Yo The other day I bought an iPhone 15 to replace my five-year-old iPhone 11. The phone is equipped with the new A17 Pro chip and has a terabyte of data storage, so it was very expensive. Of course, I had very well-thought-out reasons for spending so much money. I’ve always had a policy of only writing about gear I buy with my own money (no gifts from tech companies), for example. The fancy A17 processor is needed to run the new “AI” stuff Apple promises to release soon; the phone has a significantly better camera than my old phone had, which is important (to me) because My Substack Blog It comes out three times a week and I provide a new photo for each issue; and finally, a friend whose old iPhone is on its last legs might appreciate an iPhone 11 in good condition.
But these are rationalizations rather than solid justifications. The truth is, my old iPhone was fine for the job. Sure, it would need a new battery eventually, but other than that it had years more life left in it. And if you look coldly and objectively at the evolution of the iPhone product line, what you see from 2010’s iPhone 4 onward is really just a sequence of steady, incremental improvements. What was so special about that model? Mainly this: It had a frontal camerawhich opened up the world of selfies, video chat, social media and all the other accoutrements of our interconnected world. But from then on, there were only incremental changes and price increases.
And this is true not just of iPhones, but of smartphones in general. Samsung, Huawei, Google and other manufacturers have followed suit. The arrival of the smartphone, signalled by the launch of the first iPhone in 2007, represented a marked discontinuity in the evolution of mobile phone technology (if in doubt, ask Nokia or BlackBerry). A massive boom followed for about a decade, until the technology (and the market) matured and incremental changes became the norm.
Mathematicians have given this process a name: They call it the sigmoid function, and they draw it as an S-shaped curve. When applied to consumer electronics, the curve looks like an “S” that has flattened out a bit. Progress is slow at the bottom; then it takes a sharp turn upward, before finally flattening out at the top. And smartphones are now on that part of the curve.
If we look at the history of the technology industry over the past five decades, we can discern a pattern. First there is a major technical breakthrough: the silicon chip; the Internet; the web; the mobile phone; cloud computing; the smartphone. Each major breakthrough is followed by a period of frenetic development (often accompanied by investment bubbles), which propels the technology toward the middle part of the “S”; and then, eventually, things calm down as markets become saturated and radical improvements in the technology become increasingly difficult to achieve.
Maybe you can see where this is going: The so-called “AI”It has already had its initial breakthroughs: first, the arrival of “big data” produced by the web, social media, and surveillance capitalism; then, the rediscovery of powerful algorithms (neural networks), followed by the invention of “transformative” deep learning architecture in 2017; and then the development of large language models (LLMs) and other forms of generative AI of which ChatGPT was the poster child.
We’ve been through a period of frenetic development and inordinate amounts of corporate investment (with no clear idea of what the return on that investment will be), which has driven technology towards the middle of the sigmoid curve. So now interesting questions arise: how far along the sigmoid curve has the industry come so far? And when will it reach the plateau that smartphone technology is currently on?
In recent weeks we have started to see signs that that moment may be approaching. The technology is becoming a commodity. AI companies have started releasing smaller and (supposedly) cheaper LLMs. They won’t admit it, of course, but that may have something to do with the way the energy costs of the technology change. are growingThe irrational impulse of the industry It doesn’t have much to do with economists.And although millions of people have tried ChatGPT and its peers, most of them have not shown results. enduring interestVirtually every major company on the planet has had one or two AI pilot projects, but few of them seem to have ever been actually implemented. Could this be the case? feeling of the day Is it about to get boring? A bit like the latest shiny smartphone, in fact.
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What I’ve been reading
Zero-sum games
A transcription of a remarkable talk by Maciej Cegłowski, one of the most astute observers of digital technology, on the moral economy of technology.
In the frame
Vivian Maier: lonely nanny, great street photographer, protagonist of a… Lovely essay by Ellen Wexler on Smithsonian magazine.
Baby bomb
By Ed West A thought-provoking review from Paul Morland’s book on the coming global demographic crisis.
