“A machine learning advantage can’t be easily replicated, cloned, or reverse-engineered: to compete with the likes of Apple and Google at this game, you need to have as much computing power and user data as they do (which you probably lack) and as much time as they’ve invested (which you probably don’t have),” Savov writes. “In simple terms, machine learning promises to be the holy grail for giant tech companies that want to scale peaks that smaller rivals can’t reach. It capitalizes on vast resources and user bases, and it keeps getting better with time, so competitors have to keep moving just to stay within reach.”
“Chinese companies may work at ludicrous speeds when iterating on hardware, however the rules change when the thing you’re trying to replicate is months and years of machine learning training,” Savov writes. “The old days of phone makers being able to secure a major hardware advantage for longer than a few months are now gone. At this late stage of the evolution of smartphones, machine learning is the only path toward securing meaningful differentiation.”
Read more in the full article here.
MacDailyNews Take: Owing to the time, money, and expertise required, it will certainly be more difficult, if not downright impossible, for some rambunctious startup to unseat Apple or Google as machine learning begins to power everything from cameras to biometrics and beyond.
Meanwhile, Google has a data advantage in terms of amount of and, perhaps, ability to work with, but also a severe disadvantage when it comes to custom silicon in which Apple wisely began to invest heavily under Steve Jobs and which, under Tim Cook, has only grown in importance and capability (Secure Enclave, Neural Engine, etc.).
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