrace the weak form, a compromised version that seems more familiar, productive, serious, and safe.
He also gives a few examples, such as public internet versus private intranets.
Innovation is at the core of both weak and strong technologies, but one can hardly say a weak technology is disruptive. Billions of venture capital dollars see unicorns as strong technologies, but these do not always turn out to be disruptive. This illustrates that telling strong technologies from weak is difficult until after the fact. Some are better at this than others, but consistently picking out winners is almost impossible.
In recent years we've seen an explosion in machine learning (ML) technologies, driven by cheaper computing power. I wonder, how long till someone applies ML to historical datasets to build a predictive model of which new technologies will be strong? Much data remains online for years, if not decades, and even offline data is stored in digital format these days, so can in theory be used. What kind of data would go into such a model? Research papers, product launches, user forums, newspaper headlines, social media mentions? Or is this a fool's errand? But isn't this what people who invest in weak technologies also say about the strong ones? ?