From a firm’s perspective, the emergence of a new technology wave is a new opportunity to generate a financial return. The question is precisely how. That topic remains as salient today, in the era of artificial intelligence, as it was when firms first encountered smartphones, the commercial internet, and personal computers.
What can a nineteenth-century economist teach a twenty-first-century Chief Executive Officer (CEO) at one of the largest technology firms? More to the point, why is Microsoft’s CEO, Satya Nadella, quoting William Stanley Jevons? Jevons was a dominant figure in economic thought in Britain during the second half of the nineteenth century, but not today.
Epiphany plays an outsized role in the reductionist two-step model of invention. Step one is when an idea pops into an inventor’s head, and step two is when the invention spreads in an economy over time.
This model is misleading in numerous ways that would take a book to enumerate. Today’s column focuses on step two, aiming to one piece. How and why do businesses embed the invention in products and services while the invention spreads?
A prototype is a product or service’s early sample, model, or release. It is built to test a concept or process and serves as a tangible representation of an idea. Some prototypes are primarily commercial, while others are scientific.
It is that time of year again: Time to look back at information technology in 2024 and make light of it. As with prior year-in-reviews, this one will be arranged like an award ceremony. There are three criteria for the dozen awards given out this year:• The award must be for something involving digital technology.• The key event must have taken place this year, 2024.• The award cannot take itself seriously. The event receiving attention must lend itself to sass, sarcasm, and ridicule.
The Worlds I See. Curiosity, Exploration, and the Discovery at the Dawn of AI—Fei-Fei Li (New York, NY, USA: Flatiron Books, 2023, 322 pp.)
Generative AI has created a gold rush today, but that rush has not yet grown into either a productivity boom or a financial bubble. There are good reasons to think this rush could become either one.Which one is just around the corner? Could it be both? In case you forgot, we did live through a productivity bonanza that morphed into a financial bubble during the commercialization of the Internet.
The commercial future of AI will soon be bigger than the actions of any firm, individual, research team, or open-source community. In the near term, a massive tailwind of potential use cases and nearly completed projects will determine the rate of progress in creating value for users and suppliers. Still, the source of the next frontier commercial breakthrough and the distribution of profits look undetermined and, for reasons to be explained, underdetermined.
Large language models (LLMs) have overrun commercial markets, more like a tsunami than a normal technical wave of interest. The topic is everywhere –news stories, blogs, podcasts, startup investments, analyst reports, hackathons, and government announcements. A virtual frenzy surrounds it.
It is time to review the year in digital technology. Oh, what fun! As with prior reviews, we will arrange this review like an award ceremony.
There are three criteria for an award: