By 2021, it was widely believed that through learning algorithms and AI research, machines excelled humans in many aspects. For a long time, machines have dominated the manufacturing and supply chain sectors, even beginning to tackle more complex tasks such as autonomous driving and even writing high-difficulty comprehensive articles. However, has the development of machines in facial recognition really surpassed the human brain?
Thirteen years ago, when my identical twin sons were born, my wife and I could easily tell which one was Nicolas and which one was Alexander. After spending 8 weeks in the neonatal intensive care unit (NICU) at the California Pacific Medical Center in San Francisco, we learned how to match their individual behaviors with their names. We learned early on what most parents of identical twins come to master: who a person is depends not only on their looks but also on how they walk, talk, and various behaviors in their interactions with the world. Processing this extensive dataset enables humans to instantly recognize people we know, including identical twins.Image | Alexander and NicolasWith widespread applications ranging from identifying criminals to assisting us in shopping, facial recognition has been referred to in the news as a “Matrix-like silver bullet,”I have often wondered how far machines can go in recognizing faces when the dataset only presents very slight differences, such as recognizing identical twins.â–Ť Delving into DifferencesAs my sons grow day by day, we have discussed in detail the unique nature of their genetic makeup—essentially, they are clones from the same fertilized egg (note: there is a very high frequency of
